medicinski glasnik

MEDICINSKI GLASNIK

Official publication of the Medical Association of Zenica-Doboj Canton, Bosnia and Herzegovina Volume 9 Number 2, August 2012.

ISSN 1840-0132

Published and copyright by: Medical Assotiation of Zenica-Doboj Canton; Address: Zenica, 72000, Bulevar kralja Tvrtka I 4, Bosnia and Herzegovina; tel./fax: +387 32 444 270; Email: [email protected], web site: http//www.ljkzedo.com.ba For ordering information please contact: Tatjana Žilo, [email protected]; Access to this journal is available free online trough: www.ljkzedo.com.ba The Journal is indexed by MEDLINE, Science Citation Index Expanded (SciSearch®), and Journal Citation Reports/Science Edition, EMBASE (Exerpta Medica), Scopus, EBSCO; ISSN 1840-0132 Printed by: MINEX Trade d.o.o. Zenica, Marjanovića put 78, 72000 Zenica, tel./fax: +387 32 423-350, +387 32 425 496; E-mail: [email protected] DTP: Graphic and web design studio “B Panel” Zenica, Zmaja od Bosne bb, Poslovna zona Zenica I, 72000 Zenica; E-mail: [email protected], tel. +387 32 441 290, 441 291; www.bpanel.ba Printing supported by the Federal Ministry of Education and Science (Federalno ministarstvo obrazovanja i nauke, BiH)

Medicinski Glasnik

Official Publication of the Medical Association of Zenica-Doboj Canton Bosnia and Herzegovina Editor-in-chief

Selma Uzunović Zenica, Bosnia and Herzegovina

MANAGING EDITOR

Tarik Kapidžić Zenica, Bosnia and Herzegovina

Editors Adem Balić, Tuzla, Bosnia and Herzegovina Dubravka Bartolek, Zagreb, Croatia Branka Bedenić, Zagreb, Croatia Asja Čelebić, Zagreb, Croatia Josip Čulig, Zagreb, Croatia Filip Čulo, Mostar, Bosnia and Herzegovina Jordan Dimanovski, Zagreb, Croatia Branko Dmitrović, Osijek, Croatia Ines Drenjančević, Osijek, Croatia Harun Drljević, Zenica, Bosnia and Herzegovina Davorin Đanić, Slavonski Brod, Croatia Lejla Ibrahimagić-Šeper, Zenica, Bosnia and Herzegovina Tatjana Ille, Belgrade, Serbia Vjekoslav Jerolimov, Zagreb, Croatia Mirko Šamija, Zagreb, Croatia Sven Kurbel, Osijek, Croatia Snježana Pejičić, Banja Luka, Bosnia and Herzegovina Belma Pojskić, Zenica, Bosnia and Herzegovina Besim Prnjavorac, Tešanj, Bosnia and Herzegovina Asja Prohić, Sarajevo, Bosnia and Herzegovina Velimir Profozić, Zagreb, Croatia Radivoje Radić, Osijek, Croatia Amira Redžić, Sarajevo, Bosnia and Herzegovina Suad Sivić, Zenica, Bosnia and Herzegovina Sonja Smole-Možina, Ljubljana, Slovenia Vladimir Šimunović, Mostar, Bosnia and Herzegovina Adrijana Vince, Zagreb, Croatia Jasmina Vraneš, Zagreb, Croatia Živojin Žagar, Zagreb, Croatia Secretary: Tatjana Žilo; Proofreaders: Aras Borić (Bosnian, Croatian, Serbian), Glorija Alić (English), Cover: Amar Porobic

MEDICINSKI GLASNIK Official Publication of the Medical Association of Zenica-Doboj Canton, Bosnia and Herzegovina Volume 9, Number 2, August 2012 Free full-text online at: www.ljkzedo.com.ba, and www.doaj.org (DOAJ, Directory of Open Access Journals) Content Review

Original article

174

Assessment of patient eligibility for kidney transplant procedure Dejan Petrović, Željko Mijailović, Biljana Popovska, Predrag Čanović

180

Metabolic syndrome and psychotropic medications Pavo Filaković, Anamarija Petek Erić, Ljiljana Radanović-Grgurić

189

Erythrocyte sedimentation rate in acute myocardial infarction as a predictor of poor prognosis and impaired reperfusion Mehmet Fatih Ozlu, Nihat Şen, Mehmet Fatih Karakas, Osman Turak, Firat Ozcan, Selcuk Kanat, Dursun Aras, Serkan Topaloglu, Kumral Cagli, Mehmet Timur Selcuk

198

Overweight - early stage of “adipokines related cardiovascular diseases”: leptin and adiponectin relation to anthropometric parametars Kristina Selthofer-Relatić, Dalibor Divković, Radivoje Radić, Vedrana Vizjak, Robert Selthofer, Robert Steiner, Ivica Bošnjak

204

Risk factors for intraoperative arrhythmias in general surgery patients operated under general anesthesia: our one-year experience Milivoje P. Dostić, Marina T. Tomović, Marija T. Popović-Milenković, Srđan M. Stefanović, Slobodan M. Janković

211

Effectiveness for self-monitoring of blood sugar on blood glucose control in Turkish patients with type 2 diabetes mellitus Davut Baltaci, Ali Kutlucan, Serkan Ozturk, Ayhan Saritas, Ahmet Celer, Gokhan Celbek, Harun Deler, Yusuf Aydin, Handan Ankarali

218

Evaluation of cortisol level and cell-mediated immunity response changes in individuals with post-traumatic stress disorder as a consequence of war Abbas Masoudzadeh, Mona Modanloo Kordi, Abolghasem Ajami, Anooshiravan Azizi

223

Impact of gender on cellular immunity following gastrectomy in gastric cancer patients Nasrin Rahmani, Seyyed Abbas Hashemi, Iman Sadeghian

227

The detection of HBV DNA with polymerase chain reaction in blood donors with isolated hepatitis B core antibody Tekin Tas, Selcuk Kaya, Suleyman Onal, Abdulkadir Kucukbayrak

231

Assessment of blood donors’ satisfaction and measures to be taken to improve quality in transfusion service establishments Radmila Jovanović, Vladan Radlovački, Mladen Pečujlija, Bato Kamberović, Milan Delić, Jasmina Grujić

239

Association between iron deficiency anemia and febrile seizure in children Hojjat Derakhshanfar, Ali Abaskhanian, Hosein Alimohammadi, Mona ModanlooKordi

243

AO group, AO subgroup, Garden and Pauwels classification systems of femoral neck fractures: Are they reliable and reproducible? Drago Gašpar, Tomislav Crnković, Dražen Đurović, Dinko Podsednik, Ferdinand Slišurić

248

Prognostic significance of co-overexpression of bcl-2 and c-erbB-2/neu in uterine cervix carcinomas and premalignant lesions Zoran Protrka, Slobodan Arsenijević, Petar Arsenijević, Slobodanka Mitrović, Vesna Stanković, Miloš Milosavljević, Jasmina Nedović, Tatjana Kastratović, Janko Đurić

256

Evaluation of the relationship between heart type fatty acid binding protein levels and the risk of maternal cardiac ischemia in low risk obstetric population during delivery Nermin Akdemir, Suleyman Akarsu, Sevgi Türe, Veciha Ozlem Akcinar, Ahmet Arif Yalcin, Cemil Bilir, Arif Serhan Cevrioglu, Selcuk Ozden, Murat Yucel, Yusuf Yurumez

262

A comparison of pregnant subgroups with positive 50-gram glucose challenge test results to those with negative results in terms of obstetric and perinatal outcomes Yaşam Kemal Akpak, İsmet Gün, Nuri Kaya, Vedat Atay

268

Is adenomyosis associated with the risk of endometrial cancer? İsmet Gün, Öznur Öner, Serkan Bodur, Özkan Özdamar, Vedat Atay

273

Impact of active female smoking on controlled ovarian stimulation in intracitoplasmic sperm insemination cycles Zorancho Petanovski, Gligor Dimitrov, Byrol Aydin, Makjuli Hadzi – Lega, Valentina Sotirovska, Damjan Susleski, Stefan Saltirovski, Vladimir Matevski, Snezana Stojkovska, Emilija Petanovska, Mladen Savic, Trajan Balkanov.

281

The significance of Helicobacter pylori in patients with nasal polyposis Andrijana Včeva, Davorin Đanić, Aleksandar Včev, Darija Birtić, Hrvoje Mihalj, Željko Zubčić, Željko Kotromanović, Ana Đanić Hadžibegović

287

Quality of life in patients with larygeal/hypopharyngeal cancer following total/partial laryngectomy Marijana Filipovska-Mušanović, Đenad Hodžić, Nermin Hrnčić, Haris Hatibović

293

Heterophoria and fusional convergence and divergence in preschool children Miodrag Radaković, Vesna Ivetić, Nada Naumović, Vladimir Čanadanović, Branko Stankov

299

The prevalence rate of hepatitis B and hepatitis C co-infection in HIV positive patients in Mazandaran province, Iran Farhang Babamahmoodi, Mohammad Ali Heidari Gorji, Mohammad Mahdi Nasehi, Leila Delavarian

304

Occurrence of colonization and infection with multidrug-resistant organisms in a neonatal intensive care unit Amela Dedeić-Ljubović, Mirsada Hukić

311

Acinetobacter baumannii as a cause of sepsis Maida Šiširak, Mirsada Hukić

317

Spread of CTX-M-15 positive Providencia spp. causing urinary tract infections at the University Hospital Split in Croatia Petra Barl, Branka Bedenić, Sanda Sardelić, Selma Uzunović, Jasmina Vraneš, Vanda Plečko

325

Staphylococcus aureus carriage among medical students Sabina Mahmutović Vranić, Mediha Puškar

330

Microbial colonization of the external auditory canal and nose in hemodialysis patients Aytekin Alcelik, Tayfun Apuhan, Esra Kocoglu, Mustafa Eroglu, Ismail Necati Hakyemez, Arif Duran

334

Complex regional pain syndrome type I in the upper extremity - how efficient physical therapy and rehabilitation are Tanja Zečević Luković, Branko Ristić, Zorica Jovanović, Nemanja Rančić, Dragana Ignjatović Ristić, Saša Ćuković

341

Prevalence of permanent and transient congenital hypothyroidism in Babol City –Iran Mohsen Haghshenas,Yadollah Zahed Pasha,Mousa Ahmadpour-Kacho, Shokrollah Ghazanfari

345

A prospective study of patients absconding from a psychiatric hospital in Iran Fatemeh Sheikhmoonesi, Azar Kabirzadeh, Seyyed Taha Yahyavi, Benyamin Mohseni

Notes

Case reports

350

Sociodemographic and clinical characteristics of hospitalized patients after suicide attempt: a twenty-year retrospective study Nemanja Rančić, Dragana Ignjatović Ristić, Snežana Radovanović, Sanja Kocić, Svetlana Radević

356

Psychometric properties of the Pediatric Symptom Checklist in preschool children in Serbia Gustav Bala, Špela Golubović, Dragana Milutinović, Ratko Katić

363

Perceived parental acceptance/rejection and psychopathology in a group of sexually abused children/adolescents Pınar Vural, Şengül Hafızoğlu, Nursel Türkmen, Bülent Eren, Çağatay Büyükuysal

370

Outpatient utilization of psychopharmaceuticals: comparison between the cities of Zagreb and Sarajevo (2006-2009) Tarik Čatić, Danijela Štimac, Krešimir Živković, Ana Zelić

376

Patient’s satisfaction with removable dentures after relining Josip Kranjčić, Maja Kostelić-Stunić, Denis Vojvodić, Asja Čelebić, Dragutin Komar, Ketij Mehulić1

383

Study of obligations defined in agreements between parties involved in clinical trials of medicinal products in Bulgaria Ilko N. Getov, Tanya Gocheva-Hristova, Hristina V. Lebanova, Evgeni E. Grigorov

388

Evaluation of quality of life after radical prostatectomy-experience in Serbia Svetomir M. Dragićević, Ivan A. Soldatović, Svetlana D. Bojić, Snežana P. KrejovićMarić, Bajram H. Hasani

393

The first survey about the antibiotic usage in the Republic of Macedonia Golubinka Bosevska, Nikola Panovski, Gordana Kuzmanovska, Elizabeta Coneva, Shaban Memeti, Zaklina Cekovska, Biljana Celevska, Ilco Zahariev, Vladimir Mikik

397

The correlation of average monthly ambient sulfur dioxide concentration and the use of inhalation bronchodilators in children Smajil Durmišević, Jasminka Durmišević-Serdarević, Nihada Ahmetović, Suad Sivic, Melita Lelić

400

Takotsubo cardiomyopathy – the broken heart syndrome Jelena Vučković Filipović, Goran Davidović, Violeta Irić Ćupić, Svetlana Đukić, Zoran Kovačević

402

From hypoglycemia to right heart infarction: treatment of hypoglycemia in type 1 diabetes Tatjana Bačun, Aleksandar Kibel, Krešimir Jelić, Roman Pavić, Dunja Degmečić, Dajana Sidorov

406

HbA1C – overall glycemia marker and hemolytic anemia indicator Marica Jandrić Balen, Vesna Lukenda, Ivan Jandrić, Antonija Raguž, Sidbela Zukanović, Blaženka Miškić

408

Atypical localization of lung cancer located in lobus v. azygos Bilal Imširović, Alma Mekić-Abazović, Ibrahim Omerhodžić, Enver Zerem, Sandra Vegar-Zubović

411

An unusually large liver lipoma Željko Puljiz, Mirko Petričević, Andre Bratanić, Igor Barišić, Mario Puljiz, Željka Karin

414

Modern approach in therapy of brain edema in cerebral ischemia Slađana Anđelić

417

Complete spontaneous resolution of compressive chronic subdural hematoma in a patient with liver failure Mirela Juković, Željko Kojadinović, Viktor Till

420

Giant craniopharyngioma: 9-year follow up after stereotactic Yttrium -90 instillation and microsurgical resection Kemal Dizdarević, Ermin Hadžić, Hakija Bečulić

424

A surgical thread as a nidus for the common bile duct stone formation Aleksandar Knežević, Violeta Knežević, Vesna Pajtić, Aleksandar Gluhović, Ivan Jovanović, Ljiljana Gvozdenović

427

Atypical intrauterine parvo b19 infection Biljana Drašković, Anna Uram-Benka, Izabela Fabri, Gordana Velisavljev Filipović

429

Subcutaneous fat necrosis in newborns Dragana M. Savić, Nada D Stojanović, Vesna D. Stanković, Andjelka K. Stojković, Dragan S. Čanović, Srdjan M. Ninković, Bojan Z. Milošević, Aleksandar M. Cvetković

432

Panophthalmitis after spontaneous perforation in glaucomatous eye Svetlana Paunović, Mirjana Janićijević Petrović, Milan Paunović, Sunčica Srećković, Nenad Petrović, Tatjana Šarenac

435

Neuroretinitis caused by Bartonella quintana Željka Vuković-Arar, Željka Janjetović, Sandra Sekelj, Lidija Šapina, Ivana Pajić -Penavić

438

Twenty one months of frontal sinus stenting Pajić-Penavić Ivana, Đanić Davorin, Sauerborn Damir, Mrzljak-Vučinić Natalija

Medicinski Glasnik is indexed by Scopus, Science Citation Index Expanded (SciSearch®), Journal Citation Reports/Science Edition, MEDLINE, EMBASE (Exerpta Medica), and EBSCO.

REVIEW

Assessment of patient eligibility for kidney transplant procedure Dejan Petrović1, Željko Mijailović2, Biljana Popovska2, Predrag Čanović2

1 Urology and Nephrology Clinic, Nephrology and Dialysis Center, 2Infectious Disease Clinic; Clinical Center Kragujevac, Kragujevac, Serbia

ABSTRACT

Corresponding author: Dejan Petrović Urology and Nephrology Clinic, Nephrology and Dialysis, Center Clinical Center Zmaj Jovina St. 30, 34000 Kragujevac, Serbia Phone: +381 34 370 302,

Kidney transplantation offers better quality of life in comparison to patient dialysis. Patients with endogenous creatinine clearance < 30 mL/min/1.73m2 are introduced into the kidney transplant program. Every patient should be assessed for a degree of eligibility for the kidney transplant procedure. Basic principles of eligibility assessment include: patient education, assessment of patient’s motivation level, medical risk assessment, as well as evaluation of psychosocial status and the level of family support. Medical risk assessment involves establishing the etiology of the primary kidney disease, cardiovascular status assessment, viral status assessment, risk assessment for renal graft thrombosis, screening for early malignancy detection, assessment of mineral metabolism and bone tissue disorders, and immunological risk assessment. Identification of patients with highest degree of kidney transplant eligibility shall decrease morbidity and mortality, reduce medical costs and improve the quality of life for these patients. Keywords: medical risk, cardiac status, viral status

fax.: +381 34 300 380; E-mail: [email protected]

Original submission: 12 September 2011; Revised submission: 24 December 2011; Accepted: 17 January 2012. Med Glas Ljek komore Zenicko-doboj kantona 2012; 9(2):174-179

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Petrović et al Kidney transplant procedure

INTRODUCTION Kidney transplantation is a treatment method for renal function replacement which provides an improved quality of life and better survival in comparison to patients treated with dialysis (1-3). The patients with stage 4 chronic kidney disease and endogenous creatinine clearance < 30 mL/ min/1.73m2 (15-29 mL/min/1.73m2) are introduced into the kidney transplant program, as well as those with stage 5 CKD and endogenous creatinine clearance < 15 mL/min/1.73m2 (1-3). In these patients, the absolute contraindications for kidney transplant procedure - active ischemic heart disease, severe cardiomyopathy, active infection, liver cirrhosis or advanced fibrosis, abuse of or addiction to active substances, active psychosis, severe malignant disease, lack of cooperation by the patient - cannot be present (1-3). The paper aimed to analyze ways of patients’ eligibility assessment for kidney transplant procedure. The Medline database was used for this study. The following keywords were used to perform relevant searches: medical evaluation, renal transplant candidates, pretransplant cardiovascular evaluation, infections. Approximately 250,000 references dealing with these types of problems were found. Systematic review articles and well-controlled clinical studies were selected, while editor’s letters and uncontrolled clinical studies were not taken into consideration. Systematic review articles by the Foundation for Kidney Disease: Improving Global Outcomes (KDIGO) were used and analyzed, thus confirming validity and quality of the selected references. ELIGIBILITY ASSESSMENT OF KIDNEY RECIPIENTS Every patient should be assessed for a degree of eligibility for the kidney transplant procedure. Basic principles of eligibility assessment include: patient education, assessment of patient motivation level, medical risk assessment, as well as evaluation of the psychosocial status and the level of family support (1-3). Patients should be informed about the benefits kidney transplantation brings in comparison to other methods of renal replacement treatment, but also be made aware of the possible complications associated with the kidney transplant procedure: surgical complications, risk of allograft rejection, side effects and risks

of immunosuppressive drugs, risks of infections and malignancies (1-3). Patients should be informed about necessity of taking immunosupressive agents and a need for frequent follow-ups and blood sampling for the assessment of transplanted kidney function and monitoring blood concentrations of immunosuppressive drugs (1-3). An assessment of patient’s psychosocial status should be performed by a psychiatrist, psychologist and a social worker, and should include mental status assessments (cognitive function, anxiety, personality disorder) as well as assessments of the degree of patient’s motivation, patient’s willingness to cooperate and implement treatment recommendations, and their socioeconomic status and family support in the period following kidney transplantation (coming to regular check-ups, and ensuring that prescribed treatment is taken on a regular basis) (1-3). For cognitive function assessment, the MMSE test is used (Mini-Mental State Examination) (1-3). Studies have suggested that, following kidney transplantation, non-compliance develops in 20% of patients, accompanied by loss of willingness to continue taking the immunosuppressive treatment, which results in acute rejection and early loss of transplanted kidneys (1-3). ASSESSMENT OF MEDICAL RISK Medical risk assessment team in kidney transplant candidates includes nephrologist, cardiologist, infectious disease specialist, urologist, transfusion medicine specialist and a clinical immunologist. Assessment of medical risk begins with patient’s medical history, objective review and thorough analysis of medical records, including a kidney biopsy report, if one was performed on the patient (1-3). It is of utmost importance to determine the etiology of primary renal disease using analysis of medical records, including laboratory and immunological assays (antinuclear and anticytoplasmic antibodies, anti-glomerular basement membrane antibodies, C3 and C4 complement components) (1-3). Detailed knowledge about primary renal disease provides for assessment of disease recurrence risk, as well as assessment of kidney graft loss due to recurrence of the primary renal disease (Table 1) (1-3). Every kidney transplant candidate must be subjected to an assessment of their cardiovascular sta-

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Medicinski Glasnik, Volumen 9, Number 2, August 2012

tus (1-3). Patients with end-stage chronic kidney disease show high prevalence of traditional, but especially nontraditional risk factors for the development of cardiovascular conditions. Left ventricular hypertrophy, ischemic heart disease and heart failure show the highest prevalence among cardiovascular conditions (4-8). In patients who are kidney transplant candidates and suspected of having asymptomatic coronary artery disease the dobutamine stress echocardiography (≥ 2 cardiovascular risk factors, > 50 years of age, diabetes mellitus, history of coronary artery disease) should be performed (3, 7, 9-14). Patients with negative findings are considered eligible for kidney transplant procedure (9-14). Positive dobutamine stress echocardiography and symptomatic coronary artery disease are indications for a coronary catheterization in these patients (9-14). In cases where the coronary catheterization results are found to be positive, a revascularization should be performed prior to kidney transplant procedure (9-14). Every kidney transplant candidate should be evaluated for the presence of either active or latent infection. The evaluation includes tests for HBsAg, anti-HCV antibodies, anti-HIV antibodies, anti-HTLV-I antibodies, anti-HTLV-II antibodies (Human T-cell lymphotropic virus), anti-CMV antibodies (Cytomegalovirus), anti-EBV antibodies (Epstein-Barr virus), and TBC PPD test (Tuberculin Sensitivity Test) (3, 15). The presence of HBsAg is not an absolute contraindication for kidney transplant procedure (16). Degree of virus replication (serum HbeAg and HBV DNA) and level of liver damage (liver biopsy) should be assessed in these patients (16). Table 1. Risk for recurrent disease after renal transplantation* Recurrent Disease

Recurrence rate (%)

Graft failure due to recurrent disease (%)

FSGS

20-50%

50%

IgA nephropathy

20-60%

10-30%

MPGN I

20-50%

30-35%

MPGN II

80-100%

10-20%

Membranous nephropathy

10-30%

30%

HUS

10-40%

10-40%

Anti-GBM bolest

15-50%

< 5%

ANCA vasculitis

7-25%

< 5%

SLE

3-10%

< 5%

*Modified according to: Pham P-T, Pham P-A, Pham P-C, Parikh S, Danovitch G. Evaluation of Adult kidney transplantation. Semin Dial 2010; 23: 595-605. FSGS, focal and segmental glomerulosclerosis; MPGN, membranoproliferative glomerulonephritis; HUS, hemolytic uremic syndrome; SLE, systemic lupus erythematosus

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Patients with liver chirrosis are candidates for combined liver-kidney transplant procedure (16-19). Patients with chronic hepatitis should be administred with appropriate dose of lamivudine, depending on the level of their kidney function, both before and after the kidney transplant procedure (16-19). HCV infection does not represent an absolute contraindication to kidney transplant procedure. In HCV-positive patients, the following procedures should be performed: assessment of a virus replication degree (serum HCV RNA), HCV genotype determination (influences the treatment duration) and degree of liver damage evaluation (liver biopsy) (19, 20). Metavir score is used to evaluate the degree of liver damage. Patients with Metavir score ≥ 3 have indications for combined liver-kidney transplant procedure. If Metavir score is < 3, then treatment with interferon and ribavarin is indicated, in an appropriate dose relative to the degree of renal function (ribavarin is not recommended in patients with GFR of < 50 mL/ min) (20, 21). In patients with HCV genotype 1 and 4 anti-viral treatment lasts for 48 weeks, and in patients with HCV genotype 2 and 3 the treatment lasts for 24 weeks (20, 21). Anti-viral treatment has SVR (sustained virologic response) as its objective, defined as absence of serum HCV RNA for at least six months after completion of the interferon-INF α (pegilated interferon α) treatment (19-21). Patients in whom the objective of anti-viral treatment has been reached are considered eligible for kidney transplant, however a degree of viral replication in these patients should be tested every 6-12 months (19-21). Every kidney transplant candidate should be screened for presence of anti-CMV antibodies. Patients with positive results require that development of cytomegalovirus infection and consequent disease be prevented, using universal prohylaxis or preemptive therapy (22, 23). Universal prophylaxis consists of oral administration of valganciclovir, 900 mg once per day in early posttransplant period (initial 10 days), lasting for 3-6 months in total (22, 23). Assessment of CMV replication is needed in order to administer preemptive therapy, once a week for 12 weeks following the kidney transplant (pp65 antigen assay, CM viral load test, real time PCR) (22, 23). The preemptive therapy consists of oral valgan-


ciclovir, 900 mg BID or ganciclovir IV 5 mg/kg, BID during 2-4 weeks (22, 23). Patients with positive anti-EBV antibodies are at increased risk of lymphoproliferative disease in the early period after transplantation, as a result of administering induction immunosuppressive therapy (24-26). In EBV seronegative patients who received the kidney from an EBV seropositive donor, antibodies should be determined once in the first week, once a month during 3-6 months, then once every three months during the first year following kidney transplantation (24-26). Prevention consists of administration of acyclovir or ganciclovir (25, 26). Every kidney transplant candidate should undergo risk assessment for allograft thrombosis in early period (48 hours) following the kidney transplant procedure (27). The thrombophilic screening should include: antiphospholipid antibody test, investigation of resistancy to activated protein C, protein S, presence of genetic mutations factor V (factor V Leiden), and factor II (G20210A), prothrombin and antithrombin III (27). In patients with increased risk of trombophilia, an an intensive profylaxis using subcutaneous heparin is needed, 5000 IU/ day for 4 weeks, followed by administration of oral anticoagulant therapy in order to reach the target INR of 2.5 (27). Sudden onset of aneuria and intensive pain in the allograft region are indicative of allograft thrombosis, and treatment comprises fibrinolytic agents (recombinant tissue plasminogen activator-rtPA), percutaneous endoluminal thrombaspiration or surgical thrombectomy (27). Secondary hyperparathyroidism is a common complication in patients with end-stage chronic kidney disease. The patients in whom optimal control of secondary hyperparathyroidism has been reached are considered eligible for kidney transplant procedure (28). In patients with uncontrolled secondary hyperparathyroidism (iPTH > 800 pg/mL, presence of symptoms and signs of refractory secondary hyperparathyroidism), surgical parathyroidectomy indicated prior to kidney transplantation (29). Immediately after the transplant procedure, bone density levels should be assessed and appropriate treatment administered in order to prevent the development of osteoporosis and pathological fractures (30-35). Patients with end-stage chronic kidney disease have increased the risk of developing a malignant

disease. Patients who are kidney transplant candidates should undergo screening for early malignancy detection which includes mammography in female patients of > 40 years of age, colonoscopy in patients of ≥ 50 years of age (especially in those found positive for occult blood test), PSA test in patients ≥ 50 years of age (36). Patients treated for malignancy require a visit to an oncologist, and cannot be introduced to the transplantation program for at least 2-5 years following the resolution of malignant disease (Table 2) (3). In patients diagnosed with acquired cystic kidney disease using the ultrasound exam, a CAT scan of kidneys should also be performed for early detection of renal cell carcinoma (36). Absolute indications for native nephrectomy prior to kidney transplant procedure include: chronic kidney parenchyma infection, nephrolithiasis combined with kidney infection, urinary tract obstruction complicated by infection or calculi formation, polycystic kidney disease, severe proteinuria (3). Immunological risk should be assessed in patients eligible for kidney transplant procedure (blood type and Rh factor, HLA typing, HLA antibodies, cross-match). Testing for the presence of serum anti-HLA antibodies is performed every three months, and if the patient has been immunized, antibody control is required on day 14 and day 30 after the transfusion, or every 7 days during the first month following transplantation (3, 37-41). Serum testing is performed using lymphocytes panel of the known HLA phenotype, and the result is rendered as a percentage of panel reactive antibodies (%PRA); specificity of anti-HLA Table 2. Recommendations for minimum tumor-free waiting periods for common pretransplantation malignancies* Tumor type Renal Wilm,s tumor Renal cell carcinoma Other renal tumors Bladder cancer in situ Bladder cancer invasive Prostate cancer Cervical cancer in situ Cervical cancer invasive Uterine cancer Breast cancer Colorectal cancer Lymphoma Skin cancer - basal cell Melanoma

Minimal wait time 2 years 2 years 2 years 0 years 2 years 2 years 0 years 2-5 years 2 years 2-5 years 2-5 years 2-5 years 0 years 5 years

*Modified according to: Pham P-T, Pham P-A, Pham P-C, Parikh S, Danovitch G. Evaluation of Adult kidney transplantation. Semin Dial 2010; 23: 595-605.

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antibodies is also determined (3, 37-41). Crossreaction of recipient’s serum and donor’s kidney lymphocytes is required immediately before transplant procedure so as to avoid hyperacute and acute rejection of the transplanted kidney (3, 37-41). Immunological risk assessment makes it possible to choose and select kidney transplant pairs, and the right time for the transplantation procedure (in living donor transplantation) and intensity of immunosuppressive regime after transplant procedure (3, 37-41). In conclusion, kidney transplantation offers improved quality of life in the comparison to dialysis

patients. Therefore, a carefully crafted plan for kidney transplant eligibility assessment is needed as to enable selection of patients with the highest level of eligibility, which should in turn reduce morbidity and mortality, lower the medical costs and improve quality of life for these patients. FUNDING This work was supported by the Ministry of Science and Technological Development of the Republic of Serbia, Grant N0175014. TRANSPARENCY DECLARATIONS Competing interests: none to declare.

REFERENCES 1.

Bunnapradist S, Danovitch GM. Evaluation of adult kidney transplant candidates. Am J Kidney Dis 2007; 50: 890-8. 2. Scandling JD. Kidney transplant candidate evaluation. Semin Dial 2005; 18: 487-94. 3. Pham P-T, Pham P-A, Pham P-C, Parikh S, Danovitch G. Evaluation of adult kidney transplantation. Semin Dial 2010; 23: 595-605. 4. Petrović D, Jagić N, Miloradović V, Stojimirović B. Non-traditional risk factors for development of cardiovascular complications in haemodialysis patients. Ser J Exp Clin Res 2009; 10: 95-102. 5. Petrović D, Obrenović R, Stojimirović B. Risk factors for aortic valve calcification in patients on regular hemodialysis. Int J Artif Organs 2009; 32: 173-9. 6. Petrović D, Stojimirović B. Secondary hyperparathyroidism - risk factor for development of cardiovascular complications in patients on hemodialysis. Med Pregl 2010; LXIII: 674-80. 7. Petrović D, Miloradović V, Poskurica M, Stojimirović B. Diagnostics and treatment of ischemic heart disease in hemodialysis patients. Vojnosanit Pregl 2009; 66: 897-903. 8. Petrović D, Miloradović V, Poskurica M, Stojimirović B. Heart failure in haemodialysis patients: evaluation and treatment. Srp Arh Celok Lek 2011; 139: 248-55. 9. Gupta R, Birnbaum Y, Uretsky BF. The renal patient with coronary artery disease. J Am Coll Cardiol 2004; 44: 1343-53. 10. McCullough PA. Evaluation and treatment of coronary artery disease in patients with end-stage renal disease. Kidney Int 2005; 67(Suppl 95): 51-8. 11. Johnston N, Dargie H, Jardine A. Diagnosis and treatment of coronary artery disease in patients with chronic kidney disease. Heart 2008; 94: 1080-8. 12. Lentine KL, Schnitzler MA, Brennan DC, Snyder JJ, Hauptman PJ, Abbott KC, Axelrod D, Salvalaggio PR, Kasiske B. Cardiac evaluation before kidney transplantation: a practice patterns analysis in medicare-insured dialysis patients. Clin J Am Soc Nephrol 2008; 3: 1115-24.

178

13. Nevis IF, Mathew A, Novick RJ, Parikh CR, Devereaux PJ, Natarajan MK, Iansavichus AV, Cuerden MS, Garg AX. Optimal method of coronary revascularisation in patients receiving dialysis: systematic review. Clin J Am Soc Nephrol 2009; 4: 369-78. 14. Young JB, Neumayer H-H, Gordon RD. Pretransplant cardiovascular evaluation and posttransplant cardiovascular risk. Kidney Int 2010; 78(Suppl 118): 1-7. 15. Subramanian A, Dorman S, and the AST Infectious Diseases Community of Practice. Mycobacterium tuberculosis in solid organ transplant recipients. Am J Transplant 2009; 9(Suppl 4): 57-62. 16. Olsen SK, Brown RS. Hepatitis B treatment: lessons for the nephrologist. Kidney Int 2006; 70: 1897904. 17. Chan TM. Hepatitis B and renal disease. Curr Hepatitis Rep 2010; 9:99-105. 18. Karami A, Najafi A, Alavian SM, Kiarudi MY. Immunology of HCV and HBV in renal failure and transplantation. Hepatitis Monthly 2007; 7:93-101. 19. Levitsky J, Doucette K, the AST Infectious Diseases Community of Practice. Viral hepatitis in solid organ transplant recipients. Am J Transplant 2009; 9(Suppl 4): 116-30. 20. KDIGO Clinical Practice Guidelines for the Prevention, Diagnosis, Evaluation, and Treatment of Hepatitis C in Chronic Kidney Disease. Kidney Int 2008; 73(Suppl 109): 1-99. 21. Gordon CE, Balk EM, Becker BN, Crooks PA, Jaber BL, Johnson CA, Michael MA, Pereira BJ, Uhlig K, Levin A. KDOQI US Commentary on the KDIGO Clinical Practice Guideline for the Prevention, Diagnosis, Evaluation, and Treatment of Hepatitis C in CKD. Am J Kidney Dis 2008; 52:811-25. 22. Humar A, Snydman D, AST Infectious Diseases Community of Practice. Cytomegalovirus in solid organ transplant recipients. Am J Transplant 2009; 9(Suppl 4): 78-86. 23. Egli A, Binggeli S, Bodaghi S, Dumoulin A, Funk GA, Khanna N, Leuenberger D, Gosert R, Hirch HH. Cytomegalovirus and polyomavirus BK posttransplant. Nephrol Dial Transplant 2007; 22(Suppl 8): 72-82.


24. Kasiske BL, Zeier M, Chapman JR, Craig JC, Ekberg H, Garvey CA, Green MD, Jha V, Josephson MA, Kiberd BA, Kreis HA, McDonald RA, Newmann JM, Obrador GT, Vincenti FG, Cheung M, Earley A, Raman G, Abariga S, Wagner M, Balk EM. KDIGO clinical practice guidelines for the care of kidney transplant recipients: a summary KDIGO guidelines for kidney transplant recipients. Kidney Int 2010; 77:299-311. 25. Preiksaitis JK, Keay S. Diagnosis and management of posttransplant lymphoproliferative disorder in solid-organ transplant recipients. Clin Infect Dis 2001; 33(Suppl 1):38-46. 26. Nourse JP, Jones K, Gandhi MK. Epstein-Barr virus-related post-transplant lymphoproliferative disorders: pathogenetic insights for targeted therapy. Am J Transplant 2011; 11:888-95. 27. Ponticelli C, Moia M, Montagnino G. Renal allograft thrombosis. Nephrol Dial Transplant 2009; 24:1388-93. 28. Messa P, Macario F, Yaqoob M, Bouman K, Braun J, von Albertini B, Brink H. The OPTIMA Study: assessing a New Cinacalcet (Sensipar/Mimpara) treatment algorithm for secondary hyperparathyroidism. Clin J Am Soc Nephrol 2008; 3:36-45. 29. KDIGO Clinical Practice Guidelines for the Diagnosis, Evaluation, Prevention, and Treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Evaluation and treatment of kidney transplant bone disease. Kidney Int 2009; 76(Suppl 113):100-10. 30. Weisinger JR, Carlini RG, Rojas E, Bellorin-Font E. Bone Disease after Renal Transplantation. Clin J Am Soc Nephrol 2006; 1:1300-13. 31. Sperschneider H, Stein G. Bone disease after renal transplantation. Nephrol Dial Transplant 2003; 18:874-7. 32. Toussaint ND, Elder GJ, Kerr PG. Bisphosphonates in chronic kidney disease; balancing potential bene-

33. 34.

35. 36. 37.

38.

39.

40. 41.

fits and adverse effects on bone and soft tissue. Clin J Am Soc Nephrol 2009; 4:221-33. Perazella MA, Markowitz GS. Bisphosphonate nephrotoxicity. Kidney Int 2008; 74: 385-93. Mainra R, Elder GJ. Individualized Therapy to Prevent Bone Mineral Density Loss after Kidney Transplantation. Clin J Am Soc Nephrol 2010; 5: 11724. Copley JB, Wuthrich RB. Therapeutic management of post-kidney transplant hyperparathyroidism. Clin Transplant 2011; 25:24-39. Holley JL. Screening, diagnosis, and treatment of cancer in long-term dialysis patients. Clin J Am Soc Nephrol 2007; 2:604-10. Gaston RS, Danovitch GM, Adams PL, Wynn JJ, Merion RM, Deierhoi MH, Metzger RA, Cecka JM, Harmon WE, Leichtman AB, Spital A, Blumberg E, Herzog CA, Wolfe TA, Tyan DB, Roberts J, Rohrer R, Port FK, Delmonico FL. The Report of a National Conference on the Wait List for Kidney Transplantation. Am J Transplant 2003; 3:775-85. Kasiske BL, Vazquez MA, Harmon WE, Brown RS, Danovitch GM, Gaston RS, Roth D, Scandling JD, Singer GG. Recommendations for the outpatient surveillance of renal transplant recipients. J Am Soc Nephrol 2000; 11(Suppl 1): 1-86. Kasiske BL, Cangro CB, Hariharan S, Hricik DE, Kerman RH, Roth D, Rush DN, Vazquez MA, Weir MR, for The American Society of Transplantation. The evaluation of renal transplant candidates: clinical practice guidelines. Am J Transplant 2001; 2(Suppl 1): 5-95. Hariharan S. Recommendations for outpatient monitoring of kidney transplant recipients. Am J Kidney Dis 2006; 4(Suppl 2): 22-36. Eknoyan G, Lameire N. KDIGO Clinical Practice Guidelines for the care of kidney transplant recipients. Am J Transplant 2009; 9(Suppl 3): 1-155.

Procena podobnosti bolesnika za transplantaciju bubrega Dejan Petrović1, Željko Mijailović2, Biljana Popovska2, Predrag Čanović2 Klinika za urologiju i nefrologiju, Centar za nefrologiju i dijalizu, 2Klinika za infektivne bolesti; Klinički centar Kragujevac, Kragujevac, Srbija 1

SAŽETAK Transplantacija bubrega obezbeđuje bolji kvalitet života u odnosu na bolesnike koji se leče dijalizom. U program transplantacije bubrega uključuju se bolesnici kod kojih je klirens endogenog kreatinina manji od 30 mL/min/1.73m2. Kod svakog bolesnika potrebno je proceniti stepen podobnosti za transplantaciju bubrega, a osnovni principi procene podobnosti su: edukacija bolesnika, procena stepena motivisanosti bolesnika, procena medicinskog rizika, kao i procena psihosocijalnog statusa i stepena podrške porodice. Procena medicinskog rizika uključuje otkrivanje etiologije primarne bolesti bubrega, procenu kardiovaskularnog statusa, procenu virusološkog statusa, procenu rizika za trombozu transplantiranog bubrega, skrining za rano otkrivanje malignih bolesti, procenu poremećaja metabolizma minerala i koštanog tkiva, kao i procenu imunološkog rizika. Izdvajanje bolesnika s najvećim stepenom podobnosti za transplantaciju bubrega smanjuje morbiditet i mortalitet, smanjuje troškove lečenja i poboljšava kvalitet života ovih bolesnika. Ključne reči: medicinski rizik, kardiološki status, virusološki status

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REVIEW

Metabolic syndrome and psychotropic medications Pavo Filaković1,2, Anamarija Petek Erić1, Ljiljana Radanović-Grgurić1,2 Psychiatric Clinic, Clinical Hospital Centre Osijek, 2 School of Medicine, Osijek, University of Josip Juraj Strossmayer Osijek; Osijek, Croatia 1

ABSTRACT

Corresponding author: Pavo Filaković Psychiatric Clinic, Clinical Hospital Centre Osijek J. Huttler 4, 31000 Osijek, Croatia Phone: +385 31 511 780; fax.: +385 31 512 212; E-mail: [email protected]

Metabolic syndrome represents a cluster of interrelated metabolic dysfunctions which are risk factors for the development of diabetes and cardiovascular disease. Results of clinical studies suggest significant effects of certain psychotropic medications on weight gain and manifestation of type II diabetes. The psychoactive drugs may influence weight gain through increased food consumption and disruption of satiety signaling system. Some psychoactive medications cause weight increase, insulin resistance, dyslipidemia, impairment glucose tolerance/ type II diabetes and hypertension. Dyslipidemia and increase of insulin resistance can be collateral or a direct consequence of psychoactive drug actions. The authors have reviewed accessible literature throughout electronic databases ten years aback in order to estimate prevalence of metabolic syndrome in the mentally ill, give an overview of accomplishments in researching pathophysiology of metabolic syndrome and effects of psychotropic drugs on apparition and pathophysiological mechanisms in causing mentioned syndrome. Finally, the authors consolidated guidelines and references for prevention and treatment of patients with metabolic syndrome induced by psychotropic drugs. Key words: antidepressants, antipsychotics, pathophysiology, hyperlipidaemia, diabetes mellitus type II, hypertension

Original submission: 27 March 2012; Revised submission: 05 April 2012; Accepted: 25 April 2012. Med Glas Ljek komore Zenicko-doboj kantona 2012; 9(2):180-188

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Filaković et al Impact of psychotropics and metabolic syndrome

INTRODUCTION Metabolic syndrome represents a cluster of interrelated metabolic dysfunctions which represent risk factors for the development of diabetes and cardiovascular disease. The diagnostic criteria for metabolic syndrome are provided by the American National Cholesterol Education Programme (NCEP) (1), the American Heart Association (AHA) (2) and the International Diabetes Federation (IDF) (3-6). Almost all risk factors for the development of metabolic syndrome are more pronounced in mentally ill persons than in general population (genetic predisposition, eating habits, changes in physical activity, smoking, alcohol consumption, poor coping mechanisms, alterations in physiology of adipose tissue, hyperleptinemia, altered activity in lipoprotein lipase, sex hormones interaction, hypopituitary – hypothalamic dysfunction, hypercortisolism, impaired function of glucocorticoid receptors, proinflammatory states, atherosclerosis, increased cardiovascular risk, increased stroke risk) (7-11). Though, the prevalence of metabolic syndrome is high in general population (according to Ford et al. in the USA 24%) it is even greater among psychiatric patients - 2-4 times higher in schizophrenic patients (11,12), 30% higher in bipolar patients (13), and specific features of metabolic syndrome have also been found in patients with posttraumatic stress disorder (PTSD) (13). On average, schizophrenic patients do not have much greater body mass or body mass index (BMI) compared to general population, however regional fat distribution is predominantly abdominal one. Similar was found in patients with PTSD and bipolar affective disorder (14). Although some psychotropic drugs cause an increase in serum lipid concentrations, the researchers are not able to confirm direct causal connection between antipsychotics and dyslipidemia, stating how both dyslipidemia and insulin resistance may be primarily linked to mental disorder itself (15). PSYCHOTROPIC MEDICATIONS AND THE METABOLIC SYNDROME Psychotropic medications are one of the risk factors for the metabolic syndrome development. As the patients generally take new psychoactive drugs well, and the treatment is often long-lasting, the risk of the metabolic syndrome occurrence with the new generation of antipsychotics is hi-

gher (14). The fact that these drugs do not have to be crucial for the metabolic syndrome the development can be seen in successful prevention of these derangements with patients who suffer from psychical derangements by excluding other risk factors (psychical education, implementation of proper nutrition, physical exercise and more complex cognitive-behavior programs) (16). The mechanism of the weight gain and the insulin resistance increase induced by these medications is associated with their pharmacodynamic effect at the receptor level. They can influence the weight gain by stimulating the food intake and obstructing the satiety signal system, which indirectly causes the insulin resistance increase or directly increase the insulin resistance, which, along with hyperlipidaemia, leads to the metabolic syndrome development (17). Antipsychotics A higher frequency of individual components of the metabolic syndrome (weight gain, diabetes) is noticed with psychotic patients even before administering antipsychotics (17). After administering the first generation of antipsychotics into the therapy, the frequency increased somewhat, and a more significant increase was noted with the arrival of the second generation of antipsychotics. The second-generation antipsychotics is most frequently accompanied by weight gain, insulin resistance, dyslipidemia, damaged glucose tolerance/type 2 diabetes and hypertension, i.e. a set of mutually connected metabolic dysfunctions in a different development stage, which result in the metabolic syndrome in the end (18). The weight gain is a common side-effect with the second-generation antipsychotics. With a disrupted neuroendocrinemetabolic homeostasis, there is a pathological (abdominal) fat distribution with the insulin resistance increase as a result. Knowing some facts about the weight gain with antipsychotics makes controlling this side effect easier. As a rule, it is not linear and after several weeks or months the increase curve reaches a plateau and the weight does not increase further on. People inclined to the weight gain with antipsychotics are those people who are inclined to the weight gain anyway (17). It is more frequent with women than with men. Besides, not every weight gain is an outcome of the antipsychotics use. These facts leave enough

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maneuver space for the therapist to choose both an effective and safe therapy means. The highest weight gain is noted with olanzapine and clozapine, somewhat lower with quetiapine, and even lower with risperidone. For the newer antipsychotics, ziprasidone and aripriprazole, there is no proof that they significantly influence the weight gain (18). The most patients with the weight gain are among those who take olanzapine (29%), then quetiapine (23%), somewhat less risperidone (18%), and the least ziprasidone (10%) (19). The average weight gain in the first 10 weeks is the highest with clozapine (around 5-6 kg) and olanzapine (around 3-4 kg), moderate with risperidone and quetiapine (around 1-2 kg), and insignificant with fluphenazine and haloperidol (up to 1 kg) (20). That does not mean that in a concrete case there cannot be a significant weight gain even with the antipsychotic marked as a low-risk one, and equally there can be no weight gain at all with clozapine and olanzapine (21). Fortunately, the weight gain with the antipsychotics can be avoided with a regular individually adjusted choice of antipsychotics and modified cognitive-behavior programs (22). The link between the diabetes and schizophrenia has been known for over a hundred years. The diabetes rate among schizophrenic patients is about 15%, which is two to three times higher than in general public (20). That is why the higher diabetes occurrence among the schizophrenic patients is ascribed to traditional risk factors (genetics, physical inactivity, unhealthy nutrition) since it can not be directly associated with effects of the antipsychotics (22). These risk factors cumulatively influence the insulin resistance (23). Eliminating some of them enables a safer use of the antipsychotics. Nevertheless, that is neither sufficient nor does it explain all the cases of diabetes with the schizophrenic patients(24). That is why the FDA asked the producers of the second-generation antipsychotics to point out (25), on the label, the warning about the need for measuring the glucose concentration in the serum before beginning the treatment and in regular intervals during the treatment. This applies to all second-generation antipsychotics (26, 27). Hyperlipidaemia is an outcome of the cumulation of several different risk factors, from genetic tendency to the factors in the surroundings (nutrition, stresses). Some antipsychotics also increase the serum lipids concentration (4) (28). There is most

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evidence for the increase of the serum triglycerides concentration with clozapine. Similar increase of triglycerides and cholesterol appears with olanzapine and quetiapine. It is usually accompanied by the weight gain. Risperidone and ziprasidone have a minimal effect on the serum lipids. Scientists distance themselves from explaining the direct causeeffect link between the antipsychotics and dyslipidemia pointing out that dyslipidemia, as a key component of the metabolic syndrome, can be in a primary connection with the psychical disarrangement, aside from the antipsychotics. Nowadays, special attention is given to the role of omega 3 fatty acids as a protective factor of the cellular membranes of the neurons in the schizophrenic patients (28,29). Smoking and alcohol abuse significantly reduce omega-3 fatty acids and in such a way induce the metabolic syndrome development in the schizophrenic patients as well. On the other hand, their addition to the nutrition of the schizophrenic patients can positively influence the curbing of the metabolic syndrome (the insulin resistance decrease, a better weight regulation) and the stabilization of the brain function (30). Traditional risk factors for the development of cardiovascular diseases are more frequent in the schizophrenic patients than in general population. The clinically treated schizophrenic patients smoke twice as much (58%) and those in hospitals five times as much (79%) as the general population (31,32). Obesity, insulin resistance, type II diabetes, hyperlipidemia, and the proinflammatory state, are favorable to the development of cardiovascular diseases. With all that, some antipsychotics prolong the QT interval, so that can be an additional significant risk factor for the development of a cardiovascular incident (33). The most well-known “prolongers” of the QT interval include haloperidol, thioridazine and ziprasidone (34). They should not be combined together or given in a combination with lithium or tricyclic antidepressants (35). The insulin resistance with the damaged glucose tolerance, hypertension, dyslipidemia, and obesity, represent a cumulative risk of the cardiovascular diseases individually and in mutual combination. These conditions can additionally be induced by the antipsychotics use. The American Diabetes Association published a consensus (Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes) which points out that some antipsychotics are associated with the higher obesity risk, diabetes


type 2 and dyslipidemia. According to this publication, the ones with the highest risk are clozapine and olanzapine, those with a moderate risk are risperidone and quetiapine, and the lowest risk is borne by ziprasidone and aripriprazole (25). In this way, the second-generation antipsychotics, some more and some less, indirectly increase the risk of the cardiovascular diseases as well (36). Antidepressants Patients with bipolar affective disorder, like those with schizophrenia, are on average thicker than general population. Yet, it is difficult to distinguish weight gain as the consequence of disease and recovery from psychopharmacological effects. In bipolar affective disorder this is often even more difficult to differentiate due to frequent therapeutic combinations of antidepressants, antipsychotics and mood stabilizers (22). Each of them could influence changes in body mass and their combinations could have cumulative or nullifying effect. Unlike antipsychotics, the new generation of antidepressants has a lesser effect in causing metabolic syndrome than the old one because of significant pharmacodynamic selectivity (37). The prevalence and probability of inducing metabolic syndrome vary from one antidepressant to another. Amitriptyline has the greatest probability due to generating carbohydrate hunger with consequential weight gaining (around 4 kg in 1-6 months ) and insulin resistance development. The weight increase correlates with dosage and therapy duration. Imipramine and desipramine are less potent in inducing metabolic syndrome (about 2 kg in 1-6 months). After the treatment cessation the weight reduces but it remains above the weight prior treatment (22). IMAO effects on weight gain and other elements of metabolic syndrome vary from one drug to another – from phenelzine which mildly increases body weight (similar to imipramine) to moclobemide which induces almost no change at all. The SSRIs basically do not raise weight significantly, neither do the induce presence of features of metabolic syndrome. Moreover, they even mildly reduce body weight and for this reason the fluoxetine was trialed as weight loss agent for individuals with no psychiatric disorder. However, these SSRI effects are, without lifestyle alterations, cancelled through rebound effect during 6 months after the discontinuing therapy (38). Other SSRIs did not

show effects on weight reduction. When treating depression and anxiety with SSRIs there is initial weight loss and later on slight weight increase. The paroxetine is particularly known for causing mild increase in body weight (39). Among newly introduced antidepressants the most significant effect on weight increase was found for mirtazapine but this effect is still inferior to amitriptyline. Other novel antidepressants (venlafaxine, duloxetine, nefazodone, bupoprione ) have shown no effect on weight increase nor weight loss, although some of them (venlafaxine) are structurally similar to weight loss agent – sibutiramine, which is selective serotonin and noradrenaline reuptake inhibitor (22). Mood stabilizers With chronic administration, the lithium was found to cause certain increase in body weight, however this data vary from report to report. The usual rise is around 4 kg within two-year treatment. Rise in body mass has been greater in women compared to men suffering from bipolar disorder and in comparison with unipolar disorder regardless of a treatment outcome. Significant weight gain of 44-57% has been found in women taking sodium valproate for epilepsy when compared to men. Carbamazepine showed moderate weight increase similar to valproate effect. Lamotrigine and gabapentine did not manifest significant weight gain. Topiramate has been found to cause weight loss and is under investigation as a possible weight loss medication (22). PATHOPHYSIOLOGICAL MECHANISMS INVOLVED IN THE DEVELOPMENT OF METABOLIC SYNDROME AND USAGE OF PSYCHOTROPIC MEDICATIONS Pathological changes in body weight can occur for two reasons: psychoactive drugs can induce carbohydrate starvation with the consequence of excessive food intake, or in other case, the metabolism slows down. Insulin resistance induced by psychoactive drugs may be due to indirect effects of psychopharmacological drugs (causing abdominal type of obesity) or a direct action of these drugs on the production, transport and action of insulin. Different groups of and even different psychotropic drugs within the same group, encourage the development of metabolic syndrome using a variety of mechanisms (2,5).

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Antipsychotics Antipsychotics can increase body weight, encouraging the food intake by interfering with signals of being full-fed, or by reducing the need for physical activity. Pharmacodynamic explanation for weight gain with usage of some antipsychotics can be anchored in the fact that these drugs, beside blocking those receptors that mediate the antipsychotic effect, block the receptors that mediate control of food intake, the metabolic intensity or the intensity of physical activity of the organism. In general, alpha-adrenergic neurotransmission stimulates appetite, and beta-adrenergic, histaminergic, dopaminergic and serotonergic neurotransmission supports the feeling of being full-fed (19). In this sense, the initial weight loss with SRRIs is understandable due to increased transportation of serotonin, and a subsequent mild increase in weight can be explained by return to the initial weight before illness and by the anxiolytic effect of SRRIs. In administering clozapine and olanzapine, levels of circulating leptin are doubled at the beginning of the treatment, before the weight gain. This can be explained with the psychopharmacologic induced resistance to leptin. Thus, the increase in circulating leptin may not be a mere reflection of increased body fat in the body, but rather a consequence of psychotropic drug induced resistance to leptin and its compensatory increase in the blood. As leptin and insulin are key to the regulation of hunger and satiety and they are mutually coupled in this system, it is possible that psychopharmatics affect insulin resistance in this way, independently of weight gain. Haloperidol and second generation antipsychotics that do not cause weight gain, do not raise the concentration of leptin as well (22). Second generation antipsychotics increase the concentration of ghrelin. Raised concentration of ghrelin stimulates appetite and increases the food intake, what leads to weight gain. In the same sense, the second-generation antipsychotics affect the reduction of adiponectin concentrations with a consequent increase in insulin resistance. Pharmacodynamic profile of certain antipsychotics may indicate their possible effect on the weight gain. For example, olanzapine and clozapine block the H1, 5HT2C, and alpha-1 adrenergic receptors. Quetiapine blocks H1 and alpha-1 adrenergic receptors, but not the 5HT2C receptor, so it produces less effect on the body we-

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ight. The same goes for risperidone, which blocks alpha-1 adrenergic, but not H1 and 5HT2C receptors. Thus, the blockade of adrenergic (ά1), serotonergic (5HT2 and 5-HT2C), histaminergic (H1) transmission of certain neuropeptides in the role of neuromodulators (leptin, ghrelin) may increase the body weight (24). Those antipsychotic drugs that block more of these receptors have a greater effect on the weight gain. Antipsychotics can cause an insulin resistance in several ways: directly by increasing the resistance to insulin and/or through regional (abdominal) obesity. Type II diabetes can occur as a result of reduced sensitivity or toxic destruction of beta cells of the pancreas with the consequent reduction of available insulin (19). It is assumed that olanzapine and clozapine increase the risk of diabetes, usually via both mechanisms i.e. directly, by increasing the peripheral resistance to insulin and indirectly, by causing weight gain. Probably, different antipsychotics can cause hyperglycemia in different and multiple ways. This can be explained by their different power of inducing the diabetes. For example, olanzapine is associated with 37% of greater risk in developing diabetes, in comparison with risperidone (22). A greater risk of developing diabetes with olanzapine in comparison with risperidone may be associated with greater weight gain with the first antipsychotic drug, but also in relation to these direct effects of olanzapine on insulin resistance. In the case of clozapine, an increase in insulin resistance may be explained by increasing concentrations of TNF-α cytokines produced by adipocytes, what causes increased insulin resistance. The concentration of TNF-α levels increases only with those antipsychotic drugs that promote weight gain. As the increased concentrations of TNF-α occur early in the treatment, before weight gain, it has a predictive value for assessing the risk of obesity with specific antipsychotic (24). Antidepressants Antidepressants rarely cause metabolic syndrome unlike antipsychotics. The metabolic syndrome is more associated with old-generation antidepressants (TCAs), while for the new-generation this syndrome is rare. The term “Carbohydrate hunger” was introduced by Paykel in 1973, to describe the increased appetite in patients that were taking tricyclic antide-


pressants. In addition to causing hunger, TCA can cause weight gain and can slow down the metabolism, what is also described in their usage. Different patterns in increasing the body weight can be explained with different effects of TCA to noradrenergic, histaminergic, dopaminergic and serotonergic transmission. Strong anti-histaminergic effect of amitriptyline and doxepin, is responsible for the increase in body weight. In contrast, SSRIs, and their selective effect on the increase in transportation of serotonin, does not cause a significant increase in body weight, but can reduce it due to decreased feelings of hunger even in the first phase of treatment. The increase of leptin is not linked to antidepressants that increase body weight (amitriptyline, paroxetine, and mirtazapine). An increased TNF-α exists with amiriptilin and mirtazapine, but it is not recorded with fluoxetine, paroxetine, and venlafaxine (22). Insulin resistance in usage of TCA is associated with an increase in body weight. The direct effect of TCA on insulin resistance could not be detected in the treatment of depression, although it can be provoked experimentally by giving the TCA to animals. An interesting finding is that fluoxetine increases insulin action in patients with type II diabetes. It is generally considered that the risk of metabolic syndrome with SSRIs is very low. Mood stabilizers Mood stabilizers belong to different groups of drugs so their effect on the development of metabolic syndrome is often quite different. Sodium valproate causes weight gain accompanied by a rise in circulating leptin. The effect is similar to valproate and carbamazepine. Gabapentin and lamotrigine have no significant effect on body weight, and topiramate is decreasing it. Reports on the effects of lithium on glucose metabolism have been inconsistent, even contradictory. According to some results, it improves glucose metabolism, and according to other results, it weakens the tolerance toward glucosis (22). CLINICAL RECOMMENDATIONS Screening Identifying patients with metabolic syndrome or with the high risk of its occurrence is the first step in the prevention of the occurrence or in the worsening of existing metabolic syndrome. This

is achieved by determining patient’s risk profile (obesity, dyslipidemia, hyperglycemia, hypertension, smoking, physical inactivity, stress, unhealthy diet, hereditary factors) (19). Measuring waist circumference is the simplest and most sensitive method, which identifies 92% of patients with metabolic syndrome (22). Combination of measuring waist circumference and blood pressure, can identify 96% of patients, and combination of measuring waist circumference and blood glucose can identify all patients with metabolic syndrome. Guidelines of the American Diabetes Association (ADA) and American Psychiatric Association (APA) are more demanding and they require that body weight, waist circumference, blood pressure, fasting plasma glucose and lipid profile are checked in the screening (25). Also, patient’s personal and family tendency to obesity, diabetes, hypertension, dyslipidemia and cardiovascular disorders should be assessed. This screening should be done before treatment with psychoactive drugs, or soon after their introduction (40,41). Prevention One can approach psychopharmacological treatment after the identification of patients with the high risk of developing the metabolic syndrome and those with a diagnosis of metabolic syndrome. In the selection of psychopharmacological drugs, the degree of metabolic risks, which are associated with certain psychotropic, should be taken into account, listed in Table 1. If a patient still gets diabetes or excessive weight gain during the treatment, it is recommended to prescribe other, less risky antipsychotics, which are known not to cause metabolic abnormalities Table 1. Psychotropic medications and associated metabolic risk High risk

Antipsychotics

Moderate risk Low risk

clozapine, olanzapine, zotepin, quetiapine, risperidone, chlorpromazine, clopentixol, thioridazine, sulpiride perphenazine, trifluperazin

amitriptyline, doxepin, imipramine, Antidepressants clomipramine, maprotiline, nortriptyline, trimipramine

paroxetine, mirtazapine, desipramine, isocarboxazid

fluphenazine, haloperidol, flupentixol, amisulpride

phenelzine

Mood stabilizers lithium, valproate carbamazepine

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(19). If the existing diabetes worsens, the same procedure should be applied. In mild cases, the dose may be lowered, although this is neither safe nor a valid solution for all antipsychotics, especially not for antidepressants and mood stabilizers, thus it is not supported in the literature (22,40,41). Tracking The ADA (American Diabetes Association) recommends controlling glucose concentrations in healthy persons, starting from the age of 45, with repeated measurements every three years. If there are risk factors, the controls should begin earlier and should be practiced more often. Glucose levels should be controlled every three months in psychiatric patients on antipsychotics, and in those on clozapine and olanzapine they should be controlled more often (22,25). This attitude is supported by three other American professional associations (American Psychiatric Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity). Laboratory testing of serum lipids should be performed routinely once a year. A full range of lipids should be checked together with total cholesterol and its fractions. In antipsychotic drugs with a higher risk for cardiovascular disorders and hyperlipidemia (clozapine, olanzapine, quetiapine), screening should be done every 3 months during the first year, and later once a year, if the findings were normal (40,41). TREATMENT Lifestyle alterations and appropriate dieting should be the constituent part in treatment of psychiatric patients with metabolic syndrome. Pivotal role in guidance while maintaining certain diet should be carried by psychiatrist due to stress which, in general, these measures represent for psychiatric patients (19). Behavioral programs developed to ensure lifestyle modification are usually preformed according to previously established protocol regarding dietary measures and physical activity. Adding the weight loss drugs should be the extreme measure and always a part of integral treatment program for patients with BMI over 30 kg/m2 (22). The following drugs may be applied during the the-

186

rapy: ephedrine – beta adrenergic agonist used for weight reduction in combination with caffeine; sibutiramine – SNRI, primary designed as antidepressant with actions on central nervous system; orlistat – lipase inhibitor, reduces the fat reabsorption in intestines for 30%; topiramate – anticonvulsant, potentiates GABA activity and inhibits glutamate activity; cimetidine, nizatidine – peripheral histamine H2-receptor antagonists that inhibit stomach acid production and cause early satiety; naloxone – opiod antagonist, reduces appetite; metformin – oral antidiabetic drug, found to be useful in reducing excessive weight gain induced during treatment with second generation antipsychotic and sodium valproate; amatadine – dopamine agonist, antiparkinsonian, also investigated on patients taking antipsychotics; experimental leptin treatment – subcutaneous injections of recombinant leptin, in the long run, were found to reduce body mass. When administrating weight loss medications with psychoactive actions the possible adverse effects on pre-existing mental condition should be regarded. Surgical treatments in mentally ill patients could be recommended only for those with extreme obesity (BMI over 40 kg/m2 or with BMI over 35 kg/m2 and comorbidity ) (39). Patients with hyperlipidaemia should take medications for lowering serum lipid concentrations in order to diminish the risk of cardiovascular disease with possible fatal outcome. Finally, all these measures make sense only if the patient accepts them and follows the given instructions. Therefore, individual psychotherapeutic approach to mentally ill patient is an inevitable element of the therapeutic process. The cognitive behavioral approach with psychoeducation was found to be most effective (40). These psychotherapeutic interventions could be of greater help to psychiatric patient for weight reduction and diabetes prevention than taking weight loss medications, especially when conducted systematically in the treatment program (41). FUNDING No specific funding was received for this study. TRANSPARENCY DECLARATIONS Competing interests: none to declare.


REFERENCES 1.

2.

3. 4.

5. 6.

7. 8.

9.

10. 11.

12.

13.

14.

Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults. Executive summary of The third report of the national cholesterol education program (NCEP). Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult treatment panel III). JAMA 2001; 285:2486-97. Grundy SM, Brewer HB, Cleeman JI, Smith SC, Lenfant D, for the conference participants. Definition of metabolic syndrome: Report of the National, heart, lung, and blood institute/American Heart Association conference on scientific issues related to definition. Circulation 2004; 109:433-8 Olijhoek JK, van der Graaf Y, Haffner SM, Visseren FLJ, for the SMART study group. Eur J Inter Med 2007; 18:309-13. Ford ES, Giles WH, Deitz WH. Prevalence of the metabolic syndrome among US adults: findings form the Third national health and nutrition examination survey. JAMA 2002; 287:356-9. Meyer JM, Stahl SM. The metabolic syndrome and schizophrenia. Acta Psychiatr Scand 2009; 119:4-14 Saari KM, Lindeman SM, Viilo KM, Isohanni MK, Jarvelin MK, Lauren LH, Savolainen MJ, Koponen HJ. A 4-fold risk of metabolic syndrome in patients with schizophrenia: The Northern Finland 1966 birth cohort study. Psychiatry 2005; 66:559-63. Ryan MCM, Thakore JH. Physical consequences of schizophrenia and its treatment. The metabolic syndrome. Life Sci 2002; 71:239-57. Gavin III JR, Newcomer JW, Pi-Sunyer FX, Weiden PJ. New insights in diabetes and psychiatric illness: integrating management. http://www.medscape. com/viewprogram/2049_pnt Bauduceau B, Vachey E,Mayaudon H, Burnat P, Dupuy O, Garcia C, Ceppa F, Bordier L. Should we have more definitions of metabolic syndrome or simply take waist measurement? Diabetes Metab 2007; 33:333-9 Alberti KG, Zimmet P, Shwa J. The metabolic syndrome – a new worldwide definition. Lancet 2005; 366:1059-62. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BAGordon DJ, Krauss RM, Savage PJ, Smith Jr SC, Spertus JA, Costa F. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 2735-53. Fagiolini A, Frank E, Scott JA, Turkin S, Kupfer D. Metabolic syndrome in bipolar disorder: findings from the Bipolar disorder center for Pennsylvanians. Bipolar Disord 2005; 7:424-30. Vieweg WVR, Julius DA, Fernandez A, Tassone DM, Narla SN, Pandurangi AK. Posttraumatic stress disorder in male military veterans with comorbid overweight and obesity: psychotropic, antihypertensive, and metabolic medications. Prim Care Companion J Clin Psychiatry 2006; 8:25-31. American Diabetes Association, American Association Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes. Diabetes Care 2004; 27:596-601.

15. Muldoon MF, Mackey RH, Korytkowski MT, Flory JD, Pollock BG, Manuck SB. The metabolic syndrome is associated with reduced central serotoninergic responsivity in healthy community volunteers. J Clin Endocrinol Metab 2006; 91:718-21. 16. Aronne LJ. Epidemiology, morbidity and treatment of overweight and obesity. J Clin Psychiatry 2001; 62:13-22. 17. McIntyre RS, Mancini DA, Basile VS. Mechanisms of antipsychotics-induced weight gain. J Clin Psychiatry 2001; 62:23-9. 18. Haupt DW. Differential metabolic effects of antipsychotic treatments. Eur Neuropsychopharmacology 2006; 16:S149-55. 19. Palik E, Birkas KD, Faludi G, Karadi I, Cseh K. Correlation of serum ghrelin levels with body mass index and carbohydrate metabolism in patients treated with atypical antipsychotics. Diabetes Res Clin Pract 2005; 68S1:S60-4. 20. Correl CU, Frederickson AM, Kane JM, Manu P. Does antipsychotic polypharmacy increase the risk for metabolic syndrome? Schizophr Res 2007; 89:91-100. 21. Zimmermann U, Kraus T, Himmerich H, Schuld A, Pollmacher T. Epidemiology,implications and underlying drug-induced weight gain in psychiatric patients. J Psychiatr Res 2003; 37:193-220. 22. Henderson DC. Schizophrenia and commorbid metabolic disorders. J Clin Psychiatry 2005; 66:11-20. 23. Filaković P, Laufer D, Radanović-Grgurić Lj, Koić O, Fijačko M, Đurković M. Newer antipsychotics and glucose metabolism: a comparison between olanzapine and risperidone. Psychiatr Danub 2005; 17:63-6. 24. Lindenmayer J-P, Nathan A-M, Smith RC. Hyperglicemia associated with the use of atypical antipsychotics. J Clin Psychiatry 2001; 62:30-8. 25. American Diabetes Association, American Association Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes. Diabetes Care 2004; 27:596601. 26. De Hert M, Van Eyck D, Hanssens L, Peuskens H, Thys E, Wampers M, Scheen A, Peuskens J. Oral glucose tolerance test in treated patients with schizophrenia. Data to support an adaptation of the proposed guidelines for monitoring of patients on second generation antipsychotics? Eur Psychiatry 2006; 21:224-6. 27. Wang C, Zhang Z, Sun J, Zhang X, Mou X, Zhang X, Shang X,Zhang T. Serum free fatty acids and glucose metabolism, insulin resistence in schizophrenia with chronic antipsychotics. Biol Psychiatry 2006; 60:1309-13. 28. Peet M. The metabolic syndrome, omega-3 fatty acids and inflammatory processes in relation to schizophrenia. Prostaglandins, Leukot Essent Fatty Acids 2006; 75:323-7. 29. Sasaki J, Funakoshi M, Arakawa K. Lipids and apolipoproteins in patients treated with major tranquilisers. Clin Pharmacol Ter 1985;37:684-7. 30. Davidson S, Judd F, Jolley D, Hocking B, Thompson S, Hyland B. Cardiovascular risk factors for people with mental illness. Aust NZJ Psychiatry 2001; 35:196-202.

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31. Newman SC, Bland RC. Mortality in a cohort of patient with schizophrenia: a record linkage study. Can J Psychiatry 1991; 36:239-45. 32. Druss BG, Rosenheck RA, Desai MM, Perlin JB. Quality of preventive medical care for patients with mental disorders. Med Care 2002; 40:129-36. 33. Dixon L, Postrado L, Delahanty J, Fischer PJ, Lehman A. The association of medical commorbidity in schizophrenia with poor physical and mental health. J Nerv Ment Dis 1999; 187:496-502. 34. Dalmau A, Bergman Brismar B. Somatic morbidity in schizophrenia: a case control study. Public Health 1997; 111:393-7. 35. Akhtar S, Kelly C, Gallagher A, Petrie JR. Newer antipsychotic agents, carbohydrate metabolism and cardiovascular risk. Br J Diabetes Vasc Dis 2004; 4:303-9. 36. D’Mello DA, Narang S,Agredano G. Prevalence and consequences of metabolic syndrome in bipolar disorder. Psychiatric Times 2007; 24:1-3 http://www. psychiatrictimes.com/Bipolar Disease/showArticle. jhtm

37. Borrelli B, Spring B, Niaura R, Kristeller J, Ockene JK, Keuthen NJ. Weight suppression an weight rebound in ex-smokers treated with fluoxetin. J Consult Clin Psychol 1999; 67:124-31. 38. Hinze-Selch D, Schuld A, Kraus T, Kühn M, Uhr M, Haack M, Pollmaecher T. Effects of antidepressants on weight and on the plasma levels of leptin, TNFα and soluble TNF receptors: a longitudinal study in patients treated with amiprityline or paroxetine. Neuropsychopharmacology 2000; 23:13-9. 39. National Institute of Health. National heart lung and blood institute. Expert panel on the identification, evaluation, and treatment of overweight and obesity in adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. NIH Publication 1998; 98-4083 http:// www.nhlbi/nih/gov/ guidelines/obesity/ob. 40. Weber M, Wyne K. A cognitive/behavioral group intervention for weight loss in patients treated with atypical antipsychotics. Schizophrenia Research 2006; 83:95-101. 41. De Hert M, Schreurs V, Vancampfort D, Winkel RV. Metabolic syndrome in people with schizophrenia: a review. World Psychiatry 2009; 8:15–22.

Metabolički sindrom i psihofarmaci Pavo Filaković1,2, Anamarija Petek Erić1, Ljiljana Radanović-Grgurić1,2 Psihijatrijska klinika, Klinički bolnički centar Osijek, 2 Medicinski fakultet Osijek, Sveučilište “Josip Juraj Strossmayer” Osijek; Osijek, Hrvatska

1

SAŽETAK Metabolički sindrom je skup međusobno povezanih metaboličkih disfunkcija koje predstavljaju faktore rizika za razvoj dijabetesa i kardiovaskularnih poremećaja. Rezultati kliničkih studija sugeriraju značajan utjecaj nekih psihofarmaka na porast tjelesne težine i na pojavu dijabetesa tipa 2. Psihofarmaci mogu utjecati na porast tjelesne težine poticanjem unosa hrane i ometanjem sustava signalizacije sitosti. Uz neke psihofarmake javlja se: porast tjelesne težine, inzulinska rezistencija, dislipidemija, oštećena tolerancija glukoze/tip II dijabetes i hipertenzija. Porast inzulinske rezistencije i dislipidemija mogu biti posredna ili izravna posljedica učinka psihofarmaka. Autori su pregledali dostupnu literaturu u elektronskim bazama podataka unatrag 10 godina, kako bi procijenili učestalost metaboličkog sindroma u oboljelih od psihičkih poremećaja, te dali pregled dostignuća u utvrđivanju patofiziologije metaboličkog sindroma i doprinosa psihofarmaka njegovoj pojavi s posebnim osvrtom na patofiziološke mehanizme nastanka metaboličkog sindroma izazvanog psihofarmacima. Naposljetku, autori su objedinili preporuke za prevenciju i liječenje metaboličkog sindroma kod bolesnika koji se liječe psihofarmacima. Ključne riječi: antidepresivi, antipsihotici, patofiziologija, hiperlipidemija, diabetes melitus tip 2, hipertenzija

188

ORIGINAL ARTICLE

Erythrocyte sedimentation rate in acute myocardial infarction as a predictor of poor prognosis and impaired reperfusion Mehmet Fatih Ozlu1, Nihat Şen2, Mehmet Fatih Karakas2, Osman Turak3, Firat Ozcan3, Selcuk Kanat3, Dursun Aras3, Serkan Topaloglu3, Kumral Cagli 3, Mehmet Timur Selcuk3 Department of Cardiology, Abant Izzet Baysal University, School of Medicine, Bolu, 2 Department of Cardiology, Mustafa Kemal University, Tayfur Ata Sokmen Medical School, Hatay, 3Department of Cardiology, Yuksek Ihtisas Education and Research Hospital, Ankara; Turkey

1

ABSTRACT aim To investigate whether the elevated erythrocyte sedimentation rate (ESR) is associated with an adverse prognosis in the patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI). Methods It included 140 consecutive patients undergoing primary PCI for acute STEMI, 10 seconds). All angiograms were digitized to facilitate the subjective grading of TMPG also logarithmic nonmagnified mask-mode background subtraction was performed for eliminating noncontrast medium densities. Two invasive cardiologists who were blinded to the patients’ identity and data analyzed every case. The TMPGs were evaluated as previously defined by Gibson et al. (18). Briefly, if there is minimal or no myocardial blush, TMPG 0; if dye stains the myocardium and this stain persists on the next injection, TMPG 1; if dye enters the myocardium but washes out slowly so that dye is effectively persistent at the end of the injection, TMPG 2; and if normal entrance and exit of dye are in the myocardium so that dye is faintly persistent at the end of the injection, TMPG 3. TIMI grade 3 flow at the intervened coronary artery with a residual stenosis of < %20 was considered as successful PCI. CTFC for every case was calculated by the mean value of the two cardiologists’ measurements. In our study TMPG of 3 was accepted as normal myocardial perfusion, whereas 0,1 or 2 were abnormal. TMPG was assessed only in the area supplied by the culprit vessel. The intraobserver and interobserver variability of angiographic measurement (TFC and TMPG) were 2.5% and 8.5%, respectively. Standard 12-lead electrocardiograms (ECG) with a paper speed of 25 mm/s and amplification of 10 mm/mV were recorded on admission and 60 min after angioplasty by using a Cardiofax 9132 K (Nihon Kohden, Japan) ECG machine. The sum of ST segment elevations was measured on admission and after angioplasty to the nearest 0.025 mV, 20 ms after the end of the QRS complex from I, aVL and V1 to V6 leads for anterior myocardial infarction and leads II, III, aVF, V5 and V6 for inferior myocardial infarction as described previously (19). ST segment elevation resolution (STR) was defined as the ratio of the sum of ST segment elevations on the presen-

tation ECG to that on the ECG performed 60 min after PCI. The rate of improvement in ST elevation was defined as either complete resolution (70% or greater) or nonresolution (less than 70%) (19). STR was assessed by an investigator who was blinded to clinical, laboratory and angiographic findings of the patients. Echocardiography analysis A two-dimensional echocardiogram was performed in-hospital for the evaluation of LV ejection fraction (LVEF) by using modified Simpson’s technique. The analysis was made by two cardiologists who were blinded to the clinical and angiographic data. Adjunctive pharmacotherapy Every patient received 300 mg acetylsalicylic acid prior to intervention and unfractioned heparin during PCI. 600 mg loading dose, and subsequently 75 mg clopidogrel daily was given at least for two weeks. Decision for the use of glycoprotein IIb/IIIa receptor blockers was left at the initiative of the operator. Clopidogrel at a dose of 75 mg/day was prescribed to each patient for the time of at least one month. Clinical follow-up and study end points Clinical follow-up data were obtained from outpatient examination or by the investigators who made telephone contact with patients at about 1 year post PCI. Primary endpoint was the composite of MACE, including cardiac and non-cardiac death, target vessel revascularization (TVR) or non-fatal reinfarction, during hospitalization and at one year clinical follow-up. Reinfarction was defined as recurrent chest pain lasting for more than 30 minutes, associated with new Q waves or recurrent ST-segment elevation ≥ 0.1 mV in at least two contiguous leads and re-elevation of creatin kinase-MB to a minimum of double upper limit of the normal value and or more than 50% above the previous value after index procedure (20). TVR was described as repeating percutaneous intervention or coronary bypass grafting of any segment of the target vessel. The target vessels were defined as the whole major coronary artery proximal and distal to the target lesion including all branches and the target lesion itself (20) .

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Statistical analysis

Table 1. Baseline characteristics of study population*

Analyses were performed using SPSS software, Version 13.0, SPSS Chicago, USA. Continuous data were presented as median or mean ± SD. Differences in continuous variables between the groups were analyzed by t-test for variables with normal distribution and Mann-Whitney test for variables without normal distribution. The Kolmogorov-Smirnov test was used to test the normal distribution. Categorical variables were shown as percentages and compared with the chisquare test. The Spearman correlation coefficient was used to evaluate the association between two continuous variables.

Variable

Multivariable logistic regression analysis was applied to identify whether ESR level on admission was independently associated with TMPGdetected abnormal perfusion. At this scope, all variables showing a significant association with TMPG-detected abnormal perfusion at univariable analysis were included in the model. For univariate analyses, all variables of Table 1 were tested. Multivariate Cox regression analyses were used for the prediction of mortality and MACE at 1 year, in models including variables that were predictive by univariate analysis. Univariate correlations with p-values of < 0.1 were entered into multivariate models. Two models were tested, in the first model admission ESR was included as continuous variables. For the second model, ESR was included as categorical variables. The Kaplan-Meier technique was used to demonstrate the timing of events during long-term followup in relation to ESR level groups on admission, and statistical evaluation was performed by using the log-rank test. An investigative evaluation of additional cut-points was carried out using receiver-operating characteristics (ROC). A p-value < 0.05 was considered statistically significant.

Lower ESR group

Elevated ESR group

p

Number of patients 70 70 Age (yrs) 52.5 ± 8.7 53.1 ± 7.7 0.28 Gender (female/male) 20 / 50 18 / 52 0.24 Cigarette smoking, n (%) 35 (50) 30 (43) 0.21 Systemic hypertension, 17 (24) 15 ( 21) 0.33 n (%) Diabetes mellitus, n (%) 13 (19) 14( 20) 0.02 Total Cholesterol (mg/ 180 ± 32 176 ± 34 0.59 dl) LDL Cholesterol (mg/dl 112 ± 29 107 ± 33 0.29 HDL Cholesterol (mg/dl) 35 ± 6 33 ± 5 0.13 Triglycerides(mg/dl) 161 ± 72 164 ± 83 0.68 Creatinine (mg/dl) 0. 82 ± 0.21 0.88 ± 0.28 0.22 Peak CK-MB (ng/ml) 273 ± 110 280 ± 105 0.46 Peak troponin I (ng/ml) 55 ± 30 59 ± 29 0.43 Hs-CRP (mg/dl) 0.90 (0.65-1.67) 1.65 (1.05-3.15) < 0.01 Prior MI, (%) 15 17 0.55 Prior aspirin use, (%) 20 22 0.74 Prior ACE inh. use, (%) 21 20 0.76 Prior statin use, (%) 15 17 0.56 Anterior wall MI, (%) 35 38 0.37 Multivessel disease,% 16 15 0.76 Time to reperfusion, h 4.5 ± 4.0 4.7 ± 3.8 0.39 TIMI risk score 2 (1-4) 2 (1-5) 0.16 Killip class, (%) I 73 74 0.72 II 18 16 0.66 III 7 8 0.71 IV 2 2 0.79 IRA, % LAD 35 38 0.01 RCA 46 47 0.11 LCx 19 15 0.58 Stent utilization, % 99 98 0.92 Tirofiban administra60 64 0.33 tion, % *Data shown are n (%), median (IQR) or mean ± SD. ESR, erythrocyte sedimentation rate; HDL, high-density lipoprotein; LAD, left anterior descending coronary artery; LCx,left circumflex coronary artery; LDL, low-density lipoprotein; Hs-CRP, high sensitivity C-reactive protein; MI, myocardial infarction; RCA, right coronary artery.

RESULTS Baseline characteristics Erythrocyte sedimentation rate levels were higher in patients with STEMI than in the control group subjects (Figure 1). This study included 140 patients with STEMI. Median ESR was 24 mm/h (interquartile range: 17–38). Therefore, the elevated ESR group was defined as patients ha-

192

Figure 1. Comparison of patients with STEMI and control values for ESR

ving ESR ≥ 24 mm/h and lower ESR group was defined as patients having ESR < 24 mm/h. De-

Ozlu et al Erythrocyte sedimentation in myocard infarction

Table 2. Angiographic, electrocardiographic, echocardiographic results, and clinical outcomes of lower and elevated ESR groups Lower Elevated ESR group ESR group Success rate of PCI (%) Final TIMI flow grade (after PCI) = 3 (%) TIMI frame count LAD CX RCA Mean TIMI frame count ST segment elevation resolution (%) Abnormal perfusion (TMPG 0-2) (%) LV EF In-hospital Deaths n,(%) MACE n,(%) At one-year follow up Deaths n,(%) MACE n,(%)

p

95

94

0.62

80

86

0.23

24.7 ± 7.3 19.8 ± 4.2 16.8 ± 4.4 20.4 ± 5.2

33.7 ± 8.1 < 0.01 23.4 ± 5.9 0.01 19.1 ± 4.5 0.11 25.5 ± 6.5 < 0.01

86

68

< 0.01

29

55

< 0.01

45 ± 6

40 ± 7

< 0.01

1 (1) 3 (4)

6 (9) 10 (14)

0.04 0.02

3 (4) 9 (13)

11 (16) 18 (26)

0.02 0.01

PCI, percutaneous coronary intervention; TIMI, thrombolysis in myocardial infarction; LAD, left anterior descending coronary artery; LCx, left circumflex coronary artery; RCA, right coronary artery; LV EF, left ventricular ejection fraction; TMPG, TIMI myocardial perfusion grade; MACE, major adverse cardiac events.

mographic and clinical characteristics are shown in Table 1. There was no significant difference between groups regarding baseline characteristics (age, gender), TIMI risk score and reperfusion times. Elevated ESR group were greater admission serum hs-CRP compared to patients from the lower ESR group (Table 1). Angiographic characteristics There were no statistically significant differences between the two groups in terms of frequency of TFGs 3 in the infarct related artery after PCI, however, LAD, CX artery TIMI frame count and

Figure 2. Kaplan-Meier curves for one year mortality according to ESR.

Table 3 . Significant predictors of mortality at one-year follow up in univariable and stepwise multivariable Cox regression analyses Variable

Univariable HR (95 % CI) p

ESR as a continuous variable (Model 1) TIMI risk score 1.30 (1.14-1.39) 0.05 109.3 ± 35.3 114.1 ± 34.9

114.9 ± 31.5

p > 0.05

47.1 ±12.7 3.8 ± 0.03

45.6 ± 11.4 3.8 ± 0.03

p > 0.05

44.6 ± 10.1 3.6 ± 0.03

187.6 ±147.8 172.2 ± 105.9 195.2 ± 154.3 5.1 ± 0.1 5.0 ± 0.1 5.0 ± 0.1 p > 0.05 197.3 ± 41.6 211.8 ± 176.4 194.2 ± 43.1 p > 0.05

HbA1c (%) Unadjusted 7.4 ± 1.5 7.8 ± 1.7 Adjusted 1.9 ± 00.2 2.0 ± 00.2 SBP 135.6 ± 23.3 134.7 ± 24.1 (mm-Hg) DBP 86.3 ± 14.7 85.6 ± 13.9 (mm-Hg) ACR (mg/g) Unadjusted 42.9 ± 148.6 47.1 ± 104.4 Adjusted 1.8 ± 0.2 2.5 ± 0.2

7.7 ± 1.9 2.0 ± 0.03

p > 0.05

137.2 ± 22.5 p > 0.05 86.4 ± 15.1

p > 0.05

62.2 ± 265.9 2.3 ± 0.3 0.028

SD, standard deviation; ACR, albumin-creatinine ratio; HbA1c, glycohemoglobin; BMI, body mass index; FBG, fasting blood glucose; PBG, post-prandial glucose; LDL-chol, light density lipoprotein cholesterol; HDL-chol, high density lipoprotein cholesterol; TG, triglycerides; SBP, systolic blood pressure, DBP, diastolic blood pressure

Table 4. Categorical distribution of patients in glycemic control and diabetic nephropathy according to group distribution Values HbA1c (%)* < 6.5 6.5- 7.5 ≥ 7.5 ACR* < 30 mg/g 30-300 mg/g ≥ 300 mg/g

Number of (%) of patients Group 1 Group 2 Group 3 (n = 111) (n = 133) (n = 105)

p

36 (34.5) 41 (39.9) 34 (30.6)

30 (22.6) 46 (34.6) 57 (42.9)

27 (25.7) 32 (30.5) 46 (43.8)

0.601

89 (80.9) 17 (15.5) 4 (3.6)

92 (79.3) 19 (16.4) 5 (4.3)

92 (74.8) 24 (19.5) 7 8 (5.7)

0.551

*ADA: guideline for HbA1c and criteria for ACR was used; HbA1c, glycohemoglobin; ACR, albumin-creatinine ratio

Baltaci et al Self-monitoring blood sugar in diabetic patients

DISCUSSION The results of this study have shown that regular use of SMBG was not effective for glycemic control, but it seemed to be effective on prevention of diabetic complications, particularly diabetic nephropathy. The present study indicated that self-monitoring of blood glucose at home was not effectively used and it had no significant effect on metabolic control and prevention of complications in patients with T2DM. Majority of Turkish diabetic patients have one of the tools such as glucometer for SMBG, and most of them have irregularly used it. Although no significant difference was found in glycemic control and development of complications, it was observed that the more frequent SMBG, the better glycemic control and the less complications developed. In the study, it was observed that the patients with higher education level were more likely to regularly use SMBG. It confirmed that educating the diabetic patients increases their harmony for glycemic and metabolic control. Low literacy is common among diabetic patients and associated with poor knowledge about DM (11, 22). Scillinger et al. found that patients with type 2 diabetes who had inadequate health literacy were independently associated with worse glycemic control and higher rates of retinopathy (23). Similarly, this study has found that the patients with higher education level had significantly poor glycemic control and the number of patients with microalbuminuria and complications was higher (data not shown). Meanwhile, the ratio of current smokers was observed as higher among patients who have never and irregularly used SMBG, compared to those who have regularly used it. It suggested that diabetic patients with low education level or who were less aware of their DM were more likely to heed. Results consistent with our study have been shown in numerous studies. Farmer et al. did not show significant difference in HbA1c levels between diabetic patients performing and performing SMBG (24). In several studies, the relation between frequency of SMBG and metabolic control in patients with diabetes mellitus type I and II was investigated. Whether self-monitoring of blood glucose can improve glycemia is subject to debate and controversial in type II diabetes mellitus without insulin treatment (25, 26). Davidson

et al. reported that HbA1c level decreased for 0.2 % in patients with type 2 DM in SMBG group, compared to non-SMBG group (27). Stratton et al. found that HbA1c level statistically decreased for 0.39% in patients with type 2 DM in SMBG group, compared to control group (2/). Chubb et al. provided that SMBG data was predictive for both FBG and HbA1c in patients with type 2 DM (29). On the other hand, Meier et al. reported that SMBG more than twice a week was not effective in glycemic control in patients with type 2 (30). O’Kane et al. also found that SMBG had no effect on glycemic control in patients with newly diagnosed type 2 diabetes mellitus (31). Among our patient groups, there was approximately 0.20.3 % difference in mean HbA1c level, although it was not significant. Bajkowska-Fiedziukiewicz et al. found no correlation between frequency of SMBG and HbA1c level (32). Similarly, no correlation of SMBG frequency and HbA1c level was found in the study. In contrast, McIntosh et al. reported in a meta-analysis of 2010 that self-monitoring of blood glucose levels was associated with a modest, statistically significant reduction in hemoglobin A1c concentrations, regardless of whether patients were provided with education on how to interpret and use the test results (33). Microalbuminuria indicates early, reversible, diabetic nephropathy. The random urine ACR is a convenient effective screening test, which in the 30 to 300 (mg/d) indicate microalbuminuria (34). Levin et al. reported that intensive glycemic control retards microalbuminuria in patients who have had type 2 DM for several years but may not lessen the progressive deterioration of glomerular function (35). In this study, it was found that ACR in patients in group 1 was lower than in other two groups. Ozmen et al. reported that there was no relation between SMBG implementation and complications such as nephropathy and neuropathy, but between HbA1c and SMBG implementation (17). The mean ACR among the patients in group 1 was significantly different from the group 2 and group 3, but no significant difference was observed between the group 2 and group 3 in this study, and no correlation between SMBG frequency and ACR was found. Despite the low ratio of patients with albuminuria who had regularly used SMBG, it was not statistically significant.

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Based on screening literature, there were a few studies on effectiveness of SMBG on glycemic control in Turkish type 2 diabetic patients. Ozgur et al. conducted a study with 94 type 2 diabetic patients, and reported that HbA1c level was affected by SMBG frequency (18). Aydin et al. found that glycemic control could be more achieved with increased SMBG frequency in insulin treated patients with type 2 DM (36). The study limitations include the use of cross-sectional and observational data with shortterm, unknown levels of patient adherence, and assumptions regarding the duration of clinical outcomes. The study included non-homogeneous educational level of patients. Those were also a weak side of the study. The strong side of the study was that effectiveness of SMBG was not only evaluated with glycemic control, but also

with metabolic control parameters and status of complications development. In conclusion, there was significant difference in mean albumin-creatinine ratio between regular SMBG group and both irregular/never use of SMBG, but there was no significant difference in the status of overall developed diabetic complications and glycemic control among the groups. Therefore, it could suggest that SMBG should be recommended for type 2 diabetic patients with high education level, treated with oral regimens rather than insulin therapy, to achieve our purpose of the use of SMBG. FUNDING No specific funding was received for this study. TRANSPARENCY DECLARATIONS Competing interests: none to declare.

REFERENCES 1.

2.

3.

4.

5.

6.

7.

216

Peel E, Parry O, Douglas M, Lawton J. Blood glucose self-monitoring in non-insulin-treated type 2 diabetes: a qualitative study of patients’ perspectives. Br J Gen Pract 2004; 54:183-8. Simon J, Gray A, Clarke P, Wade A, Neil A, Farmer A; Diabetes Glycaemic Education and Monitoring Trial Group. Cost effectiveness of self monitoring of blood glucose in patients with non-insulin treated type 2 diabetes: economic evaluation of data from the DiGEM trial. BMJ 2008; 336:1177-80. Demir D, Bucaktepe GE, Kara IH. The Comparing of sociodemographic features, anthropometric and biochemical parameters of the cases with metabolic syndrome, type 2 diabetes mellitus and healthy controls. Konuralp Medical Journal 2010; 2:12-9. Franciosi M, Pellegrini F, De Berardis G, Belfiglio M, Di Nardo B, Greenfield S, Kaplan SH, Rossi MC, Sacco M, Tognoni G, Valentini M, Nicolucci A. QuED Study Group--Quality of Care and Outcomes in Type 2 Diabetes. Self-monitoring of blood glucose in non-insulin-treated diabetic patients: a longitudinal evaluation of its impact on metabolic control. Diabet Med 2005; 22:900-6. Guerci B, Drouin P, Grangé V, Bougnères P, Fontaine P, Kerlan V, Passa P, Thivolet Ch, Vialettes B, Charbonnel B; ASIA Group.Self-monitoring of blood glucose significantly improves metabolic control in patients with type 2 diabetes mellitus: the AutoSurveillance Intervention Active (ASIA) study. Diabetes Metab 2003; 29:587-94. Davis WA, Bruce DG, Davis TM. Is self-monitoring of blood glucose appropriate for all type 2 diabetic patients? The Fremantle Diabetes Study. Diabetes Care 2006; 29:1764-70. Saudek CD, Derr RL, Kalyani RR. Assessing glycemia in diabetes using self-monitoring blood glucose and hemoglobin A1c. JAMA 2006; 295:1688-97.

8.

9. 10.

11.

12.

13.

14.

Schütt M, Kern W, Krause U, Busch P, Dapp A, Grziwotz R, Mayer I, Rosenbauer J, Wagner C, Zimmermann A, Kerner W, Holl RW; DPV Initiative. Is the frequency of self-monitoring of blood glucose related to long-term metabolic control? Multicenter analysis including 24,500 patients from 191 centers in Germany and Austria. Exp Clin Endocrinol Diabetes 2006; 114:384–8. Aspinall SL, Glassman PA. Cost-effectiveness of blood glucose monitoring is controversial. Am J Manag Care 2008; 14: 398-9. Franciosi M, Pellegrini F, De Berardis G, Belfiglio M, Cavaliere D, Di Nardo B, Greenfield S, Kaplan SH, Sacco M, Tognoni G, Valentini M, Nicolucci A; QuED Study Group. The impact of blood glucose self-monitoring on metabolic control and quality of life in type 2 diabetic patients: an urgent need for better educational strategies. Diabetes Care 2001; 24: 1870-7. Cameron C, Coyle D, Ur E, Klarenbach S. Cost-effectiveness of self-monitoring of blood glucose in patients with type 2 diabetes mellitus managed without insulin. CMAJ 2009; 182:28-34. Tunis SL, Minshall ME. Self-montoring of blood glucose in type 2 diabetes mellitus: cost-effectiveness in the United States. Am J Manag Care 200; 14:131-40. Simon J, Gray A, Clarke P, Wade A, Neil A, Farmer A; Diabetes Glycaemic Education and Monitoring Trial Group. Cost-effectiveness of self-monitoring of blood glucose in patients with non-insulin treated type 2 diabetes: economic evaluation of data from DİGEM trial. BMJ 2008; 336:1177-80. Harris MI. Frequency of blood glucose monitoring in relation to glycemic control in patients with type 2 diabetes. Diabetes Care 2001; 24:979-82.

Baltaci et al Self-monitoring blood sugar in diabetic patients

15. Rothman RL, DeWalt DA, Malone R, Bryant B, Shintani A, Crigler B, Weinberger M, Pignone M. Influence of patient literacy on the effectiveness of a primary care-based diabetes disease management program. JAMA 2004; 292:1711-6. 16. McGeoch G, Derry S, Moore RA. Self-monitoring of blood glucose in type-2 diabetes: what is the evidence? Diabetes Metab Res Rev 2007; 23:423–40. 17. Ozmen B, Boyvada S. The relationship between self-monitoring of blood glucose control and glycosylated haemoglobin in patients with type 2 diabetes with and without diabetic retinopathy. J Diabetes Complications 2003; 17:128-34. 18. Ozgur R, Mavis O, Ayalp P. The relationship between self monitoring of blood glucose frequency and HbA1c in patients with type 2 diabetes Mellitus. Okmeydani Tip Dergisi 2011; 27:70-75. 19. Lohman TG, Roche AF, Martorell R, editors. Anthropometric Standardization Reference Manual. Kinetics Books, Champaign, Illinois, 1988; 1-12. 20. American Diabates Association Position Statement: Standarts of Medical Care in Diabetes. Diabetes Care 2004; 27(Suppl 1):15-35. 21. ADA Standards for accessible design http://www. ada.gov/2010ADAstandards_index.htm (September 2010) 22. Kicklighter JR, Stein MA. Factors influencing diabetic clients’ ability to read and comprehend printed diabetic diet material. Diabetes Educ. 1993; 19: 40–6. 23. Schillinger D, Grumbach K, Piette J, Wang F, Osmond D, Daher C, Palacios J, Sullivan GD, Bindman AB. Association of health literacy with diabetes outcomes. JAMA 2002; 288:475–82. 24. Farmer A, Wade A, Goyder E, Yudkin P, French D, Craven A, Holman R, Kinmonth AL, Neil A. Impact of self monitoring of blood glucose in the management of patients with non-insulin treated diabetes: open parallel group randomised trial. BMJ 2007; 335:132. 25. Monnier L, Colette C, Lapinski H, Boniface H. Selfmonitoring of blood glucose in diabetic patients: from the least common denominator to the greatest common multiple. Diabetes Metab 2004; 30:113-9. 26. Martin S, Schneider B, Heinemann L, Lodwig V, Kurth HJ, Kolb H, Scherbaum WA. Self-monitoring of blood glucose in type 2 diabetes and long-term outcome: an epidemiological cohort study. Diabetologia 2006; 49:271-8.

27. Davidson MB, Castellanos M, Kain D, Duran P. The effect of self monitoring of blood glucose concentrations on glycated hemoglobin levels in diabetic patients not taking insulin: a blinded, randomized trial. Am J Med 2005; 118:422-5. 28. Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, Hadden D, Turner RC, Holman RR. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 2000; 321:405-12. 29. Chubb SA, Van Minnen K, Davis WA, Bruce DG, Davis TM. The relationship between self-monitoring of blood glucose results and glycated haemoglobin in type 2 diabetes: the fremantle diabetes study. Diabetes Res Clin Pract 2011; 94:371-6. 30. Meier JL, Swislocki AL, Lopez JR, Noth RH, Bartlebaugh P, Siegel D. Reduction in self-monitoring of blood glucose in persons with type 2 diabetes results in cost savings and no change in glycemic control. Am J Manag Care 2002; 8:557-65. 31. O’Kane MJ, Bunting B, Copeland M, Coates VE; ESMON study group. Efficacy of self monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): randomized controlled trial. BMJ 2008; 336: 1174-7. 32. Bajkowska-Fiedziukiewicz A, Cypryk K, Kozdraj T, Mikołajczyk-Swatko A, Kosiński M, Józefowska M. American Diabates Association Position Statement: Standarts of Medical Care in Diabetes. Diabetes Care 2004; 27(Suppl 1):15-35. 33. McIntosh B, Yu C, Lal A, Chelak K, Cameron C, Singh SR, Dahl M. Efficacy of self-monitoring of blood glucose in patients with type 2 diabetes mellitus managed without insulin: a systematic review and meta-analysis. Open Med 2010; 4:e102-13. 34. Emancipator K. Laboratory diagnosis and monitoring of diabetes mellitus. Am J Clin Pathol 1999; 112:665-74. 35. Levin SR, Coburn JW, Abraira C, Henderson WG, Colwell JA, Emanuele NV, Nuttall FQ, Sawin CT, Comstock JP, Silbert CK. Effect of intensive glycemic control on microalbuminuria in type 2 diabetes. Veterans Affairs Cooperative Study on Glycemic Control and Complications in Type 2 Diabetes Feasibility Trial Investigators. Diabetes Care 2000; 23:1478-85. 36. Aydin H, Deyneli O, Yavuz D, Tarcin O, Akalin S. Does the frequency of self-monitoring blood glucose influence glycemic control in patients type 2 diabetic patients? Marmara Medical Journal 2005; 18: 13-16.

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ORIGINAL ARTICLE

Evaluation of cortisol level and cell-mediated immunity response changes in individuals with post-traumatic stress disorder as a consequence of war Abbas Masoudzadeh1, Mona Modanloo Kordi2*, Abolghasem Ajami3, Anooshiravan Azizi4 Department of Psychiatry & Research Center & Behavioral Sciences, Mazandaran University of Medical Sciences, 2Mazandaran University of Medical Sciences, 3Immunology Department, School of Medicine, Mazandaran University of Medical Sciences; Sari, 4Private Psychiatrics Practice, Bandarabbas; Iran 1

ABSTRACT Aim To investigate the level of blood and urine cortisol and cell mediated immunity response changes among patients with posttraumatic stress disorder resulting from war. Method In this case-control study, 20 patients with post traumatic stress disorder (PTSD) with the mean age of 41.9+7.6 and 20 healthy individuals (control group) with the mean age of 42.4+7.6 were compared. At the beginning, 24-hour urine and blood samples were obtained, and three antigens, tuberculosis, tetanus and candida were injected sub-cutaneously. Skin reaction was evaluated for each of the injections. Analysis was performed using t-test. Corresponding author: Mona Modanloo Kordi Education Development Center, Mazandaran University of Medical Sciences P.O.Box: 48157-33971, Sari, Mazandaran, Iran Phone: +98 911 152 04 10; fax: +98 15 12 273 689; Email: [email protected]

Results There was a significant increase regarding cell-mediated immunity in cases in comparison with the controls (p =0.017) and also a significant increase of blood cortisol was observed in cases (p = 0.003). There was no significant difference in two groups regarding urine cortisol level. Conclusion This study showed that there was a significant difference in the activation of cell-mediated immunity in PTSD patients as compared to the control group. This increase in activity was not due to the influence of life stressors or intensity of illness signs or following illnesses. It is recommended to study and treat the autoimmune disease in PTSD patients more seriously in the countries like Iran that were involved in war problems. Key words: tuberculosis, tetanus, candida, war

Original submission: 02 March 2012; Accepted: 15 May 2012.

Med Glas Ljek komore Zenicko-doboj kantona 2012; 9(2):218-222

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Masoudzadeh et al Cortisol level and cell-mediated immunity

INTRODUCTION For the first time in 1964 Hans Style described stress by harmful stimulant (1). Later on, it was known to affect immune function and influence susceptibility to different illnesses (2, 3). Post Traumatic Stress Disorder (PTSD) develops in response to exposure to a traumatic event during which an individual feels extremely fearful, horrified or helpless (4). Those exposed to war trauma report a higher incidence of illness (5). There are few studies that evaluate the cell mediated immunity of PTSD patients (6-8). The first study was conducted by Watson et al (1993) on soldiers who participated in the Vietnam War suffering from PTSD. It showed an increase in cellmediated immunity response in PTSD patients as compared to the control group (6). Another study by Altemus et al, which was done on 16 PTSD women (due to trauma of sexual abuse in childhood), showed the increase in cell-mediated immunity activity in cases as compared to controls (7). In another study that was done during the Persian Gulf War, an increase in NKcell and cell-mediated immunity (CMI) was reported, and the scale of NKcell and CMI returned to the original position with the passage of time (8). In a recent study conducted in 2010 on women suffering from PTSD due to violent sexual relationship with their sexual partner, immunity level in relation to HSV-1 virus higher than control group was reported (9). Although most studies have been in favor of plasma and urine cortisol reduction in PTSD patients (10), the recent studies have not shown a significant difference in the level of urine and plasma cortisol in PTSD patients compared with control group (11,12). In human body, cell-mediated immunity response (CMI) is measured with different methods. One of the main methods is usage of skin reaction to recall antigens. In this method, recall antigens are injected intra dermal. Then cell-mediated immunity response evaluated by a degree of induration in millimeters, 48 hours after the application in the area of injection (13,14). Considering many differences in relation to immunity response level in patients with PTSD in the past studies and also many years of country’s involvement in the war and many chronic PTSD patients, for the first time in the country this study

evaluates the cell-mediated immunity “CMI”. The main advantage of this study as compared with previous studies is using Holmes – Rahe table in two groups of patients and control. Holmes-Rahe is a scale that measures the role of life stressors leading to illnesses (15). In this design, in addition to study of cell-mediated immunity, the scale of blood and urine cortisol considering different reports and also conflicting reports were compared within two groups of patients and control. PATIENTS AND METHODS This case-control study was conducted during November 2009-January 2010 on a total of 20 male individuals from the documented PTSD patients related to the war that were referred to Esar-Garan Institute’s Clinic in Sari(Iran). They were volunteers who participated in the Iran-Iraq war. Cases were selected based on clinical interview by a senior psychiatry assistant with supervision of a psychiatrist and on DSM4-TR criteria (16). Also the Persian translation version of PSS (PTSD Symptom Scale) questionnaire was completed by the volunteers to approve the diagnosis. PSS is a semi-structural diagnostic interview that was designed by Foe and his colleagues in 1993 and is designed for the diagnosis of PTSD and assessment of its intensity signs according to DSM –III-R and DSM –IV-IR (17, 18). All of them were within their chronic phase of disorder (more than 15 years). Also they did not have a history of PTSD before the war. Control group was also selected from available volunteers in clinics who neither had a history of PTSD nor the presence in war. The exclusion criteria included history of cigarette smoking, alcohol, history of autoimmune diseases and active medical illnesses. The case and control group matched in age. All patients gave their written informed consents before being included in this study. At the beginning, 24 hours urine samples from case and control groups were obtained. Then, blood samples were taken at around 8-9 AM from all patients and control groups by 5cc syringe. Drawn samples were sent to the laboratory less than half an hour after the sampling. After drawing blood samples, the patients were injected with recall antigens (including tuberculosis, tetanus toxoid and candida Ag) intradermal and

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measuring 0.1 mL in three areas of one hand (preferably left hand) using insulin syringe at the same time. The level of skin swelling in three areas was measured in millimeters with a grading rule after 48 hours. The sampling was done by a senior psychiatry assistant with supervision of an immunologist. The patients and the control group were asked to complete Holmes-Raheh and General Health Quality (GHQ) questionnaires with thorough explanation following the measurement of the level of skin swelling. The questionnaire GHQ-28 designed by Goldberg Hilber in 1972, to study mental health situation of individuals in society, was also used (15). GHQ-28 test, which has 28 questions, is graded in four dimensional scales (physical complaints, sign of stress and sleep disorder, sign of social function and sign of depression) and with grading in likert method (3-0), the test result may be within the range of 0 to 84 (15). The study protocol was approved by the Ethics Committee of Mazandaran University of Medical Sciences. All participants gave their written informed consents before participating in the study. Data processing was done via SPSS.16 and data analysis was performed through T-test. P