目的1)發現與中風相闋的視網膜特徵2) 利用視網膜特徵建立統計模型對老年人中風風險進行分類。 / 方法:配對病例對照研究。病例為中風患者，一部分中風患者來自於糖尿病眼病的篩查項目，另外一部分是腦內科的中風患者。對照是沒有中風的老年人。對照來自糖尿病眼病篩查項目內沒有患中風的患者及在眼科門診沒有中風及特殊眼病的患者。對照與病例在年齡及是否患有糖尿病進行匹配。所有研究對象均來自香港威爾斯親王醫院。我們收集所有研究對象的中風危險因素，包括年齡，性別，吸煙，及是否患有糖尿病，高血壓，缺血性心髒病，心房顫動，高血脂。所有研究對象的彩色視網膜照片都被採集。我們應用軟件“ImageJ"分析並記錄視網膜動靜脈直徑，血管分叉係數，分叉角度，分叉對稱性，視乳頭周長。我們也記錄其他視網膜特徵，如動靜脈壓跡，出血，硬性滲出，動脈阻塞及血管彎曲性。獨立t檢驗用於對連續變量的單因素分析，卡方檢驗用於對分類變量的單因素分析。Logistic 回歸用於建立統計模型對中風風險進行分類。所有統計方法均應用SPSS16.0 軟件。 / 結果:本研究納入122 中風患者及122 例患者做對照。每組分別有81 例糖尿病患者， 41 例非糖尿病患者。視網膜特徵包括動靜脈直徑，血管彎曲度，出血，硬性滲出，動靜脈壓跡在兩組中有顯著性差異。我們建立風險模型對兩組患者進行風險分類。分類準確度最高達的模型裡面包括的因子有：1)中風相關危險因素包括:高血壓，糖尿病，心房顫動2) 視網膜特徵包括:動脈直徑，血管彎曲性，出血，動靜脈壓跡跟靜脈對稱性；3) 視網膜特徵間的交立作用包括:動脈直徑與靜脈對稱性，動脈直徑與出血，靜脈對稱性與血管彎曲度。分類的準確度為80 .4%。只包括視網膜特徵的分類模型的準確度為74.5% 。 / 結論:彩色視網膜照相可成為中風風險的分類工具。與中風相關的視網膜特徵包括血管直徑，血管彎曲度，血管對稱性，出血，動靜脈壓跡。視網膜特徵與中風之間的聯繫存在交互作用。 / Objective: 1) To detect retina characteristics that associated with stroke; 2) To develop a statistics model with variables of retina characteristics for classifying patients with stroke from those without stroke in aged population. / Method: Matched case control study. Patients with stroke from the diabetic retinopathy screening program and stroke patients from Acute Stroke Unit were selected as stroke cases. Controls (patients without history of stroke) with matched diabetes status and age were selected from the diabetic retinopathy screening program and eye outpatient clinics. All subjects in this study were from Prince of Wales Hospital, Hong Kong. Risk factors of stroke from all subjects were collected, including age, gender, diabetes, hypertension, hyperlipidemia, history of ischemic heart disease, atrial fibrillation and smoking. Color retina images of each subject were collected and analyzed. The retina characteristics, including diameters of arterioles and venules, bifurcation coefficients, bifurcation angles, branch symmetry, optic disc perimeter were extracted from the color retina images by software "ImageJ". Other retina characteristics including arteriole-venule nicking, hemorrhages, exudates, arteriole occlusion, and vessel tortuosity were also recorded. Independent t test and Chi-squire test were used to compare the continuous and categorical retina characteristics respectively between patients with stroke and those without stroke. Logistic model combining the risk factors of stroke and retina characteristics was established to classify patients with stroke from those without stroke. All data analysis was by SPSS 16.0. / Results: there were 122 stroke cases and 122 controls recruited in this study. There were 41 patients without diabetes and 81 patients with diabetes in each group. Retina characteristics including diameters of arterioles and venules, vessel tortuosity, hemorrhages, exudates, arteriole-venule nicking were significantly different between the two groups. We established risk models to classify patients with stroke from those without stroke. The risk model with highest accuracy of classification included 1) stroke risk factors including hypertension, diabetes and atrial fibrillation; 2) retina characteristics, including arteriole diameters, vessel tortuosity, hemorrhages, arteriolevenule nicking and venule symmetry; 3)interaction between retina characteristics, including arteriole diameters by venule symmetry, arteriole diameters by hemorrhage,and venule symmetry by vessel tortuosity. The accuracy of classification was 80.4%. Using retinal characteristics alone achieved an accuracy of 74.5%. / Conclusion: color retina images are a potential tool for stroke risk stratification. Useful characteristics found in the retinal images included vessel diameters, vessel tortuosity, vessel symmetry, hemorrhage, arteriole-venule nicking. The association between the retinal characteristic and stroke was modified by other retinal characteristics. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Qing. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 139-148). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.iii / Acknoledgements --- p.v / Chapter Chapter 1 --- Introduction and review of the Literature --- p.1 / Chapter Section 1: --- Stroke prevention and risk assessment tools --- p.1 / Chapter Section 2: --- Rationale of relationship of vascular circulation between retina and brain --- p.9 / Chapter Section 3: --- Manifestation of hypertensive retinopathy and diabetic retinopathy --- p.12 / Chapter Section 4: --- Retina characteristics related to stroke --- p.15 / Chapter Section 5: --- How to make retina as a tool of risk stratification for stroke --- p.28 / Chapter Section 6: --- Rationale to do study to further explore the useful information in color retina images to make it as tool for stroke risk stratification --- p.31 / Chapter Chapter 2 --- Research hypothesis and general design --- p.33 / Chapter Chapter 3 --- Methods of retia characteristics extraction --- p.34 / Chapter Chapter 4 --- A Study of the Reliability of manual measurement of Retinal characteristics using ImageJ --- p.46 / Chapter Chapter 5 --- A study of comparison of retina characteristics between patients with stroke and patients without stroke --- p.55 / Chapter Section 1: --- Method --- p.56 / Chapter Section 2: --- Result-univariate analysis --- p.62 / Chapter Section 3: --- Results-stratification analysis --- p.68 / Chapter Section 4: --- Result-risk model building for stroke risk stratification --- p.79 / Chapter Chapter 6: --- Discussion --- p.118 / Chapter Chapter 7: --- Limitation of this study --- p.133 / Chapter Chapter 8: --- Future development and application of the study results --- p.134 / Appendix --- p.136 / Reference --- p.139

Xiao, Kang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 83-103). / Abstracts in English and Chinese. / Abstract --- p.I / 摘要 --- p.VI / Chapter Chapter 1 --- Background --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Albuminuria --- p.3 / Chapter 1.2.1 --- Definition --- p.3 / Chapter 1.2.2 --- Albuminuria in adolescents/children --- p.6 / Chapter 1.2.3 --- Prevalence of albuminuria in adults and adolescents --- p.8 / Chapter 1.2.4 --- Pathogenesis of albuminuria --- p.10 / Chapter 1.3 --- CVD and risk factors --- p.12 / Chapter 1.4 --- The associations between microalbuminuria and CVD risk factors --- p.17 / Chapter 1.5 --- Heavy metals --- p.18 / Chapter 1.5.1 --- Definition of heavy metals --- p.18 / Chapter 1.5.2 --- Adverse effects of heavy metals --- p.19 / Chapter 1.5.3 --- Heavy metals exposure In Hong Kong population: the local scene --- p.28 / Chapter 1.6 --- MicroRNAs --- p.29 / Chapter 1.6.1 --- The discovery of microRNAs --- p.29 / Chapter 1.6.2 --- The biogenesis of microRNAs --- p.30 / Chapter 1.6.3 --- The function of microRNAs --- p.31 / Chapter 1.7 --- Hypothesis --- p.40 / Chapter Chapter 2 --- Methodology --- p.41 / Chapter 2.1 --- Population --- p.41 / Chapter 2.2 --- Laboratory assays --- p.42 / Chapter 2.3 --- Statistical analysis --- p.44 / Chapter Chapter 3 --- Results --- p.46 / Chapter 3.1 --- Demographic and baseline clinical data --- p.46 / Chapter 3.2 --- Microalbuminuria and cardiovascular risk factors --- p.48 / Chapter 3.3 --- Microalbuminuria and heavy metals --- p.51 / Chapter 3.4 --- Microalbuminuria and miRNAs --- p.54 / Chapter 3.5 --- "Microalbuminuria, miRNAs, heavy metals and cardiovascular risk factors" --- p.57 / Chapter 3.6 --- miRNAs and heavy metals --- p.60 / Chapter Chapter 4 --- Discussion --- p.62 / Chapter 4.1 --- Heavy metals and microalbuminuria --- p.62 / Chapter 4.2 --- Heavy metals and CVD risk factors --- p.68 / Chapter 4.3 --- Microalbuminuria and CVD risk factors --- p.75 / Chapter 4.4 --- miRNAs and Heavy metals --- p.76 / Chapter 4.5 --- miRNAs and microalbuminuria --- p.77 / Chapter 4.6 --- Conclusion --- p.79 / Acknowledgement --- p.82 / References --- p.83

A doença cardiovascular (DCV) é uma condição clínica comum entre pacientes (pcts) portadores de doença renal crônica (DRC) e é causa de eventos fatais observados peri transplante renal (TX). A melhor estratégia de avaliação cardiovascular em candidatos a transplante (CTR) ainda é controversa.Ignora-se se todos os pacientes devem ser submetidos a testes não-invasivos/invasivos ou se estes devem ser reservados aqueles com determinadas características clínicas, como população geral. O objetivo deste estudo foi comparar a estratificação de risco baseada em método nãoinvasivo de detecção de doença coronária com dois métodos de estratificação clínica de risco cardiovascular preconizados pela American Society of Transplantation (AST) e European Renal Association (ERA). A AST subdivide os pcts em : alto risco (idade maior ou igual a 50 anos e/ou diabete e/ou DCV clínica) e baixo risco (os demais). A ERA subdivide em: alto risco (DCV clínica), risco intermediário (diabéticos e/ou idade maior ou igual a 50 anos) e baixo risco (os demais). Nós estudamos 386 pcts com DRC em diálise enviados ao nosso serviço para avaliação cardiovascular antes da inclusão na lista de espera de TX. Foram estratificados quanto ao risco de eventos de acordo com os dois algoritmos acima e alterações na cintilografia de perfusão miocárdica (SPECT-MIBI) com dipiridamol e acompanhados até a morte, TX ou ocorrência de eventos. A estratificação clínica (RR:1,8 [IC95% 1,3 2,6- P<0,0001] e o SPECT-MIBI (RR:1,5 [IC95% 1,2-1,9-P=0,002] identificaram os pcts de maior risco de eventos cardiovasculares . Apenas os pcts ASTalto risco (RR1,4 [IC95%1,1-1,8-P=0,002] e ERA médio risco com SPECTMIBI alterado (RR:1,7 [IC95% 1,2-2,3-P=0,003] tiveram maior incidência de eventos. Os pcts de baixo risco pelos dois algorítmos de estratificação clínica (P=0,50) e do sistema ERA alto risco (RR:1,1 [IC95% 0,8-1,5-P=0,41], não se beneficiaram dos resultados do estudo não-invasivo. Concluímos que os estudos não-invasivos não devem ser utilizados em todos os CTR mas devem ser reservados aos pcts previamente identificados pela estratificação clínica de risco. Esses resultados permitem uma abordagem mais racional da avaliação pré- TX com melhor uso dos recursos econômicos escassos. / Cardiovascular (CV) disease is a common condition in chronic kidney disease (CKD) patients and is the leading cause of fatal events during and after renal transplantation. The best strategy for CV evaluation and coronary risk stratification in renal transplant candidates remains controversial. Moreover, there is no consensus regarding the best strategy for detection of coronary artery disease (CAD). We still do not know if all patients should be evaluated by noninvasive testing or if this approach should be restricted to individuals with clinical evidence of CAD, as in the general population. The objective of this study was to compare CV risk stratification based on nonivasive testing for CAD with two clinical stratification methods as advanced by The American Society of Transplantation (AST) and by The European Renal Association (ERA), respectively. The AST divides patients in high risk (age50 years and/or diabetes and/or CV disease) and low risk (all others).The ERA divides : high risk (CV disease), intermediate risk (age 50 years and/or diabetes), and low risk (as above). We studied 386 CKD patients treated by hemodyalisis, to CV evaluation before being admitted to the renal transplant waiting list. All patients were stratified for the risk of future major cardiovascular events (MACE) using the clinical algorithms and also by myocardial scintigraphy (SPECT-MIBI) with dipyridamol and followedup until death, transplant or MACE. Clinical algorithms (RR:1,8 [IC95% 1,3 2,6-P<0,0001] and SPECT-MIBI(RR:1,5 [IC95% 1,2-1,9-P=0,002] identified patients at increased risk of events. The combined use of clinical stratification followed by SPECT showed that the only patients that would benefit from SPECT risk stratification were those belonging the AST-high risk (RR1,4 [IC95%1,1-1,8-P=0,002] and ERA-intermediate risk groups (RR:1,7 [IC95% 1,2-2,3-P=0,003]. In all other groups :ERA-high-risk (RR:1,1[IC95% 0,8-1,5- P=0,41] and ERA and AST-low-risk (P=0,50) SPECT did not add to the probability of events defined by clinical stratification alone. We conclude that SPECT should not be applied to all renal transplant candidates but should be restricted to those considered at a category of risk as defined by clinical algorithms. These results delineate a more rational approach to risk stratification in renal transplant candidates with a better utilization of economical resources.

Made available in DSpace on 2015-07-22T20:50:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-04-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Introdução: O acidente vascular cerebral isquêmico (AVCi) é geralmente um evento catastrófico, particularmente em pacientes com idade maior ou igual a 80 anos. A idade avançada já é um fator de risco para AVCi e o acometimento cardiovascular é a principal causa de AVCi nessa população. A fibrilação atrial também (FA) é um importante fator de risco para AVCi, por isso os esquemas de estratificação de risco são importantes na indicação de tratamento antitrombótico e prevenção do AVCi nestes pacientes. Além disso, nível socioeconômico baixo tem sido descrito como um fator de maior risco para AVCi. Objetivos: Avaliar a prevalência dos fatores de risco cardiovasculares em pacientes com idade maior ou igual a 80 anos em uma população hospitalar com AVCi. Avaliar a relação desta doença com o nível socioeconômico em diferentes grupos etários, utilizando um novo modelo de estratificação socioeconômica. Método: Análise retrospectiva de pacientes consecutivos com diagnóstico de AVCi num serviço de saúde terciário. Nesta população, nós descrevemos a prevalência dos fatores de risco cardiovasculares e para os pacientes com FA, nos aplicamos os esquemas de estratificacao CHADS2 score e CHA2DS2-VASc score. Para avaliar a relacao entre nivel socioeconomico e AVCi, avaliamos a incidencia de AVCi em dois hospitais que atendem populacoes de diferentes niveis socioeconomicos da cidade de Sao Paulo, classificando os pacientes com uma nova ferramenta de segmentacao geografica socioeconomica. Os pacientes foram estratificados por nivel socioeconomico e idade (30 a 64 anos, 65 a 79 anos e maior ou igual a 80 anos). Nos tambem comparamos o numero de pacientes com AVCi com pacientes de um grupo controle dos mesmos hospitais, calculando a taxa de AVCi em cada hospital. O odds ratio entre as taxas de AVCi dos dois hospitais foi calculada. Resultados: Houve um predominio do sexo feminino (p<0.01) em 215 pacientes admitidos com AVCi. Considerando os pacientes com idade maior ou igual a 80 anos, 72% tinham hipertensao arterial sistemica (HAS) e a FA foi mais comum entre os mais idosos (p<0.01). Dentre os pacientes com FA, nenhum apresentou CHADS2 score de 0 e 25.5% tiveram score de 1 previamente ao AVCi. Todos os pacientes com CHADS2 score de 1 nao estavam em uso de anticoagulante oral, mas tinham CHA2DS2-VASc score . 2, apresentando indicacao para este tratamento. Trezentos e setenta e sete pacientes com AVCi e 2.297 pacientes do grupo controle foram estudados nos dois hospitais. Houve uma maior proporção de pacientes mais idosos na população de nível socioeconômico mais alto (χ2obs= 28.7, gl= 2, p-value < 0.0001). Em todas as idades, a taxa de AVCi foi significativamente mais alta nos pacientes com nível socioeconômico mais baixo quando comparado com os pacientes com nível socioeconômico mais alto, com χ2obs=21.3 (valor de p< 0.0001) para idade de 30 a 64 anos; χ2obs=39.8 (valor de p< 0.0001) para idade de 65 a 79 anos; e χ2obs=14.1 (valor de p= 0.0002) para pacientes com idade maior ou igual a 80 anos. O odds ratios entre as taxas de AVCi nos dois hospitais foi de 2.4, 3.6 e 2.7 para os grupos etários 30 a 64 anos, 65 a 79 anos e maior ou igual a 80 anos, respectivamente. Conclusão: HAS e FA são fatores de risco prevalentes e devem ser sempre considerados para tratamento em idosos. Estratificação de risco com CHA2DS2-VASc score poderia ter otimizado a indicação de anticoagulação oral em nossos pacientes. Nosso estudo mostrou que, em uma população estudada do município de São Paulo, nível socioeconômico baixo é associado a mais altas taxas de AVCi, independente da idade. / Background and Purpose – Ischemic stroke is usually a catastrophic event, mostly in the elderly. Advanced age itself is a risk factor for stroke and cardiovascular involvement is the leading cause of ischemic stroke in this age population. Atrial fibrillation is also an important risk factor for ischemic stroke and therefore risk stratification schemes are important in these patients for indicating antithrombotic therapyand prevent stroke. Low socioeconomic status is also associated with a higher risk for ischemic stroke. Objectives - To evaluate the prevalence of cardiovascular risk factors in patients with age 80 or older in a hospital population with ischemic stroke and the relationship between socioeconomic status and ischemic stroke in different age groups, using a new socioeconomic stratification model. Methods – Retrospective analysis of consecutive patients diagnosed with ischemic stroke admitted to a tertiary health facility. For this population, we described the prevalence of cardiovascular risk factors and, for the patients who had the diagnosis of atrial fibrillation, we applied CHADS2 score and CHA2DS2-VASc score. For assessment of the relationship beteween socioeconomic status and ischemic stroke, we evaluated the incidence of ischemic stroke in two hospitals that serve different socioeconomic populations in Sao Paulo, with a new geographic socioeconomic segmentation tool. The patients were stratified by socioeconomic status and age (30 to 64 years, 65 to 79 years and 80 years or older). We also compared the number of ischemic stroke patients with patients from control groups from the same hospitals, to obtain the ischemic stroke rates in both hospitals. The odds ratio between ischemic stroke rates in the hospitals was calculated. Results .There was a female preponderance (p<0.01) in 215 patients admitted for ischemic stroke. Considering patients over eighty, 72% had hypertension and atrial fibrillation was more common among the oldest old (p<0.01). Among those patients who had ischemic stroke and atrial fibrillation, no patient had CHADS2 score of 0 and 25.5% had score of 1. All patients with CHADS2 score of 1 were not under anticoagulation, but in retrospect, had CHA2DS2-VASc score . 2, i.e., with indication for oral anticoagulation. Three hundred and seventy-seven patients with ischemic stroke and 2,297 patients of control group were analyzed in both hospitals. There was a greater proportion of older patients in the higher socioeconomic status population (χ2obs= 28.7, df= 2, p-value < 0.0001). In all ages, the odds of ischemic stroke was significantly higher in patients with lower socioeconomic status than in those with higher status, with χ2obs=21.3 (p-value< 0.0001) for age 30 to 64 years; χ2obs=39.8 (p-value< 0.0001) for age 65 to 79 years; and χ2obs=14.1 (p-value= 0.0002) for ≥ 80 years patients. The odds ratios between ischemic stroke odds in both hospitals were 2.4, 3.6 and 2.7 for groups of ages 30 to 64 years, 65 to 79 years and 80 years or older, respectively. Conclusions – Hypertension and atrial fibrillation are prevalent risk factors and should be treated aggressively in the elderly. Risk stratification using CHA2DS2-VASc score would have optimized indication for oral anticoagulation in our patients. Our study showed that, in São Paulo, lower socioeconomic status is associated with a higher odds of ischemic stroke, independent of age. / TEDE / BV UNIFESP: Teses e dissertações

A doença cardiovascular (DCV) é uma condição clínica comum entre pacientes (pcts) portadores de doença renal crônica (DRC) e é causa de eventos fatais observados peri transplante renal (TX). A melhor estratégia de avaliação cardiovascular em candidatos a transplante (CTR) ainda é controversa.Ignora-se se todos os pacientes devem ser submetidos a testes não-invasivos/invasivos ou se estes devem ser reservados aqueles com determinadas características clínicas, como população geral. O objetivo deste estudo foi comparar a estratificação de risco baseada em método nãoinvasivo de detecção de doença coronária com dois métodos de estratificação clínica de risco cardiovascular preconizados pela American Society of Transplantation (AST) e European Renal Association (ERA). A AST subdivide os pcts em : alto risco (idade maior ou igual a 50 anos e/ou diabete e/ou DCV clínica) e baixo risco (os demais). A ERA subdivide em: alto risco (DCV clínica), risco intermediário (diabéticos e/ou idade maior ou igual a 50 anos) e baixo risco (os demais). Nós estudamos 386 pcts com DRC em diálise enviados ao nosso serviço para avaliação cardiovascular antes da inclusão na lista de espera de TX. Foram estratificados quanto ao risco de eventos de acordo com os dois algoritmos acima e alterações na cintilografia de perfusão miocárdica (SPECT-MIBI) com dipiridamol e acompanhados até a morte, TX ou ocorrência de eventos. A estratificação clínica (RR:1,8 [IC95% 1,3 2,6- P<0,0001] e o SPECT-MIBI (RR:1,5 [IC95% 1,2-1,9-P=0,002] identificaram os pcts de maior risco de eventos cardiovasculares . Apenas os pcts ASTalto risco (RR1,4 [IC95%1,1-1,8-P=0,002] e ERA médio risco com SPECTMIBI alterado (RR:1,7 [IC95% 1,2-2,3-P=0,003] tiveram maior incidência de eventos. Os pcts de baixo risco pelos dois algorítmos de estratificação clínica (P=0,50) e do sistema ERA alto risco (RR:1,1 [IC95% 0,8-1,5-P=0,41], não se beneficiaram dos resultados do estudo não-invasivo. Concluímos que os estudos não-invasivos não devem ser utilizados em todos os CTR mas devem ser reservados aos pcts previamente identificados pela estratificação clínica de risco. Esses resultados permitem uma abordagem mais racional da avaliação pré- TX com melhor uso dos recursos econômicos escassos. / Cardiovascular (CV) disease is a common condition in chronic kidney disease (CKD) patients and is the leading cause of fatal events during and after renal transplantation. The best strategy for CV evaluation and coronary risk stratification in renal transplant candidates remains controversial. Moreover, there is no consensus regarding the best strategy for detection of coronary artery disease (CAD). We still do not know if all patients should be evaluated by noninvasive testing or if this approach should be restricted to individuals with clinical evidence of CAD, as in the general population. The objective of this study was to compare CV risk stratification based on nonivasive testing for CAD with two clinical stratification methods as advanced by The American Society of Transplantation (AST) and by The European Renal Association (ERA), respectively. The AST divides patients in high risk (age50 years and/or diabetes and/or CV disease) and low risk (all others).The ERA divides : high risk (CV disease), intermediate risk (age 50 years and/or diabetes), and low risk (as above). We studied 386 CKD patients treated by hemodyalisis, to CV evaluation before being admitted to the renal transplant waiting list. All patients were stratified for the risk of future major cardiovascular events (MACE) using the clinical algorithms and also by myocardial scintigraphy (SPECT-MIBI) with dipyridamol and followedup until death, transplant or MACE. Clinical algorithms (RR:1,8 [IC95% 1,3 2,6-P<0,0001] and SPECT-MIBI(RR:1,5 [IC95% 1,2-1,9-P=0,002] identified patients at increased risk of events. The combined use of clinical stratification followed by SPECT showed that the only patients that would benefit from SPECT risk stratification were those belonging the AST-high risk (RR1,4 [IC95%1,1-1,8-P=0,002] and ERA-intermediate risk groups (RR:1,7 [IC95% 1,2-2,3-P=0,003]. In all other groups :ERA-high-risk (RR:1,1[IC95% 0,8-1,5- P=0,41] and ERA and AST-low-risk (P=0,50) SPECT did not add to the probability of events defined by clinical stratification alone. We conclude that SPECT should not be applied to all renal transplant candidates but should be restricted to those considered at a category of risk as defined by clinical algorithms. These results delineate a more rational approach to risk stratification in renal transplant candidates with a better utilization of economical resources.