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1.
J Int Med Res ; 50(9): 3000605221123697, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-36112810

RESUMO

OBJECTIVE: To undertake a meta-analysis to investigate if there is an association between the glutathione S-transferase mu 1 (GSTM1) gene polymorphism, coronary artery disease (CAD) susceptibility and smoking. METHODS: Electronic databases, including PubMed®, Web of Science and Embase®, were searched for relevant case-control studies. Data were extracted and the odds ratio (OR) was calculated and appropriate statistical methods were used for the meta-analysis. RESULTS: The analysis included eight studies with a total of 1880 cases with CAD and 1758 control subjects. The results of this meta-analysis demonstrated that there is no association between the GSTM1 null and CAD (OR 1.24, 95% confidence interval [CI] 1.00, 1.55). An increased risk of CAD was observed in the smoking population with the GSTM1 null genotype (OR 1.48, 95% CI 1.02, 2.15). Subgroup analyses of geographical region, genotyping method and publication language category demonstrated potential relationships among gene polymorphism, smoking and CAD. CONCLUSIONS: Based on the current literature, the GSTM1 null genotype was associated to CAD in the smoking population. The interaction between smoking and GSTM1 polymorphism may contribute to the susceptibility of CAD.


Assuntos
Doença da Artéria Coronariana , Glutationa Transferase , Fumar , Doença da Artéria Coronariana/etiologia , Doença da Artéria Coronariana/genética , Predisposição Genética para Doença , Glutationa Transferase/genética , Humanos , Polimorfismo Genético , Fatores de Risco , Fumar/efeitos adversos , Fumar/genética
3.
Int J Cardiol ; 321: 1-5, 2020 12 15.
Artigo em Inglês | MEDLINE | ID: mdl-32805329

RESUMO

INTRODUCTION: The effectiveness of treatment and prognosis of patients with type 1 myocardial infarction are highly correlated with time of diagnosis. This study aimed to develop a type 1 MI rapid screening scale (T1MIrs scale) suitable for emergency pre-diagnosis. METHODS: A total of 1928 patients who underwent coronary angiography were enrolled. Multivariate regression analysis was used to identify the independent risk factors of type 1 MI. And the T1MIrs scale was developed and evaluated according to the multivariate regression result. RESULTS: The incidence of type 1 MI was 23.3% in the population with suspected acute coronary syndrome. After 5 adjusting for relevant factors, MEWS score (OR = 1.809, 95%CI 1.623-2.016, P < .001), typical symptoms (OR = 9.826, 95%CI 7.379-13.084, P < .001), male (OR = 2.184, 95%CI 1.602-2.979, P < .001), age (OR = 1.021, 95%CI 1.009-1.033, P = .001), history of diabetes (OR = 2.174, 95%CI 1.594-2.963, P < .001) and current smoker (OR = 2.498, 95%CI 1.550-4.026, P < .001) were the independent risk factors for type 1 MI. The T1MIrs scale is established based on risk factors, with a range of 0-8 points. The incidence of type 1 MI is ascending with the scale (0.3% vs. 3.7% vs. 14.3% vs. 34.9% vs. 57% vs. 76.4% vs. 84.2% vs. 87.5% vs. 100%, P for trend <0.001). CONCLUSIONS: Type 1 MI is common in patients with suspected acute coronary syndrome in emergency department. The T1MIrs scale could act as a rapid pre-examination triage of suspected population in emergency department, which is meaningful to screen out type 1 MI patients as soon as possible.


Assuntos
Síndrome Coronariana Aguda , Infarto do Miocárdio , Síndrome Coronariana Aguda/diagnóstico por imagem , Síndrome Coronariana Aguda/epidemiologia , Dor no Peito/diagnóstico por imagem , Dor no Peito/epidemiologia , Angiografia Coronária , Serviço Hospitalar de Emergência , Humanos , Masculino , Infarto do Miocárdio/diagnóstico por imagem , Infarto do Miocárdio/epidemiologia , Fatores de Risco , Triagem
4.
Zhongguo Yi Liao Qi Xie Za Zhi ; 26(2): 112-4, 2002 Mar.
Artigo em Chinês | MEDLINE | ID: mdl-16104174

RESUMO

This paper introduces an automatic microscopic urinary sediment analyzer. A set of basic algorithms, including pretreatment and picking up characteristics is brought forward to realize the automatic segmentation of urinary sediment. This paper also characterizes the visible components in urinary sediment in morphology and has sum up 7 morphology parameters and a simple method of classification.


Assuntos
Algoritmos , Processamento de Imagem Assistida por Computador/instrumentação , Urinálise/instrumentação , Inteligência Artificial , Computadores , Desenho de Equipamento , Humanos , Processamento de Imagem Assistida por Computador/métodos , Armazenamento e Recuperação da Informação/métodos , Design de Software , Urinálise/métodos
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