Air pollution effects on myocardial infarction

OBJECTIVE: Myocardial infarction is an acute and severe cardiovascular disease that generally leads to patient admissions to intensive care units and few cases are initially admitted to infirmaries. The objective of the study was to assess whether estimates of air pollution effects on myocardial infarction morbidity are modified by the source of health information. METHODS: The study was carried out in hospitals of the Brazilian Health System in the city of São Paulo, Southern Brazil. A time series study (1998-1999) was performed using two outcomes: infarction admissions to infirmaries and to intensive care units, both for people older than 64 years of age. Generalized linear models controlling for seasonality (long and short-term trends) and weather were used. The eight-day cumulative effects of air pollutants were assessed using third degree polynomial distributed lag models. RESULTS: Almost 70% of daily hospital admissions due to myocardial infarction were to infirmaries. Despite that, the effects of air pollutants on infarction were higher for intensive care units admissions. All pollutants were positively associated with the study outcomes but SO2 presented the strongest statistically significant association. An interquartile range increase on SO2 concentration was associated with increases of 13% (95% CI: 6-19) and 8% (95% CI: 2-13) of intensive care units and infirmary infarction admissions, respectively. CONCLUSIONS: It may be assumed there is a misclassification of myocardial infarction admissions to infirmaries leading to overestimation. Also, despite the absolute number of events, admissions to intensive care units data provides a more adequate estimate of the magnitude of air pollution effects on infarction admissions.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Gender differences in serum CK-MB mass levels in healthy Braziliansubjects

The creatine kinase-isoenzyme MB (CK-MB) mass assay is one of the laboratory tests used for the diagnosis of myocardial infarction. It is recommended, however, that reference limits should take gender and race into account. In the present study, we analyzed the plasma CK-MB mass and troponin levels of 244 healthy volunteers without a personal history of coronary artery disease and with no chronic diseases, muscular trauma or hypothyroidism, and not taking statins. The tests were performed with commercial kits, CK-MB mass turbo kit and Troponin I turbo kit, using the Immulite 1000 analyzer from Siemens Healthcare Diagnostic. The values were separated according to gender and showed significant differences by the Mann-Whitney test. Mean (± SD) CK-MB mass values were 2.55 ± 1.09 for women (N = 121; age = 41.20 ± 10.13 years) and 3.49 ± 1.41 ng/mL for men (N = 123; age = 38.16 ± 11.12 years). Gender-specific reference values at the 99th percentile level, according to the Medicalc statistical software, were 5.40 ng/mL for women and 7.13 ng/mL for men. The influence of race was not considered because of the high miscegenation of the Brazilian population. The CK-MB values obtained were higher than the 5.10 mg/mL proposed by the manufacturer of the laboratory kit. Therefore, decision limits should be related to population and gender in order to improve the specificity of this diagnostic tool, avoiding misclassification of patients