南充市社区中老年人群血脂血糖现状水平分析

【摘要】 目的 了解社区中老年人群的血脂、血糖现状水平，探讨其与性别和年龄的关系，为本地区心脑血管疾病、糖尿病等疾病的防治提供诊疗依据。方法 对我市38078名社区居民采集清晨空腹血清标本，检测血糖（GLU）、甘油三酯（TG）、总胆固醇（TC）、高密度脂蛋白胆固醇（HDL C）和低密度脂蛋白胆固醇（LDL C）的结果，并对其进行年龄、性别分组统计分析。结果 不同性别和年龄组间的血脂、血糖水平差异有统计学意义（P＜005），74~89岁年龄组血脂、血糖总体水平高于其他各年龄组（P＜005）；女性血脂水平普遍高于男性（P＜005）。结论 中老年人群血脂、血糖异常率高，应定期对中老年人进行血脂、血糖监测，开展宣传教育活动，提高自我保健意识，预防高血脂、高血糖的发生和发展。     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Spatial distribution of intestinal parasitic infections in a Kaingáng indigenous village from Southern Brazil

The spatial distribution of enteroparasitosis in an indigenous village from Paraná was evaluated to identify areas of risk for these infections. A cross-sectional study (from November 2010 to June 2011) was performed using Three Faecal Test^® and Kato &; Katz method and a questionnaire on housing and hygiene conditions was administered. Local geostatistical analyses were performed to determine the spatial distribution of intestinal parasitic infections. The overall prevalence of enteroparasites was 67.2?% (457/680), and the most prevalent taxa were Ascaris lumbricoides (48.8?%) and Trichuris trichiura (44.7?%). The prevalence of heavy infection by soil-transmitted helminths was 3.6?% and the families lived in houses with an average of 5.1 residents and < 2 bedrooms per household. The average number of species per individual present spatial heterogeneity with the highest values (≥0.8) in areas with high clustering of residences. The visualization of the spatial distribution of intestinal parasites in this indigenous village is an important contribution to determining health risk areas and planning decisions and services.     

中青年脑梗死68例临床分析

脑梗死多见于老年人，但近年来中青年（16-45岁）患者逐渐增多且有年轻化趋势，深人探讨中青年脑梗死的致病因素及临床表现对其防治有重要意义。本文回顾性分析了我院自1998年1月到2004年12月问收治的中青年脑梗死患者68例，现报告如下。