Esophageal Surveillance Practices in Esophageal Atresia Patients: A Survey by the Eastern Pediatric Surgery Network

IntroductionEndoscopic surveillance guidelines for patients with repaired esophageal atresia (EA) rely primarily on expert opinion. Prior to embarking on a prospective EA surveillance registry, we sought to understand EA surveillance practices within the Eastern Pediatric Surgery Network (EPSN).MethodsAn anonymous, 23-question Qualtrics survey was emailed to 181 physicians (surgeons and gastroenterologists) at 19 member institutions. Likert scale questions gauged agreement with international EA surveillance guideline-derived statements. Multiple-choice questions assessed individual and institutional practices.ResultsThe response rate was 77%. Most respondents (80%) strongly agree or agree that EA surveillance endoscopy should follow a set schedule, while only 36% claimed to perform routine upper GI endoscopy regardless of symptoms. Many institutions (77%) have an aerodigestive clinic, even if some lack a multi-disciplinary EA team. Most physicians (72%) expressed strong interest in helping develop evidence-based guidelines.ConclusionsOur survey reveals physician agreement with current guidelines but weak adherence. Surveillance methods vary greatly, underscoring the lack of evidence-based data to guide EA care. Aerodigestive clinics may help implement surveillance schedules. Respondents support evidence-based protocols, which bodes well for care standardization. Results will inform the first multi-institutional EA databases in the United States (US), which will be essential for evidence-based care.Level of EvidenceThis is a prognosis study with level 4 evidence.     

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。     

Applications of geospatial analyses in health research among homeless people: A systematic scoping review of available evidence

BackgroundUnequal housing access resulted in more than 150 million homeless people worldwide, with millions more expected to be added every year due to the ongoing climate-related crises. Homeless population has a counterproductive effect on the social, psychological integration efforts by the community and exposure to other severe health-related issues. Geographic Information Systems (GIS) have long been applied in urban planning and policy, housing and homelessness, and health-related research.MethodsWe used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to systematically review 24 articles collected from multiple databases (n = 10) that focused on health-related issues among homeless people and used geospatial analysis techniques in their research.ResultsOur findings indicated a geographic clustering of case study locations– 26 out of the 31 case study sites are from the USA and Canada. Studies used spatial analysis techniques to identify hotspots, clusters and patterns of patient location and population distribution. Studies also reported relationships among the location of homeless shelters and substance use, discarded needles, different infectious and non-infectious disease clusters.ConclusionMost studies were restricted in analyzing and visualizing the patterns and disease clusters; however, geospatial analyses techniques are useful and offer diverse techniques for a more sophisticated understanding of the spatial characteristics of the health issues among homeless people. Better integration of GIS in health research among the homeless would help formulate sensible policies to counter health inequities among this vulnerable population group.     

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.     

Clinical Outcomes at 1 Year Following Transcatheter Left Atrial Appendage Occlusion in the United States

ObjectivesThe aim of this study was to report 1-year clinical outcomes following commercial transcatheter left atrial appendage occlusion (LAAO) in the United States.BackgroundThe National Cardiovascular Data Registry LAAO Registry was initiated to meet a condition of Medicare coverage and allow the assessment of clinical outcomes. The 1-year rates of thromboembolic events after transcatheter LAAO in such a large cohort of “real-world” patients have not been previously reported.MethodsPatients entered into the National Cardiovascular Data Registry LAAO Registry for a Watchman procedure between January 1, 2016, and December 31, 2018, were included. The primary endpoint was ischemic stroke. Key secondary endpoints included the rate of ischemic stroke or systemic embolism, mortality, and major bleeding. Major bleeding was defined as any bleeding requiring hospitalization, and/or causing a decrease in hemoglobin level > 2g/dL, and/or requiring blood transfusion that was not hemorrhagic stroke. The Kaplan-Meier method was used for 1-year estimates of cumulative event rates.ResultsThe study population consisted of 36,681 patients. The mean age was 76.0 ± 8.1 years, the mean CHA₂DS₂-VASc score was 4.8 ± 1.5, and the mean HAS-BLED score was 3.0 ± 1.1. Prior stroke was present in 25.5%, clinically relevant bleeding in 69.5%, and intracranial bleeding in 11.9%. Median follow-up was 374 days (IQR: 212-425 days). The Kaplan-Meier–estimated 1-year rate of ischemic stroke was 1.53% (95% CI: 1.39%-1.69%), the rate of ischemic stroke or systemic embolism was 2.19% (95% CI: 2.01%-2.38%), and the rate of mortality was 8.52% (95% CI: 8.19%-8.87%). The 1-year estimated rate of major bleeding was 6.93% (95% CI: 6.65%-7.21%). Most bleeding events occurred between discharge and 45 days following the procedure.ConclusionsThis study characterizes important outcomes in a national cohort of patients undergoing transcatheter LAAO in the United States. Clinicians and patients can integrate these data in shared decision making when considering this therapy.     

理气中药组方对糖尿病大鼠胃排空延迟的作用

目的:观察理气中药经验组方对糖尿病大鼠胃排空延迟的干预作用。方法:雌雄各半成年SD大鼠110只,随机分为正常组(A组)、糖尿病中药组(B组)、糖尿病胃复安组(C组)、糖尿病组(D组)。A组、D组1次/d按10 mL/只予0.9%生理盐水灌胃,B组1次/d按8 mL/只予中药煎剂灌胃,C组1次/d按0.5 mg/只予胃复安片灌胃。喂养12周后,行13C胃排空实验及甲基橙水溶液胃排空实验,观察各组大鼠胃排空情况。结果:糖尿病大鼠胃排空较正常大鼠明显延迟(P0.01),糖尿病大鼠胃排空延迟模型制作成功。糖尿病中药组和糖尿病胃复安组大鼠胃排空较糖尿病组快(P0.01);糖尿病中药组大鼠胃排空较糖尿病胃复安组大鼠快(P0.05)。结论:常规喂养12周后糖尿病大鼠出现胃排空延迟。理气中药陈皮、枳实、木香、香附组方煎剂和胃复安均能促进糖尿病大鼠胃排空,理气中药组方煎剂的效果优于胃复安。