@文章{信息:doi/10.2196/35860，作者="Rosario, Bedda和Zhang, Andrew和Patel, Mehool和Rajmane, Amol和Xie, Ning和Weeraratne, Dilhan和Alterovitz, Gil"，标题="通过异质患者数据表征与COVID-19相关的血栓并发症危险因素:回顾性观察研究"，期刊="J Med Internet Res"，年="2022"，月="10"，日="21"，卷="24"，数="10"，页数="e35860"，关键词="COVID-19;血栓性并发症;逻辑回归;电子健康档案;电子健康档案;背景:COVID-19已被观察到与静脉和动脉血栓形成有关。炎症性疾病延长了住院时间，先前存在的合并症可加重COVID-19患者的血栓负担。然而，静脉血栓栓塞、动脉血栓形成和其他血管并发症可能在重症监护环境中被忽视。在COVID-19患者群体中，早期风险分层对于主动监测血栓并发症至关重要。目的:本探索性研究的目的是利用电子健康记录(EHR)和保险理赔数据库的信息，描述与COVID-19相关的血栓并发症风险因素。 The goal is to develop an approach for analysis using real-world data evidence that can be generalized to characterize thrombotic complications and additional conditions in other clinical settings as well, such as pneumonia or acute respiratory distress syndrome in COVID-19 patients or in the intensive care unit. Methods: We extracted deidentified patient data from the insurance claims database IBM MarketScan, and formulated hypotheses on thrombotic complications in patients with COVID-19 with respect to patient demographic and clinical factors using logistic regression. The hypotheses were then verified with analysis of deidentified patient data from the Research Patient Data Registry (RPDR) Mass General Brigham (MGB) patient EHR database. Data were analyzed according to odds ratios, 95{\%} CIs, and P values. Results: The analysis identified significant predictors (P<.001) for thrombotic complications in 184,831 COVID-19 patients out of the millions of records from IBM MarketScan and the MGB RPDR. With respect to age groups, patients 60 years and older had higher odds (4.866 in MarketScan and 6.357 in RPDR) to have thrombotic complications than those under 60 years old. In terms of gender, men were more likely (odds ratio of 1.245 in MarketScan and 1.693 in RPDR) to have thrombotic complications than women. Among the preexisting comorbidities, patients with heart disease, cerebrovascular diseases, hypertension, and personal history of thrombosis all had significantly higher odds of developing a thrombotic complication. Cancer and obesity were also associated with odds>1. The results from RPDR validated the IBM MarketScan findings, as they were largely consistent and afford mutual enrichment. Conclusions: The analysis approach adopted in this study can work across heterogeneous databases from diverse organizations and thus facilitates collaboration. Searching through millions of patient records, the analysis helped to identify factors influencing a phenotype. Use of thrombotic complications in COVID-19 patients represents only a case study; however, the same design can be used across other disease areas by extracting corresponding disease-specific patient data from available databases. ", issn="1438-8871", doi="10.2196/35860", url="//www.mybigtv.com/2022/10/e35860", url="https://doi.org/10.2196/35860", url="http://www.ncbi.nlm.nih.gov/pubmed/36044652" }