Chachkhiani David, Soliman Michael Y, Barua Delphi, Isakadze Marine, Villemarette-Pittman Nicole R, Devier Deidre J, Lovera Jesus F
Department of Neurology, Louisiana State University Health Sciences Center, New Orleans, LA, USA.
Data Brief. 2021 Apr;35:106944. doi: 10.1016/j.dib.2021.106944. Epub 2021 Mar 5.
We reviewed the electronic medical records (EMR) of patients hospitalized during the peak of the pandemic, March 1st through March 31st, to document the type and frequency of neurological problems seen in patients with COVID-19 at presentation to the emergency room. Secondary aims were to determine: 1) the frequency of neurological complaints during the hospital stay; 2) whether the presence of any neurological complaint at presentation or any of the individual types of neurological complaints at admission predicted three separate outcomes: death, length of hospital stay, or the need for intubation; and 3) if the presence of any neurological complaint or any of the individual types of neurological complaints developed during hospital stay predicted the previous three outcomes.
The Louisiana Health Sciences Center - New Orleans Institutional Review Board and the University Medical Center Clinical Research Review Committee approved the study protocol.
We reviewed the electronic medical records (EMR) of patients hospitalized during March (March 1st through March 31st) 2020 at the University Medical Center New Orleans (UMCNO), who tested positive for SARS-CoV-2 during the same hospitalization. The EMR team generated a list of 257 patients admitted for COVID-19. We excluded seven patients because of a negative COVID-19 test result or incomplete medical record documentation. Three neurology residents (DC, MS, DB) reviewed the EMR in detail to capture the relevant medical history, clinical course, and laboratory test results and abstracted data into an electronic data collection spreadsheet.We recorded the presentation or development of the following neurological complaints: headache, syncope, altered mental status, seizure, status epilepticus, and ischemic or hemorrhagic stroke.
We used "R" (statistics software) and Microsoft Excel to generate summary tables. To analyze hospital length of stay or death, we fitted a competing risks proportional hazards model for time to discharge or death using the crr() function in R version 4.0.0. The competing risks model allowed the analysis of hospital stay, taking into account that the censoring of cases due to death was not random. To predict the likelihood of intubation, we used the glm() function in R to fit a logistic regression model. For each model, we determined baseline demographic variables predictive of the outcomes and generated adjusted models. For variables with less than five cases per cell, we reported the p-values for Fisher's Exact Test.The analyses and results are published in:Chachkhiani, David et al. "Neurological complications in a predominantly African American population of COVID-19 predict worse outcomes during hospitalization." Clinical Neurology and Neurosurgery (in press).These data will be useful for researchers trying to build larger datasets regarding COVID19 neurological complications for metanalysis or to answer other questions requiring larger sample sizes.
我们回顾了在疫情高峰期（3月1日至3月31日）住院患者的电子病历（EMR），以记录新冠病毒疾病（COVID-19）患者在急诊室就诊时出现的神经问题类型和频率。次要目的是确定：1）住院期间神经症状的频率；2）就诊时出现的任何神经症状或入院时任何一种单独的神经症状类型是否能预测三个不同的结果：死亡、住院时间或插管需求；3）住院期间出现的任何神经症状或任何一种单独的神经症状类型是否能预测上述三个结果。
路易斯安那州新奥尔良健康科学中心机构审查委员会和大学医学中心临床研究审查委员会批准了该研究方案。
我们回顾了2020年3月（3月1日至3月31日）在新奥尔良大学医学中心（UMCNO）住院且在同一住院期间新冠病毒2（SARS-CoV-2）检测呈阳性的患者的电子病历（EMR）。电子病历团队生成了一份257名因COVID-19入院患者的名单。我们排除了7名患者，原因是COVID-19检测结果为阴性或病历记录不完整。三名神经科住院医师（DC、MS、DB）详细审查了电子病历，以获取相关病史、临床病程和实验室检查结果，并将数据提取到电子数据收集电子表格中。我们记录了以下神经症状的出现或发展情况：头痛、晕厥、精神状态改变、癫痫发作、癫痫持续状态以及缺血性或出血性中风。
我们使用“R”（统计软件）和微软Excel生成汇总表。为了分析住院时间或死亡情况，我们使用R 4.0.0版本中的crr()函数拟合了一个竞争风险比例风险模型，用于分析出院或死亡时间。竞争风险模型允许在考虑到因死亡导致的病例截尾并非随机的情况下分析住院时间。为了预测插管的可能性，我们使用R中的glm()函数拟合了一个逻辑回归模型。对于每个模型，我们确定了预测结果的基线人口统计学变量，并生成了调整模型。对于每个单元格中病例数少于5例的变量，我们报告了Fisher精确检验的p值。分析和结果发表于：查赫基阿尼，大卫等人。“在以非裔美国人为主的COVID-19人群中，神经并发症预示住院期间预后更差。”《临床神经病学与神经外科学》（即将出版）。这些数据将有助于研究人员构建关于COVID- nineteen神经并发症的更大数据集，用于荟萃分析或回答其他需要更大样本量的问题。
