预测严重和极严重冠状病毒感染孕妇的不良临床结果

A. V. Shchegolev, R. Lakhin, A. A. Nikulin, S. G. Meshchaninova, V. F. Bezhenar
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摘要

目的是确定重度和极重度COVID-19孕妇不利结局的预后标准,并建立预测临床结局的模型。该研究是一项队列式单中心回顾性研究,纳入了 2021 年 1 月 1 日至 12 月 31 日期间在重症监护室(ICU)接受治疗的 83 名患者。其中,13 名患者出现了不利的结果--死亡,70 名患者出现了成功的结果--康复。分析了两组患者在重症监护室住院期间和治疗第三天的主要临床和实验室指标(Δ - delta)的差异。Cox回归分析确定了实验室指标,这些指标在入住重症监护室时和治疗第三天的差异(Δ)与不良结局(死亡)的发生有关。这些指标被用作线性回归方程中的变量。计算预后指数的方程符合具有统计学意义的模型标准(灵敏度 84.6%,特异性 85.7%,操作特征曲线下面积(AUROC - Receiver Operator Curve 下面积)- 0.959(95 % 置信区间 [95 % CI] 0.918 - 1.0)。预后指数的计算可以作为一种额外的临床工具,使人们能够预测不利预后的发展,集中多学科团队的工作,吸引医疗机构的额外储备,和/或将此类患者后送至高级医院。
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Prediction of adverse clinical outcomes in pregnant women with severe and extremely severe forms of coronavirus infection
The objective was to identify prognostic criteria for unfavorable outcome in pregnant women with severe and extremely severe forms of COVID-19 and to build a model for predicting clinical outcome.Materials and methods. The cohort single-center retrospective study was conducted, which included 83 patients who were treated in the intensive care unit (ICU) from January 1 to December 31, 2021. Of these, 13 patients had an unfavorable outcome – death, and 70 patients with a successful outcome – recovery. The differences in the main clinical and laboratory parameters of patients of both groups during hospitalization in the ICU and on the 3rd day of treatment (Δ – delta) were analyzed.Results. The Cox regression analysis identified laboratory parameters, the difference of which (Δ) on admission to the ICU and on the 3rd day of treatment is associated with the development of the unfavorable outcome (death). These indicators were used as variables in a linear regression equation. The equation for calculating the prognostic index met the criteria of a statistically significant model (sensitivity 84.6 %, specificity 85.7 %, area under the operating characteristic curve (AUROC – Area Under Receiver Operator Curve) – 0.959 (95 % confidence interval [95 % CI] 0.918 – 1.0).Conclusion. The calculation of the prognostic index can be an additional clinical tool that allows one to predict the development of an unfavorable outcome, concentrate the work of a multidisciplinary team, attract additional reserves of a medical institution and/or evacuate such patients to high-level hospitals.
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