COVID-19 住院后早期的身体功能恢复:高血压和结果预测模型的影响

O. Honchar
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Pre-discharge 6-minute walk distance was 378±57 m in patients with HT and 418±75 m without it, p=0.001, during the second visit – 440±52 versus 478±68, p=0.002; the achieved percentage of the individually predicted distance was 67.4±10.5 vs. 69.5±13.6 % and 81.6±9.9 vs. 81.9±15.7 %, respectively, p>0.05 for both visits. The increase in heart rate during the test at visit 1 was 18.5±8.3 versus 30.1±19.3 bpm, p<0.001, the percentage of chronotropic reserve utilizatoin was 21.3±9.6 % versus 29.2±11.4 %, p<0.001. During the second visit, residual manifestations of this trend were observed, with an increase in HR by 24.0±9.5 vs. 30.8±12.1, p=0.003 and the use of chronotropic reserve of 28.1±10.1 % vs. 33.4±12.4 %, respectively, p=0.029. The developed multivariate linear regression model explained 59 % of the variability in the achieved percentage of the individually predicted 6-minute walk distance at 1 month after discharge. 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引用次数: 0

摘要

目的--研究高血压(HT)对 COVID-19 住院后早期身体功能状态自然恢复动态的影响,并建立一个预测出院后 1 个月恢复结果的模型。研究纳入了221名COVID-19住院患者(年龄为53.4±13.6岁,53%为女性),其中176名患者在出院前1-2天内使用扩展方案进行了6分钟步行测试(6MWT)。出院后 1 个月进行了复诊,以评估自然恢复的动态。HT 患者出院前的 6 分钟步行距离为 378±57 米,无 HT 患者为 418±75 米,P=0.001;第二次复诊时,HT 患者的 6 分钟步行距离为 440±52 米,无 HT 患者为 478±68 米,P=0.002;两次复诊的个人预测距离达标率分别为 67.4±10.5% vs. 69.5±13.6% 和 81.6±9.9% vs. 81.9±15.7%,P>0.05。在第一次就诊时,测试期间心率的增加为 18.5±8.3 对 30.1±19.3 bpm,P<0.001;慢性动力储备利用率为 21.3±9.6 % 对 29.2±11.4 %,P<0.001。在第二次就诊时,观察到了这一趋势的残余表现,心率分别增加了 24.0±9.5% 和 30.8±12.1%,p=0.003;促时储备的使用率分别为 28.1±10.1% 和 33.4±12.4%,p=0.029。所建立的多元线性回归模型可解释出院后1个月时个人预测的6分钟步行距离百分比变异的59%。机器学习的使用使得基于人工神经网络的回归模型得以建立,该模型将年龄、身高、治疗中使用雷米替韦的情况以及出院时的SBP和DBP值作为预测因素,并解释了90%的观察变异。COVID-19住院患者的特点是出院时通过6MWT评估的一般身体功能状态下降,1个月后未完全恢复。高血压与更明显的心率自主神经调节紊乱有关,但并不影响步行距离的达标率。所提出的基于人工神经网络的回归模型可高精度预测出院后 1 个月的 6MWT 结果,可用于选择心肺康复计划的候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physical functional recovery in the early period after hospitalization for COVID-19: impact of hypertension and outcome prediction model
The aim – to study the influence of hypertension (HT) on the dynamics of natural recovery of physical functional status in the early period after hospitalization for COVID-19 and to develop a model for predicting recovery results at 1 month after discharge.Materials and methods. 221 hospitalized patients with COVID-19 (age 53.4±13.6 years, 53 % women) were included in the study, 176 of whom underwent the 6-minute walk test (6MWT) using an extended protocol within 1-2 days before discharge. A repeat visit to assess the dynamics of natural recovery was performed at 1 month after discharge.Results and discussion. Pre-discharge 6-minute walk distance was 378±57 m in patients with HT and 418±75 m without it, p=0.001, during the second visit – 440±52 versus 478±68, p=0.002; the achieved percentage of the individually predicted distance was 67.4±10.5 vs. 69.5±13.6 % and 81.6±9.9 vs. 81.9±15.7 %, respectively, p>0.05 for both visits. The increase in heart rate during the test at visit 1 was 18.5±8.3 versus 30.1±19.3 bpm, p<0.001, the percentage of chronotropic reserve utilizatoin was 21.3±9.6 % versus 29.2±11.4 %, p<0.001. During the second visit, residual manifestations of this trend were observed, with an increase in HR by 24.0±9.5 vs. 30.8±12.1, p=0.003 and the use of chronotropic reserve of 28.1±10.1 % vs. 33.4±12.4 %, respectively, p=0.029. The developed multivariate linear regression model explained 59 % of the variability in the achieved percentage of the individually predicted 6-minute walk distance at 1 month after discharge. The use of machine learning allowed to create an artificial neural network based regression model that used age, height, use of remdesivir in treatment, and SBP and DBP values at the time of discharge as predictors, and explained 90 % of observed variability.Conclusions. Hospitalized patients with COVID-19 were characterized by a decrease in the general physical functional status as assessed by 6MWT at the time of discharge and incomplete recovery after 1 month. Presence of hypertension was associated with more pronounced disturbances of the autonomic regulation of heart rate, but did not affect the reached percentage of the distance walked. The proposed artificial neural network based regression model allows for a high accuracy prediction of the 6MWT results at 1 month after discharge, which can be used in the selection of candidates for cardiopulmonary rehabilitation programs.
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