Biostatistics Unit, South African Medical Research Council, Tygerberg, SOUTH AFRICA.
Wits Sport and Health (WiSH), School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, SOUTH AFRICA.
Med Sci Sports Exerc. 2023 Jan 1;55(1):1-8. doi: 10.1249/MSS.0000000000003027. Epub 2022 Aug 16.
This study aimed to determine factors predictive of prolonged return to training (RTT) in athletes with recent SARS-CoV-2 infection.
This is a cross-sectional descriptive study. Athletes not vaccinated against COVID-19 ( n = 207) with confirmed SARS-CoV-2 infection (predominantly ancestral virus and beta-variant) completed an online survey detailing the following factors: demographics (age and sex), level of sport participation, type of sport, comorbidity history and preinfection training (training hours 7 d preinfection), SARS-CoV-2 symptoms (26 in 3 categories; "nose and throat," "chest and neck," and "whole body"), and days to RTT. Main outcomes were hazard ratios (HR, 95% confidence interval) for athletes with versus without a factor, explored in univariate and multiple models. HR < 1 was predictive of prolonged RTT (reduced % chance of RTT after symptom onset). Significance was P < 0.05.
Age, level of sport participation, type of sport, and history of comorbidities were not predictors of prolonged RTT. Significant predictors of prolonged RTT (univariate model) were as follows (HR, 95% confidence interval): female (0.6, 0.4-0.9; P = 0.01), reduced training in the 7 d preinfection (1.03, 1.01-1.06; P = 0.003), presence of symptoms by anatomical region (any "chest and neck" [0.6, 0.4-0.8; P = 0.004] and any "whole body" [0.6, 0.4-0.9; P = 0.025]), and several specific symptoms. Multiple models show that the greater number of symptoms in each anatomical region (adjusted for training hours in the 7 d preinfection) was associated with prolonged RTT ( P < 0.05).
Reduced preinfection training hours and the number of acute infection symptoms may predict prolonged RTT in athletes with recent SARS-CoV-2. These data can assist physicians as well as athletes/coaches in planning and guiding RTT. Future studies can explore whether these variables can be used to predict time to return to full performance and classify severity of acute respiratory infection in athletes.
本研究旨在确定近期 SARS-CoV-2 感染运动员中与延长恢复训练（RTT）相关的预测因素。
这是一项横断面描述性研究。未接种 COVID-19 疫苗（n=207）的运动员确诊 SARS-CoV-2 感染（主要为原始病毒和β变体），完成了一项在线调查，详细说明了以下因素：人口统计学特征（年龄和性别）、运动参与水平、运动类型、合并症病史和感染前训练（感染前 7 天的训练小时数）、SARS-CoV-2 症状（26 项，分为 3 类：“鼻咽喉”、“胸颈”和“全身”）以及 RTT 天数。主要结局是有无因素的运动员的风险比（HR，95%置信区间），在单变量和多变量模型中进行了探讨。HR<1 提示 RTT 延长（症状出现后 RTT 机会减少）。P<0.05 具有统计学意义。
年龄、运动参与水平、运动类型和合并症病史均不是 RTT 延长的预测因素。RTT 延长的显著预测因素（单变量模型）如下（HR，95%置信区间）：女性（0.6，0.4-0.9；P=0.01）、感染前 7 天训练减少（1.03，1.01-1.06；P=0.003）、按解剖部位出现症状（任何“胸颈”（0.6，0.4-0.8；P=0.004）和任何“全身”（0.6，0.4-0.9；P=0.025））以及几种特定症状。多变量模型显示，每个解剖部位症状的数量越多（调整感染前 7 天的训练小时数），与 RTT 延长相关（P<0.05）。
感染前训练小时数减少和急性感染症状数量可能预测近期 SARS-CoV-2 感染运动员的 RTT 延长。这些数据可以帮助医生以及运动员/教练规划和指导 RTT。未来的研究可以探索这些变量是否可用于预测恢复到完全运动表现的时间，并对运动员的急性呼吸道感染进行严重程度分类。
