Impact of post-acute COVID-19 exercise training on cardiovascular autonomic function in amateur runners: A self-controlled longitudinal study

• Published in: Chinese medical journal 2024-10, Vol.137 (19), p.2392-2394
• Main Authors: Xu, Shen, Xian, Hong, Liao, Yue, Zhang, Haowei, Xia, Ling, Liu, Yixin, Tong, Nanwei
• Format: Article
• Language: English
• Subjects: Age; Antibodies; Asymptomatic; Body mass index; Cardiac arrhythmia; Correspondence; COVID-19; Fitness training programs; Gender; Heart rate; Infections; Longitudinal studies; Pediatrics; Running; Severe acute respiratory syndrome coronavirus 2
• ISSN: 0366-6999; 2542-5641; 2542-5641
• DOI: 10.1097/CM9.0000000000003251

The study protocol involved (1) recruiting amateur runners through social media; (2) collecting baseline data including demographic information, 24-Hour Holter monitoring, and three autonomic nervous function tests (Deep Breathing Test, Valsalva Maneuver, and Orthostatic Test); (3) conducting a 10-km run test; (4) random assignment into either the Performance Improvement Group or Safety First Group using a paired randomization approach that ensured there were no significant differences in baseline characteristics between the two groups; (5) devising a weekly exercise prescription by a fitness coach based on the 10-km run test results and group assignment, focusing on improving running performance through a blend of various running techniques and training modalities; (6) participants recording their exercise data using wearable devices, with weekly reporting for subsequent prescription adjustments; and (7) post-six-week training program, re-assessment using 24-Hour Holter monitoring and autonomic function tests [Supplementary Figure 1, http://links.lww.com/CM9/C103]. Statistical analysis included (1) presenting categorical variables as n (%), using Fisher’s exact test for correlations between two independent binary variables, McNemar’s test for differences between paired binary variables, and McNemar–Bowker test for paired multicategorical variables; (2) assessing continuous variables for normality with the Shapiro–Wilk test, expressing normally distributed data as mean ± standard deviation and non-normally distributed data as median (Q1–Q3); comparisons between groups using independent samples t-tests or Wilcoxon rank-sum tests, and within-group pre- and post-intervention comparisons utilized paired samples t-tests or Wilcoxon signed-rank tests; (3) displaying Holter monitoring indicators like heart rate (HR), heart rate variability (HRV), and others in tables with definitions in Supplementary Table 1, http://links.lww.com/CM9/C103; (4) subgroup analyses by baseline characteristics (exercise load, gender, age, body mass index [BMI], days after last infection [DALI], and total COVID-19 antibody levels), with the latter four variables grouped based on the median of their baseline levels; (5) multiple linear regressions corrected for age and gender were used to show the relationship between other baseline characteristics and the change in values of the measured indicators; and (6) using SPSS version 27.10 (IBM Corp., Armonk, NY, USA) for data analysis, with a