Risk Factors and Multidimensional Assessment of Long Coronavirus Disease Fatigue: A Nested Case-Control Study.

BACKGROUND: Fatigue is the most prevalent and debilitating long-COVID (coronavirus disease) symptom; however, risk factors and pathophysiology of this condition remain unknown. We assessed risk factors for long-COVID fatigue and explored its possible pathophysiology. METHODS: This was a nested case-control study in a COVID recovery clinic. Individuals with (cases) and without (controls) significant fatigue were included. We performed a multidimensional assessment evaluating various parameters, including pulmonary function tests and cardiopulmonary exercise testing, and implemented multivariable logistic regression to assess risk factors for significant long-COVID fatigue. RESULTS: A total of 141 individuals were included. The mean age was 47 (SD: 13) years; 115 (82%) were recovering from mild coronavirus disease 2019 (COVID-19). Mean time for evaluation was 8 months following COVID-19. Sixty-six (47%) individuals were classified with significant long-COVID fatigue. They had a significantly higher number of children, lower proportion of hypothyroidism, higher proportion of sore throat during acute illness, higher proportions of long-COVID symptoms, and of physical limitation in daily activities. Individuals with long-COVID fatigue also had poorer sleep quality and higher degree of depression. They had significantly lower heart rate [153.52 (22.64) vs 163.52 (18.53); P = .038] and oxygen consumption per kilogram [27.69 (7.52) vs 30.71 (7.52); P = .036] at peak exercise. The 2 independent risk factors for fatigue identified in multivariable analysis were peak exercise heart rate (OR: .79 per 10 beats/minute; 95% CI: .65-.96; P = .019) and long-COVID memory impairment (OR: 3.76; 95% CI: 1.57-9.01; P = .003). CONCLUSIONS: Long-COVID fatigue may be related to autonomic dysfunction, impaired cognition, and decreased mood. This may suggest a limbic-vagal pathophysiology. CLINICAL TRIALS REGISTRATION: NCT04851561.

Prediction of Maximal Heart Rate in Children and Adolescents.

OBJECTIVE: To identify a method to predict the maximal heart rate (MHR) in children and adolescents, as available prediction equations developed for adults have a low accuracy in children. We hypothesized that MHR may be influenced by resting heart rate, anthropometric factors, or fitness level. DESIGN: Cross-sectional study. SETTING: Sports medicine center in primary care. PARTICIPANTS: Data from 627 treadmill maximal exercise tests performed by 433 pediatric athletes (age 13.7 ± 2.1 years, 70% males) were analyzed. INDEPENDENT VARIABLES: Age, sex, sport type, stature, body mass, BMI, body fat, fitness level, resting, and MHR were recorded. MAIN OUTCOME MEASURES: To develop a prediction equation for MHR in youth, using stepwise multivariate linear regression and linear mixed model. To determine correlations between existing prediction equations and pediatric MHR. RESULTS: Observed MHR was 197 ± 8.6 b·min. Regression analysis revealed that resting heart rate, fitness, body mass, and fat percent were predictors of MHR (R = 0.25, P < 0.001), whereas age was not. Resting heart rate explained 15.6% of MHR variance, body mass added 5.7%, fat percent added 2.4%, and fitness added 1.2%. Existing adult equations had low correlations with observed MHR in children and adolescents (r = -0.03-0.34). CONCLUSIONS: A new equation to predict MHR in children and adolescents was developed, but was found to have low predictive ability, a finding similar to adult equations applied to children. CLINICAL RELEVANCE: Considering the narrow range of MHR in youth, we propose using 197 b·min as the mean MHR in children and adolescents, with 180 b·min the minimal threshold value (-2 standard deviations).

Metabolic rate prediction by massless actigraphy for outdoor activities.

PURPOSE: In military scenarios, there is a need for a system that can enable identification of possible future injury during different activities that are considered to be physically strenuous. The purpose of the present study was to determine whether the use of an octagonal actigraph in conjunction with heart rate (fc) measurements could serve as an accurate method for metabolic rate estimation for different free-living activities in field settings. METHODS: Twenty young healthy volunteers (10 men, 22 +/- 3 years of age, and 10 women, 23 +/- 3 years of age) participated in this study. All participants were exposed to six different activities (walking, running, sweeping, climbing and descending stairs, and shopping). Continuous actigraphic measurements were collected from the hip and wrist, fc was monitored with a Polar chest belt, and oxygen consumption (VO2) was measured with a K4b2 system. RESULTS: A prediction model for VO2 was constructed from actigraphic and fc measurements. Comparisons between predicted and measured VO2 values revealed high correlations (hip, R2 = 0.842; wrist, R2 = 0.822). CONCLUSIONS: This new prediction model highly correlated with VO2 measurements. The hip was found to be more favorable than the wrist for assessment of VO2 for different free-living activities.