Rehabilitation Is a Global Health Priority

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Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections

Accelerometer Validation of Questionnaires Used in Clinical Settings to Assess MVPA

Introduction The exercise vital sign (EVS) and General Practice Physical Activity Questionnaire (GPPAQ) are questionnaires designed for clinical settings to identify individuals who are not meeting physical activity (PA) guidelines in the United States and United Kingdom, respectively. To date, neither has been objectively validated. Methods Subjects (N = 76) from the United States (n = 38; age, 49 ± 20 yr) and United Kingdom (n = 38; age, 43 ± 21 yr) completed a health history questionnaire, wore an accelerometer for 7 d, and then completed the EVS and GPPAQ. Accelerometry, EVS, and GPPAQ data were scored to dichotomize subjects into groups of meeting (≥150 min of moderate-to-vigorous PA (MVPA) per week) or not meeting (<150 min of MVPA per week) the PA guidelines, and accelerometry was used as a criterion measure for comparing both questionnaires. The sensitivity and specificity of the EVS and GPPAQ were calculated to represent the ability of the questionnaires to identify subjects who did not and did meet the PA guidelines. Total MVPA accumulated in ≥10-min bouts were compared between accelerometry and the EVS using a 2 × 2 × 2 repeated measures ANOVA with one within-subjects effect (PA assessment method) and two between-subjects effects (gender and country). The alpha level was P = 0.05 for all analyses. Results The EVS had marginally better sensitivity (59% vs 46%) and specificity (77% vs 50%) than the GPPAQ. The EVS grossly overestimated the minutes of MVPA when compared to accelerometry (P < 0.05) for all subjects, except UK women. Conclusion In practice, the EVS and GPPAQ may not identify ∼50% of patients who should be advised to increase their PA. Therefore, physicians should advocate that all of their patients adopt an active lifestyle, including the achievement of ≥150 min of MVPA per week

New Equations for Predicting Maximum Oxygen Uptake in Patients With Heart Failure

We obtained directly measured maximal oxygen uptake (VO2 max) by open-circuit spirometry in 1,453 patients with chronic heart failure (HF) who completed a treadmill test (n = 1,453) or cycle ergometry (n = 1,838), as participants in The Fitness Registry and the Importance of Exercise National Data Base (FRIEND) dataset. We developed a new equation to predict measured VO2 max in those using a treadmill by randomly sampling 70% of the participants from each of the following age categories: &amp;lt;40, 40 to 50, 50 to 70, and &amp;gt;70 and used the remaining 30% for validation. Multivariable linear regression analysis was applied to identify the most relevant variables and construct the best prediction model for VO2 max. Treadmill speed and treadmill speed * grade were considered in the final model as predictors of measured VO2 max and the following equation was generated: VO2 max in ml O2 kg/min = speed (m/min) * (0.17 + fractional grade * 0.32) +3.5. To assess the efficacy of the equation, we applied it to 1,612 patients in the HF-ACTION cohort. To assess the efficacy of the FRIEND cycle ergometry equation developed for healthy individuals we applied it to 1,838 HF patients in the FRIEND cohort and 306 patients in a Greek population of HF patients with directly measured VO2 max. The FRIEND equations were superior to ACSM equations in predicting VO2 max regardless of the cohort or exercise mode used (treadmill or cycle ergometry) to access VO2 max. © 2020 Elsevier Inc