3.8 Article

Prediction models for physical function in COVID-19 survivors

Journal

JOURNAL OF BODYWORK AND MOVEMENT THERAPIES
Volume 37, Issue -, Pages 70-75

Publisher

ELSEVIER
DOI: 10.1016/j.jbmt.2023.11.002

Keywords

COVID-19; Physical functioning; Fatigue; Muscle strength; Rehabilitation

Categories

Ask authors/readers for more resources

This study built prediction models for the Post-COVID-19 Functional Status (PCFS) scale using sociodemographic data, clinical findings, lung function, and muscle strength. The results showed that worse general fatigue and handgrip strength were associated with more severe physical function impairments in patients with post-COVID-19 syndrome. Additionally, a history of prior hospitalization resulted in worse physical function. Prediction models incorporating objective measures can better assess the physical function of these patients and aid in the selection of candidates for a physical reconditioning program.
Background: The burden of caring for patients who have survived COVID-19 will be enormous in the coming years, especially with respect to physical function. Physical function has been routinely assessed using the PostCOVID-19 Functional Status (PCFS) scale. Aim: This study built prediction models for the PCFS scale using sociodemographic data, clinical findings, lung function, and muscle strength.Method: Two hundred and one patients with post-COVID-19 syndrome (PCS) completed the PCFS scale to assess physical function. Their levels of general fatigue were also assessed using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) scale, handgrip strength (HGS), and spirometry.Results: The number of participants who scored 0 (none), 1 (negligible), 2 (slight), 3 (moderate), and 4 (severe) on the PCFS scale was 25 (12%), 40 (20%), 39 (19%), 49 (24%), and 48 (24%), respectively. The PCFS scale was significantly correlated with the following variables: FACIT-F score (r =-0.424, P < 0.001), HGS (r =-0.339, P < 0.001), previous hospitalization (r = 0.226, P = 0.001), body mass index (r = 0.163, P = 0.021), and sex (r =-0.153, P = 0.030). The regression model with the highest coefficient of regression (R = 0.559) included the following variables: age, sex, body mass index, FACIT-F, HGS, and previous hospitalization.Conclusions: Worse general fatigue and HGS are associated with more severe physical function impairments in PCS patients. Furthermore, a history of prior hospitalization results in worse physical function. Thus, prediction models for the PCFS scale that incorporate objective measures enable a better assessment of the physical function of these patients, thus helping in the selection of candidates for a program of physical reconditioning.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available