Estimation of peak oxygen consumption in individuals with spinal cord injury patients using multiple linear regression analysis: a preliminary study.

Purpose: This study aims to develop a regression model to estimate peak oxygen consumption (VO2peak) in individuals with spinal cord injury (SCI) by employing different variables.

Methods: In this study, 34 participants were divided into two groups: 19 with cervical injury (CI) and 15 with thoracic injury (TI). Key measurements included VO2peak and related factors such as age, height, weight, body mass index (BMI), fat-free mass, body fat percentage, limb and trunk circumferences, spinal cord independence (SCIM III), Korean activities of daily living (K-ADL), and respiratory functions (forced vital capacity (FVC), peak expiratory flow (PEF), and maximum voluntary ventilation (MVV)). Statistical analyses were conducted using forward selection regression to examine the relationships between these variables.

Results: Height, calf circumference, SCIM III score, and PEF were key variables in all patients with SCI (TSCI). For patients with CI, the key variables were height, calf circumference, and MVV, whereas for patients with TI, the key variable was calf circumference. The average explanatory powers of the VO2peak regression model for TSCI were 70.3% (R2) and 66.2% (adjusted R2), with an average standard error of estimate (SEE) of 2.94 ml/kg/min. The average explanatory power for patients with CI was 71.7% (R2) and 66.1% (adjusted R2), with an average SEE of 1.88 ml/kg/min. The average explanatory power for patients with TI was 55.9% (R2) and 52.5% (adjusted R2), with an average SEE of 3.41 ml/kg/min. There was no significant difference between the VO2peak measured and predicted VO2peak for each type of injury.

Conclusion: The regression model for estimating VO2peak in SCI patients in this preliminary study is as follows: TSCI=39.684-0.144×(Height)-0.513×(Calf)+0.136×(SCIM III)+1.187×(PEF), CI=38.842-0 .158×(Height) - 0.371×(Calf)+0.093×(MVV), TI=42.325-0.813×(Calf).