Prediction models and development of an easy to use open-access tool for measuring lung function of individuals with motor complete spinal cord injury

Abstract

Objective: To develop statistical models to predict lung function and respiratory muscle strength from personal and lesion characteristics of individuals with motor complete spinal cord injury. Design: Cross-sectional, multi-centre cohort study. Subjects: A total of 440 individuals with traumatic, motor complete spinal cord injury, time post-injury ≥ 6 months, lesion level C4?T12, underwent measurements of lung function and respiratory muscle strength. Methods: Prediction models for lung volumes and peak inspiratory and expiratory muscle strength were calculated. Using multi-level regression models, the effects of personal characteristics (gender, age, height, body mass) and lesion characteristics (time post-injury and lesion level) were determined. Results: Positive predictors of lung function parameters were: male gender, younger age, greater height, greater body mass and lower lesion level. For maximal inspiratory muscle strength, male gender, younger age, greater body mass and lower lesion level were significant positive predictors, whereas for maximal expiratory muscle strength, male gender, younger age, longer time post-injury and lower lesion level were positive influencing parameters. Conclusion: In contrast to predictive models for able-bodied individuals, lung function parameters of persons with spinal cord injury are influenced by body mass and lesion level. Maximal expiratory muscle strength improves with longer time post-injury.