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Agyapong-Badu S, Warner MB, Samuel D, et al. Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender. J Clin Med. 2021;10(7)doi: 10.3390/jcm10071352.
Agyapong-Badu, S., Warner, M. B., Samuel, D., Koutra, V., & Stokes, M. (2021). Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender. Journal of clinical medicine, 10(7), . https://doi.org/10.3390/jcm10071352
Agyapong-Badu, Sandra, et al. "Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender." Journal of clinical medicine vol. 10,7 (2021). doi: https://doi.org/10.3390/jcm10071352
Agyapong-Badu S, Warner MB, Samuel D, Koutra V, Stokes M. Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender. J Clin Med. 2021 Mar 25;10(7). doi: 10.3390/jcm10071352. PMID: 33805889; PMCID: PMC8036700.
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J Clin Med. 2021 Mar 25;10(7). doi: 10.3390/jcm10071352.

Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender.

Journal of clinical medicine

Sandra Agyapong-Badu, Martin B Warner, Dinesh Samuel, Vasiliki Koutra, Maria Stokes

Affiliations

  1. School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham B15 2TT, UK.
  2. School of Health Sciences, University of Southampton, Southampton SO17 1BJ, UK.
  3. Centre for Sport, Exercise and Osteoarthritis Research versus Arthritis, Southampton SO17 1BJ, UK.
  4. Southampton Biomedical Research Centre, Southampton SO16 6YD, UK.

PMID: 33805889 PMCID: PMC8036700 DOI: 10.3390/jcm10071352

Abstract

A novel approach to ageing studies assessed the discriminatory ability of a combination of routine physical function tests and novel measures, notably muscle mechanical properties and thigh composition (ultrasound imaging) to classify healthy individuals according to age and gender. The cross-sectional study included 138 community-dwelling, self-reported healthy males and females (65 young, mean age ± SD = 25.7 ± 4.8 years; 73 older, 74.9 ± 5.9 years). Handgrip strength; quadriceps strength; respiratory peak flow; timed up and go; stair climbing time; anterior thigh tissue thickness; muscle stiffness, tone, elasticity (Myoton technology), and self-reported health related quality of life (SF36) were assessed. Stepwise feature selection using cross-validation with linear discriminant analysis was used to classify cases based on criterion variable derived from known effects of age on physical function. A model was trained and features selected using 126 cases with 0.92 accuracy (95% CI = 0.86-0.96; Kappa = 0.89). The final model included five features (peak flow, timed up and go, biceps brachii elasticity, anterior thigh muscle thickness, and percentage thigh muscle) with high sensitivity (0.82-0.96) and specificity (0.94-0.99). The most sensitive novel biomarkers require no volition, highlighting potentially useful tests for screening and monitoring effects of interventions on musculoskeletal health for vulnerable older people with pain or cognitive impairment.

Keywords: ageing; musculoskeletal health; physical frailty; physical function; screening

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