RESUMEN
Half of osteoporotic fractures occur in patients with normal/osteopenic bone density or at intermediate or low estimated risk. Muscle measures have been shown to contribute to fracture risk independently of bone mineral density. The objectives were to review the measurements of muscle health (muscle mass/quantity/quality, strength and function) and their association with incident fragility fractures and to summarize their use in clinical practice. This scoping review follows the PRISMA-ScR guidelines for reporting. Our search strategy covered the three overreaching concepts of 'fragility fractures', 'muscle health assessment' and 'risk'. We retrieved 14 745 references from Medline Ovid SP, EMBASE, Web of Science Core Collection and Google Scholar. We included original and prospective studies on community-dwelling adults aged over 50 years that analysed an association between at least one muscle parameter and incident fragility fractures. We systematically extracted 17 items from each study, including methodology, general characteristics and results. Data were summarized in tables and graphically presented in adjusted forest plots. Sixty-seven articles fulfilled the inclusion criteria. In total, we studied 60 muscle parameters or indexes and 322 fracture risk ratios over 2.8 million person-years (MPY). The median (interquartile range) sample size was 1642 (921-5756), age 69.2 (63.5-73.6) years, follow-up 10.0 (4.4-12.0) years and number of incident fragility fractures 166 (88-277). A lower muscle mass was positively/not/negatively associated with incident fragility fracture in 28 (2.0), 64 (2.5) and 10 (0.2 MPY) analyses. A lower muscle strength was positively/not/negatively associated with fractures in 53 (1.3), 57 (1.7 MPY) and 0 analyses. A lower muscle function was positively/not/negatively associated in 63 (1.9), 45 (1.0 MPY) and 0 analyses. An in-depth analysis shows how each single muscle parameter was associated with each fragility fractures subtype. This review summarizes markers of muscle health and their association with fragility fractures. Measures of muscle strength and function appeared to perform better for fracture risk prediction. Of these, hand grip strength and gait speed are likely to be the most practical measures for inclusion in clinical practice, as in the evaluation of sarcopenia or in further fracture risk assessment scores. Measures of muscle mass did not appear to predict fragility fractures and might benefit from further research, on D3-creatine dilution test, lean mass indexes and artificial intelligence methods.
RESUMEN
The individual and societal burden of osteoporosis is high and will continue to increase due to the demographic situation. Applications based on artificial intelligence models can provide concrete solutions at each step of the management of osteoporosis: screening, diagnostic, therapy management and prognostic assessment. The implementation of such models could assist clinicians in their workflow while improving overall patient care.
L'ostéoporose représente un fléau important, à l'échelle individuelle mais aussi sociétale. Avec le vieillissement de la population, le nombre de patients concernés augmente de manière considérable. Des applications basées sur des modèles d'intelligence artificielle nous apportent des solutions de plus en plus concrètes, à chaque étape de la prise en charge de l'ostéoporose : dépistage, diagnostic, prise en charge médicamenteuse et évaluation pronostique. L'implémentation de tels modèles pourrait aider les professionnels de santé, aussi bien dans l'optimisation du flux du travail que dans la prise en charge clinique du patient.
Asunto(s)
Inteligencia Artificial , Osteoporosis , Humanos , Osteoporosis/diagnóstico , Osteoporosis/terapia , PronósticoRESUMEN
Sarcopenia is an aging syndrome with multiple contributing factors, characterized by a loss of muscle strength, function and mass. It affects a third of the elderly population, increasing morbidity and mortality, as well as health costs. It should be suspected in the event of a decrease in physical capacities reported or observed during the consultation, in a patient with risk factors. Five questions (SARC-F formulary) or the measure of the gait speed makes screening easy to perform ; the diagnosis is confirmed by supplementary examinations in a specialized center. Treatment consists on performing physical exercises against resistance and ensuring sufficient caloric and protein intake; drug treatments are under study.
La sarcopénie est un syndrome lié au vieillissement avec de multiples facteurs favorisants, caractérisé par une perte de la force, de la fonction et de la masse musculaires. Elle affecte un tiers de la population âgée, chez qui elle augmente la morbidité et la mortalité ainsi que les coûts de la santé. On doit la suspecter en cas de diminution des capacités physiques rapportée ou observée lors de la consultation chez un patient présentant des facteurs de risque. Cinq questions (formulaire SARC-F) ou la mesure de la vitesse de la marche rendent facile le dépistage ; le diagnostic est confirmé par des examens complémentaires dans un centre spécialisé. La prise en charge consiste en la réalisation d'exercices physiques contre résistance en assurant des apports caloriques et protéiques suffisants ; des traitements médicamenteux sont à l'étude.