Muscle failure and risk of adverse outcomes in older adults: a derivation and multicohort validation study.

BACKGROUND: Sarcopenia is inconsistently defined, and its definition might not adequately capture muscle failure, underlying disability, and other adverse outcomes in older adults. We aimed to develop and validate an evidence-based, outcome-driven model of muscle failure. METHODS: In this derivation and multicohort validation study, we analysed data from the SPRINTT randomised controlled trial (1519 participants; mean age 78·9 years [SD 5·8]; 431 [28·4%] men, 1088 (71·6%) women) and validated findings in five independent cohorts (ilSIRENTE, NHANES, HRS, ELSA, and CHARLS). Neuromuscular domains including appendicular lean mass, muscle strength and power, mobility, and physical activity were assessed. Principal component analysis identified clusters of measures, which were tested for associations with disability in mobility and disability in activities of daily living, hospitalisation, and mortality using adjusted regression models. Predictive performance was evaluated with receiver operating characteristic curves. Area under the curve (AUC) values were defined as acceptable (0·7-0·8), excellent (0·8-0·9), or outstanding (>0·9). FINDINGS: We identified two major muscle failure indexes: mobility (short-distance walking speed, 400 m walk) and physical activity (step counts, time spent standing, stepping, and sitting). In SPRINTT, the mobility model strongly predicted disability (AUC 0·721, 95% CI 0·698-0·795; p<0·0001), whereas the physical activity model was more closely associated with hospitalisation (0·646, 0·570-0·731; p=0·00040) and mortality (0·746, 0·612-0·926; p=0·0020). Combined models including mobility, handgrip strength, appendicular lean mass, and absolute muscle power improved prediction of mortality (0·746, 0·549-0·955; p=0·0076). External validation confirmed acceptable-to-strong discrimination for disability outcomes across cohorts (AUCs 0·7-0·9), while associations with hospitalisation and mortality were weaker and inconsistent (0·4-0·9). Compared with consensus-based sarcopenia definitions, the evidence-based model seemed to show better predictive ability for disability. INTERPRETATION: Distinct mobility measures provide a robust framework for identifying muscle failure and predicting disability in older adults. Continuous activity monitoring might improve prediction of hospitalisation and mortality. This outcome-driven approach supports refinement of sarcopenia assessment and its implementation in clinical practice. FUNDING: None.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2026-05-12
DOI
https://doi.org/10.1016/j.lanhl.2026.100843
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Muscle failure and risk of adverse outcomes in older adults: a derivation and multicohort validation study.

Alejandro Álvarez‐Bustos, Isabel Rodríguez-Sánchez, Emanuele Marzetti, Francesco Landi et al.
PubMed
Nutrition and Health in Aging
article

Muscle failure and risk of adverse outcomes in older adults: a derivation and multicohort validation study.

Alejandro Álvarez‐Bustos, Isabel Rodríguez-Sánchez, Emanuele Marzetti, Francesco Landi, Hélio José Coelho-Júnior
article en

Abstract

BACKGROUND: Sarcopenia is inconsistently defined, and its definition might not adequately capture muscle failure, underlying disability, and other adverse outcomes in older adults. We aimed to develop and validate an evidence-based, outcome-driven model of muscle failure. METHODS: In this derivation and multicohort validation study, we analysed data from the SPRINTT randomised controlled trial (1519 participants; mean age 78·9 years [SD 5·8]; 431 [28·4%] men, 1088 (71·6%) women) and validated findings in five independent cohorts (ilSIRENTE, NHANES, HRS, ELSA, and CHARLS). Neuromuscular domains including appendicular lean mass, muscle strength and power, mobility, and physical activity were assessed. Principal component analysis identified clusters of measures, which were tested for associations with disability in mobility and disability in activities of daily living, hospitalisation, and mortality using adjusted regression models. Predictive performance was evaluated with receiver operating characteristic curves. Area under the curve (AUC) values were defined as acceptable (0·7-0·8), excellent (0·8-0·9), or outstanding (>0·9). FINDINGS: We identified two major muscle failure indexes: mobility (short-distance walking speed, 400 m walk) and physical activity (step counts, time spent standing, stepping, and sitting). In SPRINTT, the mobility model strongly predicted disability (AUC 0·721, 95% CI 0·698-0·795; p<0·0001), whereas the physical activity model was more closely associated with hospitalisation (0·646, 0·570-0·731; p=0·00040) and mortality (0·746, 0·612-0·926; p=0·0020). Combined models including mobility, handgrip strength, appendicular lean mass, and absolute muscle power improved prediction of mortality (0·746, 0·549-0·955; p=0·0076). External validation confirmed acceptable-to-strong discrimination for disability outcomes across cohorts (AUCs 0·7-0·9), while associations with hospitalisation and mortality were weaker and inconsistent (0·4-0·9). Compared with consensus-based sarcopenia definitions, the evidence-based model seemed to show better predictive ability for disability. INTERPRETATION: Distinct mobility measures provide a robust framework for identifying muscle failure and predicting disability in older adults. Continuous activity monitoring might improve prediction of hospitalisation and mortality. This outcome-driven approach supports refinement of sarcopenia assessment and its implementation in clinical practice. FUNDING: None.

PubMed
Agostino Gemelli University Polyclinic (IT), Hospital Clínico San Carlos (ES), Camilo José Cela University (ES)
Gender equality
Openalex Percentile: Top 5%
Nutrition and Health in Aging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.