Application of <scp>Cut‐Points</scp> for Low Muscle Strength and Lean Mass in <scp>Mobility‐Limited</scp> Older Adults
Bibliographic record
Abstract
BACKGROUND: The Sarcopenia Definitions and Outcomes Consortium (SDOC) is a collaborative initiative seeking to develop and evaluate cut-points for low muscle strength and lean mass that predict an increased risk for slowness (usual walking speed <.8 m/s) among older adults. OBJECTIVES: The goal of the present study was to provide clinicians and researchers with an understanding of the diagnostic implications of using SDOC variables and cut-points in mobility-limited older adults. Using data from older individuals with specific conditions that render them at increased risk for mobility limitation, we evaluated the performance characteristics (ie, sensitivity and specificity) of five putative sarcopenia parameters and then compared these values with previously recommended diagnostic criteria for sarcopenia. DESIGN: Retrospective analysis of six randomized controlled trials enriched in persons at risk for mobility limitation. SETTING: National and international geriatric clinical research centers. PARTICIPANTS: A total of 925 mobility-limited older adults (≥55 years of age; 58% women) were included in the analysis. MEASUREMENTS: The prevalence of low muscle strength and lean mass were assessed using five candidate metrics discriminative of slowness. Analyses of sensitivity and specificity were used to compare muscle weakness criteria with published diagnostics for sarcopenia. RESULTS: Odds ratios (ORs) supported maximal grip strength (Grip max <35.5 and 20.0 in men and women, respectively) as the most discriminative of slowness in both men and women (OR = 3.66 and 3.53, respectively). More men (58%) than women (30%) fell below sex-specific maximal grip cut-points. When applying previously recommended sarcopenia component definitions in our population, we found that fewer individuals met those criteria (range = 6%-32%). CONCLUSION: A greater number of individuals fall below SDOC Grip max cut-points compared with previous recommendations. Clinicians and researchers working with older adults may consider these thresholds as an inclusive means to identify candidates for low-risk lifestyle promyogenic and function-promoting therapies. J Am Geriatr Soc 68:1445-1453, 2020.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".