Do Different Ascertainment Techniques Identify the Same Individuals as Sarcopenic in the Canadian Longitudinal Study on Aging?
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Sarcopenia is associated with poor health outcomes such as disability, institutionalization, and mortality. Efforts to manage sarcopenia clinically have been hindered by challenges in determining how to ascertain sarcopenia status correctly. The objective of this project was to assess the agreement between the different methods of ascertaining sarcopenia recommended by expert groups. DESIGN: Cross-sectional study of baseline data (2011-2015) from the Canadian Longitudinal Study on Aging. SETTING: Population-based multicenter study of community-dwelling participants. PARTICIPANTS: Eligible participants (n = 12,646) aged 65 to 85 living within 25 to 50 km of 11 data collection sites in Canada. The analyses included 10,820 participants with the data required to diagnose sarcopenia. MEASUREMENTS: Sarcopenia was operationalized as appendicular lean mass (ALM), ALM and grip strength, ALM and gait speed, and grip strength and gait speed. Within each combination, ALM was adjusted for height squared, weight, body mass index, and the residual of regressing lean mass on height and fat mass. The lowest 20th sex-specific percentile values were used as the cutoffs for low ALM. Low grip strength cutoffs of 35.5 kg for men and 20 kg for women and a gait speed cutoff of .8 m/s were used. RESULTS: The mean age was 73.0 ± 5.6 years, and 51.9% of the sample was male. The agreement (Cohen's κ) between the different combinations of variables used to ascertain sarcopenia status was below .50. Agreement for the different lean mass adjustment techniques ranged from .04 to .76. CONCLUSION: The combination of variables used to ascertain sarcopenia and many of the ALM adjustment techniques have insufficient agreement to be considered equivalent. This has important clinical implications for the management of sarcopenia because treatments may differ based on how sarcopenia is identified. To improve the clinical utility of sarcopenia, a unified definition of sarcopenia is required.
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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 | 0.116 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".