Long‐term strength and functional status in inclusion body myositis and identification of trajectory subgroups
Bibliographic record
Abstract
INTRODUCTION: Objective information on longitudinal disease progression in inclusion body myositis (IBM) is lacking. METHODS: Longitudinal dynamometry and functional status data were collated from a cohort of IBM patients. Annual change was calculated by means of linear modeling. Trajectories of change in grip, knee extension, IBM Functional Rating Scale (IBM-FRS) and Neuromuscular Symptom Score (NSS) were identified by means of latent growth mixture modeling. RESULTS: Data were collated from 75 IBM patients (348 person-years follow-up). Annual strength loss was greatest for pinch (-10%) and knee extension (-4%). Functional deterioration was greatest for males. Three distinct trajectory groups were identified. Rapid deterioration trajectory for grip strength was associated with younger diagnosis age. Rapid deterioration for knee extension strength was associated with older age of diagnosis. DISCUSSION: This study has quantified strength change in IBM and identified distinct trajectory groups, which will aid prognostication and stratification for inclusion into future clinical trials.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".