Validation of a clinical prediction model for falls in community-dwelling older adults with COPD: A preliminary analysis
Bibliographic record
Abstract
BACKGROUND: People with chronic obstructive pulmonary disease (COPD) are at a higher risk of falls. This preliminary study aims to externally validate a previously developed clinical prediction model for falls in community-dwelling older adults with COPD. METHODS: This was a secondary analysis of a 12-month prospective cohort study. Older adults (≥60 years) with COPD, who reported a fall in the past year and/or had balance concerns, were tracked for 12-month future falls. Baseline predictors included 12-month history of ≥2 falls, total chronic conditions, and Timed Up and Go Dual-Task (TUG-DT) test scores. Model performance was assessed for discrimination (c-statistic), calibration (E:O, CITL, and calibration slope), and clinical value (decision curve analysis). RESULTS: %predicted = 47%). Of these, 35 (39%) reported ≥1 future fall, totaling 89 falls. The model demonstrated acceptable discrimination (c-statistic = 0.62, CI [0.51,0.72]), and calibration (E:O = 1, CITL = 0, and a calibration slope = 1). Decision curve analysis showed greater clinical value when using the prediction model compared to screening for fall history alone. CONCLUSIONS: A 12-month history of ≥2 falls, higher total chronic conditions, and worse TUG-DT test scores, predicts falls in community-dwelling older adults with COPD. Larger studies are needed before clinical application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".