Development and validation of the Fracture Risk Scale (FRS) that predicts fracture over a 1-year time period in institutionalised frail older people living in Canada: an electronic record-linked longitudinal cohort study
Bibliographic record
Abstract
OBJECTIVES: To develop and validate our Fracture Risk Scale (FRS) over a 1-year time period, using the long-term care (LTC) Resident Assessment Instrument Minimum Data Set Version 2.0 (RAI-MDS 2.0). DESIGN: A retrospective cohort study. SETTING: LTC homes in Ontario, Canada. PARTICIPANTS: Older adults who were admitted to LTC and received a RAI-MDS 2.0 admission assessment between 2006 and 2010. RESULTS: A total of 29 848 LTC residents were enrolled in the study. Of these 22 386 were included in the derivation dataset and 7462 individual were included in the validation dataset. Approximately 2/3 of the entire sample were women and 45% were 85 years of age or older. A total of 1553 (5.2%) fractures were reported over the 1-year time period. Of these, 959 (61.8%) were hip fractures. Following a hip fracture, 6.3% of individuals died in the emergency department or as an inpatient admission and did not return to their LTC home. Using decision tree analysis, our final outcome scale had eight risk levels of differentiation. The percentage of individuals with a hip fracture ranged from 0.6% (lowest risk level) to 12.6% (highest risk level). The area under the curve of the outcome scale was similar for the derivation (0.67) and validation (0.69) samples, and the scale exhibited a good level of consistency. CONCLUSIONS: Our FRS predicts hip fracture over a 1-year time period and should be used as an aid to support clinical decisions in the care planning of LTC residents. Future research should focus on the transformation of our scale to a Clinical Assessment Protocol and to assess the FRS in other healthcare settings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".