Accuracy of Offspring-Reported Parental Hip Fractures: A Novel Population-Based Parent-Offspring Record Linkage Study
Bibliographic record
Abstract
The objective of this study was to test the validity of offspring-reported parental hip fracture in a unique bone mineral density (BMD) registry linked to administrative databases spanning 4 decades. Population-based data were from Manitoba, Canada, and included hospital abstracts, health insurance registrations, and the provincewide BMD registry. The cohort included individuals aged ≥40 years with BMD tests and self-reports of parental hip fracture between 2006 and 2014. Population registry data for 1966-2014 were used to link offspring with their parents, and hospital records were used to ascertain parental fractures. Overall, 8,112 offspring met the inclusion criteria; 13.6% had a parental hip fracture diagnosis in administrative data during an average of 32.9 years of follow-up. Agreement between parental hip fracture from offspring reports and diagnoses in administrative data was good (κ = 0.68). The sensitivity of offspring reports was 0.70 (95% confidence interval: 0.67, 0.73), and specificity was 0.96 (95% confidence interval: 0.96, 0.97). Offspring characteristics associated with disagreement included male sex, northern rural residence, early BMD test year, and longer interval between BMD test and parental hip fracture diagnosis. This proof-of-concept study focused on hip fractures, but use of record linkage techniques to validate offspring-reported parental information can be extended to other conditions.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".