Incidence of and Risk of Mortality After Hip Fractures in Rheumatoid Arthritis Relative to the General Population
Bibliographic record
Abstract
OBJECTIVE: Osteoporosis, a known complication of rheumatoid arthritis (RA), increases the risk of hip fracture, which is associated with high morbidity and mortality. Fracture risk estimates in patients with RA treated with contemporary treatment strategies are lacking. The objectives were (1) estimate age-specific and sex-specific incidence rates and compare the risk of hip fractures in RA relative to age-matched and sex-matched general population controls, and (2) compare the risk of all-cause mortality in RA and general population controls after hip fracture. METHODS: A longitudinal study of a population-based incident cohort of patients with RA diagnosed between 1997 and 2009, followed until 2014, with age-matched and sex-matched controls from the general population of British Columbia, using administrative health data. Hip fracture outcomes (International Classification of Diseases, Ninth Edition, Clinical Modification [ICD-9-CM] codes 820.0 or 820.2; ICD-10-Canada code S72.0 to S72.2) and mortality at predefined intervals after fracture (in hospital, 90 days, 1-year, 5-year) were identified. Hip fracture incidence rates for RA and controls, and incidence rate ratios (IRRs), were calculated. Cox proportional hazards models compared hip fracture and mortality risk in RA versus controls; logistic regression compared in-hospital mortality risk. RESULTS: Overall, 1,314 hip fractures over 360,521 person-years were identified in 37,616 individuals with RA and 2,083 over 732,249 person-years in 75,213 controls, yielding a 28% greater fracture risk in RA (IRR 1.28 [95% confidence interval 1.20-1.37]). Mean age at time of fracture was slightly younger for RA than controls (79.6 ± 10.8 vs 81.6 ± 9.3 years). Postfracture mortality risk at one-year and five-years did not differ between RA and general population controls. Results were similar in a sensitivity analysis including only individuals with RA who received disease-modifying antirheumatic drugs. CONCLUSION: People with RA had a greater risk of hip fractures, but no greater risk of mortality post fracture, than the general population. The relative risk of hip fractures observed was not as high as previously reported, likely reflecting better treatment of inflammation and management of osteoporosis and its risk factors.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".