Impact of Systemic Lupus Erythematosus on the Risk of Newly Diagnosed Hip Fracture: A General Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: Hip fractures have serious consequences, including a 1-year mortality rate of 30%. Population-based studies on hip fractures in individuals with systemic lupus erythematosus (SLE) are scarce. Our objective was to assess the independent risk of hip fractures in patients with newly diagnosed SLE compared to the general population, accounting for baseline and time-varying confounders. METHODS: A cohort of all patients with incident SLE who received health care between January 1, 1997 and March 31, 2015 was assembled. The primary outcome was the occurrence of the first hip fracture since the study entry date. Individuals without SLE were randomly selected from the general population and matched (5:1) to those with SLE based on age, sex, and index year. Cumulative incidence was calculated after accounting for competing risks of death. Marginal structural Cox models were used to estimate the impact of SLE on hip fractures, adjusting for baseline and time-dependent covariates (i.e., glucocorticoid use and the number of outpatient, inpatient, and rheumatologist visits). RESULTS: Among 5,047 individuals with incident SLE and 25,235 individuals without SLE (86% female, mean age 40 years), we found 73 and 272 hip fractures during 78,915 and 395,427 person-years, respectively. The crude incidence rate ratio was 1.34 (95% confidence interval [95% CI] 1.02-1.75). After adjusting for baseline covariates, the hazard ratio (HR) was 1.86 (95% CI 1.37-2.52). After further adjustment for time-dependent covariates, the HR remained significant at 1.62 (95% CI 1.06-2.48). CONCLUSION: Patients with newly diagnosed SLE have a 62% increased risk of hip fractures compared to individuals without SLE. For patients with SLE, this result has important implications for prevention of osteoporosis, which may lead to hip fractures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".