Risk of Heart Failure in Patients With Immune-Mediated Inflammatory Diseases: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the risk of heart failure (HF) in patients with immune-mediated inflammatory diseases (IMIDs) compared to the general population with and without diabetes mellitus (DM). METHODS: A population-based cohort study was conducted in patients with rheumatoid arthritis (RA), radiographic axial spondyloarthritis (r-axSpA), psoriatic arthritis, and psoriasis (PsO) in Ontario from 2011 until 2019. The study outcome was first hospitalization for HF. Incidence rates of HF were calculated for each cohort. Hazard ratios (HRs) for HF were calculated using Cox proportional hazard models. The etiology of HF was descriptively classified into mutually exclusive groups based on comorbidities during HF hospitalization. RESULTS: A total of 243,061 patients with IMID, 748,517 with DM, and 8,278,934 non-IMID, non-DM controls were analyzed. The crude incidence rate for HF in IMID was 2.70 per 1000 person-years, with the highest rate in RA and lowest in r-axSpA. The risk of being hospitalized for HF was higher in IMID compared with non-IMID comparators (HR 1.34, 95% CI 1.30-1.38). This risk was highest among patients with RA (HR 1.61, 95% CI 1.54-1.68) and lowest in PsO (HR 1.09, 95% CI 1.03-1.15). In comparison, the risk of HF hospitalization in patients with DM was higher (HR 2.19, 95% CI 2.16-2.21). The most common antecedent comorbidity associated with HF in all patients with IMID was ischemic heart disease. In patients with IMID without DM, atrial fibrillation had a similar effect as ischemic heart disease. CONCLUSION: The risk of HF hospitalization is increased in patients with IMID compared to the general population.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".