Health Assessment Questionnaire at One Year Predicts All‐Cause Mortality in Patients With Early Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Higher self-reported disability (high Health Assessment Questionnaire [HAQ] score) has been associated with hospitalizations and mortality in established rheumatoid arthritis (RA), but associations in early RA are unknown. METHODS: Patients with early RA (symptom duration <1 year) enrolled in the Canadian Early Arthritis Cohort who initiated disease-modifying antirheumatic drugs and had completed HAQ data at baseline and 1 year were included in the study. Discrete-time proportional hazards models were used to estimate crude and multi-adjusted associations of baseline HAQ and HAQ at 1 year with all-cause mortality in each year of follow-up. RESULTS: A total of 1,724 patients with early RA were included. The mean age was 55 years, and 72% were women. Over 10 years, 62 deaths (3.6%) were recorded. Deceased patients had higher HAQ scores at baseline (mean ± SD 1.2 ± 0.7) and at 1 year (0.9 ± 0.7) than living patients (1.0 ± 0.7 and 0.5 ± 0.6, respectively; P < 0.001). Disease Activity Score in 28 joints (DAS28) was higher in deceased versus living patients at baseline (mean ± SD 5.4 ± 1.3 versus 4.9 ± 1.4) and at 1 year (mean ± SD 3.6 ± 1.4 versus 2.8 ± 1.4) (P < 0.001). Older age, male sex, lower education level, smoking, more comorbidities, higher baseline DAS28, and glucocorticoid use were associated with mortality. Contrary to HAQ score at baseline, the association between all-cause mortality and HAQ score at 1 year remained significant even after adjustment for confounders. For baseline HAQ score, the unadjusted hazard ratio (HR) was 1.46 (95% confidence interval [95% CI] 1.02-2.09), and the adjusted HR was 1.25 (95% CI 0.81-1.94). For HAQ score at 1 year, the unadjusted HR was 2.58 (95% CI 1.78-3.72), and the adjusted HR was 1.75 (95% CI 1.10-2.77). CONCLUSION: Our findings indicate that higher HAQ score and DAS28 at 1 year are significantly associated with all-cause mortality in a large early RA cohort.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".