Mortality in Patients With Sjögren Disease: A Prospective Cohort Study Identifying Key Predictors
Bibliographic record
Abstract
OBJECTIVE: We aimed to quantify the mortality risk in a large, well-characterized cohort of patients with Sjögren disease (SjD) and to identify independent predictors of mortality in this population. METHODS: We included 314 patients diagnosed with SjD according to the 2002 American-European Consensus Group criteria from a prospective, multicenter SjögrenSER Prospective cohort. Detailed data on systemic manifestations, serological markers, disease activity, and mortality were collected after a median of 9.5 (IQR 9.2-9.9) years of follow-up. The primary outcome was overall mortality, and secondary analyses aimed to identify independent predictors of mortality using Cox proportional hazards models. Standardized mortality ratios were calculated by comparing the observed deaths in the SjD cohort to the expected deaths in an age- and sex-matched general population. RESULTS: The study identified a 70% increased mortality risk in the SjD cohort compared to the general population, with a standard mortality ratio of 1.7. Infections (35.7%), malignancies (23.8%), and cardiovascular disease (CVD; 7.1%) were the most common causes of death. Multivariate analysis revealed that older age (HR 1.11/year, 95% CI 1.07-1.15), C4 hypocomplementemia (HR 3.75, 95% CI 1.55-9.06), elevated erythrocyte sedimentation rate (ESR; HR 1.01, 95% CI 1.00-1.03), history of heart failure (HR 4.24, 95% CI 1.02-17.58), and pulmonary involvement (HR 3.31, 95% CI 1.39-7.88) were independent predictors of mortality. CONCLUSION: This study found a significantly increased mortality risk in SjD, with infections, malignancies, and CVD as leading causes of death. Independent predictors of mortality include advanced age, C4 hypocomplementemia, elevated ESR, heart failure, and pulmonary involvement, underscoring the need for proactive, individualized management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".