Clinical Course, Prognosis, and Causes of Death in Mixed Connective Tissue Disease
Bibliographic record
Abstract
OBJECTIVE: To study the survival rate and prognostic indicators of mixed connective tissue disease (MCTD) in a Hungarian population. METHODS: Two hundred eighty patients with MCTD diagnosed between 1979 and 2011 were followed prospectively. Clinical features, autoantibodies, and mortality data were assessed. Prognostic factors for survival were investigated and survival was calculated from the time of the diagnosis by Kaplan-Meier method. RESULTS: A total of 22 of 280 patients died: the causes of death were pulmonary arterial hypertension (PAH) in 9 patients, thrombotic thrombocytopenic purpura in 3, infections in 3, and cardiovascular events in 7. The 5, 10, and 15-year survival rates after the diagnosis was established were 98%, 96%, and 88%, respectively. The deceased patients were younger at the diagnosis of MCTD compared to patients who survived (35.5 ± 10.4 vs 41.8 ± 10.7 yrs; p < 0.03), while there was no difference in the duration of the disease (p = 0.835). Our cohort study showed that the presence of cardiovascular events (p < 0.0001), esophageal hypomotility (p = 0.04), serositis (p < 0.001), secondary antiphospholipid syndrome (p = 0.039), and malignancy (p < 0.001) was significantly higher in the deceased patients with MCTD. The presence of anticardiolipin (p = 0.019), anti-β2-glycoprotein I (p = 0.002), and antiendothelial cell antibodies (p = 0.002) increased the risk of mortality. CONCLUSION: Overall, PAH remained the leading cause of death in patients with MCTD. The prevalence of cardiovascular morbidity and mortality, malignancy, and thrombotic events increased during the disease course of MCTD. The presence of antiphospholipid antibodies raised the risk of mortality.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".