Abstract 13880: Autoimmune Connective Tissue Diseases and Cardiac Surgery
Bibliographic record
Abstract
Introduction: The results of cardiac surgery in patients affected by autoimmune connective tissue diseases (ACTD) have not been extensively reported. Accordingly, we sought to assess the outcomes of ACTD patients after cardiac surgery, focusing on postoperative complications and survival at short and long term. Methods: Since 2008, 1002 cardiac surgical patients affected by ACTD (rheumatoid arthritis (RA) 59%, autoimmune vasculitis 14%, autoimmune inflammatory disease 12%, psoriatic arthritis 9%, and systemic lupus erythematosus (SLE) 6%), were retrospectively analysed in two centres. Demographics, clinical characteristics and specific treatment were recorded. Type of surgery, postoperative complications, early and late mortality were analysed. Results: Median age was 71 (22-92) years, and 48% were female. Most patients presented severe comorbidities (shown in the table) and required urgent surgery in 17% of cases, most frequently CABG (56%). Perioperative mortality was 2% but 60% of patients developed postoperative complications (mainly acute renal failure 15%). Patients affected by systemic inflammatory autoimmune diseases needed longer time of mechanical ventilation (p<0.01), while those with vasculitis more frequently had pneumonia (p=0.05). SLE patients had higher 30-day mortality (7%, p=0.04). Survival at 1, 5 and 10 years was 97±1%, 82±1% and 59±2%, respectively, and most common causes of death were not cardiac related (75%). By multivariate analysis, RA (HR 1.30, 1.00-1.70) was a risk factor for late mortality while both SLE and vasculitis were risk factors for re-operation (p=0.04 and p<0.01, respectively), at a median follow up of 59 months (1-184). Conclusions: Cardiac surgery in ACTD patients can achieve satisfactory short- and long-term results despite higher rate of postoperative complications, mainly renal failure and infections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".