Comparing Cardiac Surgery in Peritoneal Dialysis and Hemodialysis Patients: Perioperative Outcomes and Two-Year Survival
Bibliographic record
Abstract
BACKGROUND: We sought to compare perioperative outcomes and 2-year survival in a cohort of peritoneal dialysis (PD) patients compared with matched hemodialysis (HD) patients who underwent cardiothoracic surgery at our institution. METHODS: We obtained a list of all dialysis-dependent patients who underwent cardiac surgery (coronary artery bypass grafting, valve replacement, or both) at our center between 1994 and 2008. All patients undergoing PD at the time of surgery were included in our analysis. Two HD patients matched for age, diabetes status, and Charleston comorbidity score were obtained for each PD patient. RESULTS: The analysis included 36 PD patients and 72 HD patients. Mean age, sex, diabetes status, cardiac unit stay, hospital stay, and operative mortality did not differ by dialysis modality. The incidence of 1 or more postoperative complications (infection, prolonged intubation, death) was higher for HD patients (50% vs. 28% for PD patients, p = 0.046). After surgery, 2 PD patients required conversion to HD. The 2-year survival was 69% for PD patients and 66% for HD patients (p = 0.73). CONCLUSIONS: Our findings suggest that, compared with HD patients, PD patients who require cardiac surgery do not experience more early complications or a lesser 2-year survival and that 2-year survival for dialysis patients after cardiac surgery is acceptable.
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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 | 0.000 |
| 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".