Continuous Renal Replacement Therapy after Cardiac Surgery
Bibliographic record
Abstract
BACKGROUND/AIMS: To evaluate the outcome of patients who require continuous renal replacement therapy (CRRT) following cardiac surgery. METHODS: All patients who received CRRT after cardiac surgery over more than 4 years at the Surgical Intensive Care Unit of the Montreal Heart Institute were reviewed. Among 5,564 consecutive patients, 85 underwent CRRT postoperatively. RESULTS: The mean delay between surgery and CRRT initiation was 5 days, and the duration of CRRT was 9 days, without a difference between survivors and non-survivors. Delivered clearances with CRRT were estimated at 25-28 ml/min (approximately 40 liters/day), 29-32 ml/min (approximately 46 liters/day) and 17 ml/min (approximately 25 liters/day) for continuous veno-venous hemofiltration, continuous veno-venous hemodiafiltration and continuous veno-venous hemodialysis, respectively. In-hospital mortality was 43.5%. No difference in mortality was observed between patients with normal renal function at baseline and those with pre-operative renal dysfunction. Mortality was 33.3% after a coronary artery bypass graft (CABG), 57.1% after CABG and valve surgery, 60% after valve surgery, and 72.7% for redo-CABG or redo-valve surgery. 79% of survivors and 86% of non-survivors had received a cardiopulmonary bypass (p = NS). The Simplified Acute Physiology Score II upon intensive care unit (ICU) admission and the requirement of an intra-aortic balloon pump were higher in non-survivors (p < 0.05). The mean length of ICU and hospital stay was 27.4 and 34.2 days for survivors and 17.9 and 22.3 days for non-survivors, respectively (p < 0.05). CONCLUSIONS: Renal impairment is relatively common after cardiac surgery. The mortality of patients who required CRRT after cardiac surgery was 43.5% and was particularly influenced by the type of surgery.
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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 | 0.002 |
| 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) | 0.001 | 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".