Derivation and Validation of a Simplified Predictive Index for Renal Replacement Therapy After Cardiac Surgery
Bibliographic record
Abstract
CONTEXT: A predictive index for renal replacement therapy (RRT; hemodialysis or continuous venovenous hemodiafiltration) after cardiac surgery may improve clinical decision making and research design. OBJECTIVES: To develop a predictive index for RRT using preoperative information. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort of 20 131 cardiac surgery patients at 2 hospitals in Ontario, Canada. The derivation cohort consisted of 10,751 patients at Toronto General Hospital (1999-2004). The validation cohorts consisted of 2566 patients at Toronto General Hospital (2004-2005) and 6814 patients at Ottawa Heart Institute (1999-2003). MAIN OUTCOME MEASURE: Postoperative RRT. RESULTS: RRT rates in the derivation, Toronto validation, and Ottawa validation cohorts were 1.3%, 1.8%, and 2.2%, respectively. Multivariable predictors of RRT were preoperative estimated glomerular filtration rate, diabetes mellitus requiring medication, left ventricular ejection fraction, previous cardiac surgery, procedure, urgency of surgery, and preoperative intra-aortic balloon pump. The predictive index was scored from 0 to 8 points. An estimated glomerular filtration rate less than or equal to 30 mL/min was assigned 2 points; other components were assigned 1 point each: estimated glomerular filtration rate 31 to 60 mL/min, diabetes mellitus, ejection fraction less than or equal to 40%, previous cardiac surgery, procedure other than coronary artery bypass grafting, intra-aortic balloon pump, and nonelective case. Among the 53% of patients with low risk scores (< or =1), the risk of RRT was 0.4%; by comparison, this risk was 10% among the 6% of patients with high-risk scores (> or =4). The predictive index had areas under the receiver operating characteristic curve in the derivation, Toronto validation, and Ottawa validation cohorts of 0.81, 0.78, and 0.78, respectively. When these cohorts were stratified based on index scores, likelihood ratios for RRT were more concordant than observed RRT rates. CONCLUSIONS: RRT after cardiac surgery is predicted by readily available preoperative information. A simple predictive index based on this information discriminated well between low- and high-risk patients in derivation and validation cohorts. The index had improved generalizability when used to predict likelihood ratios for RRT.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".