Incorporation of Procedure-specific Risk Into the ACS-NSQIP Surgical Risk Calculator Improves the Prediction of Morbidity and Mortality After Pancreatoduodenectomy
Bibliographic record
Abstract
OBJECTIVE: This multicenter study sought to evaluate the accuracy of the American College of Surgeons National Surgical Quality Improvement Program's (ACS-NSQIP) surgical risk calculator for predicting outcomes after pancreatoduodenectomy (PD) and to determine whether incorporating other factors improves its predictive capacity. BACKGROUND: The ACS-NSQIP surgical risk calculator has been proposed as a decision-support tool to predict complication risk after various operations. Although it considers 21 preoperative factors, it does not include procedure-specific variables, which have demonstrated a strong predictive capacity for the most common and morbid complication after PD - clinically relevant pancreatic fistula (CR-POPF). The validated Fistula Risk Score (FRS) intraoperatively predicts the occurrence of CR-POPF and serious complications after PD. METHODS: This study of 1480 PDs involved 47 surgeons at 17 high-volume institutions. Patient complication risk was calculated using both the universal calculator and a procedure-specific model that incorporated the FRS and surgeon/institutional factors. The performance of each model was compared using the c-statistic and Brier score. RESULTS: The FRS was significantly associated with 30-day mortality, 90-day mortality, serious complications, and reoperation (all P < 0.0001). The procedure-specific model outperformed the universal calculator for 30-day mortality (c-statistic: 0.79 vs 0.68; Brier score: 0.020 vs 0.021), 90-day mortality, serious complications, and reoperation. Neither surgeon experience nor institutional volume significantly predicted mortality; however, surgeons with a career PD volume >450 were less likely to have serious complications (P < 0.001) or perform reoperations (P < 0.001). CONCLUSIONS: Procedure-specific complication risk influences outcomes after pancreatoduodenectomy; therefore, risk adjustment for performance assessment and comparative research should consider these preoperative and intraoperative factors along with conventional ACS-NSQIP preoperative variables.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".