The Influence of Intraoperative Blood Loss on Fistula Development Following Pancreatoduodenectomy
Bibliographic record
Abstract
OBJECTIVE: To investigate the role of intraoperative estimated blood loss (EBL) on development of clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreatoduodenectomy (PD). BACKGROUND: Minimizing EBL has been shown to decrease transfusions and provide better perioperative outcomes in PD. EBL is also felt to be influential on CR-POPF development. METHODS: This study consists of 5534 PDs from a 17-institution collaborative (2003-2018). EBL was progressively categorized (≤150mL; 151-400mL; 401-1,000 mL; > 1,000 mL). Impact of additive EBL was assessed using 20 3- factor fistula risk score (FRS) scenarios reflective of endogenous CR-POPF risk. RESULTS: CR-POPF developed in 13.6% of patients (N = 753) and median EBL was 400 mL (interquartile range 250-600 mL). CR-POPF and Grade C POPF were associated with elevated EBL (median 350 vs 400 mL, P = 0.002; 372 vs 500 mL, P < 0.001, respectively). Progressive EBL cohorts displayed incremental CR-POPF rates (8.5%, 13.4%, 15.2%, 16.9%; P < 0.001). EBL >400mL was associated with increased CR-POPF occurrence in 13/20 endogenous risk scenarios. Moreover, 8 of 10 scenarios predicated on a soft gland demonstrated increased CR-POPF incidence. Hypothetical projections demonstrate significant reductions in CR-POPF can be obtained with 1-, 2-, and 3-point decreases in FRS points attributed to EBL risk (12.2%, 17.4%, and 20.0%; P < 0.001). This is especially pronounced in high-risk (FRS7-10) patients, who demonstrate up to a 31% reduction (P < 0.001). Surgeons in the lowest-quartile of median EBL demonstrated CR-POPF rates less than half those in the upper-quartile (7.9% vs 18.8%; P < 0.001). CONCLUSION: EBL independently contributes significant biological risk to CR-POPF. Substantial reductions in CR-POPF occurrence are projected and obtainable by minimizing EBL. Decreased individual surgeon EBL is associated with improvements in CR-POPF.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".