Development and internal validation of the Comprehensive ALPPS Preoperative Risk Assessment (CAPRA) score: is the patient suitable for Associating Liver Partition and Portal vein ligation for Staged hepatectomy (ALPPS)?
Bibliographic record
Abstract
Background: Preoperative patient selection in Associating Liver Partition and Portal vein ligation for Staged hepatectomy (ALPPS) is not always reliable with currently available scores, particularly in patients with primary liver tumor. This study aims to (I) to determine whether comorbidities and patients characteristics are a risk factor in ALPPS and (II) to create a score predicting 90-day mortality preoperatively. Methods: Thirteen high-volume centers participated in this retrospective multicentric study. A risk analysis based on patient characteristics, underlying disease and procedure type was performed to identify risk factors and model the Comprehensive ALPPS Preoperative Risk Assessment (CAPRA) score. A nonparametric receiver operating characteristic analysis was performed to estimate the predictive ability of our score against the Charlson Comorbidity Index (CCI), the age-adjusted CCI (aCCI), the ALPPS risk score before Stage 1 (ALPPS-RS1) and Stage 2 (ALPPS-RS2). The model was internally validated applying bootstrapping. Results: A total of 451 patients were included. Mortality was 14.4%. The CAPRA score is calculated based on the following formula: (0.1 × age) - (2 × BSA) + 1 (in the presence of primary liver tumor) + 1 (in the presence of severe cardiovascular disease) + 2 (in the presence of moderate or severe diabetes) + 2 (in the presence of renal disease) + 2 (if classic ALPPS is planned). The predictive ability was 0.837 for the CAPRA score, 0.443 for CCI, 0.519 for aCCI, 0.693 for ALPPS-RS1 and 0.807 for ALPPS-RS2. After 1,000 cycles of bootstrapping the C statistic was 0.793. The accuracy plot revealed a cut-off for optimal prediction of postoperative mortality of 4.70. Conclusions: Comorbidities play an important role in ALPPS and should be carefully considered when planning the procedure. By assessing the patient's preoperative condition in relation to ALPPS, the CAPRA score has a very good ability to predict postoperative mortality.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".