External Validation of Eight Ruptured Abdominal Aortic Aneurysm Mortality Prediction Models Demonstrates Limited Predictive Accuracy
Bibliographic record
Abstract
Objective Over a dozen ruptured abdominal aortic aneurysm (rAAA) mortality risk prediction models currently exist; however, lack of external validation limits their applicability. This study aimed to evaluate the accuracy of eight common rAAA mortality risk prediction models in a large, contemporary, external validation cohort. Methods A retrospective review of rAAA repairs at a multicentre integrated regional healthcare system with large central quaternary referral facility (2010 – 2020) was performed. Eight models were used to predict 30 day post-operative death, including the Updated Glasgow Aneurysm Score (GAS), Vascular Study Group of New England rAAA Risk Score, Harborview Pre-operative rAAA Risk Score, Modified Harborview Risk Score, Vancouver Scoring System (VSS), Artificial Neural Network Score, Dutch Aneurysm Score, and Edinburgh Ruptured Aneurysm Score. The models were assessed for discrimination, calibration, and clinical utility using receiver operating characteristic curves (area under the curve [AUC]), Hosmer–Lemeshow χ 2 test, Brier scores, and decision curve analysis. The proportion of unexpected survivors (survival despite > 80% predicted 30 day death) to expected deaths was compared across calculators, and both groups were compared using the model demonstrating the highest unexpected survival frequency. Results Three hundred and fifteen rAAA repairs were included (mean age 73.6 ± 10.0 years; 72.1% male; 49.8% open repair) with a 30 day mortality rate of 32.1%. Three models had fair discrimination (AUC ≥ 0.70), with GAS having the highest AUC (0.74, 95% confidence interval 0.68 – 0.79). All models demonstrated poor to adequate calibration. Using VSS, unexpected survivors ( n = 25) had less pre-operative shock (72% vs. 96%; p = .050) and statistically significantly less coagulopathy (median international normalised ratio 1.2 [interquartile range 1.1, 1.5] vs. 1.8 [1.3, 2.2]; p = .015) compared with expected deaths ( n = 23). Conclusion Current rAAA risk prediction models demonstrated only fair discrimination and poor to adequate calibration. These findings suggest that existing risk prediction models have not sufficiently captured important physiological characteristics associated with rAAA death and should be applied cautiously to clinical practice.
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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 | 0.033 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".