Usefulness of APORTEI score beyond mortality predictor
Bibliographic record
Abstract
Abstract Background Aportei score is a validated scale for predicting postoperative mortality in patients with infective endocarditis (IE). This score is mainly used to avoid futility in patients who would not benefit from surgery due to their high risk. Purpose Our objective was to compare the occurrence of clinical complications (atrioventricular block (AVB), embolism, stroke) not included as items in the score between the different risk groups; in addition we compare the performance of cardiac surgery in each group. We registered mortality during hospitalization and CV mortality during follow-up. Methods For this purpose, a single-center prospective observational study was conducted in a tertiary hospital. We included patients admitted with a diagnosis of IE between 2016 and 2023 in a tertiary hospital, dividing them according to the Aportei score into low, medium, high and very high risk to compare the incidence of complications among them. Results From 188 patients with a definitive diagnosis of infective endocarditis (men 72.5%; median age 69 years (RIQ 68)), they were distributed as follows: 27 at low risk, 28 at moderate risk, 53 at high risk and 80 at extreme risk. Surgery was performed in 48.4% of the total; when comparing the performance of surgery between risk groups, no statistically significant differences were found. Regarding stroke complications, a higher percentage was found in patients at high (37%) and very high risk (50%) (p=0.04), although no systemic embolism was found (p=0.5). Patients at higher Aportei risk had a statistically significant higher percentage of AVB (p=0.002). Mortality, regardless of whether surgery was performed, was higher in the groups of patients with higher scores, both cardiovascular (low risk 7.4% vs high risk 20.8%, p<0.001) and overall mortality during admission (low risk 7.2% vs high risk 15.1%, p<0.001). Conclusions Aportei score, in addition to being a good predictor of mortality in both interventional and non-interventional patients, seems to be related to the appearance of complications such as atrioventricular block and stroke. In our hospital, the indication for surgery was not guided by the Aportei score, with no differences in intervention between the different risk groups.Clinical complicationsAPORTEI risk
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".