Standardisation of management after Norwood operation has not improved 1-year outcomes
Bibliographic record
Abstract
INTRODUCTION: Treatment of hypoplastic left heart syndrome varies across institutions. This study examined the impact of introducing a standardised programme. METHODS: This retrospective cohort study evaluated the effects of a comprehensive strategy on 1-year transplant-free survival with preserved ventricular and atrioventricular valve (AVV) function following a Norwood operation. This strategy included standardised operative and perioperative management and dedicated interstage monitoring. The post-implementation cohort (C2) was compared to historic controls (C1). Outcomes were assessed using logistic regression and Kaplan-Meier analysis. RESULTS: The study included 105 patients, 76 in C1 and 29 in C2. Groups had similar baseline characteristics, including percentage with preserved ventricular (96% C1 versus 100% C2, p = 0.28) and AVV function (97% C1 versus 93% C2, p = 0.31). Perioperatively, C2 had higher indexed oxygen delivery (348 ± 67 ml/minute/m2 C1 versus 402 ± 102ml/minute/m2 C2, p = 0.015) and lower renal injury (47% C1 versus 3% C2, p = 0.004). The primary outcome was similar in both groups (49% C1 and 52% C2, p = 0.78), with comparable rates of death and transplantation (36% C1 versus 38% C2, p = 0.89) and ventricular (2% C1 versus 0% C2, p = 0.53) and AVV dysfunction (11% C1 versus 11% C2, p = 0.96) at 1-year. When accounting for cohort and 100-day freedom from hospitalisation, female gender (OR 3.7, p = 0.01) increased and ventricular dysfunction (OR 0.21, p = 0.02) and CPR (OR 0.11, p = 0.002) or ECMO use (OR 0.15, p = 001) decreased the likelihood of 1-year transplant-free survival. CONCLUSIONS: Standardised perioperative management was not associated with improved 1-year transplant-free survival. Post-operative ventricular or AVV dysfunction was the strongest predictor of 1-year mortality.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".