Development of the Residual Lesion Score for congenital heart surgery: the RAND Delphi methodology
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The Residual Lesion Score is a novel tool for assessing the achievement of surgical objectives in congenital heart surgery based on widely available clinical and echocardiographic characteristics. This article describes the methodology used to develop the Residual Lesion Score from the previously developed Technical Performance Score for five common congenital cardiac procedures using the RAND Delphi methodology. METHODS: A panel of 11 experts from the field of paediatric and congenital cardiology and cardiac surgery, 2 co-chairs, and a consultant were assembled to review and comment on validity and feasibility of measuring the sub-components of intraoperative and discharge Residual Lesion Score for five congenital cardiac procedures. In the first email round, the panel reviewed and commented on the Residual Lesion Score and provided validity and feasibility scores for sub-components of each of the five procedures. In the second in-person round, email comments and scores were reviewed and the Residual Lesion Score revised. The modified Residual Lesion Score was scored independently by each panellist for validity and feasibility and used to develop the "final" Residual Lesion Score. RESULTS: The Residual Lesion Score sub-components with a median validity score of ≥7 and median feasibility score of ≥4 that were scored without disagreement and with low absolute deviation from the median were included in the "final" Residual Lesion Score. CONCLUSION: Using the RAND Delphi methodology, we were able to develop Residual Lesion Score modules for five important congenital cardiac procedures for the Pediatric Heart Network's Residual Lesion Score study.
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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 | 0.171 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".