Transitioning to Del Nido cardioplegia for all-comers: the next switching gear?
Bibliographic record
Abstract
BACKGROUND: Exclusive use of Del Nido cardioplegia administration in all adult patients undergoing cardiac surgery has been studied for operative, postoperative and myocardial protection outcomes. METHODS: From November 2016 to October 2017, Del Nido cardioplegia was used in 131 consecutive patients (DN group). Using a propensity score, DN group was compared to 251 patients having received intermittent cold blood cardioplegia (CB group). RESULTS: Preoperative characteristics were similar in DN and CB groups. Operative outcomes were statistically different (p < 0.0001): cardiopulmonary bypass (CPB) time (DN 105.9 ± 46.5, CB 131.2 ± 38.8); aortic cross-clamp time (DN 80.8 ± 35.5, CB 102.2 ± 31.3); operative time (DN 203.1 ± 65.0, CB 241.5 ± 54.7); total cardioplegia volume (DN 1328 ± 879, CB 3773 ± 1226); and peak glycemia on CPB (DN 8.2 ± 2.3, CB 9.0 ± 1.8). No statistical differences were noted in intensive care unit stay, hospital stay and hospital death. Myocardial protection outcomes were similar: discharge left ventricular ejection fraction (DN 52 ± 11, CB 51 ± 10); Troponin levels at the end of the surgery (DN 871 ± 1623, CB 1958 ± 854), day 1 (DN 853 ± 1139, CB 993 ± 8234) and day 4 (DN 442 ± 540, CB 463 ± 317). CONCLUSION: Del Nido cardioplegia use in all adult cardiac surgeries is associated with improved surgical efficiency. The design of larger trials including adults combined cardiac procedures and emergencies is needed.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".