Rapid-recovery protocol for minimally invasive mitral valve repair
Bibliographic record
Abstract
Background: Minimally invasive mitral valve repair (MIMVR), often performed within specialized care pathways, has been shown to reduce hospital length of stay and improve patient recovery. The relative value of rapid-recovery protocols as a component of care pathways, including enhanced recovery programs (ERPs), has not been well described. This study compared clinical outcomes following implementation of a new, comprehensive rapid-recovery protocol within a previously established, mature ERP for patients undergoing MIMVR. Methods: The rapid-recovery protocol was developed and implemented by a multidisciplinary team to further optimize patient recovery within an existing ERP. The protocol was applied to 75 consecutive patients undergoing MIMVR between September 2022 and December 2023. Outcomes were compared retrospectively to 75 ERP control patients who did not receive the rapid-recovery protocol but experienced the ERP. The primary outcome was a composite of discharge from the intensive care unit (ICU) by postoperative day (POD) 1, discharge to home by POD 4, and no all-cause hospital readmission by 30 days. Results: Baseline characteristics were similar in the 2 groups. Patients in the rapid-recovery group achieved the primary composite outcome significantly more often compared to the control group (60% vs 40%, respectively). There was no between-group difference in postoperative complications. Multivariable logistic regression showed that age ≤60 years was significantly associated with rapid-recovery protocol success. Clinical barriers to achieving individual components of the primary outcome were described. Conclusions: A rapid-recovery protocol for MIMVR was associated with early ICU and hospital discharge. These benefits were safely achieved without any increase in hospital readmission, morbidity, or mortality up to 30 days postoperatively.
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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 | 0.004 | 0.008 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".