MENDing Recovery: Comprehensive Perioperative Care Cuts Hospital Stay After Minimally Invasive CABG
Bibliographic record
Abstract
Objective: To evaluate the impact of a novel multidisciplinary initiative, known as the Multimodal ENhanced Discharge (MEND), on length of stay (LOS) for patients undergoing minimally invasive coronary artery bypass grafting (MICS CABG). Methods: The MEND program aims to optimize the patient’s preoperative condition and increase preparedness, provide individualized perioperative care, and ensure early postdischarge follow-up to support active recovery and facilitate early discharge. This single-center, retrospective analysis reviewed LOS and readmission data for 198 consecutive patients who underwent MICS CABG by a single surgeon. Of these, 91 patients received routine care (RC) and 107 patients received care through the MEND program. Results: The median ward (non–intensive care unit) LOS was significantly shorter by 33% in the MEND group versus the RC group (2 vs 3 days, P < 0.001), resulting in a 40% shorter median total hospital LOS in the MEND group versus the RC group (2 vs 5 days, P < 0.001). Readmission rates were 14.3% for RC and 6.6% in the MEND group ( P = 0.12). Conclusions: Implementation of the MEND program in patients undergoing MICS CABG was associated with significantly shorter overall hospital LOS without an increase in readmission rates. No statistically significant differences in baseline characteristics between the RC and MEND cohorts were observed. These findings suggest MEND is an effective and generalizable program for optimizing recovery. Ultimately, this model of care has the potential to positively affect health care costs, improve surgical wait times, and expand capacity in MICS CABG programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".