Postoperative Discharge Destination Impacts 30-Day Outcomes: A National Surgical Quality Improvement Program Multi-Specialty Surgical Cohort Analysis
Bibliographic record
Abstract
Surgical patients can be discharged to a variety of facilities which vary widely in intensity of care. Postoperative readmissions have been found to be more strongly associated with post-discharge events than pre-discharge complications, indicating the importance of discharge destination. We sought to evaluate the association between discharge destination and 30-day outcomes. A retrospective cohort study was conducted using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database. Patients were dichotomized based on discharge destination: home versus non-home. The main outcome of interest was 30-day unplanned readmission. The secondary outcomes included post-discharge pulmonary, infectious, thromboembolic, and bleeding complications, as well as death. In this cohort study of over 1.5 million patients undergoing common surgical procedures across eight surgical specialties, we found non-home discharge to be associated with adverse 30-day post-operative outcomes, namely, unplanned readmissions, post-discharge pulmonary, infectious, thromboembolic, and bleeding complications, as well as death. Non-home discharge is associated with worse 30-day outcomes among patients undergoing common surgical procedures. Patients and caregivers should be counseled regarding discharge destination, as non-home discharge is associated with adverse post-operative outcomes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".