Systematic Review of Patient Safety and Quality Improvement Initiatives in Breast Reconstruction
Bibliographic record
Abstract
Background Improving patient care and safety requires high-quality evidence. The objective of this study was to systematically review the existing evidence for patient safety (PS) and quality improvement initiatives in breast reconstruction. Methods A systematic review of the published plastic surgery literature was undertaken using a computerized search and following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Publication descriptors, methodological details, and results were extracted. Articles were assessed for methodological quality and clinical heterogeneity. Descriptive statistics were completed, and a meta-analysis was considered. Results Forty-six studies were included. Most studies were retrospective (52.2%) and from the third level of evidence (60.9%). Overall, the scientific quality was moderate, with randomized controlled trials generally being higher quality. Studies investigating approaches to reduce seroma (28.3% of included articles) suggested a potential benefit of quilting sutures. Studies focusing on infection (26.1%) demonstrated potential benefits to prophylactic antibiotics and drain use under 21 days. Enhanced recovery after surgery protocols (10.9%) overall did not compromise PS and was beneficial in reducing opioid use and length of stay. Interventions to increase flap survival (10.9%) demonstrated a potential benefit of nitroglycerin on mastectomy skin flaps. Conclusions Overall, studies were of moderate quality and investigated several worthwhile interventions. More validated, standardized outcome measures are required, and studies focusing on interventions to reduce thromboembolic events and bleeding risk could further improve PS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".