Influencing Factors Associated With Peristomal Skin Complications After Colorectal Ostomy Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Peristomal skin complications (PSCs) are the most common complication among patients with ostomies after ostomy creation. PURPOSE: This systematic review and meta-analysis aimed to evaluate the factors influencing the occurrence of peristomal skin complications. METHODS: A systematic review was conducted across multiple databases by using a combination of subject terms and free words for online search. The databases were searched from their inception to October 31, 2023. All studies that met inclusion criteria were examined to identify risk factors for PSCs. Two researchers independently conducted literature screening and information extraction, evaluated the literature quality using the Newcastle-Ottawa Scale, and performed descriptive analysis of the results. RESULTS: Ten studies were included in this review. A total of 3753 patients with ostomies participated in the studies, and 981 patients suffered from PSCs, with PSC incidence ranging from 15.5% to 47.7%. Type of ostomy, diabetes, self-care knowledge, and chemotherapy were significant factors associated with PSCs. CONCLUSION: This review highlighted 4 factors that influence the occurrence of peristomal skin complications. The quality of included literature is generally low, with significant heterogeneity in study design and choice of outcome indicators. Therefore, further research involving high-quality studies with larger sample sizes is needed for deeper investigation.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.024 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".