Meta-analysis Investigating the Efficacy of Liquid Dressing and Ostomy Powder for the Treatment of Incontinence-Associated Dermatitis
Bibliographic record
Abstract
OBJECTIVE: To study the effect of liquid dressing and ostomy powder on the treatment of incontinence-associated dermatitis (IAD). METHODS: The authors searched PubMed, Web of Science, CNKI (China National Knowledge Internet), and Google Scholar databases for literature through July 28, 2022. After literature screening, two investigators independently extracted data from the included studies and applied the Newcastle-Ottawa Scale to assess the quality of the included studies. The χ2-based Q statistic test and the I2 statistic were used to measure the heterogeneity of the included studies. Publication bias was measured with funnel plots and the Egger test. Sensitivity analysis was conducted by eliminating each study one by one. RESULTS: Four high-quality studies were included in the meta-analysis, involving a total of 307 participants. The meta-analysis results showed that compared with traditional care, treatment with liquid dressing and ostomy powder significantly improved the effective rate (pooled odds ratio, 21.42; 95% CI, 8.58 to 53.44), shortened the healing time (pooled mean difference, -10.73; 95% CI, -12.92 to -8.54), and reduced the recurrence rate (pooled mean difference, -2.03; 95% CI, -2.30 to -1.77) of IAD. Among the included studies, no publication bias was detected. Sensitivity analysis results confirmed the robustness of the pooled estimates. CONCLUSIONS: Treatment with liquid dressing and ostomy powder has clinical value for patients with IAD.
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 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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.053 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".