Bibliographic record
Abstract
OBJECTIVE: To evaluate if ostomy care pathways improve outcomes for adults anticipating or living with an ostomy. DATA SOURCES: In this systematic review, the authors searched the MEDLINE, CINAHL, Cochrane Central, and EMBASE databases. STUDY SELECTION: Studies were included if they met the following criteria: written in English, targeted adults anticipating or currently living with an ostomy, evaluated the impact of two or more components of an ostomy care pathway, and included one or more of the pertinent outcomes (patient satisfaction, hospital length of stay, hospital readmission rates, and staff satisfaction). DATA EXTRACTION: Details recorded included design, setting, descriptions of intervention and control groups, patient characteristics, outcomes, data collection tools, effect size, and potential harms. DATA SYNTHESIS: Of 5,298 total records, 11 met the inclusion criteria: 2 randomized controlled trials and 9 nonrandomized studies. The overall quality of the studies was low. Of the four studies that examined patient satisfaction, all studies reported improvement or positive satisfaction rates. Of the six studies that evaluated hospital length of stay, five noted a decrease in length of stay. Of the eight studies that evaluated hospital readmission rates, five found a reduction in hospital readmission rates. No studies reported on staff satisfaction. CONCLUSIONS: Ostomy care pathways included preoperative education and counseling, postoperative education and discharge planning, and outpatient home visits and telephone follow-ups. Ostomy care pathways may contribute to patient satisfaction and decrease both hospital length of stay and hospital readmission rates. However, higher-quality literature is needed to be confident in the effectiveness of ostomy care pathways.
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 | 0.015 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".