Changes in the quality of life of adults with an ostomy during the first year after surgery as part of the Best Practice Spotlight Organisation® Programme
Bibliographic record
Abstract
The aim was to analyse changes in the perceived quality of life of patients with an ostomy during the first year after surgery at two or three follow-ups. This is a prospective study of a cohort of 55 patients who were ostomised between June 2021 and September 2022 and cared for under the recommendations set out in the Registered Nurses' Association of Ontario® best practice guideline Supporting Adults Who Anticipate or Live with an Ostomy as part of the Best Practice Spotlight Organisation® (BPSO®) programme. The Stoma Quality of Life tool was used. A univariate analysis was performed to identify variables associated with a non-improvement in quality of life. Variables showing p < 0.1 were included in a multivariate model. Patients with an ostomy exhibited a moderate-to-good perception of quality of life in both the personal and social dimensions, with no worsening over the first year. Being female (OR = 10.32) and being younger (OR = 0.89) were associated with a higher risk of no improvement in quality of life. The most frequent complications were urinary leakage (p = 0.027) and dermatitis (p = 0.052) at first follow-up; and parastomal hernia (p = 0.009) and prolapse (p = 0.05) at third follow-up. However, they did not lead to a worsening of quality of life, suggesting that these patients were adequately supported under the BPSO® programme.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".