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Record W4388680718 · doi:10.1111/iwj.14456

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

2023· article· en· W4388680718 on OpenAlexaboutno aff
Belén Martín‐Gil, Noel Rivas‐González, Teresa Santos‐Boya, María López, José María Jiménez, Natán Redondo‐Pérez, Isaías del Río‐García, María Berdón‐ Berdón, Mercedes Fernández‐Castro

Bibliographic record

VenueInternational Wound Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Quality (philosophy)General surgeryNursing

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.123

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.326
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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