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Record W4403113298 · doi:10.25270/wmp.23114

Influencing Factors Associated With Peristomal Skin Complications After Colorectal Ostomy Surgery: A Systematic Review and Meta-Analysis

2024· review· en· W4403113298 on OpenAlexaboutno aff
Lili Ma, Yajuan Zhang, Jin-Xiu Yao, Weiying Zhang, Huiren Zhuang

Bibliographic record

VenueWound Management & Prevention · 2024
Typereview
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColorectal surgeryMeta-analysisGeneral surgeryComplicationSurgeryAbdominal surgeryInternal medicine

Abstract

fetched live from OpenAlex

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.002
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 head0.086
GPT teacher head0.352
Teacher spread0.266 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations6
Published2024
Admission routes1
Has abstractyes

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