Evidence map›Paper›PMID 39099185›Full record

SynthesisInternational wound journal2024

Best practices in wound care for gastrointestinal stoma and colorectal cancer patients from a nursing perspective: A meta-analysis.

Jing Xu, Tianyu Gan

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in International wound journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jing XuDepartment of Gastrointestinal Surgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Tianyu GanDepartment of Cardiology, Nanxiang Branch of Ruijin Hospital, Shanghai, China.ORCID https://orcid.org/0009-0008-2006-9407

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer, a type of colon or bowel cancer, poses a major challenge in the treatment of colorectal lesions. Colorectal endoscopic mucosal resection (EMR) is a minimally invasive technique, but the risk of wound infections remains a significant concern. These infections can impede the healing process, affecting daily activities and patient satisfaction. To mitigate the risk of wound infections, various prophylactic measures have been explored, including medication, vaccines, lifestyle adjustments and hygiene practices. This study aims to investigate the prevention of wound infections through prophylactic measures in colorectal EMR. A comprehensive literature review was conducted to identify prophylactic measures that can prevent wound infections. A systematic literature search was conducted using both free words and search terms. The data extraction was performed after a comprehensive literature screening. The meta-analysis was performed using the metabin function of the meta library in R to evaluate the infection incidences in intervention and control groups. A total of 599 infection incidences were considered, with 267 in intervention and 332 in the control group. The results of meta analysis demonstrated significant reduction of wound incidences following the prophylactic measures (risk ratio [RR] = 0.77, 95% confidence interval [CI]: 0.6747; 0.9016, I

Indexed as

Colorectal NeoplasmsSurgical StomasSurgical Wound InfectionEndoscopic Mucosal ResectionHumansPractice Guidelines as TopicWound Healingcolorectal cancerhealing processhygienewound infection

Identifiers

PMID39099185
PMCPMC11298617

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.