Evidence map›Paper›PMID 35211501›Full record

ArticleFrontiers in surgery2022

Wound Irrigation Using Wet Gauze May Reduce Surgical Site Infection Following Laparoscopic Appendectomy.

Abdullah Al-Sawat, Ji Yeon Mun, Sung Hoon Yoon, Chul Seung Lee

Open access · goldAbstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
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, 4 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Abdullah Al-SawatDepartment of Surgery, College of Medicine, Taif University, Taif, Saudi Arabia.
Ji Yeon MunDepartment of Surgery, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, South Korea.
Sung Hoon YoonDepartment of Surgery, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, South Korea.
Chul Seung LeeDepartment of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Suwon, South Korea.
St. Vincent's Hospital · KRCatholic University of Korea · KRTaif University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to compare the perioperative outcomes of wet gauze and conventional irrigation after laparoscopic appendectomy to determine whether wet gauze irrigation can help reduce surgical site infection (SSI).

methodsA total of 308 patients undergoing laparoscopic appendectomy were included in this study between December 2018 and May 2020. Of these, 132 (42.9%) received gauze irrigation (group 1), and 176 patients (57.1%) received conventional irrigation (group 2). Pre-operative outcomes and complications, including SSI, were compared after propensity score matching (PSM) to adjust for baseline differences and selection bias.

resultsAfter 1:1 PSM, 92 well-matched patients in each group were evaluated. Regarding perioperative outcomes between groups 1 and 2, the rate of severe complications (Clavien-Dindo Classification grades III, IV, and V), operative time, and readmission rate did not differ between the groups. Superficial/deep SSIs were observed more frequently in group 2 (8/92 cases) than in group 1 (1/92 cases;

conclusionsWound irrigation using wet gauze after fascia closure has a significant beneficial effect on reducing post-operative superficial/deep SSI following laparoscopic appendectomy.

Indexed as

appendectomylaparoscopylength of staysurgical wound infectionwound irrigation

Identifiers

PMID35211501
PMCPMC8860892
OpenAlexW4210943929

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.