Evidence map›Paper›PMID 33572218›Full record

ReviewJournal of clinical medicine2021

Randomised Controlled Trials of Alcohol-Based Surgical Site Skin Preparation for the Prevention of Surgical Site Infections: Systematic Review and Meta-Analysis.

Trisha N Peel, Eliza Watson, Sue J Lee

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 5 pooled it
3.6field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 5 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Review
  8. Article
  9. Review
  10. 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

3 authors at 1 institution in 1 country.

Trisha N PeelDepartment of Infectious Diseases, Alfred Hospital and Central Clinical School, Monash University, 85 Commercial Road, Melbourne, VIC 3004, Australia.
Eliza WatsonDepartment of Infectious Diseases, Alfred Hospital and Central Clinical School, Monash University, 85 Commercial Road, Melbourne, VIC 3004, Australia.ORCID 0000-0003-1279-0508
Sue J LeeDepartment of Infectious Diseases, Alfred Hospital and Central Clinical School, Monash University, 85 Commercial Road, Melbourne, VIC 3004, Australia.ORCID 0000-0002-8409-4248
Monash University · AU

Funding

National Health and Medical Research Council APP1140350
6 · The paper itself

Abstract

(1) Background: Surgical site skin preparation is an important approach to prevent postoperative wound infections. International guidelines recommend that alcohol-based combinations be used, however, the optimal combination remains uncertain. This study compares the effectiveness of alcohol-based chlorhexidine and alcohol-based iodophor for surgical site skin preparation for prevention of surgical site infections (SSIs). (2) Methods: Randomised controlled trials comparing alcohol-based interventions for surgical site skin preparation were included. The proportion of SSIs was compared using risk ratios (RR) with 95% confidence intervals (95% CI). The meta-analysis was performed with a fixed effect model using Mantel-Haenszel methods. As an a priori subgroup analysis SSI risk was examined according to different surgical procedural groups. (3) Results: Thirteen studies were included (

Indexed as

infection preventionmeta-analysissurgical site infectionsurgical site skin preparation

Identifiers

PMID33572218
PMCPMC7914441
OpenAlexW3127164726

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.