Evidence map›Paper›PMID 37443543›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Diagnosis and Management of Severe Water-Related Skin and Soft Tissue Sepsis: A Summative Review of the Literature.

Shanisa Naidoo, Arnold M Zwane, Ahmed Paruk, Timothy Craig Hardcastle

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. 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
3.8field-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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Guideline
  2. Review
  3. Review
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 2 institutions in 1 country.

Shanisa NaidooDepartment of Surgery, University of KwaZulu-Natal, Durban 4001, South Africa.ORCID 0000-0002-3356-3163
Arnold M ZwaneDepartment of Surgery, University of KwaZulu-Natal, Durban 4001, South Africa.
Ahmed ParukTrauma and Burn Service, Inkosi Albert Luthuli Central Hospital, Mayville 4058, South Africa.
Timothy Craig HardcastleDepartment of Surgery, University of KwaZulu-Natal, Durban 4001, South Africa.ORCID 0000-0002-3967-0234
University of KwaZulu-Natal · ZAAddington Hospital · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSkin and soft tissue infections (SSTIs) are common presentations in the emergency department. However, this is less common after contact with contaminated saltwater or freshwater. This review presents the diagnosis and management of water-related soft tissue sepsis in this vulnerable and difficult-to-treat subgroup of necrotizing soft tissue sepsis.

methodsA summative literature overview is presented regarding bacterial and fungal SSTI after contact with contaminated water, with practical diagnostic and management aspects.

resultsThe literature indicates that these wounds and infections remain difficult to treat. An approach using appropriate diagnostic tools with both medical and surgical management strategies is provided.

conclusionsSSTIs due to water contamination of wounds involve unusual organisms with unusual resistance patterns, and require a nuanced and directed diagnostic approach with an adaptation of the usual antibiotic or antifungal selection to achieve a successful cure, along with aggressive debridement and wound care.

Indexed as

aeromonasdebridementfungalnecrotizing infectionnegative pressure wound caresoft tissuevibriowater borne

Identifiers

PMID37443543
PMCPMC10340249
OpenAlexW4382067792

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.