Evidence map›Paper›PMID 38575708›Full record

ReviewNature reviews. Microbiology2024

The wound microbiota: microbial mechanisms of impaired wound healing and infection.

Aayushi Uberoi, Amelia McCready-Vangi, Elizabeth A Grice

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 303 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
303citing papers in PubMed, 3 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

303 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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243 more citing papers are in PubMed but not listed here.

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.

Aayushi UberoiDepartments of Dermatology and Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-2389-5957
Amelia McCready-VangiDepartments of Dermatology and Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Elizabeth A GriceDepartments of Dermatology and Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. egrice@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0003-3939-2200

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The skin barrier protects the human body from invasion by exogenous and pathogenic microorganisms. A breach in this barrier exposes the underlying tissue to microbial contamination, which can lead to infection, delayed healing, and further loss of tissue and organ integrity. Delayed wound healing and chronic wounds are associated with comorbidities, including diabetes, advanced age, immunosuppression and autoimmune disease. The wound microbiota can influence each stage of the multi-factorial repair process and influence the likelihood of an infection. Pathogens that commonly infect wounds, such as Staphylococcus aureus and Pseudomonas aeruginosa, express specialized virulence factors that facilitate adherence and invasion. Biofilm formation and other polymicrobial interactions contribute to host immunity evasion and resistance to antimicrobial therapies. Anaerobic organisms, fungal and viral pathogens, and emerging drug-resistant microorganisms present unique challenges for diagnosis and therapy. In this Review, we explore the current understanding of how microorganisms present in wounds impact the process of skin repair and lead to infection through their actions on the host and the other microbial wound inhabitants.

Indexed as

MicrobiotaWound HealingWound InfectionAnimalsBiofilmsHumansSkin

Identifiers

What OpenQuestion holds

Textmetadata
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.