Evidence map›Paper›PMID 38292500›Full record

SynthesisThe Ulster medical journal2024

Computed Tomography Scanning for Sternal Wound Infections: A Systematic Review.

Manasi Mahesh Shirke, Catherine Dominic, Pradipta Debnath, Jesvin Sunny, Mawiyah Haq, Hamza Nawaz, Amer Harky

Abstract readSystematic Review
In one paragraph

Synthesis in The Ulster medical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

7 authors.

Manasi Mahesh ShirkeSchool of Medicine, Queen's University Belfast, School of Medicine, Belfast, UK.
Catherine DominicBarts and the London School of Medicine, QMUL.
Pradipta DebnathSchool of Medicine, University of Nottingham, Nottingham, UK.
Jesvin SunnyDepartment of Medicine, University of Central Lancashire, Preston, UK.
Mawiyah HaqFaculty of Medicine, St. George's University of London, London, UK.
Hamza NawazBarts and the London School of Medicine, QMUL.
Amer HarkyDepartment of Cardiothoracic Surgery, Liverpool Heart and Chest, Liverpool, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sternal wound infection (SWI) has always been a significant risk in patients who undergo sternotomies as part of their cardiac surgical procedures. Computed tomography (CT) imaging is often used to diagnose and assess sternal wound infections. Its purpose includes identifying and locating infection and any sternal dehiscence. Methods: A systematic literature review across PubMed, Embase, and Ovid was performed according to PRISMA guidelines to identify relevant articles that discussed the utility of CT scanning for SWI, common features identified, patient outcomes and sensitivity/specificity (Figure 1). Results: 25 papers were included. 100% (n=25) of the papers were published in peer-reviewed journals. CT scans in SWIs can be seen as a beneficial aid in diagnosing as well as determining the components of infection. Commonalities were identified such as fluid collection in the mediastinum, free gas, pleural effusions, and sternal dehiscence which point towards the presence of sternal wound infection. Conclusion: CT scanning is a novel and emerging methodology for imaging in SWI and post-sternotomy complications, hence increased research is required to expand the literature on this area as well as the creation of guidelines and cut-offs or signs for radiology professionals to identify and determine the extent of infection.

Indexed as

SternumSurgical Wound InfectionHumansRetrospective StudiesSternotomyTomography, X-Ray Computed

Identifiers

PMID38292500
PMCPMC10824137

What OpenQuestion holds

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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.