Evidence map›Paper›PMID 36632248›Full record

ArticleCureus2022

Routine Computed Tomography Versus Selective Imaging: An Audit of Negative Appendicectomy Rates in Two Hospitals.

Tristan Symonds, Helen Buschel, John Avramovic, Pranavan Palamuthusingam

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Observational
  2. 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

4 authors at 2 institutions in 2 countries.

Tristan SymondsOrthopaedics, Ipswich General Hospital, Ipswich, AUS.
Helen BuschelGeneral Surgery, Townsville University Hospital, Townsville, AUS.
John AvramovicGeneral Surgery, Townsville University Hospital, Townsville, AUS.
Pranavan PalamuthusingamGeneral Surgery, Townsville University Hospital, Townsville, AUS.
Ipswich Hospital · AUIpswich Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction There are a variety of conflicting recommendations in the literature for pre-operative imaging in acute appendicitis. There is debate over what the ideal imaging protocol is to lower the negative appendicectomy rate (NAR) without increasing missed appendicitis. The aim of this study is to compare the audited NAR between two groups with different imaging approaches: (i) mandatory pre-operative computed tomography (CT) imaging and (ii) selective imaging with CT, ultrasound (US), or no imaging prior to appendicectomy. Materials and methods A retrospective chart audit was conducted of 400 patients who underwent an appendicectomy at two hospitals with different approaches to pre-operative imaging (hospital A and hospital B). The primary outcome measure was histologically confirmed appendicitis. It was also documented whether there was radiological (CT or US) evidence of appendicitis.  Results At hospital A, all 200 patients underwent CT imaging prior to appendicectomy. The total histologically confirmed NAR for this group was 9.5% (19/200). At hospital B, 97 (48.5%) patients underwent CT, 41 (25.5%) underwent US, 10 (5%) had both US and CT, and 52 (26%) had no imaging. The total NAR was 11.5% (23/200). Conclusion There was no statistically significant difference (p=0.62) in audited NARs when comparing clinician-guided selective imaging versus routine CT imaging for all patients undergoing appendicectomy.

Indexed as

appendectomyappendicitiscomputer tomographyimagingnegative appendectomy rateultrasonography

Identifiers

PMID36632248
PMCPMC9830005
OpenAlexW4311036086

What OpenQuestion holds

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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.