Evidence map›Paper›PMID 38329949›Full record

ArticlePloS one2024

Findings on emergent magnetic resonance imaging in pregnant patients with suspected appendicitis: A single center perspective.

Hila Bufman, Daniel Raskin, Yiftach Barash, Yael Inbar, Roy Mashiach, Noam Tau

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

6 authors.

Hila BufmanDepartment of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel.ORCID 0000-0001-9116-1923
Daniel RaskinDepartment of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel.
Yiftach BarashDepartment of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel.
Yael InbarDepartment of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel.
Roy MashiachSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Noam TauDepartment of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel.ORCID 0000-0003-0849-1708

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study's aim is to describe the imaging findings in pregnant patients undergoing emergent MRI for suspected acute appendicitis, and the various alternative diagnoses seen on those MRI scans. This is a single center retrospective analysis in which we assessed the imaging, clinical and pathological data for all consecutive pregnant patients who underwent emergent MRI for suspected acute appendicitis between April 2013 and June 2021. Out of 167 patients, 35 patients (20.9%) were diagnosed with acute appendicitis on MRI. Thirty patients (18%) were diagnosed with an alternative diagnosis on MRI: 17/30 (56.7%) patients had a gynecological source of abdominal pain (e.g. ectopic pregnancy, red degeneration of a leiomyoma); 8 patients (26.7%) had urological findings such as pyelonephritis; and 6 patients (20%) had gastrointestinal diagnoses (e.g. abdominal wall hernia or inflammatory bowel disease). Our conclusions are that MRI is a good diagnostic tool in the pregnant patient, not only in diagnosing acute appendicitis, but also in providing information on alternative diagnoses to acute abdominal pain. Our findings show the various differential diagnoses on emergent MRI in pregnant patients with suspected acute appendicitis, which may assist clinicians and radiologists is patient assessment and imaging utilization.

Indexed as

AppendicitisPregnancy ComplicationsAbdominal PainAcute DiseaseDiagnosis, DifferentialFemaleHumansMagnetic Resonance ImagingPregnancyRetrospective StudiesSensitivity and Specificity

Identifiers

PMID38329949
PMCPMC10852244

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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.