Evidence map›Paper›PMID 40821184›Full record

ArticleCureus2025

See to Believe: The Clinical Gaps in the Utility of Ultrasound Imaging in Screening for Ovarian Torsion.

Joachim Kavalakatt, Jalal Ibrahim, Matthew Thomas, Peter Richa, Hussain Rawiji

Abstract readCase Reports
In one paragraph

Article in Cureus, 2025. 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. 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

5 authors.

Joachim KavalakattOncology, Lake Erie College of Osteopathic Medicine, Bradenton, USA.
Jalal IbrahimDermatology, Lake Erie College of Osteopathic Medicine, Bradenton, USA.
Matthew ThomasPediatrics and Child Health, Lake Erie College of Osteopathic Medicine, Bradenton, USA.
Peter RichaMedicine, Lake Erie College of Osteopathic Medicine, Jacksonville, USA.
Hussain RawijiPediatrics and Obstetrics, AdventHealth Central Florida, Orange City, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian torsion is a gynecologic emergency requiring prompt diagnosis and intervention to prevent ischemic damage and loss of ovarian function. However, its diagnosis remains challenging due to nonspecific symptoms and limitations in imaging modalities. This case report presents two patients with suspected ovarian torsion based on ultrasound findings, both of whom were ultimately found to have alternative diagnoses. One patient underwent surgery, revealing an ovarian endometrioma rather than torsion, while the other was spared unnecessary surgery after MRI findings clarified the diagnosis. These cases underscore the limitations of ultrasound with Doppler as a standalone diagnostic tool and highlight the need for a multimodal imaging approach, incorporating CT or MRI in equivocal cases. A more nuanced analysis is warranted, one that takes into consideration different subpopulations of women by age range and menopausal status to refine clinical management, and also looks at certain diagnostic and imaging features that present within these specific patient groups that can aid in confirming torsion and expediting care. By integrating additional imaging techniques and leveraging emerging diagnostic tools, clinicians can improve accuracy, reduce morbidity, and ensure that surgical intervention is increasingly reserved for true cases of ovarian torsion.

Indexed as

adnexal torsionclinical decision supportct imagingemergency diagnostic laparoscopymri imagingmultimodal imaging approachovarian torsionovarian torsion managementovary torsionultrasound imaging

Identifiers

PMID40821184
PMCPMC12357748

What OpenQuestion holds

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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.