Evidence map›Paper›PMID 42733809›Full record

ArticleOpen access emergency medicine : OAEM2026

Emergency CT KUB: Incidental Findings and Their Clinical Significance.

Mostafa Dayraki, Shahzad Anjum, Lolwa AlKhulaifi, Lara Miranda, Duha Adil Musa Mohmmad, Atika Jabeen, Zain Ali Bhutta, Yavuz Yigit

Abstract read
In one paragraph

Article in Open access emergency medicine : OAEM, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Mostafa DayrakiDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.ORCID 0009-0005-6810-8709
Shahzad AnjumDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.ORCID 0000-0001-6521-0680
Lolwa AlKhulaifiDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.
Lara MirandaDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.
Duha Adil Musa MohmmadDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.
Atika JabeenDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.ORCID 0000-0002-2937-743X
Zain Ali BhuttaDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.
Yavuz YigitDepartment of Emergency Medicine, Hamad Medical Corporation, Doha, Qatar.ORCID 0000-0002-7226-983X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Incidental findings (IFs) on computed tomography of the kidneys, ureters, and bladder (CT KUB) are increasingly common in emergency departments (EDs) due to the widespread use of advanced imaging. These findings, often unrelated to the primary diagnostic indication, present clinical and operational challenges, particularly in high-volume, demographically diverse settings. Objective: To evaluate the prevalence, classification, and clinical significance of incidental findings on CT KUB scans performed in the ED for suspected obstructive uropathy, and to identify factors associated with clinically significant IFs and evaluate their clinical outcomes. Methods: A retrospective single-center observational study was conducted at a national tertiary-care hospital in Qatar, including all adult patients who underwent non-contrast CT KUB for suspected renal colic between January 1 and November 30, 2024. Demographic, clinical, and radiological data were extracted. IFs were categorized as major, moderate, or minor based on clinical relevance. Outcomes included prevalence and distribution of IFs, subsequent management actions, and factors associated with major IFs. Results: Of 2786 CT KUB scans analyzed, 1531 (54.9%) revealed at least one incidental finding. Most incidental findings were classified as minor (63.2%), whereas 6.1% were major and 30.8% were moderate according to the highest-severity incidental finding per scan. Major IFs (e.g, suspected malignancy, aortic aneurysm) accounted for most urgent interventions and admissions. Multivariable analysis identified that older age, nationality, fever, desaturation, and abdominal tenderness were independently associated with major IFs (all p<0.05). Management of the primary condition was delayed due to IFs in only 0.6% of cases. The most frequent IFs were vascular calcifications, bone lesions, and hernias. Conclusion: Incidental findings on CT KUB are common in the ED, with a significant proportion requiring further intervention or specialist referral. The high prevalence in a younger, multi-ethnic population underscores the need for context-specific protocols, structured reporting, and robust follow-up systems.

Indexed as

CT KUBemergency departmentincidental findingsobstructive uropathyrisk stratification

Identifiers

PMID42733809
PMCPMC13571618

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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.