Evidence map›Paper›PMID 42354486›Full record

ArticleHealthcare (Basel, Switzerland)2026

Prior X-Ray and Diagnostic Yield of Knee MRI: A Retrospective Study of Imaging Pathways and Healthcare Utilization.

Bandar Alwadani

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Bandar AlwadaniDepartment of Diagnostic Radiography Technology, College of Nursing and Health Sciences, Jazan University, Jazan 45142, Saudi Arabia.ORCID 0000-0001-8951-630X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeVariation in knee MRI diagnostic yield is often interpreted as reflecting imaging effectiveness. However, in real-world healthcare systems, diagnostic yield may instead be driven by referral behavior and patient selection. Understanding this distinction is essential for evaluating imaging utilization, healthcare efficiency, and potential overuse of advanced imaging. This study examines whether differences in MRI yield reflect imaging pathways or underlying referral patterns in routine clinical practice. MATERIALS AND

methodsThis retrospective cohort study included consecutive patients undergoing knee MRI between January 2020 and December 2024. Patients with red flag indications were excluded to focus on discretionary imaging. The primary outcome was clinically relevant MRI findings based on final report impressions. The primary exposure was prior X-ray before MRI. Multivariable logistic regression was used for adjusted analysis, including age, sex, trauma status, mechanical symptoms, and symptom duration.

resultsAmong 486 patients, 59.5% had prior X-ray. Clinically relevant MRI findings were less frequent among patients with prior X-ray (40.1%) than among those without (49.7%), corresponding to an absolute difference of 9.6%. After adjustment for sex and clinical covariates, prior X-ray showed lower odds of clinically relevant findings, although this association was attenuated and no longer statistically significant (aOR 0.74, 95% CI 0.50-1.10;

conclusionsMRI yield in routine practice may be influenced by differences in clinical context and referral-related patient selection. Further studies are needed to better understand the contribution of imaging pathways to observed variation in diagnostic yield.

Indexed as

diagnostic yieldhealthcare utilizationimaging stewardshipknee MRIreferral patterns

Identifiers

PMID42354486
PMCPMC13299063

What OpenQuestion holds

Textmetadata
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.