Evidence map›Paper›PMID 39114706›Full record

ReviewAmerican journal of translational research2024

Comparison of CT and MRI in diagnosing occult hip fracture: a systematic review and meta-analysis.

Hongxue Qu, Lei Bian

Abstract readReview
In one paragraph

Review in American journal of translational research, 2024. 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
–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

2 citing papers in PubMed.

  1. Article
  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

2 authors.

Hongxue QuDepartment of Orthopedics and Traumatology, Yantai Hospital of Traditional Chinese Medicine Yantai 264001, Shandong, China.
Lei BianDepartment of Imaging, Yantai Hospital of Traditional Chinese Medicine Yantai 264000, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the diagnostic accuracy of computed tomography (CT) scans and magnetic resonance imaging (MRI) in detecting occult hip fractures.

methodsWe conducted a systematic literature review and identified 12 articles involving 1,819 participants for inclusion. Data extraction and quality assessment were performed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Publication bias was assessed with the Deek funnel plot asymmetry test. We conducted a meta-analysis using a random-effects model to derive pooled estimates of sensitivity, specificity, positive and negative likelihood ratios, and the diagnostic odds ratio, along with their 95% confidence intervals. A summary receiver operating characteristic curve was generated to illustrate the overall diagnostic accuracy.

resultsThe methodological quality of the included studies was high, with minimal concerns about the applicability of the tests in clinical settings. Both CT and MRI showed good diagnostic efficacy for occult hip fractures. However, MRI consistently outperformed CT, exhibiting significantly higher sensitivity, specificity, and likelihood ratios, thereby providing superior accuracy in confirming or excluding occult fractures. Meta-regression analysis revealed that sequence parameters and sample size significantly influenced the differences in sensitivity and specificity between CT and MRI.

conclusionBoth CT and MRI are effective modalities for detecting occult hip fractures, with MRI demonstrating greater diagnostic accuracy. This meta-analysis supports the use of MRI when higher sensitivity and specificity are required in clinical practice.

Indexed as

computed tomographydiagnostic accuracydiagnostic odds ratiomagnetic resonance imagingOccult hip fracture

Identifiers

PMID39114706
PMCPMC11301482

What OpenQuestion holds

Textmetadata
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.