Evidence map›Paper›PMID 39568751›Full record

ReviewFrontiers in medicine2024

The diagnostic performance of dual-energy CT imaging in cervical lymph node metastasis of papillary thyroid cancer: a meta-analysis.

Aiping Han, Yanqiu Liu, Lingxian Cai, Jing Xie, Shouzhang Hu

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2024. 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. 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

5 authors.

Aiping HanDepartment of Radiology, Affiliated Geriatric Hospital of Wuhan University of Science and Technology, Wuhan, China.
Yanqiu LiuDepartment of Radiology, Affiliated Geriatric Hospital of Wuhan University of Science and Technology, Wuhan, China.
Lingxian CaiDepartment of Radiology, Affiliated Geriatric Hospital of Wuhan University of Science and Technology, Wuhan, China.
Jing XieDepartment of Radiology, Affiliated Geriatric Hospital of Wuhan University of Science and Technology, Wuhan, China.
Shouzhang HuDepartment of Radiology, Affiliated Geriatric Hospital of Wuhan University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This meta-analysis aimed to evaluate the diagnostic efficacy of dual-energy computed tomography (DECT) in detecting cervical lymph node metastasis among papillary thyroid cancer (PTC) patients. Methods: A comprehensive search across PubMed, Embase, and Web of Science databases was conducted to identify pertinent publications up to May 2024. This search focused on studies examining the diagnostic accuracy of DECT in detecting cervical lymph node metastases in PTC patients. We employed a bivariate random-effects model to calculate pooled sensitivity and specificity of DECT. The degree of heterogeneity in the studies was quantified using the Results: This meta-analysis encompassed 14 articles, collectively involving 1,615 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting cervical lymph node metastases in PTC patients were 0.81 (95% CI: 0.76-0.85), 0.86 (95% CI: 0.80-0.91), and 0.89 (95% CI: 0.86-0.92), respectively. According to Fagan's nomogram, for DECT, with a pre-test probability of 50%, the post-test probability was calculated as 85% for a positive result and 18% for a negative result. Deeks' funnel plot asymmetry test showed no significant publication bias was observed for DECT ( Conclusion: Our meta-analysis indicates that DECT demonstrates superior sensitivity and specificity in cervical lymph node metastasis among PTC patients. To corroborate these findings and evaluate their clinical applicability, further prospective studies are necessary.

Indexed as

cervical lymph node metastasisdiagnostic efficacydual-energy CTmeta-analysispapillary thyroid cancer

Identifiers

PMID39568751
PMCPMC11577284

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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.