Evidence map›Paper›PMID 37091165›Full record

SynthesisFrontiers in oncology2023

Diagnostic value of superb microvascular imaging and color doppler for thyroid nodules: A meta-analysis.

Haorou Luo, Lixue Yin

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

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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 at 1 institution in 1 country.

Haorou LuoChengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Lixue YinSichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, School of Medicine University of Electronic Science and Technology of China (UESTC), Chengdu, Sichuan, China.
University of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Superb micro-vascular imaging (SMI) is a new noninvasive modality for the diagnosis of thyroid nodules. However, the performance of SMI in differentiating malignant and benign thyroid nodules has not been systematically evaluated. This meta-analysis was performed to assess the accuracy of SMI in diagnosing thyroid nodules. Methods: PubMed, Cochrane Library, Embase, Web of Science, Sinomed, Scopus were searched. We recorded the characteristics of the included studies and assessed the quality of each study using the QUADAS-2 tool. The pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated. We also evaluated the publication bias. Results: This meta-analysis included 10 studies with a total of 1083 thyroid nodules. The pooled the sensitivity, specificity, and positive and negative LR were 0.84, 0.86, 6.2, and 0.18, respectively. The DOR and AUC were 33 and 0.91, respectively. Heterogeneity existed between the included studies. No significant publication bias was observed. Conclusion: Compared with CDFI, Superb micro-vascular imaging (SMI) has higher diagnostic sensitivity and specificity, better diagnostic efficiency, and could be used to diagnose benign and malignant nodules in the display of blood flow distribution capabilities of thyroid nodules; at the same time, Fagan plot showed that the SMI technique had a good clinical application value, and it could supplement the deficiencies of color Doppler imaging in the diagnosis of thyroid nodules.

Indexed as

meta-analysisSMI = superb microvascular imagingsuperb microvascular imagingthyroid nodulesultrasonography

Identifiers

PMID37091165
PMCPMC10113672
OpenAlexW4362623152

What OpenQuestion holds

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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.