Evidence map›Paper›PMID 34123819›Full record

ArticleFrontiers in oncology2021

Contrast-Enhanced Ultrasound in the Differential Diagnosis and Risk Stratification of ACR TI-RADS Category 4 and 5 Thyroid Nodules With Non-Hypovascular.

Yanfang Wang, Tiantian Dong, Fang Nie, Guojuan Wang, Ting Liu, Qian Niu

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Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

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0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
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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

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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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Yanfang WangMedical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Tiantian DongMedical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Fang NieMedical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Guojuan WangMedical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Ting LiuMedical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Qian NiuDepartment of Pathology, Lanzhou University Second Hospital, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to investigate the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis and risk stratification of ACR TI-RADS category 4 and 5 thyroid nodules with non-hypovascular.

methodsFrom January 2016 to December 2019 in our hospital, 217 ACR TI-RADS category 4 and 5 nodules with non-hypovascular in 210 consecutive patients were included for a derivation cohort. With surgery and/or fine-needle aspiration (FNA) as a reference, conventional ultrasound (US) features and CEUS features were analyzed. Multivariate logistic regression analysis was used to screen the independent risk factors and establish a risk predictive model. Between January 2020 and March 2021, a second cohort of 100 consecutive patients with 101 nodules were included for an external validation cohort. The model was converted into a simplified risk score and was validated in the validation cohort. The area under the receiver operating characteristic curves (AUC) were used to assess the models' diagnostic performance.

resultsMicro-calcification, irregular margin, earlier wash-out, centripetal enhancement, and absence of ring enhancement were independent risk factors and strongly discriminated malignancy in the derivation cohort (AUC = 0.921, 95% CI 0.876-0.953) and the validation cohort (0.900, 0.824-0.951). There was no significant difference (

conclusionsCEUS is helpful in combination with conventional US in differentiating ACR TI-RADS category 4 and 5 nodules with non-hypovascular. The risk score in this study has the potential to improve the diagnosis and risk stratification of non-hypovascular thyroid nodules.

Indexed as

contrast mediafine-needle aspirationrisk stratificationthyroid imaging reporting and data systemthyroid nodulesultrasonography

Identifiers

PMID34123819
PMCPMC8189148

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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.