Evidence map›Paper›PMID 33019411›Full record

ArticleMedicine2020

The diagnostic accuracy of superb microvascular imaging in distinguishing thyroid nodules: A protocol for systematic review and meta analysis.

Congliang Tian, Zinan Wang, Xiukun Hou, Cong Wang

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. 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
0.6field-weighted citation impact, top 31% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  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

4 authors at 2 institutions in 1 country.

Congliang TianPediatrics Department of the First Affiliated Hospital of Dalian Medical University.
Zinan WangNutrition Department of the First Affiliated Hospital of Dalian Medical University.
Xiukun HouUltrasound Department of the First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China.
Cong WangUltrasound Department of the First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China.
Dalian Medical University · CNFirst Affiliated Hospital of Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUltrasonography is the first choice for clinical diagnosis and differentiation of thyroid cancer Currently. However, due to the complexity and overlapping nature of the thyroid nodule sonograms, it remains difficult to accurately identify nodules with atypical ultrasound characteristics. Previous studies showed that superb microvascular imaging (SMI) can detect tumor neovascularization to differentiate benign from malignant thyroid nodules. However, the results of these studies have been contradictory with low sample sizes. This meta-analysis tested the hypothesis that SMI is accurate in distinguishing benign and malignant thyroid nodules.

methodsWe will search PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases from their inceptions to the August 20, 2020, without language restrictions. Two authors will independently carry out searching literature records, scanning titles and abstracts, full texts, collecting data, and assessing risk of bias. Review Manager 5.2 and Stata14.0 software ((Stata Corp, College Station, TX) will be used for data analysis.

resultsThis systematic review will determine the accuracy of SMI in distinguishing thyroid nodules.

conclusionIts findings will provide helpful evidence for the accuracy of SMI in in distinguishing thyroid nodules.Systematic review registration: INPLASY202080084.

Indexed as

Diagnosis, DifferentialImage Processing, Computer-AssistedMeta-Analysis as TopicNeovascularization, PathologicResearch DesignSystematic Reviews as TopicThyroid NeoplasmsThyroid NoduleUltrasonography

Identifiers

PMID33019411
PMCPMC7535557
OpenAlexW3080163558

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.