Evidence map›Paper›PMID 31261536›Full record

ArticleMedicine2019

Contrast ultrasound versus ultrasound elastography for diagnosis of breast lumps: A cross-sectional study.

Wei Zhao, Kaituo Yan, Yingying Liu, Zaibin Zhang

Open access · goldAbstract readComparative Study
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
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 1 institution in 1 country.

Wei ZhaoDepartment of Ultrasound, Weifang Yidu Central Hospital, Weifang, China.
Kaituo Yan
Yingying Liu
Zaibin Zhang
Yidu Central Hospital of Weifang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chinese women have dense and small breasts. Therefore, in China, contrast ultrasound and ultrasound elastography are commonly used for detection of the breast lumps. Purpose of the study was to compare the sensitivity and accuracy of ultrasound elastography with contrast ultrasound for the diagnosis of the breast lumps.A total of 1000 women with a damp in breast mass, breast pain, nipple discharge, and/or breast skin discharge were subjected to contrast ultrasound and ultrasound elastography. Women were subjected to stereotactic vacuum-assisted biopsy under B-mode ultrasonography (n = 750). The ultrasound examinations were graded on a 5-points scale method. Data were subjected to the Chi-square Independence test at 99% of confidence level.Ultrasound elastography was detected the same numbers of benign lesions (648 vs 651, P = .88), malignant lesions (90 vs 99, P = .53), and false positive lesions (5 vs 0, P = .07) as those detected by biopsies. However, diagnostic parameters for contrast ultrasound had a significant difference with those detected by biopsies (P < .0001 for all). For contrast ultrasound and ultrasound elastography, the working area to detect deformation in the image of the breast lesions at least 1 time were 0% to 45% and 5% to 100%.Ultrasound elastography is the most reliable diagnostic method for detection of the breast lumps.

Indexed as

Elasticity Imaging TechniquesUltrasonography, MammaryAgedBreast DiseasesContrast MediaCross-Sectional StudiesFemaleHumansMiddle AgedSensitivity and SpecificityContrast Media

Identifiers

PMID31261536
PMCPMC6617358
OpenAlexW2954895223

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.