Evidence map›Paper›PMID 34306481›Full record

ArticleAmerican journal of translational research2021

Correlation analysis between rim enhancement features of contrast-enhanced ultrasound and lymph node metastasis in breast cancer.

Yanling Guo, Qingfei Song, Qiaohong Pan

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2021. 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
0.2field-weighted citation impact, top 51% 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, 2 citations in OpenAlex.

  1. Article
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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

3 authors at 1 institution in 1 country.

Yanling GuoDepartment of Ultrasound Medicine, Heping Hospital Affiliated to Changzhi Medical College Changzhi, Shanxi, China.
Qingfei SongDepartment of Ultrasound Medicine, Heping Hospital Affiliated to Changzhi Medical College Changzhi, Shanxi, China.
Qiaohong PanDepartment of Ultrasound Medicine, Heping Hospital Affiliated to Changzhi Medical College Changzhi, Shanxi, China.
Changzhi Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the correlation between rim enhancement features of contrast-enhanced ultrasound and lymphatic metastasis, and to provide theoretical support for clinical treatment of breast cancer.

methods387 breast cancer patients (748 axillary lymph nodes in total) treated in our hospital from January 2017 to January 2020 were selected and analyzed by contrast-enhanced ultrasound. Pathological examination showed that 540 axillary lymph nodes showed metastasis whereas 208 axillary lymph nodes did not show metastasis. Univariate analysis and Logistic stepwise regression were used to analyze the correlation between rim enhancement features of contrast-enhanced ultrasound and axillary lymph node metastasis of breast cancer.

resultsPeripheral halo, peripheral convergence, rim enhancement, enhancement mode, enhancement amplitude, enhancement sequence, expansion after enhancement, peak intensity, time to peak, area under curve, thrombolysis in myocardial infarction, perfusion sequence, aspect ratio, and maximum cortical thickness were all related to lymph node metastasis of breast cancer by univariate analysis, and the difference was statistically significant (

conclusionRim enhancement features of contrast-enhanced ultrasound of breast cancer are related to lymph node metastasis, which will provide a guidance for clinical treatment of breast cancer.

Indexed as

Breast cancercontrast enhanced ultrasoundlymph node metastasisrelevance

Identifiers

PMID34306481
PMCPMC8290713
OpenAlexW3186710828

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.