Evidence map›Paper›PMID 32629735›Full record

ArticleMedicine2020

Low-dose CT combined mammography in diagnosis of overflow breast disease: A protocol of systematic review.

Hao Tian, Shao-Jun Hu, Qun Tang, Fei-Hong Ma, Rong-Rong Yao

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Hao TianDepartment of General Surgery.
Shao-Jun HuDepartment of Tumor Surgery.
Qun TangDepartment of Hematology.
Fei-Hong MaDepartment of Interventional Radiology, First Affiliated Hospital of Jiamusi University, Jiamusi, China.
Rong-Rong YaoDepartment of Interventional Radiology, First Affiliated Hospital of Jiamusi University, Jiamusi, China.ORCID 0000-0003-4062-2990
Jiamusi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOverflow breast disease (OBD), also known as breast nipple discharge, refers fluid or liquid that comes out of nipple. Many patients with breast cancer experience such condition. However, it is not easy to detect it at early stage, especially for pathological OBD. Previous study found low-dose CT combined mammography (LDCTMG) could help in diagnosis of OBD. However, there is no systematic review investigating this issue. Therefore, this study will examine the accuracy of LDCTMG in diagnosis of OBD.

methodsThis study protocol will search literature sources in electronic databases and other sources. The electronic databases will be retrieved in The Cochrane Library, the Cochrane Register of Diagnostic Test Accuracy Studies, PUBMED, EMBASE, Web of Science, CINAHL, CNKI, and WANGFANG from inception to the present. We will also search other sources. All literature sources will be sought without restrictions to the language and publication status. Two researchers will independently carry out study selection, data extraction, and study quality assessment. Statistical analysis will be performed using RevMan 5.3.

resultsThis study will exert a high-quality synthesis of eligible studies on the analysis of LDCTMG in diagnosis of OBD.

conclusionsThe results of this study may provide evidence to help judge whether LDCTMG is accurate in diagnosis of OBD. STUDY REGISTRATION: INPLASY202050116.

Indexed as

AdultBreast DiseasesEvaluation Studies as TopicFemaleHumansMammographyMeta-Analysis as TopicMultimodal ImagingNipple DischargeSystematic Reviews as TopicTomography, X-Ray Computed

Identifiers

PMID32629735
PMCPMC7337454
OpenAlexW3030566976

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.