Evidence map›Paper›PMID 32518782›Full record

ArticleWorld journal of clinical cases2020

Four-microRNA signature for detection of type 2 diabetes.

Li-Na Yan, Xin Zhang, Fang Xu, Yuan-Yuan Fan, Biao Ge, Hui Guo, Zi-Ling Li

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

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  11. Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes.International journal of molecular sciences · 2021
    Review
  12. Review
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  14. MicroRNAs, Parkinson's Disease, and Diabetes Mellitus.International journal of molecular sciences · 2021
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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

7 authors at 3 institutions in 1 country.

Li-Na YanDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China.
Xin ZhangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital and Institute, Beijing 100142, China.
Fang XuDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China.
Yuan-Yuan FanDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China.
Biao GeDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China.
Hui GuoDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China.
Zi-Ling LiDepartment of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China. 3301922766@qq.com.
Peking University · CNBaogang Group (China) · CNPeking University Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSensitive, novel, and accurate biomarkers for the detection of physiological changes in type 2 diabetes (T2DM) at an early stage are urgently needed.

aimTo build a multi-parameter diagnostic model for the early detection of T2DM.

methodsMiR-148b, miR-223, miR-130a, and miR-19a levels were detected by real-time polymerase chain reaction in serum of healthy controls, individuals with impaired glucose regulation, and T2DM patients. The diagnostic value of miR-148b, miR-223, miR-130a, and miR-19a, alone or in combination, was analyzed.

resultsThe area under the curve (AUC) of miR-223, which had the best diagnostic value for discriminating the impaired glucose regulation and T2DM groups, was 0.84, and the sensitivity and specificity were 73.37% and 81.37%, respectively. The AUC of the four-miRNA signature was 0.90, and the sensitivity and specificity were 78.82% and 88.23%, respectively. In the validation set, the AUC was 0.88, and the sensitivity and specificity were 78.36% and 87.63%, respectively.

conclusionIn summary, we have built a multi-parameter diagnostic model consisting of miR-148b, miR-223, miR-130a, and miR-19a for the detection of T2DM. It may be a potential tool for the early detection of T2DM.

Indexed as

BiomarkerMicroRNAsMulti-parameterSerumType 2 diabetes

Identifiers

PMID32518782
PMCPMC7262691
OpenAlexW3028904506

What OpenQuestion holds

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LicenceCC BY-NC
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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.