Evidence map›Paper›PMID 34096884›Full record

ArticleAging2021

Galectin-3/adiponectin as a new biological indicator for assessing the risk of type 2 diabetes: a cross-sectional study in a community population.

Diaozhu Lin, Xiaosi Hong, Kan Sun, Xiaoyun Zhang, Hong Lian, Jiahuan Wang, Na Mao, Xiuwei Zhang, Meng Ren, Li Yan and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 43% 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

8 citing papers in PubMed, 11 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

12 authors at 3 institutions in 1 country.

Diaozhu LinDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Xiaosi HongDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Kan SunDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Xiaoyun ZhangDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Hong LianDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Jiahuan WangDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Na MaoDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Xiuwei ZhangDepartment of Endocrinology, Dongguan People's Hospital, Dongguan 523000, People's Republic of China.
Meng RenDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Li YanDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Feng LiDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Lili YouDepartment of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People's Republic of China.
Sun Yat-sen University · CNDongguan People’s Hospital · CNSun Yat-sen Memorial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to explore the association between the risk of newly diagnosed type 2 diabetes and galectin-3 and adiponectin and to investigate whether their joint action shows a favorable diabetes assessment performance.

methodsWe conducted a community-based study in 135 newly diagnosed patients with type 2 diabetes and 270 age- and sex-matched nondiabetic patients. Odds ratios and 95% confidence intervals were determined using logistic regression analysis. Receiver operating characteristic curve, decision curve analysis and calibration plot were used to explore their efficacy and clinical utility for models.

resultsHigh quartiles of galectin-3/adiponectin (quartile 4 vs 1: OR 2.43 [95% CIs: 1.21-5.00]) showed the strongest correlation with an increased risk of type 2 diabetes in the total population, which was consistent in the older population (age≥50 years old) in adjustment models. The combination + lipids + galectin-3/adiponectin model (AUC = 0.72 [95% CIs: 0.66-0.77]) displayed better diabetes assessment performance than the other two models.

conclusionsHigh galectin-3 and low adiponectin levels were associated with the high risk of diabetes, and their joint action was a superior promising factor for evaluating diabetes risk. The diabetes discriminative strength of galectin-3/adiponectin was better in the older population than the younger.

Indexed as

AdiponectinBiomarkersCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleGalectin 3HumansMaleMiddle AgedModels, BiologicalOdds RatioRisk FactorsROC CurveAdiponectinBiomarkersGalectin 3agediabetes risk assessment modelgalectin-3/adiponectintype 2 diabetes

Identifiers

PMID34096884
PMCPMC8221326
OpenAlexW3172023688

What OpenQuestion holds

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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.