Evidence map›Paper›PMID 34963041›Full record

ArticleJournal of diabetes2022

New clusters of serum electrolytes aid in stratification of diabetes and metabolic risk.

Yanan Hou, Jiali Xiang, Huajie Dai, Tiange Wang, Mian Li, Hong Lin, Shuangyuan Wang, Yu Xu, Jieli Lu, Yuhong Chen and 5 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Journal of diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05791188 (Electrolyte Disorders in Prediabetics and in Patients With Type 2 Diabetes Mellitus), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 33% 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.

NCT05791188 unknown statusnot on this mapstarted 2023, after this paper: background citation

Electrolyte Disorders in Prediabetics and in Patients With Type 2 Diabetes Mellitus

TypeobservationalSponsorAssiut UniversityRan2023 to 2024Enrolled200ConditionsType 2 Diabetes Mellitus and Electrolyte Disorders
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 5 citations in OpenAlex.

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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

15 authors at 1 institution in 1 country.

Yanan HouDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jiali XiangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Huajie DaiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tiange WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mian LiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hong LinDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuangyuan WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jieli LuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-1317-0896
Yuhong ChenDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weiqing WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guang NingDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhiyun ZhaoDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0001-5950-2732
Yufang BiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Min XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-3930-8718
Shanghai Jiao Tong University · CN

Funding

National Natural Science Foundation of China 81930021National Natural Science Foundation of China 81941017National Natural Science Foundation of China 81970728National Natural Science Foundation of China 82088102National Natural Science Foundation of China 91857205Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support Round 2 20152508Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support Round 2 20161307Shanghai Shenkang Hospital Development Center SHDC12019101Shanghai Shenkang Hospital Development Center SHDC2020CR1001AShanghai Shenkang Hospital Development Center SHDC2020CR3069B
6 · The paper itself

Abstract

backgroundSerum electrolytes were found to associate with type 2 diabetes. Our study aimed to stratify nondiabetes by clusters based on multiple serum electrolytes and evaluate their associations with risk of developing diabetes and longitudinal changes in glucose and lipid metabolic traits.

methodsWe performed a data-driven cluster analysis in 4937 nondiabetes individuals aged ≥40 years at baseline from a cohort follow-up for an average of 4.4 years. Cluster analysis was based on seven commonly measured serum electrolytes (iron, chlorine, magnesium, sodium, potassium, calcium, and phosphorus) by using the k-means method.

resultsA total of 4937 nondiabetes individuals were classified into three distinct clusters, with 1635 (33.1%) assigned to Cluster A, 1490 (30.2%) to Cluster B, and 1812 (36.7%) to Cluster C. Individuals in Cluster A had higher serum chlorine, were older, and more were women. Individuals in Cluster B had higher serum iron and body mass index (BMI). Individuals in Cluster C had higher serum phosphorus, were younger, and had lower BMI. Cluster B had 1.41-fold higher risk of developing diabetes and Cluster C's risk was 1.33-fold higher compared with Cluster A. Over an average follow-up of 4.4 years, Cluster A showed a moderate and stable BMI, Cluster B showed an accelerated deterioration in glucose metabolism, and Cluster C showed the most sharply increased serum low-density lipoprotein cholesterol level.

conclusionsClusters based on seven common serum electrolytes differed in diabetes risk and progression of glucose and lipid metabolic traits. Serum electrolytes clusters could provide a powerful tool to differentiate individuals into different risk stratification for developing type 2 diabetes.

Indexed as

Diabetes Mellitus, Type 2AdultBody Mass IndexCluster AnalysisCohort StudiesElectrolytesFemaleHumansRisk FactorsElectrolytes2型糖尿病cluster analysismetabolic riskrisk stratificationserum electrolytestype 2 diabetes代谢风险危险分层聚类分析血清电解质

Identifiers

PMID34963041
PMCPMC9060051
OpenAlexW4200199625

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Registered trials

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.