Evidence map›Paper›PMID 36778594›Full record

ArticleFrontiers in endocrinology2022

The management correlation between metabolic index, cardiovascular health, and diabetes combined with cardiovascular disease.

Yi Zhang, Chao Liu, Yijing Xu, Yanlei Wang, Fang Dai, Honglin Hu, Tian Jiang, Yunxia Lu, Qiu Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Yi ZhangDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Chao LiuDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Yijing XuDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Yanlei WangDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Fang DaiDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Honglin HuDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Tian JiangDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Yunxia LuDepartment of Biochemistry and Molecular Biology, Anhui Medical University, Hefei, China.
Qiu ZhangDepartment of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular disease (CVD) has become a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Although there is also evidence that multifactorial interventions to control blood glucose, blood pressure, and lipid profiles can reduce macrovascular complications and mortality in patients with T2DM, the link between these risk factors has not been established. Methods: On 10 December 2018, 1,920 people in four cities in Anhui Province were included. Latent category analysis (LCA) was used to explore the clustering mode of HRBs (health risk behaviors). The primary exposure was HRBs and exercise and diet interventions, and the primary outcome was CVD and other variables, including zMS, triglyceride-glucose index (TyG), TyG-WC (waist circumference), TyG-BMI, TG/HDL, and cardiovascular health (CVH). A multivariable logistic regression model was used to establish the relationship between HRBs, exercise, diet interventions, and CVD. Moderate analysis and mediation moderation analysis were employed by the PROCESS method to explore the relationship between these variables. Sensitivity analysis explored the robustness of the model. Results: The mean age was 57.10 ± 10.0 years old. Overall, CVD affects approximately 19.9% of all persons with T2DM. Macrovascular complications of T2DM include coronary heart disease, myocardial infarction (MI), cardiac insufficiency, and cerebrovascular disease. Elderly age ( Conclusions: CVD is one of the common complications in patients with type 2 diabetes, and its long-term outcome will have more or less impact on patients. Our findings suggest the potential benefits of scaling up multifactorial and multifaceted interventions to prevent CVD in patients with T2DM.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2AgedBlood GlucoseGlucoseHumansMiddle AgedRisk FactorsBlood GlucoseGlucosecardiovascular diseasescardiovascular health (CVH)diabetesmanagementmetabolic index

Identifiers

PMID36778594
PMCPMC9911412

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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.