Evidence map›Paper›PMID 35659300›Full record

ArticleCardiovascular diabetology2022

Correlation between the triglyceride-to-high-density lipoprotein cholesterol ratio and other unconventional lipid parameters with the risk of prediabetes and Type 2 diabetes in patients with coronary heart disease: a RCSCD-TCM study in China.

Tong Yang, Yijia Liu, Lin Li, Yanchao Zheng, Yang Wang, Jinyu Su, Rongrong Yang, Mingchi Luo, Chunquan Yu

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 1 pooled it
21.3field-weighted citation impact, top 1% 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

93 citing papers in PubMed, 1 synthesis or guideline pooled it, 160 citations in OpenAlex.

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33 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Tong Yang *Tianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Yijia Liu *Tianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Lin Li *Tianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Yanchao ZhengTianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Yang WangTianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Jinyu SuTianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Rongrong YangTianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China.
Mingchi LuoSecond Teaching Hospital of Tianjin University of Traditional Chinese Medicine, No. 816, Truth Road, Hebei District, Tianjin, 300150, China.
Chunquan YuTianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, Wet Zone, Tuanbo New City, Jinghai District, Tianjin, 301617, China. ycqtjutcm@foxmail.com.
Tianjin University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveType 2 diabetes mellitus (T2DM) is often accompanied by undiagnosed dyslipidemia. Research on the association of unconventional lipid markers with prediabetes (pre-DM) and T2DM simultaneously is limited in coronary heart disease (CHD) patients.

methodsThis study included 28,476 patients diagnosed with CHD. Their lipid levels, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were measured, and non-traditional lipid parameters were calculated. The patients were divided into three groups based on the diabetic status including normoglycemic (NG), pre-DM, and T2DM. Multiple logistic regression was used to compare the association of TG/HDL-C and other non-traditional lipid parameters with pre-DM and T2DM. The tertiles of TG/HDL-C included T1 (TG/HDL-C < 1.10), T2 (1.10 ≤ TG/HDL-C ≤ 1.89) and T3 (TG/HDL-C > 1.89). Low and high TG/HDL-C was defined with sex-specific cutoff points.

resultsMultiple logistic regression results showed that the non-traditional lipid parameters, including non-HDL-C, LDL-C/HDL-C, TC/HDL-C, non-HDL-C/HDL-C and TG/HDL-C, were all correlated with the risk of pre-DM and T2DM. Meanwhile TG/HDL-C showed the strongest correlation (odds ratio [OR]: 1.19; 95% confidence interval [CI] 1.16-1.23), (OR: 1.36; 95% CI 1.33-1.39). When dividing TG/HDL-C into tertiles, using T1 as a reference, T3 was observed to have the highest association with both pre-DM and T2DM (OR: 1.60; 95% CI 1.48-1.74), (OR: 2.79; 95% CI 2.60-3.00). High TG/HDL-C was significantly associated with pre-DM and T2DM (OR: 1.69; 95% CI 1.52-1.88), (OR: 2.85; 95% CI 2.60-3.12). The association of TG/HDL-C with T2DM and pre-DM existed across different sex, age, smoking, and drinking statuses.

conclusionElevated non-traditional lipid parameters were significantly associated with pre-DM and T2DM in CHD patients, especially TG/HDL-C. High TG/HDL-C was the risk factor with a strong correlation with the risk of pre-DM and T2DM.

Indexed as

Coronary DiseaseDiabetes Mellitus, Type 2Prediabetic StateCholesterolCholesterol, HDLCholesterol, LDLFemaleHumansMaleRisk FactorsTriglyceridesCholesterolCholesterol, HDLCholesterol, LDLTriglyceridesCoronary heart diseaseLipidPrediabetesTG/HDL-CType 2 diabetes

Identifiers

PMID35659300
PMCPMC9166647
OpenAlexW4281654610

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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.