Evidence map›Paper›PMID 39696298›Full record

ArticleLipids in health and disease2024

Association of non-insulin-dependent insulin resistance indices with lower limb artery restenosis after drug-coated balloon angioplasty.

Zhentao Qiao, Yuansong Zhuang, Zhiwei Wang

Abstract read
In one paragraph

Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Zhentao Qiao *Department of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. qzt212@163.com.
Yuansong Zhuang *Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Zhiwei WangDepartment of Vascular and Endovascular Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

the Joint Construction Project of Henan Medical Science and Technology Research Plan LHGJ20240265
6 · The paper itself

Abstract

backgroundThis study aimed to investigate the associations between noninsulin-dependent insulin resistance indices (NI-IRIs), including the triglyceride-glucose (TyG) index, TyG-BMI, triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), and metabolic score for insulin resistance (METS-IR), as well as the occurrence of restenosis in patients with lower extremity atherosclerotic occlusive disease after drug-coated balloon (DCB) treatment.

methodsThe primary endpoint was restenosis within one year after the procedure, which was defined as ≥ 50% stenosis of the treated artery segment. The association between NI-IRIs and restenosis was assessed via multivariable logistic regression analysis. Restricted cubic spline (RCS) analysis was performed to quantify nonlinearity. The consistency of these associations was confirmed through subgroup and interaction analyses. Additionally, the additional predictive value of NI-IRIs beyond established risk factors for restenosis was evaluated via receiver operating characteristic (ROC) curves, the net reclassification improvement (NRI), and integrated discrimination improvement (IDI) indices.

resultsExcept for the TyG index, the other three NI-IRIs demonstrated nonlinear relationships with the probability of postoperative restenosis. Specifically, TG/HDL-C (inflection point: 1.48, P for nonlinearity: 0.003) exhibited a saturating effect, whereas METS-IR (inflection point: 49.30, P for nonlinearity: 0.017) and TyG-BMI (inflection point: 221.53, P for nonlinearity: 0.039) showed threshold effects. Subgroup analysis revealed that the interactions among the subgroups were not statistically significant. Furthermore, among the four NI-IRIs, the addition of the TG/HDL-C index significantly enhanced the predictive power of the base model for restenosis in ASO patients following DCB angioplasty (AUC values: 0.726 vs. 0.760, P = 0.042). The P values for the NRI and IDI were 0.001 and 0.002, respectively.

conclusionTG/HDL-C showed a saturating effect on restenosis within one year after DCB treatment in ASO patients, and METS-IR and TyG-BMI showed threshold effects. The addition of the TG/HDL-C index significantly improved the predictive ability of the base model for restenosis in ASO patients who underwent DCB angioplasty.

Indexed as

Angioplasty, BalloonInsulin ResistanceLower ExtremityTriglyceridesAgedBlood GlucoseCholesterol, HDLFemaleHumansMaleMiddle AgedPeripheral Arterial DiseaseRisk FactorsROC CurveBlood GlucoseCholesterol, HDLTriglyceridesAtherosclerotic occlusive diseaseDrug-coated balloonInsulin resistanceRestenosisRetrospective study

Identifiers

PMID39696298
PMCPMC11654070

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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.