{
  "abstract": "Background: The early stages 0–3 of cardiovascular–kidney–metabolic (CKM) syndrome represent a critical window for cardiovascular disease (CVD) prevention. Although insulin resistance (IR) is a key driver of CVD risk, systematic comparisons of IR surrogates in CVD remain limited. This study examined the associations of 12 IR surrogates with CVD in participants with stages 0–3 CKM syndrome.\n\nMethods: This prospective study included 5,625 participants with stages 0–3 CKM syndrome from the Qingdao Diabetes Program. Twelve IR surrogates related to CVD were evaluated using multivariable-adjusted Cox models, restricted cubic splines, sensitivity analyses, and predictive performance analyses, such as triglyceride–glucose index, atherogenic index of plasma, cardiometabolic index, metabolic score for IR (METS-IR), cholesterol-high-density lipoprotein-glucose (CHG) index, CHG plus body mass index, CHG plus waist circumference, CHG plus waist-to-height ratio, CHG plus body roundness index, CHG plus weight-adjusted waist index, CHG plus A body shape index, and CHG plus Chinese visceral adiposity index (CVAI).\n\nResults: Over a median follow-up of 15.2 years, 1,407 incident CVD events occurred. In multivariable-adjusted analyses, all 12 IR surrogates were significantly associated with CVD risk (all P < 0.05), of CHG-CVAI showing the best performance (Q4 vs. Q1: HR = 2.10, 95% CI = 1.74–2.52). Most indices showed nonlinear dose–response relationships. The associations were higher risk for adults aged <60 years and urban residents as compared with counterparts, and sensitivity analyses confirmed the robustness of the primary findings. Furthermore, addition of each IR surrogate improved CVD risk prediction: C-index ranging from 0.669 to 0.674, NRI ranging from 0.089 to 0.205 and IDI ranging from 0.0004 to 0.0032 (all P < 0.001).\n\nConclusion: All IR surrogates, particularly CHG-CVAI were independently associated with incident CVD in early-stages CKM syndrome. These simple, low-cost indices improved risk stratification and moderately identify CVD individuals in high risk population.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Epidemiology and Health Statistics, Qingdao Medical College, Qingdao University",
    "Qingdao Centers for Disease Control and Prevention",
    "Qingdao Municipal Health Big Data Center",
    "Huangdao Centers for Disease Control and Prevention",
    "Department of Rehabilitation Medicine, Qingdao Municipal Hospital",
    "Qingdao Binhai Medical College",
    "Qingdao Prevention Medicine Institute",
    "Qingdao Endocrine and Diabetes Hospital"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ao Li"
    },
    {
      "affs": [
        1
      ],
      "name": "Shiyu Tian"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Jianjun Zhang"
    },
    {
      "affs": [
        3
      ],
      "name": "Dong Zhang"
    },
    {
      "affs": [
        4
      ],
      "name": "Jie Xu"
    },
    {
      "affs": [
        1
      ],
      "name": "Xianyun Wang"
    },
    {
      "affs": [
        5
      ],
      "name": "Hongxuan Yan"
    },
    {
      "affs": [
        1,
        6
      ],
      "name": "Xiaohui Sun"
    },
    {
      "affs": [
        0,
        1,
        6
      ],
      "name": "Feng Ning"
    },
    {
      "affs": [
        7
      ],
      "name": "Lei Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fr06anwj0vrrj.bib",
  "cited_by": 0,
  "doi": "10.3389/fcvm.2026.1876121",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13727414/?tool=EBI",
  "id": "fr06anwj0vrrj",
  "issns": [
    "2297-055X"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fcvm.2026.1876121/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2712|Diabetes, Cardiovascular Risks, and Lipoproteins"
    ]
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  "openalex": "W7223057404",
  "pdf_url": "https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2026.1876121/pdf",
  "pmcid": "PMC13727414",
  "pmid": "42978645",
  "published": "2026-10-20",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/fr06anwj0vrrj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:10Z",
      "native_id": "10.3389/fcvm.2026.1876121",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fcvm.2026.1876121/full"
    },
    {
      "first_seen": "2026-11-04T15:20:45Z",
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  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2712|Diabetes, Cardiovascular Risks, and Lipoproteins",
      "subfield": "endocrinology-metabolism"
    }
  ],
  "title": "Associations of insulin resistance surrogates with cardiovascular disease in early stage cardiovascular–kidney–metabolic syndrome: a prospective cohort study",
  "title_text": "Associations of insulin resistance surrogates with cardiovascular disease in early stage cardiovascular–kidney–metabolic syndrome: a prospective cohort study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T12:20:36Z",
  "url": "https://research.draconitic.com/paper/fr06anwj0vrrj",
  "venue": "Frontiers in Cardiovascular Medicine",
  "versions": []
}