ArticleScientific reports2025
A nomogram based on the TyG index for the prediction of lower-limb venous thrombosis in patients with intracerebral hemorrhage.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Triglyceride-glucose body mass index and risk of incident venous thromboembolism: a prospective cohort study from the UK Biobank.European journal of medical research · 2026Article
- Association between triglyceride glucose- systemic immune inflammation index and deep venous thrombosis in fresh fracture patient: a real-world retrospective study.Frontiers in endocrinology · 2026Article
- The triglyceride-glucose index: updating evidence from clinical settings to molecular mechanisms in ageing-related cerebrovascular diseases.Cardiovascular diabetology · 2025Review
- Risk factors for lower limb deep vein thrombosis in patients with intracerebral hemorrhage: a retrospective study using LASSO regression to develop a nomogram.Frontiers in neurologyArticle
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Abstract
Venous thrombosis is a serious complication that adversely impacts the prognosis of patients with intracerebral hemorrhage (ICH) and even threatens their lives. Triglyceride glucose product (TyG) index is closely related to the pathophysiological process of cerebral hemorrhage and venous thrombosis. A total of 308 ICH patients were divided into training (n = 215) and validation groups (n = 93). Single factor logistic regression analysis and multiple factor logistic regression analysis were performed. Seven factors associated with lower extremity venous thrombosis were identified: emergency cranial surgery, pneumonia, stroke history, age, TyG index, capryini score ≥ 10, and glomerular filtration rate. The area under the curve was found to be 0.79 (95% CI: 0.72-0.86) in the training group and 0.70 (95% CI: 0.58-0.83) in the validation group. Calibration plots demonstrated strong concordance between predicted probabilities from our model and observed outcomes; Decision curve analysis further confirmed that our nomogram provides substantial clinical net benefit. By integrating the TyG index with recognized clinical risk factors for ICH patients, we have developed a predictive nomogram that aids in early identification of individuals at high risk for lower extremity venous thrombosis as well as supports personalized management strategies for these patients.
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