ArticleFrontiers in neurology
A nomogram integrating hemodynamic and inflammatory markers to predict early neurological deterioration after tenecteplase in branch atheromatous disease: an early in-hospital risk stratification model.
Article in Frontiers in neurology. 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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Abstract
Objective: To investigate the risk factors for early neurological deterioration (END) in patients with branch atheromatous disease (BAD) receiving intravenous tenecteplase thrombolysis, and to construct a predictive nomogram model. Methods: Clinical data of BAD patients receiving intravenous tenecteplase thrombolysis from September 2021 to October 2025 were retrospectively collected from Anhui No. 2 Provincial People's Hospital (training set, Results: LASSO regression identified four predictors: 24-h systolic blood pressure coefficient of variation (CV-24hSBP), fasting blood glucose (FBG), systemic inflammatory response index (SIRI), and blood urea nitrogen to albumin ratio (BAR). Multivariate logistic regression showed that CV-24hSBP (OR = 2.704, 95% CI: 1.471-4.967, Conclusion: The nomogram model based on CV-24hSBP, FBG, SIRI, and BAR demonstrates good predictive performance and generalizability for END in BAD patients receiving intravenous tenecteplase thrombolysis. Because CV-24hSBP requires continuous blood pressure monitoring for 24 h after thrombolysis, this model is not suitable for pre-thrombolysis or ultra-early prediction but can serve as an in-hospital early risk stratification tool to identify high-risk patients and guide individualized intervention.
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