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.

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, n = 193) and Bozhou People's Hospital (external validation set, n = 265). END was defined as an increase of ≥1 point in the motor items of the National Institutes of Health Stroke Scale (NIHSS) or an increase of ≥2 points in the total score within 72 h after onset. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to identify relevant factors and construct the nomogram. Model performance was evaluated using receiver operating characteristic curves, calibration curves, and clinical impact curves. Optimism correction was performed using 500 bootstrap resampling, and model generalizability was validated using an external validation 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, p = 0.001), FBG (OR = 1.253, 95% CI: 1.016-1.547, p = 0.034), SIRI (OR = 3.140, 95% CI: 1.584-6.223, p < 0.001), and BAR (OR = 1.480, 95% CI: 1.207-1.815, p < 0.001) were independent factors associated with END. The apparent AUC of the model in the training set was 0.850 (95% CI: 0.796-0.904); after bootstrap optimism correction, the corrected AUC was 0.837 (95% CI: 0.780-0.889). The AUC in the external validation set was 0.824 (95% CI: 0.778-0.879). Calibration curves and clinical impact curves demonstrated good calibration and clinical utility of the model. 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.