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Background <p>This study aims to develop and validate a novel nomogram for predicting ischemic early neurological deterioration (END) following intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS).</p> Methods <p>We conducted a retrospective study that consecutively enrolled patients with AIS who received IVT at two hospitals from January 2020 to June 2025. We employed Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariable logistic regression analyses to identify independent risk factors for ischemic END and to construct the nomogram. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), calibration curves, and decision curve analysis (DCA).</p> Results <p>Among the 880 patients included in the study, 18.6% experienced END. We identified six independent risk factors: age, National Institutes of Health Stroke Scale (NIHSS) score, systolic blood pressure (SBP), Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification, neutrophil-to-lymphocyte ratio (NLR), and stress hyperglycemia ratio (SHR). The nomogram showed a strong ability to discriminate effectively, with AUCs of 0.745 (95% CI, 0.684–0.805) in the training set, 0.722 (95% CI, 0.615–0.829) in the internal validation set, and 0.773 (95% CI, 0.708–0.838) in the external validation set. It also exhibited favorable calibration. DCA confirmed the clinical utility of the model across a wide range of threshold probabilities, from 0.1 to 0.9, in the external validation set.</p> Conclusion <p>The novel nomogram that incorporates age, NIHSS score, initial SBP, TOAST classification, NLR, and SHR shows promise in predicting the risk of ischemic END after intravenous thrombolysis in stroke patients.</p>

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A new nomogram for predicting the risk of ischemic early neurological deterioration after intravenous thrombolysis in acute ischemic stroke: a multicenter retrospective study

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  • 发表日期：

    2026年3月8日

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  • Chunhao Mei,
  • Lingzhi Chen,
  • Qin Shi,
  • Xiaoning Guo,
  • Yang Yang,
  • Qingguang Wang,
  • Bojun Han,
  • Tao Fan,
  • Jiajia Chen,
  • Tingting Tao

摘要

Background

This study aims to develop and validate a novel nomogram for predicting ischemic early neurological deterioration (END) following intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS).

Methods

We conducted a retrospective study that consecutively enrolled patients with AIS who received IVT at two hospitals from January 2020 to June 2025. We employed Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariable logistic regression analyses to identify independent risk factors for ischemic END and to construct the nomogram. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), calibration curves, and decision curve analysis (DCA).

Results

Among the 880 patients included in the study, 18.6% experienced END. We identified six independent risk factors: age, National Institutes of Health Stroke Scale (NIHSS) score, systolic blood pressure (SBP), Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification, neutrophil-to-lymphocyte ratio (NLR), and stress hyperglycemia ratio (SHR). The nomogram showed a strong ability to discriminate effectively, with AUCs of 0.745 (95% CI, 0.684–0.805) in the training set, 0.722 (95% CI, 0.615–0.829) in the internal validation set, and 0.773 (95% CI, 0.708–0.838) in the external validation set. It also exhibited favorable calibration. DCA confirmed the clinical utility of the model across a wide range of threshold probabilities, from 0.1 to 0.9, in the external validation set.

Conclusion

The novel nomogram that incorporates age, NIHSS score, initial SBP, TOAST classification, NLR, and SHR shows promise in predicting the risk of ischemic END after intravenous thrombolysis in stroke patients.