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Purpose <p>This study aimed to develop novel nomogram models capable of predicting early neurological deterioration (END) and 90-day prognosis outcomes in acute ischemic stroke (AIS) patients treated with IV thrombolysis.</p> Methods <p>A retrospective derivation cohort comprising 298 AIS patients was enrolled from January 2021 to March 2024. A separate validation cohort of 94 patients was retrospectively enrolled between April 2024 and December 2024. END was defined as a sustained NIHSS increase of ≥ 2 points within 24&#xa0;h, and poor prognosis outcome a mRS score of 3–6 at 90&#xa0;days. Multivariate logistic regression analysis was employed to construct nomogram models for the prediction of outcomes.</p> Results <p>In the derivation cohort, 23.83% patients with END experienced a poor 90-day outcome, as compared to 12.42% of those from NO-END group. Independent risk factors for END included a lower initial NIHSS score, a delayed DNT, a reduced ASPECTS score, and incomplete Willis Artery. END patients were found to be at a significantly increased risk of poor 90-day prognosis (odds ratio 0.163, <i>p</i> &lt; 0.001). In addition, elevated initial NIHSS and glucose levels, the presence of nonlacunar infarction, and history of hypertension were predictive of poor prognosis. Two separate nomogram models, developed based on the previously identified risk factors to predict the occurrence of END and a poor 90-day prognosis, demonstrated AUC values of 0.740 (95% CI 0.686–0.789) and 0.859 (95% CI 0.814–0.896). These models also exhibited good discriminatory capacity in the validation cohort, with corresponding AUC values of 0.716 (95% CI 0.541–0.892) and 0.795 (95% CI 0.689–0.900).</p> Conclusion <p>This study has successfully constructed reliable nomogram models for forecasting END and poor 90-day outcomes in AIS patients treated with IV thrombolysis; thereby, facilitating personalized prediction of adverse outcomes and adjustment of treatment strategy.</p>

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Accurate forecasting in acute ischemic stroke: innovative nomogram models for early neurological deterioration and 90-day prognosis outcomes following intravenous thrombolysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月25日

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  • Lai Wei,
  • Xiang Zhou,
  • Zhenyuan Zhou,
  • Kangwei Zhang,
  • Jinxi Meng,
  • Xiyi Huang,
  • Xiaoyan Wu,
  • Peijun Wang

摘要

Purpose

This study aimed to develop novel nomogram models capable of predicting early neurological deterioration (END) and 90-day prognosis outcomes in acute ischemic stroke (AIS) patients treated with IV thrombolysis.

Methods

A retrospective derivation cohort comprising 298 AIS patients was enrolled from January 2021 to March 2024. A separate validation cohort of 94 patients was retrospectively enrolled between April 2024 and December 2024. END was defined as a sustained NIHSS increase of ≥ 2 points within 24 h, and poor prognosis outcome a mRS score of 3–6 at 90 days. Multivariate logistic regression analysis was employed to construct nomogram models for the prediction of outcomes.

Results

In the derivation cohort, 23.83% patients with END experienced a poor 90-day outcome, as compared to 12.42% of those from NO-END group. Independent risk factors for END included a lower initial NIHSS score, a delayed DNT, a reduced ASPECTS score, and incomplete Willis Artery. END patients were found to be at a significantly increased risk of poor 90-day prognosis (odds ratio 0.163, p < 0.001). In addition, elevated initial NIHSS and glucose levels, the presence of nonlacunar infarction, and history of hypertension were predictive of poor prognosis. Two separate nomogram models, developed based on the previously identified risk factors to predict the occurrence of END and a poor 90-day prognosis, demonstrated AUC values of 0.740 (95% CI 0.686–0.789) and 0.859 (95% CI 0.814–0.896). These models also exhibited good discriminatory capacity in the validation cohort, with corresponding AUC values of 0.716 (95% CI 0.541–0.892) and 0.795 (95% CI 0.689–0.900).

Conclusion

This study has successfully constructed reliable nomogram models for forecasting END and poor 90-day outcomes in AIS patients treated with IV thrombolysis; thereby, facilitating personalized prediction of adverse outcomes and adjustment of treatment strategy.