Related Experiment Video

Updated: May 4, 2026

A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
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A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia

Published on: August 18, 2015

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A one-year relapse prediction model for acute ischemic stroke (AIS) based on clinical big data

Wenle Li1,2, Zhendong Ding3, Liangqun Rong2,4

  • 1The State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, China.

Heliyon
|June 17, 2024
PubMed

Insights

This study developed a nomogram to predict acute ischemic stroke (AIS) recurrence within one year. The model, incorporating factors like homocysteine and stroke severity, demonstrated high accuracy and clinical utility for healthcare professionals.

Area of Science:

  • Neurology
  • Cardiovascular Medicine
  • Biostatistics

Background:

  • Acute ischemic stroke (AIS) poses a significant risk for recurrence, necessitating accurate prediction models.
  • Early identification of patients at high risk of AIS recurrence is crucial for timely intervention and improved outcomes.

Purpose of the Study:

  • To develop and validate a nomogram prediction model for forecasting the recurrence of AIS within a one-year timeframe.
  • To identify independent risk factors associated with AIS recurrence for inclusion in the predictive model.

Main Methods:

  • A cohort of 645 AIS patients was analyzed, collecting data on demographics, risk factors, laboratory tests, etiological types, and MRI features.
  • Cox regression analysis was employed to determine significant predictors for the nomogram.
  • Model performance was assessed using receiver operating characteristic (ROC) curves, decision curve analysis, calibration curves, and the C-index.

Main Results:

  • Key independent risk factors for AIS recurrence included side of hemisphere, homocysteine (HCY), C-reactive protein (CRP), and stroke severity (SS).
  • The developed nomogram achieved a high C-index of 0.872 and an area under the ROC curve of 0.900 for one-year recurrence.
  • The model demonstrated good performance in calibration and decision curve analyses, with a recurrence risk cutoff score of 1.73.

Conclusions:

  • The developed nomogram is a well-performing tool for predicting one-year AIS recurrence.
  • This nomogram can serve as a valuable clinical aid for healthcare professionals in managing AIS patients and guiding treatment strategies.
Abstract

Keywords:
Acute ischemic strokeNomogramRecurrence

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