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Prediction of Stroke After the COVID-19 Infection

Mahsa Babaee1, Karim Atashgar1, Ali Amini Harandi2

  • 1Faculty of Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.

Basic and Clinical Neuroscience
|September 18, 2024
PubMed

Insights

COVID-19 patients face a high risk of ischemic stroke, a serious complication. This study developed a predictive model using clinical factors, achieving 97.5% accuracy in identifying stroke risk.

Area of Science:

  • Neurology
  • Infectious Diseases
  • Medical Informatics

Background:

  • Ischemic stroke is a significant complication in COVID-19 patients, often leading to mortality.
  • Understanding risk factors is crucial for early diagnosis and treatment of stroke in COVID-19 survivors.

Purpose of the Study:

  • To develop a predictive model for identifying stroke incidence in COVID-19 patients.
  • To identify key clinical and laboratory factors associated with stroke in COVID-19 patients.

Main Methods:

  • A retrospective analysis of 128 COVID-19 patients' data (March-September 2020).
  • Development of a logistic regression model to predict stroke incidence.
  • Evaluation of model performance using Receiver Operating Characteristic-Area Under the Curve (ROC-AUC), accuracy, sensitivity, and specificity.

Main Results:

  • The logistic regression model achieved 93.8% accuracy and 97.5% ROC-AUC.
  • Ventilator dependence, cardiac ejection fraction, and lactate dehydrogenase (LDH) were identified as significant predictors of stroke.
  • The model effectively predicted stroke occurrence in COVID-19 patients.

Conclusions:

  • The developed model demonstrates high efficacy in predicting stroke in COVID-19 patients.
  • Key factors like ventilator dependence, cardiac ejection fraction, and LDH levels are critical indicators for stroke risk assessment.
  • The model can aid physicians in clinical decision-making for early stroke diagnosis and management in COVID-19 patients.
Abstract

Keywords:
COVID-19Logistic regressionPredictionSARS-CoV-2Stroke

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