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<p>Prognostication after acute ischemic stroke is crucial for long-term care plans. Although hyperacute management significantly affects outcomes, prognostic factors for patients receiving delayed care remain unknown. This study aimed to evaluate predictors and develop a method for estimating long-term mortality in patients with delayed hospital arrival 24&#xa0;h after stroke symptom onset. Between January 2008 and December 2014, ischemic stroke patients who were admitted to the hospital more than 24&#xa0;h from symptom onset were included in the linked dataset provided by the Clinical Research Center for Stroke, linked with claims data from the Health Insurance Review and Assessment Service. A nomogram was developed to estimate long-term mortality using clinical variables, with a predictive model assessed by Harrell’s C-index. A total of 14,298 patients with acute ischemic stroke (66.5&#xa0;years, mean age; 58.3%, male) were randomly assigned to training (<i>n</i> = 10,009) and validation (<i>n</i> = 4289) groups. Significant predictors of long-term mortality included older age, lower BMI, higher NIHSS score, stroke etiology, comorbidities (diabetes, coronary artery disease, dialysis, cancer), fasting blood sugar, use of antithrombotics/statins, and functional status at discharge. The Stroke Measures Analysis for Prognostic Testing – Mortality24 (SMART-M24) nomogram incorporated 17 predictors and achieved a C-index of 0.80 (95% CI, 0.79–0.81) in both groups. The SMART-M24 nomogram provides a prognostic tool for estimating long-term mortality in ischemic stroke patients with delayed hospital arrival 24&#xa0;h after symptom onset. This model can assist clinical decision-making and long-term care planning for patients who have not undergone hyperacute treatment.</p>

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SMART-M24: A Prognostic Nomogram for Long-Term Mortality in Acute Ischemic Stroke Beyond 24 H from Symptom Onset

  • 期刊论文

  • 发表日期：

    2025年6月9日

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  • Soo-Hyun Park,
  • Ji Sung Lee,
  • Tae Jung Kim,
  • Mi Sun Oh,
  • Ji-Woo Kim,
  • Kyungbok Lee,
  • Kyung-Ho Yu,
  • Byung-Chul Lee,
  • Byung-Woo Yoon,
  • Sang-Bae Ko

摘要

Prognostication after acute ischemic stroke is crucial for long-term care plans. Although hyperacute management significantly affects outcomes, prognostic factors for patients receiving delayed care remain unknown. This study aimed to evaluate predictors and develop a method for estimating long-term mortality in patients with delayed hospital arrival 24 h after stroke symptom onset. Between January 2008 and December 2014, ischemic stroke patients who were admitted to the hospital more than 24 h from symptom onset were included in the linked dataset provided by the Clinical Research Center for Stroke, linked with claims data from the Health Insurance Review and Assessment Service. A nomogram was developed to estimate long-term mortality using clinical variables, with a predictive model assessed by Harrell’s C-index. A total of 14,298 patients with acute ischemic stroke (66.5 years, mean age; 58.3%, male) were randomly assigned to training (n = 10,009) and validation (n = 4289) groups. Significant predictors of long-term mortality included older age, lower BMI, higher NIHSS score, stroke etiology, comorbidities (diabetes, coronary artery disease, dialysis, cancer), fasting blood sugar, use of antithrombotics/statins, and functional status at discharge. The Stroke Measures Analysis for Prognostic Testing – Mortality24 (SMART-M24) nomogram incorporated 17 predictors and achieved a C-index of 0.80 (95% CI, 0.79–0.81) in both groups. The SMART-M24 nomogram provides a prognostic tool for estimating long-term mortality in ischemic stroke patients with delayed hospital arrival 24 h after symptom onset. This model can assist clinical decision-making and long-term care planning for patients who have not undergone hyperacute treatment.