INTRODUCTION:Patients receivingintravenous thrombolysis with recombinant tissue plasminogen activator (IVT) for ischemic stroke are monitored in an intensive care unit (ICU) or a comparable unit capable of ICU interventions due to the high frequency of standardized neurological exams and vital sign checks. The present study evaluates quantitative infarct volume on early post-IVT MRI as a predictor of critical care needs and aims to identify patients who may not require resource intense monitoring. METHODS: We identified 46 patients who underwent MRI within 6 h ofIVT. Infarct volume was measured using semiautomated software. Logistic regression and receiver operating characteristics (ROC) analysis were used to determine factors associated with ICU needs. RESULTS:Infarct volume was an independent predictor of ICU need after adjusting for age, sex, race, systolic blood pressure, NIH Stroke Scale (NIHSS), and coronary artery disease (odds ratio 1.031 per cm(3) increase in volume, 95% confidence interval [CI] 1.004-1.058, p = 0.024). The ROC curve with infarct volume alone achieved an area under the curve (AUC) of 0.766 (95% CI 0.605-0.927), while the AUC was 0.906 (95% CI 0.814-0.998) after adjusting for race, systolic blood pressure, and NIHSS. Maximum Youden index calculations identified an optimal infarct volume cut point of 6.8 cm(3) (sensitivity 75.0%, specificity 76.7%). Infarct volume greater than 3 cm(3) predicted need for critical care interventions with 81.3% sensitivity and 66.7% specificity. CONCLUSION:Infarct volume may predict needs for ICU monitoring and interventions in stroke patients treated withIVT.
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INTRODUCTION:Patients receiving intravenous thrombolysis with recombinant tissue plasminogen activator (IVT) for ischemic stroke are monitored in an intensive care unit (ICU) or a comparable unit capable of ICU interventions due to the high frequency of standardized neurological exams and vital sign checks. The present study evaluates quantitative infarct volume on early post-IVT MRI as a predictor of critical care needs and aims to identify patients who may not require resource intense monitoring. METHODS: We identified 46 patients who underwent MRI within 6 h of IVT. Infarct volume was measured using semiautomated software. Logistic regression and receiver operating characteristics (ROC) analysis were used to determine factors associated with ICU needs. RESULTS:Infarct volume was an independent predictor of ICU need after adjusting for age, sex, race, systolic blood pressure, NIH Stroke Scale (NIHSS), and coronary artery disease (odds ratio 1.031 per cm(3) increase in volume, 95% confidence interval [CI] 1.004-1.058, p = 0.024). The ROC curve with infarct volume alone achieved an area under the curve (AUC) of 0.766 (95% CI 0.605-0.927), while the AUC was 0.906 (95% CI 0.814-0.998) after adjusting for race, systolic blood pressure, and NIHSS. Maximum Youden index calculations identified an optimal infarct volume cut point of 6.8 cm(3) (sensitivity 75.0%, specificity 76.7%). Infarct volume greater than 3 cm(3) predicted need for critical care interventions with 81.3% sensitivity and 66.7% specificity. CONCLUSION:Infarct volume may predict needs for ICU monitoring and interventions in strokepatients treated with IVT.
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