학술논문
Development and Validation of a Postprocedural Model to Predict Outcome After Endovascular Treatment for Ischemic Stroke.
Document Type
Academic Journal
Author
Chalos V; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Venema E; Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Department of Emergency Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Mulder MJHL; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Roozenbeek B; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Steyerberg EW; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.; Wermer MJH; Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.; Lycklama À Nijeholt GJ; Department of Radiology, Medical Center Haaglanden, The Hague, the Netherlands.; van der Worp HB; Department of Neurology and Neurosurgery, University Medical Center Utrecht, Brain Center, Utrecht University, Utrecht, the Netherlands.; Goyal M; Departments of Clinical Neuroscience and Radiology, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Campbell BCV; Department of Medicine and Neurology, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia.; Muir KW; Institute of Neuroscience & Psychology, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, United Kingdom.; Guillemin F; CHRU Nancy, Inserm, Université de Lorraine, CIC Clinical Epidemiology, Nancy, France.; Bracard S; Department of Diagnostic and Interventional Neuroradiology, University of Lorraine and University Hospital of Nancy, Nancy, France.; White P; Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.; Dávalos A; Department of Neuroscience, Hospital Germans Trias y Pujol, Barcelona, Spain.; Jovin TG; Stroke Institute, Department of Neurology, University of Pittsburgh Medical Center Stroke Institute, Presbyterian University Hospital, Pittsburgh, Pennsylvania.; Hill MD; Departments of Clinical Neuroscience and Radiology, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Mitchell PJ; Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia.; Demchuk AM; Departments of Clinical Neuroscience and Radiology, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Saver JL; Department of Neurology and Comprehensive Stroke Center, David Geffen School of Medicine, University of Los Angeles, Los Angeles, California.; van der Lugt A; Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Brown S; Altair Biostatistics, Mooresville, North Carolina.; Dippel DWJ; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.; Lingsma HF; Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Source
Publisher: American Medical Association Country of Publication: United States NLM ID: 101589536 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2168-6157 (Electronic) Linking ISSN: 21686149 NLM ISO Abbreviation: JAMA Neurol Subsets: MEDLINE
Subject
Language
English
Abstract
Importance: Outcome prediction after endovascular treatment (EVT) for ischemic stroke is important to patients, family members, and physicians.
Objective: To develop and validate a model based on preprocedural and postprocedural characteristics to predict functional outcome for individual patients after EVT.
Design, Setting, and Participants: A prediction model was developed using individual patient data from 7 randomized clinical trials, performed between December 2010 and December 2014. The model was developed within the Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials (HERMES) collaboration and external validation in data from the Dutch Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) Registry of patients treated in clinical practice between March 2014 and November 2017. Participants included patients from multiple centers throughout different countries in Europe, North America, East Asia, and Oceania (derivation cohort), and multiple centers in the Netherlands (validation cohort). Included were adult patients with a history of ischemic stroke from an intracranial large vessel occlusion in the anterior circulation who underwent EVT within 12 hours of symptom onset or last seen well. Data were last analyzed in July 2022.
Main Outcome(s) and Measure(s): A total of 19 variables were assessed by multivariable ordinal regression to predict functional outcome (modified Rankin Scale [mRS] score) 90 days after EVT. Variables were routinely available 1 day after EVT. Akaike information criterion (AIC) was used to optimize model fit vs model complexity. Probabilities for functional independence (mRS 0-2) and survival (mRS 0-5) were derived from the ordinal model. Model performance was expressed with discrimination (C statistic) and calibration.
Results: A total of 781 patients (median [IQR] age, 67 [57-76] years; 414 men [53%]) constituted the derivation cohort, and 3260 patients (median [IQR] age, 72 [61-80] years; 1684 men [52%]) composed the validation cohort. Nine variables were included in the model: age, baseline National Institutes of Health Stroke Scale (NIHSS) score, prestroke mRS score, history of diabetes, occlusion location, collateral score, reperfusion grade, NIHSS score at 24 hours, and symptomatic intracranial hemorrhage 24 hours after EVT. External validation in the MR CLEAN Registry showed excellent discriminative ability for functional independence (C statistic, 0.91; 95% CI, 0.90-0.92) and survival (0.89; 95% CI, 0.88-0.90). The proportion of functional independence in the MR CLEAN Registry was systematically higher than predicted by the model (41% vs 34%), whereas observed and predicted survival were similar (72% vs 75%). The model was updated and implemented for clinical use.
Conclusion and Relevance: The prognostic tool MR PREDICTS@24H can be applied 1 day after EVT to accurately predict functional outcome for individual patients at 90 days and to provide reliable outcome expectations and personalize follow-up and rehabilitation plans. It will need further validation and updating for contemporary patients.
Objective: To develop and validate a model based on preprocedural and postprocedural characteristics to predict functional outcome for individual patients after EVT.
Design, Setting, and Participants: A prediction model was developed using individual patient data from 7 randomized clinical trials, performed between December 2010 and December 2014. The model was developed within the Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials (HERMES) collaboration and external validation in data from the Dutch Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) Registry of patients treated in clinical practice between March 2014 and November 2017. Participants included patients from multiple centers throughout different countries in Europe, North America, East Asia, and Oceania (derivation cohort), and multiple centers in the Netherlands (validation cohort). Included were adult patients with a history of ischemic stroke from an intracranial large vessel occlusion in the anterior circulation who underwent EVT within 12 hours of symptom onset or last seen well. Data were last analyzed in July 2022.
Main Outcome(s) and Measure(s): A total of 19 variables were assessed by multivariable ordinal regression to predict functional outcome (modified Rankin Scale [mRS] score) 90 days after EVT. Variables were routinely available 1 day after EVT. Akaike information criterion (AIC) was used to optimize model fit vs model complexity. Probabilities for functional independence (mRS 0-2) and survival (mRS 0-5) were derived from the ordinal model. Model performance was expressed with discrimination (C statistic) and calibration.
Results: A total of 781 patients (median [IQR] age, 67 [57-76] years; 414 men [53%]) constituted the derivation cohort, and 3260 patients (median [IQR] age, 72 [61-80] years; 1684 men [52%]) composed the validation cohort. Nine variables were included in the model: age, baseline National Institutes of Health Stroke Scale (NIHSS) score, prestroke mRS score, history of diabetes, occlusion location, collateral score, reperfusion grade, NIHSS score at 24 hours, and symptomatic intracranial hemorrhage 24 hours after EVT. External validation in the MR CLEAN Registry showed excellent discriminative ability for functional independence (C statistic, 0.91; 95% CI, 0.90-0.92) and survival (0.89; 95% CI, 0.88-0.90). The proportion of functional independence in the MR CLEAN Registry was systematically higher than predicted by the model (41% vs 34%), whereas observed and predicted survival were similar (72% vs 75%). The model was updated and implemented for clinical use.
Conclusion and Relevance: The prognostic tool MR PREDICTS@24H can be applied 1 day after EVT to accurately predict functional outcome for individual patients at 90 days and to provide reliable outcome expectations and personalize follow-up and rehabilitation plans. It will need further validation and updating for contemporary patients.