Andrea Loggini, Faddi G Saleh Velez, Jonatan Hornik, Jessie Henson, Julie Wesler, Alejandro Hornik
{"title":"农村地区接受静脉溶栓治疗的缺血性脑卒中患者功能预后量表的验证。","authors":"Andrea Loggini, Faddi G Saleh Velez, Jonatan Hornik, Jessie Henson, Julie Wesler, Alejandro Hornik","doi":"10.1159/000541801","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Early prediction of functional outcome after rtPA helps clinicians in prognostic conversations with stroke patients and their families. Three prognostic tools have been developed in this regard: DRAGON, MRI-DRAGON, and S-TPI scales. These tools, all performing with comparable accuracy, have been internally and externally validated in tertiary care centers. However, their performance in rural areas remains uncertain. This study addresses this gap in the literature by evaluating the effectiveness of those prognostic tools in stroke patients treated in a rural area of the Midwest.</p><p><strong>Methods: </strong>We conducted a retrospective study of stroke patients treated with thrombolytics at Southern Illinois Healthcare Stroke Network from July 2017 to June 2024. Data on demographics, clinical presentations, laboratory values, neuroimaging, and stroke metrics were collected. Modified Rankin Scale (mRS) at 1 month, classified into good (mRS ≤2) and poor (mRS ≥5) outcomes were noted. DRAGON and MRI-DRAGON scores were calculated. S-TPI model was built. Area under the receiver operating characteristic curve (AUC) with its 95% confidence interval was calculated for each prognostic model.</p><p><strong>Results: </strong>A total of 279 patients were included in this study. Of those, 43% (n = 119) were male. Median age (interquartile range [IQR]) was 69 (57-80) years. NIHSS at presentation (IQR) was 7 (4-13). 12% of the cohort (n = 34) had posterior circulation stroke. At 1 month, 66% of patients (n = 185) had mRS ≤2, whereas 14% of patients (n = 39) had mRS ≥5. MRI-DRAGON showed the highest accuracy in predicting both good (AUC = 0.86, 95% CI: 0.81-0.90) and poor outcomes (AUC = 0.84, 95% CI: 0.76-0.91). DRAGON also demonstrated high accuracy for good (AUC = 0.85, 95% CI: 0.80-0.89) and poor (AUC = 0.82, 95% CI: 0.75-0.90) outcomes. Conversely, in our population, the S-TPI model had the lowest accuracy for good (AUC = 0.56, 95% CI: 0.49-0.63) and poor (AUC = 0.68, 95% CI: 0.61-0.76) outcomes.</p><p><strong>Conclusion: </strong>Among the available grading scores, MRI-DRAGON score can be considered the more accurate short-term prognostic tool for stroke patients treated with rtPA in the rural setting.</p>","PeriodicalId":45709,"journal":{"name":"Cerebrovascular Diseases Extra","volume":" ","pages":"148-157"},"PeriodicalIF":2.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11509495/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validation of Prognostic Scales for Functional Outcome in Ischemic Stroke Patients Treated with Intravenous Thrombolysis in a Rural Setting.\",\"authors\":\"Andrea Loggini, Faddi G Saleh Velez, Jonatan Hornik, Jessie Henson, Julie Wesler, Alejandro Hornik\",\"doi\":\"10.1159/000541801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Early prediction of functional outcome after rtPA helps clinicians in prognostic conversations with stroke patients and their families. Three prognostic tools have been developed in this regard: DRAGON, MRI-DRAGON, and S-TPI scales. These tools, all performing with comparable accuracy, have been internally and externally validated in tertiary care centers. However, their performance in rural areas remains uncertain. This study addresses this gap in the literature by evaluating the effectiveness of those prognostic tools in stroke patients treated in a rural area of the Midwest.</p><p><strong>Methods: </strong>We conducted a retrospective study of stroke patients treated with thrombolytics at Southern Illinois Healthcare Stroke Network from July 2017 to June 2024. Data on demographics, clinical presentations, laboratory values, neuroimaging, and stroke metrics were collected. Modified Rankin Scale (mRS) at 1 month, classified into good (mRS ≤2) and poor (mRS ≥5) outcomes were noted. DRAGON and MRI-DRAGON scores were calculated. S-TPI model was built. Area under the receiver operating characteristic curve (AUC) with its 95% confidence interval was calculated for each prognostic model.</p><p><strong>Results: </strong>A total of 279 patients were included in this study. Of those, 43% (n = 119) were male. Median age (interquartile range [IQR]) was 69 (57-80) years. NIHSS at presentation (IQR) was 7 (4-13). 12% of the cohort (n = 34) had posterior circulation stroke. At 1 month, 66% of patients (n = 185) had mRS ≤2, whereas 14% of patients (n = 39) had mRS ≥5. MRI-DRAGON showed the highest accuracy in predicting both good (AUC = 0.86, 95% CI: 0.81-0.90) and poor outcomes (AUC = 0.84, 95% CI: 0.76-0.91). DRAGON also demonstrated high accuracy for good (AUC = 0.85, 95% CI: 0.80-0.89) and poor (AUC = 0.82, 95% CI: 0.75-0.90) outcomes. 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Validation of Prognostic Scales for Functional Outcome in Ischemic Stroke Patients Treated with Intravenous Thrombolysis in a Rural Setting.
Introduction: Early prediction of functional outcome after rtPA helps clinicians in prognostic conversations with stroke patients and their families. Three prognostic tools have been developed in this regard: DRAGON, MRI-DRAGON, and S-TPI scales. These tools, all performing with comparable accuracy, have been internally and externally validated in tertiary care centers. However, their performance in rural areas remains uncertain. This study addresses this gap in the literature by evaluating the effectiveness of those prognostic tools in stroke patients treated in a rural area of the Midwest.
Methods: We conducted a retrospective study of stroke patients treated with thrombolytics at Southern Illinois Healthcare Stroke Network from July 2017 to June 2024. Data on demographics, clinical presentations, laboratory values, neuroimaging, and stroke metrics were collected. Modified Rankin Scale (mRS) at 1 month, classified into good (mRS ≤2) and poor (mRS ≥5) outcomes were noted. DRAGON and MRI-DRAGON scores were calculated. S-TPI model was built. Area under the receiver operating characteristic curve (AUC) with its 95% confidence interval was calculated for each prognostic model.
Results: A total of 279 patients were included in this study. Of those, 43% (n = 119) were male. Median age (interquartile range [IQR]) was 69 (57-80) years. NIHSS at presentation (IQR) was 7 (4-13). 12% of the cohort (n = 34) had posterior circulation stroke. At 1 month, 66% of patients (n = 185) had mRS ≤2, whereas 14% of patients (n = 39) had mRS ≥5. MRI-DRAGON showed the highest accuracy in predicting both good (AUC = 0.86, 95% CI: 0.81-0.90) and poor outcomes (AUC = 0.84, 95% CI: 0.76-0.91). DRAGON also demonstrated high accuracy for good (AUC = 0.85, 95% CI: 0.80-0.89) and poor (AUC = 0.82, 95% CI: 0.75-0.90) outcomes. Conversely, in our population, the S-TPI model had the lowest accuracy for good (AUC = 0.56, 95% CI: 0.49-0.63) and poor (AUC = 0.68, 95% CI: 0.61-0.76) outcomes.
Conclusion: Among the available grading scores, MRI-DRAGON score can be considered the more accurate short-term prognostic tool for stroke patients treated with rtPA in the rural setting.
期刊介绍:
This open access and online-only journal publishes original articles covering the entire spectrum of stroke and cerebrovascular research, drawing from a variety of specialties such as neurology, internal medicine, surgery, radiology, epidemiology, cardiology, hematology, psychology and rehabilitation. Offering an international forum, it meets the growing need for sophisticated, up-to-date scientific information on clinical data, diagnostic testing, and therapeutic issues. The journal publishes original contributions, reviews of selected topics as well as clinical investigative studies. All aspects related to clinical advances are considered, while purely experimental work appears only if directly relevant to clinical issues. Cerebrovascular Diseases Extra provides additional contents based on reviewed and accepted submissions to the main journal Cerebrovascular Diseases.