Predictive Value of the Systemic Immune Inflammation Index for Adverse Outcomes in Patients With Acute Ischemic Stroke
The systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined t...
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Published in | Frontiers in neurology Vol. 13; p. 836595 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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Frontiers Media S.A
18.03.2022
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ISSN | 1664-2295 1664-2295 |
DOI | 10.3389/fneur.2022.836595 |
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Abstract | The systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined the relationship between systemic immune-inflammation index levels at hospital admission and the outcomes of patients 3 months after onset, and plotted a nomogram to predict the probability of adverse outcomes in patients with acute ischemic stroke.
We retrospectively analyzed a total of 208 patients with acute ischemic stroke who were admitted between January 2020 and December 2020, and recorded the modified Rankin score 3 months later. A modified Rankin score ≥ 3 was defined as an adverse outcome. Age, sex, NIHSS score, SII, hypertension and coronary heart disease were included in the binary logistic regression, and the nomogram was plotted with a regression equation.
Receiver operating characteristic (ROC) curve analysis indicated that the best cutoff value of the systemic immune-inflammation index was 802.8, with a sensitivity of 70.9% and specificity of 58.2% (area under the curve: 0.657, 95% confidence interval: 0.572-0.742). The nomogram had a C index of 0.802. The average error of the calibration curves of the training set and the validation set was 0.021 and 0.034, respectively.
The systemic immune-inflammation index is associated with short-term adverse outcomes in patients with acute ischemic stroke, and the nomograms can predict the risk of adverse outcomes in patients with acute ischemic stroke. |
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AbstractList | The systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined the relationship between systemic immune-inflammation index levels at hospital admission and the outcomes of patients 3 months after onset, and plotted a nomogram to predict the probability of adverse outcomes in patients with acute ischemic stroke.Background and PurposeThe systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined the relationship between systemic immune-inflammation index levels at hospital admission and the outcomes of patients 3 months after onset, and plotted a nomogram to predict the probability of adverse outcomes in patients with acute ischemic stroke.We retrospectively analyzed a total of 208 patients with acute ischemic stroke who were admitted between January 2020 and December 2020, and recorded the modified Rankin score 3 months later. A modified Rankin score ≥ 3 was defined as an adverse outcome. Age, sex, NIHSS score, SII, hypertension and coronary heart disease were included in the binary logistic regression, and the nomogram was plotted with a regression equation.MethodsWe retrospectively analyzed a total of 208 patients with acute ischemic stroke who were admitted between January 2020 and December 2020, and recorded the modified Rankin score 3 months later. A modified Rankin score ≥ 3 was defined as an adverse outcome. Age, sex, NIHSS score, SII, hypertension and coronary heart disease were included in the binary logistic regression, and the nomogram was plotted with a regression equation.Receiver operating characteristic (ROC) curve analysis indicated that the best cutoff value of the systemic immune-inflammation index was 802.8, with a sensitivity of 70.9% and specificity of 58.2% (area under the curve: 0.657, 95% confidence interval: 0.572-0.742). The nomogram had a C index of 0.802. The average error of the calibration curves of the training set and the validation set was 0.021 and 0.034, respectively.ResultsReceiver operating characteristic (ROC) curve analysis indicated that the best cutoff value of the systemic immune-inflammation index was 802.8, with a sensitivity of 70.9% and specificity of 58.2% (area under the curve: 0.657, 95% confidence interval: 0.572-0.742). The nomogram had a C index of 0.802. The average error of the calibration curves of the training set and the validation set was 0.021 and 0.034, respectively.The systemic immune-inflammation index is associated with short-term adverse outcomes in patients with acute ischemic stroke, and the nomograms can predict the risk of adverse outcomes in patients with acute ischemic stroke.ConclusionThe systemic immune-inflammation index is associated with short-term adverse outcomes in patients with acute ischemic stroke, and the nomograms can predict the risk of adverse outcomes in patients with acute ischemic stroke. Background and PurposeThe systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined the relationship between systemic immune-inflammation index levels at hospital admission and the outcomes of patients 3 months after onset, and plotted a nomogram to predict the probability of adverse outcomes in patients with acute ischemic stroke.MethodsWe retrospectively analyzed a total of 208 patients with acute ischemic stroke who were admitted between January 2020 and December 2020, and recorded the modified Rankin score 3 months later. A modified Rankin score ≥ 3 was defined as an adverse outcome. Age, sex, NIHSS score, SII, hypertension and coronary heart disease were included in the binary logistic regression, and the nomogram was plotted with a regression equation.ResultsReceiver operating characteristic (ROC) curve analysis indicated that the best cutoff value of the systemic immune-inflammation index was 802.8, with a sensitivity of 70.9% and specificity of 58.2% (area under the curve: 0.657, 95% confidence interval: 0.572–0.742). The nomogram had a C index of 0.802. The average error of the calibration curves of the training set and the validation set was 0.021 and 0.034, respectively.ConclusionThe systemic immune-inflammation index is associated with short-term adverse outcomes in patients with acute ischemic stroke, and the nomograms can predict the risk of adverse outcomes in patients with acute ischemic stroke. The systemic immune-inflammation index, a new index based on platelets, neutrophils and lymphocytes, has been shown to be associated with outcomes of patients with venous sinus thrombosis and cancer. However, its application in acute ischemic stroke has rarely been reported. Therefore, we examined the relationship between systemic immune-inflammation index levels at hospital admission and the outcomes of patients 3 months after onset, and plotted a nomogram to predict the probability of adverse outcomes in patients with acute ischemic stroke. We retrospectively analyzed a total of 208 patients with acute ischemic stroke who were admitted between January 2020 and December 2020, and recorded the modified Rankin score 3 months later. A modified Rankin score ≥ 3 was defined as an adverse outcome. Age, sex, NIHSS score, SII, hypertension and coronary heart disease were included in the binary logistic regression, and the nomogram was plotted with a regression equation. Receiver operating characteristic (ROC) curve analysis indicated that the best cutoff value of the systemic immune-inflammation index was 802.8, with a sensitivity of 70.9% and specificity of 58.2% (area under the curve: 0.657, 95% confidence interval: 0.572-0.742). The nomogram had a C index of 0.802. The average error of the calibration curves of the training set and the validation set was 0.021 and 0.034, respectively. The systemic immune-inflammation index is associated with short-term adverse outcomes in patients with acute ischemic stroke, and the nomograms can predict the risk of adverse outcomes in patients with acute ischemic stroke. |
Author | Wang, Wen-Bo Tang, Can Li, Wen-Cai Xiang, Ting Zhou, Yun-Xiang Lin, Ming-Jian Xia, Xue-Wei Luo, Jia-Li Xia, Shao-Huai |
AuthorAffiliation | 2 Department of Neurosurgery, Huizhou Municipal Central Hospital , Huizhou , China 3 Department of Neurosurgery, Nanxishan Hospital of Guangxi Zhuang Autonomous Region , Guilin , China 1 Department of Neurosurgery, Affiliated Hospital of Guilin Medical University , Guilin , China |
AuthorAffiliation_xml | – name: 2 Department of Neurosurgery, Huizhou Municipal Central Hospital , Huizhou , China – name: 3 Department of Neurosurgery, Nanxishan Hospital of Guangxi Zhuang Autonomous Region , Guilin , China – name: 1 Department of Neurosurgery, Affiliated Hospital of Guilin Medical University , Guilin , China |
Author_xml | – sequence: 1 givenname: Yun-Xiang surname: Zhou fullname: Zhou, Yun-Xiang – sequence: 2 givenname: Wen-Cai surname: Li fullname: Li, Wen-Cai – sequence: 3 givenname: Shao-Huai surname: Xia fullname: Xia, Shao-Huai – sequence: 4 givenname: Ting surname: Xiang fullname: Xiang, Ting – sequence: 5 givenname: Can surname: Tang fullname: Tang, Can – sequence: 6 givenname: Jia-Li surname: Luo fullname: Luo, Jia-Li – sequence: 7 givenname: Ming-Jian surname: Lin fullname: Lin, Ming-Jian – sequence: 8 givenname: Xue-Wei surname: Xia fullname: Xia, Xue-Wei – sequence: 9 givenname: Wen-Bo surname: Wang fullname: Wang, Wen-Bo |
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Copyright | Copyright © 2022 Zhou, Li, Xia, Xiang, Tang, Luo, Lin, Xia and Wang. Copyright © 2022 Zhou, Li, Xia, Xiang, Tang, Luo, Lin, Xia and Wang. 2022 Zhou, Li, Xia, Xiang, Tang, Luo, Lin, Xia and Wang |
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Keywords | systemic immune-inflammation index (SII) nomogram inflammation outcome acute ischemic stroke (AIS) |
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License | Copyright © 2022 Zhou, Li, Xia, Xiang, Tang, Luo, Lin, Xia and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Christos Savopoulos, Aristotle University of Thessaloniki, Greece; Peter Kelly, University College Dublin, Ireland This article was submitted to Stroke, a section of the journal Frontiers in Neurology These authors have contributed equally to this work Edited by: Marios K. Georgakis, LMU Munich University Hospital, Germany |
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SubjectTerms | acute ischemic stroke (AIS) inflammation Neurology nomogram outcome systemic immune-inflammation index (SII) |
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Title | Predictive Value of the Systemic Immune Inflammation Index for Adverse Outcomes in Patients With Acute Ischemic Stroke |
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