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Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis
BACKGROUND: Acute ischemic stroke (AIS), the most common type of stroke, is a major cause of morbidity and mortality worldwide. A growing number of studies have demonstrated that inflammation is a critical mechanism in AIS. Being an easily available and effective inflammatory marker, the systemic in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871574/ https://www.ncbi.nlm.nih.gov/pubmed/36703636 http://dx.doi.org/10.3389/fneur.2022.1049241 |
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author | Dang, Hui Mao, Wenjuan Wang, Shanshan Sha, Jing Lu, Mingjia Cong, Li Meng, Xuegang Li, Hongyan |
author_facet | Dang, Hui Mao, Wenjuan Wang, Shanshan Sha, Jing Lu, Mingjia Cong, Li Meng, Xuegang Li, Hongyan |
author_sort | Dang, Hui |
collection | PubMed |
description | BACKGROUND: Acute ischemic stroke (AIS), the most common type of stroke, is a major cause of morbidity and mortality worldwide. A growing number of studies have demonstrated that inflammation is a critical mechanism in AIS. Being an easily available and effective inflammatory marker, the systemic inflammation response index (SIRI) shows a high association with mortality in patients with cancer and intracerebral hemorrhage. In this study, we evaluated the potential prognostic role of SIRI in critically ill patients with AIS. METHODS: Clinic data were extracted from the Medical Information Mart data for the Intensive Care IV (MIMIC-IV) database. The optimal cutoff value of SIRI was determined by X-tile software. The primary outcome was the 90-day all-cause mortality, and the secondary outcomes were 30-day and 1-year all-cause mortality of patients with AIS. Cox proportional hazards regression analyses were used to assess the association between SIRI levels and all-cause mortality, and survival curves were estimated using the Kaplan–Meier method. Furthermore, a 1:1 propensity score matching (PSM) method was performed to balance the influence of potential confounding factors. RESULTS: A total of 2,043 patients were included in our study. X-tile software indicated that the optimal cutoff value of the SIRI for 90-day mortality was 4.57. After PSM, 444 pairs of score-matched patients were generated. Cox proportional hazard model showed that after adjusting for possible confounders, high SIRI level (≥4.57) was independently associated with the 90-day all-cause mortality in the cohort before PSM (HR = 1.56, 95% CI: 1.30–1.89, p < 0.001) and the PSM subset (HR = 1.47, 95% CI: 1.16–1.86, p = 0.001). The survival curves showed that patients with SIRI ≥4.57 had a significantly lower 90-day survival rate in the cohort before PSM (56.7 vs. 77.3%, p < 0.001) and the PSM subset (61.0 vs. 71.8%, p = 0.001). Consistently, AIS patients with high SIRI levels (≥4.57) presented a significantly high risk of 30-day and 1-year all-cause mortality before and after PSM. CONCLUSION: A higher SIRI (≥4.57) was associated with a higher risk of 90-day, 30-day, and 1-year mortality and was an independent risk factor of mortality in patients with acute ischemic stroke. |
format | Online Article Text |
id | pubmed-9871574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98715742023-01-25 Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis Dang, Hui Mao, Wenjuan Wang, Shanshan Sha, Jing Lu, Mingjia Cong, Li Meng, Xuegang Li, Hongyan Front Neurol Neurology BACKGROUND: Acute ischemic stroke (AIS), the most common type of stroke, is a major cause of morbidity and mortality worldwide. A growing number of studies have demonstrated that inflammation is a critical mechanism in AIS. Being an easily available and effective inflammatory marker, the systemic inflammation response index (SIRI) shows a high association with mortality in patients with cancer and intracerebral hemorrhage. In this study, we evaluated the potential prognostic role of SIRI in critically ill patients with AIS. METHODS: Clinic data were extracted from the Medical Information Mart data for the Intensive Care IV (MIMIC-IV) database. The optimal cutoff value of SIRI was determined by X-tile software. The primary outcome was the 90-day all-cause mortality, and the secondary outcomes were 30-day and 1-year all-cause mortality of patients with AIS. Cox proportional hazards regression analyses were used to assess the association between SIRI levels and all-cause mortality, and survival curves were estimated using the Kaplan–Meier method. Furthermore, a 1:1 propensity score matching (PSM) method was performed to balance the influence of potential confounding factors. RESULTS: A total of 2,043 patients were included in our study. X-tile software indicated that the optimal cutoff value of the SIRI for 90-day mortality was 4.57. After PSM, 444 pairs of score-matched patients were generated. Cox proportional hazard model showed that after adjusting for possible confounders, high SIRI level (≥4.57) was independently associated with the 90-day all-cause mortality in the cohort before PSM (HR = 1.56, 95% CI: 1.30–1.89, p < 0.001) and the PSM subset (HR = 1.47, 95% CI: 1.16–1.86, p = 0.001). The survival curves showed that patients with SIRI ≥4.57 had a significantly lower 90-day survival rate in the cohort before PSM (56.7 vs. 77.3%, p < 0.001) and the PSM subset (61.0 vs. 71.8%, p = 0.001). Consistently, AIS patients with high SIRI levels (≥4.57) presented a significantly high risk of 30-day and 1-year all-cause mortality before and after PSM. CONCLUSION: A higher SIRI (≥4.57) was associated with a higher risk of 90-day, 30-day, and 1-year mortality and was an independent risk factor of mortality in patients with acute ischemic stroke. Frontiers Media S.A. 2023-01-10 /pmc/articles/PMC9871574/ /pubmed/36703636 http://dx.doi.org/10.3389/fneur.2022.1049241 Text en Copyright © 2023 Dang, Mao, Wang, Sha, Lu, Cong, Meng and Li. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Neurology Dang, Hui Mao, Wenjuan Wang, Shanshan Sha, Jing Lu, Mingjia Cong, Li Meng, Xuegang Li, Hongyan Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title | Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title_full | Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title_fullStr | Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title_full_unstemmed | Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title_short | Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis |
title_sort | systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: a propensity score matching analysis |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871574/ https://www.ncbi.nlm.nih.gov/pubmed/36703636 http://dx.doi.org/10.3389/fneur.2022.1049241 |
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