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ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage

PURPOSE: We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH). METHOD: We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between...

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Autores principales: Yan, Jing, Zhai, Weiqi, Li, Zhaoxia, Ding, LingLing, You, Jia, Zeng, Jiayi, Yang, Xin, Wang, Chunjuan, Meng, Xia, Jiang, Yong, Huang, Xiaodi, Wang, Shouyan, Wang, Yilong, Li, Zixiao, Zhu, Shanfeng, Wang, Yongjun, Zhao, Xingquan, Feng, Jianfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066782/
https://www.ncbi.nlm.nih.gov/pubmed/35509104
http://dx.doi.org/10.1186/s12967-022-03389-5
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author Yan, Jing
Zhai, Weiqi
Li, Zhaoxia
Ding, LingLing
You, Jia
Zeng, Jiayi
Yang, Xin
Wang, Chunjuan
Meng, Xia
Jiang, Yong
Huang, Xiaodi
Wang, Shouyan
Wang, Yilong
Li, Zixiao
Zhu, Shanfeng
Wang, Yongjun
Zhao, Xingquan
Feng, Jianfeng
author_facet Yan, Jing
Zhai, Weiqi
Li, Zhaoxia
Ding, LingLing
You, Jia
Zeng, Jiayi
Yang, Xin
Wang, Chunjuan
Meng, Xia
Jiang, Yong
Huang, Xiaodi
Wang, Shouyan
Wang, Yilong
Li, Zixiao
Zhu, Shanfeng
Wang, Yongjun
Zhao, Xingquan
Feng, Jianfeng
author_sort Yan, Jing
collection PubMed
description PURPOSE: We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH). METHOD: We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups – 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC). RESULTS: The incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739–0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694–0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762–0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774–0.794]. CONCLUSION: ICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03389-5.
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spelling pubmed-90667822022-05-04 ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage Yan, Jing Zhai, Weiqi Li, Zhaoxia Ding, LingLing You, Jia Zeng, Jiayi Yang, Xin Wang, Chunjuan Meng, Xia Jiang, Yong Huang, Xiaodi Wang, Shouyan Wang, Yilong Li, Zixiao Zhu, Shanfeng Wang, Yongjun Zhao, Xingquan Feng, Jianfeng J Transl Med Research PURPOSE: We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH). METHOD: We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups – 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC). RESULTS: The incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739–0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694–0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762–0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774–0.794]. CONCLUSION: ICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03389-5. BioMed Central 2022-05-04 /pmc/articles/PMC9066782/ /pubmed/35509104 http://dx.doi.org/10.1186/s12967-022-03389-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yan, Jing
Zhai, Weiqi
Li, Zhaoxia
Ding, LingLing
You, Jia
Zeng, Jiayi
Yang, Xin
Wang, Chunjuan
Meng, Xia
Jiang, Yong
Huang, Xiaodi
Wang, Shouyan
Wang, Yilong
Li, Zixiao
Zhu, Shanfeng
Wang, Yongjun
Zhao, Xingquan
Feng, Jianfeng
ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title_full ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title_fullStr ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title_full_unstemmed ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title_short ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
title_sort ich-lr2s2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066782/
https://www.ncbi.nlm.nih.gov/pubmed/35509104
http://dx.doi.org/10.1186/s12967-022-03389-5
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