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Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram

BACKGROUND: Currently no reliable tools are available for predicting the risk of central nervous system (CNS) infections in patients with intracerebral hemorrhage after undergoing ventriculostomy drainage. The current study sought to develop and validate a nomogram to identify high-risk factors of C...

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Autores principales: Zhang, Yanfeng, Zeng, Qingkao, Fang, Yuquan, Wang, Wei, Chen, Yunjin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135812/
https://www.ncbi.nlm.nih.gov/pubmed/35462608
http://dx.doi.org/10.1007/s43441-022-00403-2
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author Zhang, Yanfeng
Zeng, Qingkao
Fang, Yuquan
Wang, Wei
Chen, Yunjin
author_facet Zhang, Yanfeng
Zeng, Qingkao
Fang, Yuquan
Wang, Wei
Chen, Yunjin
author_sort Zhang, Yanfeng
collection PubMed
description BACKGROUND: Currently no reliable tools are available for predicting the risk of central nervous system (CNS) infections in patients with intracerebral hemorrhage after undergoing ventriculostomy drainage. The current study sought to develop and validate a nomogram to identify high-risk factors of CNS infection after ventriculomegaly drain placement for intracerebral hemorrhage. METHODS: A total of 185 patients with intracerebral hemorrhage who underwent ventriculoperitoneal drainage were enrolled to the current study. Patients were divided into a CNS infection group (20 patients) and a non-CNS infection group (165 patients). The baseline data from both groups was used to develop and evaluate a model for predicting the likelihood of developing CNS infection after ventriculoperitoneal drain placement for intracerebral hemorrhage. RESULTS: The finding showed that operative time, intraventricular drainage duration, postoperative temperature, white blood cell count in cerebrospinal fluid (CSF), neutrophils ratio in CSF, Red blood cell count in CSF, and glucose content in CSF were correlated with CNS infection. A nomogram for predicting the risk of CNS infection was constructed based on these variables. The c-index and the AUC of the ROC curve was 0.961, showing good discrimination. Clinical decision curve analysis indicated that the nomogram clinical application ranged between 1 and 100%. The clinical impact curve was generated to set with a threshold probability of 0.5. CONCLUSION: The nomogram reported in the current study can be used by clinicians to identify patients likely to have secondary CNS infections, so that clinicians can better treat these patients at earlier stages.
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spelling pubmed-91358122022-05-28 Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram Zhang, Yanfeng Zeng, Qingkao Fang, Yuquan Wang, Wei Chen, Yunjin Ther Innov Regul Sci Original Research BACKGROUND: Currently no reliable tools are available for predicting the risk of central nervous system (CNS) infections in patients with intracerebral hemorrhage after undergoing ventriculostomy drainage. The current study sought to develop and validate a nomogram to identify high-risk factors of CNS infection after ventriculomegaly drain placement for intracerebral hemorrhage. METHODS: A total of 185 patients with intracerebral hemorrhage who underwent ventriculoperitoneal drainage were enrolled to the current study. Patients were divided into a CNS infection group (20 patients) and a non-CNS infection group (165 patients). The baseline data from both groups was used to develop and evaluate a model for predicting the likelihood of developing CNS infection after ventriculoperitoneal drain placement for intracerebral hemorrhage. RESULTS: The finding showed that operative time, intraventricular drainage duration, postoperative temperature, white blood cell count in cerebrospinal fluid (CSF), neutrophils ratio in CSF, Red blood cell count in CSF, and glucose content in CSF were correlated with CNS infection. A nomogram for predicting the risk of CNS infection was constructed based on these variables. The c-index and the AUC of the ROC curve was 0.961, showing good discrimination. Clinical decision curve analysis indicated that the nomogram clinical application ranged between 1 and 100%. The clinical impact curve was generated to set with a threshold probability of 0.5. CONCLUSION: The nomogram reported in the current study can be used by clinicians to identify patients likely to have secondary CNS infections, so that clinicians can better treat these patients at earlier stages. Springer International Publishing 2022-04-24 2022 /pmc/articles/PMC9135812/ /pubmed/35462608 http://dx.doi.org/10.1007/s43441-022-00403-2 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, visithttp://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Original Research
Zhang, Yanfeng
Zeng, Qingkao
Fang, Yuquan
Wang, Wei
Chen, Yunjin
Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title_full Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title_fullStr Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title_full_unstemmed Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title_short Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram
title_sort risk prediction of central nervous system infection secondary to intraventricular drainage in patients with intracerebral hemorrhage: development and evaluation of a new predictive model nomogram
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135812/
https://www.ncbi.nlm.nih.gov/pubmed/35462608
http://dx.doi.org/10.1007/s43441-022-00403-2
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