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Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis

BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease involving the neuromuscular junction. Myasthenic crisis (MC), which is characterized by respiratory failure and the requirement of mechanical ventilation in patients with MG, is still a medical emergency despite the decrease in mortality wi...

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Autores principales: Hsu, Che-Wei, Chen, Nai-Ching, Huang, Wei-Chin, Lin, Hui-Chen, Tsai, Wan-Chen, Huang, Chih-Cheng, Cheng, Ben-Chung, Tsai, Nai-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493047/
https://www.ncbi.nlm.nih.gov/pubmed/34615473
http://dx.doi.org/10.1186/s12883-021-02412-4
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author Hsu, Che-Wei
Chen, Nai-Ching
Huang, Wei-Chin
Lin, Hui-Chen
Tsai, Wan-Chen
Huang, Chih-Cheng
Cheng, Ben-Chung
Tsai, Nai-Wen
author_facet Hsu, Che-Wei
Chen, Nai-Ching
Huang, Wei-Chin
Lin, Hui-Chen
Tsai, Wan-Chen
Huang, Chih-Cheng
Cheng, Ben-Chung
Tsai, Nai-Wen
author_sort Hsu, Che-Wei
collection PubMed
description BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease involving the neuromuscular junction. Myasthenic crisis (MC), which is characterized by respiratory failure and the requirement of mechanical ventilation in patients with MG, is still a medical emergency despite the decrease in mortality with the advances in acute management. Hemogram is a cost-effective test for evaluating hematological complications and systemic inflammation, and hemogram data have been used to predict various clinical outcomes of several diseases. The relationship between hemogram and MG has been discussed, but the role of hemogram data in predicting the prognosis of MC patients has not been established. METHODS: To identify whether hemogram data can predict in-hospital mortality in patients with MC, we retrospectively investigated 188 myasthenic crisis events from the Chang Gung Research Database between April 2001 and March 2019. Demographic and clinical characteristics were collected, as well as hemogram data before intubation and extubation. The endpoints were mortality during mechanical ventilation and mortality after extubation. RESULTS: The overall in-hospital mortality rate was 22%. Multivariate logistic regression analysis for predicting mortality during mechanical ventilation showed that old age at MC onset (OR = 1.039, p = 0.022), moderate-to-severe anemia (OR = 5.851, p = 0.001), and extreme leukocytosis (OR = 5.659, p = 0.022) before intubation were strong predictors of mortality, while acute management with plasma exchange or double-filtration plasmapheresis (PE/DFPP) significantly decreased mortality (OR = 0.236, p = 0.012). For predicting mortality after extubation, moderate-to-severe anemia before extubation (OR = 8.452, p = 0.017) and non-treated with disease-modifying therapy before MC (OR = 5.459, p = 0.031) were crucial predictive factors. CONCLUSION: This study demonstrated that both old age at MC onset and moderate-to-severe anemia are important predictors of in-hospital mortality in patients with MC, and extreme leukocytosis is another crucial predictor of mortality during mechanical ventilation. The suggested mechanism is that anemia-induced hypoxia may enhance the release of proinflammatory cytokines, exacerbate systemic inflammation, and lead to multiple organ dysfunction syndrome and, finally, mortality.
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spelling pubmed-84930472021-10-06 Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis Hsu, Che-Wei Chen, Nai-Ching Huang, Wei-Chin Lin, Hui-Chen Tsai, Wan-Chen Huang, Chih-Cheng Cheng, Ben-Chung Tsai, Nai-Wen BMC Neurol Research BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease involving the neuromuscular junction. Myasthenic crisis (MC), which is characterized by respiratory failure and the requirement of mechanical ventilation in patients with MG, is still a medical emergency despite the decrease in mortality with the advances in acute management. Hemogram is a cost-effective test for evaluating hematological complications and systemic inflammation, and hemogram data have been used to predict various clinical outcomes of several diseases. The relationship between hemogram and MG has been discussed, but the role of hemogram data in predicting the prognosis of MC patients has not been established. METHODS: To identify whether hemogram data can predict in-hospital mortality in patients with MC, we retrospectively investigated 188 myasthenic crisis events from the Chang Gung Research Database between April 2001 and March 2019. Demographic and clinical characteristics were collected, as well as hemogram data before intubation and extubation. The endpoints were mortality during mechanical ventilation and mortality after extubation. RESULTS: The overall in-hospital mortality rate was 22%. Multivariate logistic regression analysis for predicting mortality during mechanical ventilation showed that old age at MC onset (OR = 1.039, p = 0.022), moderate-to-severe anemia (OR = 5.851, p = 0.001), and extreme leukocytosis (OR = 5.659, p = 0.022) before intubation were strong predictors of mortality, while acute management with plasma exchange or double-filtration plasmapheresis (PE/DFPP) significantly decreased mortality (OR = 0.236, p = 0.012). For predicting mortality after extubation, moderate-to-severe anemia before extubation (OR = 8.452, p = 0.017) and non-treated with disease-modifying therapy before MC (OR = 5.459, p = 0.031) were crucial predictive factors. CONCLUSION: This study demonstrated that both old age at MC onset and moderate-to-severe anemia are important predictors of in-hospital mortality in patients with MC, and extreme leukocytosis is another crucial predictor of mortality during mechanical ventilation. The suggested mechanism is that anemia-induced hypoxia may enhance the release of proinflammatory cytokines, exacerbate systemic inflammation, and lead to multiple organ dysfunction syndrome and, finally, mortality. BioMed Central 2021-10-06 /pmc/articles/PMC8493047/ /pubmed/34615473 http://dx.doi.org/10.1186/s12883-021-02412-4 Text en © The Author(s) 2021 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
Hsu, Che-Wei
Chen, Nai-Ching
Huang, Wei-Chin
Lin, Hui-Chen
Tsai, Wan-Chen
Huang, Chih-Cheng
Cheng, Ben-Chung
Tsai, Nai-Wen
Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title_full Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title_fullStr Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title_full_unstemmed Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title_short Hemogram parameters can predict in-hospital mortality of patients with Myasthenic crisis
title_sort hemogram parameters can predict in-hospital mortality of patients with myasthenic crisis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493047/
https://www.ncbi.nlm.nih.gov/pubmed/34615473
http://dx.doi.org/10.1186/s12883-021-02412-4
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