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Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia
PURPOSE: Difficult mask ventilation (DMV) is a potentially life-threatening situation that can arise during anesthesia. However, most clinical predictors of DMV are based on European and US populations. On the other hand, most predictive models consist of multiple factors and complicated assessments...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590653/ https://www.ncbi.nlm.nih.gov/pubmed/33550561 http://dx.doi.org/10.1007/s11325-021-02310-6 |
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author | Wang, Jiayi Li, Jingjie Zhao, Pengcheng Pu, Xuan Hu, Rong Jiang, Hong |
author_facet | Wang, Jiayi Li, Jingjie Zhao, Pengcheng Pu, Xuan Hu, Rong Jiang, Hong |
author_sort | Wang, Jiayi |
collection | PubMed |
description | PURPOSE: Difficult mask ventilation (DMV) is a potentially life-threatening situation that can arise during anesthesia. However, most clinical predictors of DMV are based on European and US populations. On the other hand, most predictive models consist of multiple factors and complicated assessments. Since obstructive sleep apnea (OSA) is among the most important risk factors associated with DMV, the apnea-hypopnea index (AHI) may play an important role in determining patient risk.The purpose of this study was to investigate the relationship between DMV and AHI, and to determine preoperative risk factors for DMV in Chinese patients. METHODS: A prospective cohort trial enrolled patients scheduled for elective surgery. After obtaining informed consent, patient demographic information was collected, and patients were tested with pre-operative polysomnography. The anesthesiologist who managed the airway graded the mask ventilation. The difficult mask ventilation was defined as the mask ventilation provided by an unassisted anesthesiologist without oral airway or other adjuvant. A logistic regression model was used to analyze the association between AHI and DMV. RESULTS: A total of 159 patients were analyzed. For both primary and secondary outcomes, the unadjusted and adjusted odds ratio for DMV showed significant increases by 5 AHI units. AHI, age, and the Mallampati classification were found to be independent predictive factors for DMV. CONCLUSIONS: AHI is associated with DMV as a novel independent risk factor in Chinese patients. Along with age and Mallampati classification, AHI should be included in establishing a superior predictive strategy for DMV screening. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-DDD-17013076 |
format | Online Article Text |
id | pubmed-8590653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-85906532021-11-15 Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia Wang, Jiayi Li, Jingjie Zhao, Pengcheng Pu, Xuan Hu, Rong Jiang, Hong Sleep Breath Sleep Breathing Physiology and Disorders • Original Article PURPOSE: Difficult mask ventilation (DMV) is a potentially life-threatening situation that can arise during anesthesia. However, most clinical predictors of DMV are based on European and US populations. On the other hand, most predictive models consist of multiple factors and complicated assessments. Since obstructive sleep apnea (OSA) is among the most important risk factors associated with DMV, the apnea-hypopnea index (AHI) may play an important role in determining patient risk.The purpose of this study was to investigate the relationship between DMV and AHI, and to determine preoperative risk factors for DMV in Chinese patients. METHODS: A prospective cohort trial enrolled patients scheduled for elective surgery. After obtaining informed consent, patient demographic information was collected, and patients were tested with pre-operative polysomnography. The anesthesiologist who managed the airway graded the mask ventilation. The difficult mask ventilation was defined as the mask ventilation provided by an unassisted anesthesiologist without oral airway or other adjuvant. A logistic regression model was used to analyze the association between AHI and DMV. RESULTS: A total of 159 patients were analyzed. For both primary and secondary outcomes, the unadjusted and adjusted odds ratio for DMV showed significant increases by 5 AHI units. AHI, age, and the Mallampati classification were found to be independent predictive factors for DMV. CONCLUSIONS: AHI is associated with DMV as a novel independent risk factor in Chinese patients. Along with age and Mallampati classification, AHI should be included in establishing a superior predictive strategy for DMV screening. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-DDD-17013076 Springer International Publishing 2021-02-06 2021 /pmc/articles/PMC8590653/ /pubmed/33550561 http://dx.doi.org/10.1007/s11325-021-02310-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Sleep Breathing Physiology and Disorders • Original Article Wang, Jiayi Li, Jingjie Zhao, Pengcheng Pu, Xuan Hu, Rong Jiang, Hong Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title | Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title_full | Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title_fullStr | Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title_full_unstemmed | Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title_short | Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia |
title_sort | utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the chinese population under general anesthesia |
topic | Sleep Breathing Physiology and Disorders • Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590653/ https://www.ncbi.nlm.nih.gov/pubmed/33550561 http://dx.doi.org/10.1007/s11325-021-02310-6 |
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