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The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard
BACKGROUND: The Nijmegen questionnaire is one of the most common tools for diagnosing hyperventilation syndrome (HVS). However, there is no precise cut-off score for differentiating patients with HVS from those without HVS. This study was conducted to evaluate the accuracy of Nijmegen questionnaire...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Salvia Medical Sciences Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397298/ https://www.ncbi.nlm.nih.gov/pubmed/34466581 http://dx.doi.org/10.31661/gmj.v9i0.1738 |
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author | Azizmohammad Looha, Mehdi Masaebi, Fatemeh Abedi, Mohsen Mohseni, Navid Fakharian, Atefeh |
author_facet | Azizmohammad Looha, Mehdi Masaebi, Fatemeh Abedi, Mohsen Mohseni, Navid Fakharian, Atefeh |
author_sort | Azizmohammad Looha, Mehdi |
collection | PubMed |
description | BACKGROUND: The Nijmegen questionnaire is one of the most common tools for diagnosing hyperventilation syndrome (HVS). However, there is no precise cut-off score for differentiating patients with HVS from those without HVS. This study was conducted to evaluate the accuracy of Nijmegen questionnaire for detecting patients with HVS and to provide the best cut-off score for differentiating patients with HVS from normal individuals using a Bayesian model in the absence of a gold standard. MATERIALS AND METHODS: A total of 490 students from a rehabilitation center in Tehran, Iran, were asked to participate in this case study of HVS from January to August 2018. RESULTS: A total of 215 students (40% male and 60% female) completed the Nijmegen questionnaire. The area under the receiver operating characteristic curve (AUC) was 0.93 (male: 0.95; female: 94) for all of the cut-off scores. The optimal cut-off score of ≥20 could predict HVS with sensitivity of 0.91 (male: 0.99; female: 91) and specificity of 0.92 (male: 96; female: 89). CONCLUSION: Accurate differentiation of HVS patients from individuals without HVS can be accomplished by estimating the cut-off score of Nijmegen questionnaire based on a non-parametric Bayesian model. |
format | Online Article Text |
id | pubmed-8397298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Salvia Medical Sciences Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-83972982021-08-30 The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard Azizmohammad Looha, Mehdi Masaebi, Fatemeh Abedi, Mohsen Mohseni, Navid Fakharian, Atefeh Galen Med J Original Article BACKGROUND: The Nijmegen questionnaire is one of the most common tools for diagnosing hyperventilation syndrome (HVS). However, there is no precise cut-off score for differentiating patients with HVS from those without HVS. This study was conducted to evaluate the accuracy of Nijmegen questionnaire for detecting patients with HVS and to provide the best cut-off score for differentiating patients with HVS from normal individuals using a Bayesian model in the absence of a gold standard. MATERIALS AND METHODS: A total of 490 students from a rehabilitation center in Tehran, Iran, were asked to participate in this case study of HVS from January to August 2018. RESULTS: A total of 215 students (40% male and 60% female) completed the Nijmegen questionnaire. The area under the receiver operating characteristic curve (AUC) was 0.93 (male: 0.95; female: 94) for all of the cut-off scores. The optimal cut-off score of ≥20 could predict HVS with sensitivity of 0.91 (male: 0.99; female: 91) and specificity of 0.92 (male: 96; female: 89). CONCLUSION: Accurate differentiation of HVS patients from individuals without HVS can be accomplished by estimating the cut-off score of Nijmegen questionnaire based on a non-parametric Bayesian model. Salvia Medical Sciences Ltd 2020-06-24 /pmc/articles/PMC8397298/ /pubmed/34466581 http://dx.doi.org/10.31661/gmj.v9i0.1738 Text en Copyright© 2020, Galen Medical Journal. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ) |
spellingShingle | Original Article Azizmohammad Looha, Mehdi Masaebi, Fatemeh Abedi, Mohsen Mohseni, Navid Fakharian, Atefeh The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title | The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title_full | The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title_fullStr | The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title_full_unstemmed | The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title_short | The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard |
title_sort | optimal cut-off score of the nijmegen questionnaire for diagnosing hyperventilation syndrome using a bayesian model in the absence of a gold standard |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397298/ https://www.ncbi.nlm.nih.gov/pubmed/34466581 http://dx.doi.org/10.31661/gmj.v9i0.1738 |
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