The Optimal Cut-off Score of the Nijmegen Questionnaire for Diagnosing Hyperventilation Syndrome Using a Bayesian Model in the Absence of a Gold Standard


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. 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. 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 more than 20 could predict HVS with sensitivity of 0.91 (male : 0.99; female : 91) and specificity of 0.92 (male : 96; female : 89).

Galen Medical Journal
Navid Mohseni
Navid Mohseni

My research interests include data science, artificial intelligence, machine learning, and data visualization.