Phenotyping Obstructive Sleep Apnea Patients: A First Approach to Cluster Visualization

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Ferreira Santos, D (Author) FMUP; Pedro Pereira Rodrigues (Author) FMUP

Conference proceedings International

Title: DECISION SUPPORT SYSTEMS AND EDUCATION: HELP AND SUPPORT IN HEALTHCARE

Pages: 75-79

Special Topic Conference of the European-Fedeeration-for-Medical-Informatics (EFMI STC)

Zagreb, CROATIA, OCT 15-16, 2018

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00P-SJD

DOI: 10.3233/978-1-61499-921-8-75

Abstract (EN): The varied phenotypes of obstructive sleep apnea (OSA) poses critical challenges, resulting in missed or delayed diagnosis. In this work, we applied k-modes, aiming to identify groups of OSA patients, based on demographic, physical examination, clinical history, and comorbidities characterization variables (n=41) collected from 318 patients. Missing values were imputed with k-nearest neighbours (k-NN) and chi-square test was held. Thirteen variables were inserted in cluster analysis, resulting in three clusters. Cluster 1 were middle-aged men, while Cluster 3 were the oldest men and Cluster 2 mainly middle-aged women. Cluster 3 weighted the most, whereas Cluster 1 weighted the least. The same effect was described in increased neck circumference. The percentages of variables driving sleepiness, congestive heart failure, arrhythmias and pulmonary hypertension were very low (<20%) and OSA severity was more common in mild level. Our results suggest that it is possible to phenotype OSA patients in an objective way, as also, different (although not considered innovative) visualizations improve the recognition of this common sleep pathology.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5