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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

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

Ata de Conferência Internacional

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

Páginas: 75-79

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

Zagreb, CROATIA, OCT 15-16, 2018

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 4 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 5