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CC BY-NC-ND 4.0 · Sleep Sci 2023; 16(04): e446-e453
DOI: 10.1055/s-0043-1776770
Original Article

Clinical Application of the Multicomponent Grading System for Sleep Apnea Classification and Incident Cardiovascular Mortality

Jorge Jorquera
1   Center for Respiratory Diseases, Las Condes Clinic, Faculty of Medicine, Finis Terrae University, Santiago, Chile
,
Jorge Dreyse
1   Center for Respiratory Diseases, Las Condes Clinic, Faculty of Medicine, Finis Terrae University, Santiago, Chile
,
Constanza Salas
1   Center for Respiratory Diseases, Las Condes Clinic, Faculty of Medicine, Finis Terrae University, Santiago, Chile
,
Francisca Letelier
1   Center for Respiratory Diseases, Las Condes Clinic, Faculty of Medicine, Finis Terrae University, Santiago, Chile
,
Bunio Weissglas
2   Department of Clinical Biochemistry and Immunology, Facultad de Farmacia, Universidad de Concepción, Bío-Bío, Chile
,
Javiera Del-Río
2   Department of Clinical Biochemistry and Immunology, Facultad de Farmacia, Universidad de Concepción, Bío-Bío, Chile
,
Mario Henríquez-Beltrán 
3   Núcleo de Investigación en Ciencias de la Salud, Universidad Adventista de Chile, Chillán, Chile
4   Escuela de Kinesiología, Facultad de Salud, Universidad Santo Tomas, Chile
5   Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, Biomedical Research Institute of Lleida (IRBLleida), Lleida, Spain
,
Gonzalo Labarca 
2   Department of Clinical Biochemistry and Immunology, Facultad de Farmacia, Universidad de Concepción, Bío-Bío, Chile
4   Escuela de Kinesiología, Facultad de Salud, Universidad Santo Tomas, Chile
,
Jorge Jorquera-Díaz
5   Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, Biomedical Research Institute of Lleida (IRBLleida), Lleida, Spain
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Abstract

Objective To evaluate the clinical utility of the Baveno classification in predicting incident cardiovascular mortality after five years of follow-up in a clinic-based cohort of patients with obstructive sleep apnea (OSA).

Materials and Methods We evaluated the reproducibility of the Baveno classification using data from the Santiago Obstructive Sleep Apnea (SantOSA) study. The groups were labeled Baveno A (minor symptoms and comorbidities), B (severe symptoms and minor comorbidities), C (minor symptoms and severe comorbidities), and D (severe symptoms and comorbidities). Within-group comparisons were performed using analysis of variance (ANOVA) and post hoc tests. The associations between groups and incident cardiovascular mortality were determined through the Mantel-Cox and Cox proportional hazard ratios (HRs) adjusted by covariables.

Results A total of 1,300 OSA patients were included (Baveno A: 27.7%; B: 28%; C: 16.8%; and D: 27.5%). The follow-up was of 5.4 years. Compared to Baveno A, the fully-adjusted risk of cardiovascular mortality with Baveno B presented an HR of 1.38 (95% confidence interval [95%CI]: 0.14–13.5; p = 0.78); with Baveno C, it was of 1.71 (95%CI: 0.18–16.2; p = 0.63); and, with Baveno D, of 1.04 (95%CI: 0.12–9.2; p = 0.98). We found no interactions involving Baveno group, sex and OSA severity.

Discussion Among OSA patients, the Baveno classification can describe different subgroups. However, its utility in identifying incident cardiovascular mortality is unclear. Long-term follow-up studies and the inclusion of demographic variables in the classification could improve its ability to detect a high-risk phenotype associated with cardiovascular mortality.

Conclusion The Baveno classification serves as a valuable method for categorizing varying groups of patients afflicted with OSA. Nevertheless, its precision in identifying occurrence of cardiovascular mortality is still unclear.

Keywords

obstructive sleep apnea - cardiovascular - hypoxia - latino - precision medicine

Supplementary Material



Publikationsverlauf

Eingereicht: 14. Juli 2022

Angenommen: 14. Februar 2023

Artikel online veröffentlicht:
22. November 2023

© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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