Prevalence and characterization of exercise oscillatory ventilation in apparently healthy individuals at variable risk for cardiovascular disease: A subanalysis of the EURO-EX trial. (29th August 2020)

• Record Type: Journal Article
• Authors: Guazzi, Marco; Arena, Ross; Pellegrino, Marta; Bandera, Francesco; Generati, Greta; Labate, Valentina; Alfonzetti, Eleonora; Villani, Simona; Gaeta, Maddalena M; Halle, Martin; Haslbauer, Robert; Phillips, Shane A; Cahalin, Lawrence P
• Is Part Of: European journal of preventive cardiology. Volume 23:Number 3(2016)
• Page Start: 328
• Page End: 334
• Publication Date: 2020-08-29
• Subjects: Cardiopulmonary exercise testing -- aerobic capacity -- oscillatory ventilation -- clinical assessment; Cardiovascular system -- Diseases -- Prevention -- Periodicals; Cardiac patients -- Rehabilitation -- Periodicals; 616.12
• DOI: 10.1177/2047487315580445
• Languages: English
• ISSNs: 2047-4873

Abstract

Abstract: Introduction: There has been a greater appreciation of several variables obtained by cardiopulmonary exercise testing (CPX). Exercise oscillatory ventilation (EOV) is a CPX pattern that has gained recognition as an ominous marker of poor prognosis in cardiac patients. The purpose of the present study is to characterize whether such an abnormal ventilatory pattern may also be detected in apparently healthy subjects and determine its clinical significance. Methods: The study involved 510 subjects (mean age 60 ± 14 years; 49% male) with a broad cardiovascular (CV) risk factor profile who underwent CPX. Results: The population was divided into two groups according to the presence (17%) or absence of EOV. Subjects with EOV were significantly older and a higher percentage was female. Risk factor profile and medication use was significantly different between subgroups, indicating subjects with EOV had a worse CV risk factor profile and were prescribed CV-focused preventive medications at a significantly higher frequency. Subjects with EOV had comparatively poorer CPX performance and gas exchange phenotype. Multivariate binary logistic regression analysis found being female was the strongest predictor of EOV (odds ratio: 2.77, 95% confidence interval (CI): 1.66-4.61, p < 0.001). A diagnosis of diabetes (odds ratio: 2.40, 95% CI: 1.34–4.15.2, p < 0.001) added significant value for predicting EOV and was retained in the regression. The likelihood for EOV for subjects who were female and diagnosed with diabetes was 3.71 (95% CI 1.88–7.30, p < 0.001). Conclusions: This is the first study to examine EOV prevalence and characterization in apparently healthy persons with results supporting an in-depth definition of abnormal exercise phenotypes.