Abstract 13636: Derivation and Validation of a Clinical Prediction Rule for Sleep Disordered Breathing in Patients With Cardiovascular Disease

Abstract

Introduction: There is a growing demand for polysomnography (PSG) indispensable for the diagnosis of sleep apnea which is associated with the development of cardiovascular disease. Hypothesis: We assessed the hypothesis that a prediction rule without PSG could identify obstructive sleep apnea (OSA) patients in which the continuous positive airway pressure (CPAP) treatment was recommended. Methods: Consecutive 326 cardiovascular disease patients simultaneously underwent a full-night PSG and a digital-installed built-in memory pulse-oximeter. A logistic regression-based prediction rule was developed in patients at university hospital (n=278) and validated in patients at community hospital (n=48). Results: In the derivation group, apnea-hypopnea index (AHI) was correlated with 3% oxygen desaturation index (ODI) (r=0.94, P<0.0001) and 223 patients were diagnosed as sleep disordered breathing (SDB) (AHI >=5). Four independent parameters were identified to distinguish between OSA (n=161) and central sleep apnea patients (n=62): pulse pressure, left atrial diameter, minimum oxygen saturation and B-type natriuretic peptide levels. The observed probability of OSA, by calculated score, was comparable between derivation and validation groups (Figure 1). The model-based rule was well calibrated (Hosmer-Lemeshow χ2=4.23) and demonstrated good discrimination in the derivation group. Discriminatory ability was also reasonable in the validation group and the difference between these groups was limited (Figure 2). Provided that cutoff levels of 3%ODI and 4 independent parameters were entirely satisfied, positive predictive value was 100% in both groups for the diagnosis of OSA necessary for CPAP treatment. Conclusions: A prediction rule for the type of sleep apnea without PSG can quantify the difference of pathophysiological mechanism in SDB patients. This index may be useful in detecting eligible candidates for CPAP in cardiovascular disease patients.