Abstract
Study Objectives: The Epworth Sleepiness Scale (ESS) and multiple sleep latency test (MSLT) are the most commonly used measures of subjective and objective sleepiness, respectively. The strength of the association between these measures as well as the optimal ESS threshold that indicates objective sleepiness remains a topic of significant interest in the clinical and research arenas. The current investigation sought to: (a) examine the association between the ESS and the average sleep latency from the MSLT using the techniques of survival analysis; (b) determine whether specific patient factors influence the association; (c) examine the utility of each ESS question; and (d) identify the optimal ESS threshold that indicates objective sleepiness.
Design: Cross-sectional study.
Patients and Settings: Patients (N = 675) referred for polysomnography and MSLT.
Measurements and Results: Using techniques of survival analysis, a significant association was noted between the ESS score and the average sleep latency. The adjusted hazard ratios for sleep onset during the MSLT for the ESS quartiles were 1.00 (ESS < 9), 1.32 (ESS: 10-13), 1.85 (ESS: 14-17), and 2.53 (ESS >= 18), respectively. The association was independent of several patient factors and was distinct for the 4 naps. Furthermore, most of the ESS questions were individually predictive of the average sleep latency except the tendency to doze off when lying down to rest in the afternoon, which was only predictive in patients with less than a college education. Finally, an ESS score >= 13 optimally predicted an average sleep latency < 8 minutes.
Conclusions: In contrast to previous reports, the association between the ESS and the average sleep latency is clearly apparent when the data are analyzed by survival analysis, and most of the ESS questions are predictive of objective sleepiness. An ESS score >= 13 most effectively predicts objective sleepiness, which is higher than what has typically been used in clinical practice. Given the ease of administering the ESS, it represents a relatively simple and cost-effective method for identifying individuals at risk for daytime sleepiness.
