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Correlating subjective and objective sleepiness: revisiting the association using survival analysis
R Nisha Aurora1, Brian Caffo, Ciprian Crainiceanu
1Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA.
The Epworth Sleepiness Scale (ESS) effectively predicts objective sleepiness, with a score of 13 or higher indicating increased risk. Survival analysis revealed a strong association between ESS scores and multiple sleep latency test results.
Area of Science:
- Sleep Medicine
- Clinical Neurophysiology
Background:
- The Epworth Sleepiness Scale (ESS) and multiple sleep latency test (MSLT) are standard measures for subjective and objective sleepiness.
- The relationship between ESS scores and objective sleep latency, and the optimal ESS threshold for identifying sleepiness, require further investigation.
Purpose of the Study:
- To examine the association between ESS scores and MSLT average sleep latency using survival analysis.
- To determine if patient factors influence this association.
- To evaluate the predictive utility of individual ESS questions and identify an optimal ESS threshold for objective sleepiness.
Main Methods:
- Cross-sectional study involving 675 patients referred for polysomnography and MSLT.
- Survival analysis techniques were employed to assess the association between ESS scores and MSLT sleep latency.
Main Results:
- A significant association was found between ESS scores and MSLT average sleep latency, with higher ESS scores correlating with shorter sleep latencies.
- An ESS score of 13 or greater optimally predicted an average MSLT sleep latency of less than 8 minutes.
- Most ESS questions were predictive of objective sleepiness, with some variations based on patient factors.
Conclusions:
- Survival analysis clearly demonstrates the association between ESS and MSLT average sleep latency.
- An ESS score of 13 or higher is an effective threshold for predicting objective sleepiness, surpassing previously used clinical cutoffs.
- The ESS is a simple, cost-effective tool for identifying individuals at risk of excessive daytime sleepiness.
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