1. Can a Prediction Model Combining Self-Reported Symptoms, Sociodemographic and Clinical Features Serve as a Reliable First Screening Method for Sleep Apnea Syndrome in Patients With Stroke? 
Justine A. Aaronson, MSc, Janneke Nachtegaal, PhD, Tijs van Bezeij, MD, Erny Groet, MSc, Winni F. Hofman, PhD, Joost G. van den Aardweg, MD, PhD, Coen A.M. van Bennekom, MD, PhD 
Archives of Physical Medicine and Rehabilitation 
Volume 95, Issue 4, Pages (April 2014)
DOI: /j.apmr
Copyright © 2014 American Congress of Rehabilitation Medicine Terms and Conditions

2. Fig 1
ROC curve for the prediction model for a high likelihood of SAS. The prediction model includes the following variables: age, sex, BMI, apneas, and falling asleep during daytime. The area under the curve is .76 (95% CI, .71–.81).
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2014 American Congress of Rehabilitation Medicine Terms and Conditions

3. Fig 2
Sensitivity and specificity for selected cutoff points of the predicted probability of a high likelihood of SAS.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2014 American Congress of Rehabilitation Medicine Terms and Conditions