A screening tool for obstructive sleep apnea in cerebrovascular patients

Publication date: Available online 20 February 2016
Source:Sleep Medicine
Author(s): Irene L. Katzan, Nicolas R. Thompson, Ken Uchino, Nancy Foldvary-Schaefer
BackgroundA majority of stroke patients suffer from Obstructive Sleep Apnea (OSA), which can go unrecognized as current OSA screens do not perform well in stroke patients. The objective of this study is to modify existing OSA screening tools for use in stroke patients.MethodsThe cohort study consisted of patients who completed the validated OSA STOP screen and underwent polysomnography within 1 year. Six prediction models were created and sensitivity and specificity of various cutpoints were calculated.ResultsThere were 208 patients with mean age of 55.4 years; 61.0% had sleep apnea. Models with the highest c-statistics included the STOP items plus BMI, age, and sex (STOP-BAG). Addition of neck circumference and other variables did not significantly improve the models. The STOP-BAG2 model, using continuous variables, had a greater sensitivity of 0.94 (95% 0.89-0.98) and specificity 0.60 (95% CI 0.49 – 0.71) compared to the STOP-BAG model, which used dichotomous variables, and had a sensitivity of 0.91 (95% CI 0.85-0.96) and specificity of 0.48 (95% CI 0.37 – 0.60).ConclusionsThe STOP-BAG screen can be used to identify cerebrovascular patients at increased risk for OSA. The use of continuous variables (STOP-BAG2) is preferable if automated score calculation is available. It can improve the efficiency of evaluation for OSA and lead to improved outcomes of patients with cerebrovascular disease.



from #SleepMedicine via xlomafota13 on Inoreader http://ift.tt/1RdSb3C
via IFTTT