INTRODUCTION: Obstructive sleep apnea (OSA) is a disorder with high prevalence in primary care. However, little research exists on screening for OSA in primary care samples. METHODS: One hundred family medicine patients completed standardized symptom and demographic questionnaires and a structured clinical interview for sleep disorders. Two-step logistic regression was performed to determine the independent predictive value of insomnia for clinical identification of OSA. Additional t tests were computed to examine age and sex patterns of insomnia. RESULTS: A model including body mass index and daytime sleepiness predicted OSA status (χ(2) = 18.63; P < .001) and explained 27% of the variance in OSA clinical diagnosis. Addition of insomnia scores to the model significantly improved predictive utility (χ(2) = 25.79; P < .001) and explained 36% of the variance in OSA. Insomnia scores were higher for women compared with men (P = .033) and women with OSA compared with women without OSA (P = .007). CONCLUSIONS: Inquiry regarding insomnia may improve clinical identification of OSA when screening for OSA in primary care. This finding possibly is unique to the evaluation of OSA in a primary care versus sleep laboratory sample. The predictive utility of insomnia may be specific to women.
INTRODUCTION:Obstructive sleep apnea (OSA) is a disorder with high prevalence in primary care. However, little research exists on screening for OSA in primary care samples. METHODS: One hundred family medicine patients completed standardized symptom and demographic questionnaires and a structured clinical interview for sleep disorders. Two-step logistic regression was performed to determine the independent predictive value of insomnia for clinical identification of OSA. Additional t tests were computed to examine age and sex patterns of insomnia. RESULTS: A model including body mass index and daytime sleepiness predicted OSA status (χ(2) = 18.63; P < .001) and explained 27% of the variance in OSA clinical diagnosis. Addition of insomnia scores to the model significantly improved predictive utility (χ(2) = 25.79; P < .001) and explained 36% of the variance in OSA. Insomnia scores were higher for women compared with men (P = .033) and women with OSA compared with women without OSA (P = .007). CONCLUSIONS: Inquiry regarding insomnia may improve clinical identification of OSA when screening for OSA in primary care. This finding possibly is unique to the evaluation of OSA in a primary care versus sleep laboratory sample. The predictive utility of insomnia may be specific to women.
Authors: Megan R Crawford; Diana A Chirinos; Toni Iurcotta; Jack D Edinger; James K Wyatt; Rachel Manber; Jason C Ong Journal: J Clin Sleep Med Date: 2017-07-15 Impact factor: 4.062