Vidya T Raman1,2, Mark Splaingard3, Dmitry Tumin1, Julie Rice1, Kris R Jatana4, Joseph D Tobias1,2. 1. Department of Anesthesiology & Pain Medicine, Nationwide Children's Hospital, Columbus, OH, USA. 2. Department of Anesthesiology & Pain Medicine, The Ohio State University, Columbus, OH, USA. 3. Department of Pediatrics and Division of Pediatric Pulmonology, Nationwide Children's Hospital, Columbus, OH, USA. 4. Department of Pediatric Otolaryngology, Nationwide Children's Hospital, Columbus, OH, USA.
Abstract
BACKGROUND: Polysomnography (PSG) remains the gold standard for diagnosing obstructive sleep apnea (OSA) and sleep-disordered breathing in children. Yet, simple screening tools are needed as it is not feasible to perform PSG in all patients with possible OSA. AIM: The study adapted questions from the Pediatric Sleep Questionnaire-Sleep-Related Breathing Disorder (SRBD) Questionnaire to develop a predictive scale for OSA identified on PSG. We also tested whether adding anthropometric measurements (body mass index and neck circumference) improved prediction of OSA. METHODS: After IRB approval, OSA questionnaires and anthropometric measurements were collected on 948 consecutive patients scheduled for PSG, aged 4 months to 24.5 years (median = 8.5 years). The sample was reduced to 636 patients in the age range (6-18 years old) where normative values for neck circumference are defined. OSA was characterized using the obstructive apnea-hypopnea index (AHI). After identifying questions related to OSA in univariate logistic regression, multivariable models were fitted to select questions for a short scale, and points for exceeding body mass or neck circumference cutoffs were added to assess improvement in predictive value. RESULTS: A long scale of 16 questionnaire items was constructed using univariate models, while six items were selected for the short scale by multivariable regression. The short scale was associated with greater odds of moderate/severe OSA (OR = 1.964; 95% CI = 1.620, 2.381; P < 0.001) and attained good predictive value (area under receiver operating characteristics curve [AUC] = 0.74), which was not significantly improved by addition of BMI and neck circumference data (AUC = 0.75). CONCLUSIONS: We developed a six-question scale with good predictive utility for OSA. These findings may contribute to developing a preoperative clinical tool to help clinicians identify children with OSA for determining risk stratification and postoperative disposition.
BACKGROUND: Polysomnography (PSG) remains the gold standard for diagnosing obstructive sleep apnea (OSA) and sleep-disordered breathing in children. Yet, simple screening tools are needed as it is not feasible to perform PSG in all patients with possible OSA. AIM: The study adapted questions from the Pediatric Sleep Questionnaire-Sleep-Related Breathing Disorder (SRBD) Questionnaire to develop a predictive scale for OSA identified on PSG. We also tested whether adding anthropometric measurements (body mass index and neck circumference) improved prediction of OSA. METHODS: After IRB approval, OSA questionnaires and anthropometric measurements were collected on 948 consecutive patients scheduled for PSG, aged 4 months to 24.5 years (median = 8.5 years). The sample was reduced to 636 patients in the age range (6-18 years old) where normative values for neck circumference are defined. OSA was characterized using the obstructive apnea-hypopnea index (AHI). After identifying questions related to OSA in univariate logistic regression, multivariable models were fitted to select questions for a short scale, and points for exceeding body mass or neck circumference cutoffs were added to assess improvement in predictive value. RESULTS: A long scale of 16 questionnaire items was constructed using univariate models, while six items were selected for the short scale by multivariable regression. The short scale was associated with greater odds of moderate/severe OSA (OR = 1.964; 95% CI = 1.620, 2.381; P < 0.001) and attained good predictive value (area under receiver operating characteristics curve [AUC] = 0.74), which was not significantly improved by addition of BMI and neck circumference data (AUC = 0.75). CONCLUSIONS: We developed a six-question scale with good predictive utility for OSA. These findings may contribute to developing a preoperative clinical tool to help clinicians identify children with OSA for determining risk stratification and postoperative disposition.
Authors: Mohammed Hakim; Shabana Zainab Shafy; Rebecca Miller; Kris R Jatana; Mark Splaingard; Dmitry Tumin; Joseph D Tobias; Vidya T Raman Journal: Med Devices (Auckl) Date: 2018-12-12