Bilgay Izci Balserak1, Bingqian Zhu2, Michael A Grandner3, Nicholas Jackson4, Grace W Pien5. 1. College of Nursing, University of Illinois at Chicago, Chicago, IL, USA. 2. School of Nursing, Shanghai Jiao Tong University, 227 S Chongqing Rd, Shanghai, 200025, China. zhubq@shsmu.edu.cn. 3. Department of Psychiatry, University of Arizona College of Medicine, Tucson, AZ, USA. 4. Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. 5. School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
Abstract
PURPOSE: The Sleep Apnea Symptom Score (SASS) has been commonly used to assess obstructive sleep apnea (OSA). The aim of this study was to examine the psychometric properties of the SASS and the predictive value of SASS incorporating bedpartner-reported information in identifying OSA in pregnant women. METHODS: A cohort of healthy pregnant women completed the SASS and Pittsburgh Sleep Quality Index. Participants underwent overnight laboratory polysomnography (PSG) monitoring. Reliability and validity of the SASS were evaluated. A multivariable predictive model, incorporating the SASS score along with BMI, age, and bedpartner-reported information, was developed to assess the risk for OSA (AHI ≥ 5 events/h). Receiver operating characteristic curves for OSA were constructed to evaluate the sensitivity and specificity of the predictive model. RESULTS: A total of 126 and 105 participants completed the PSG during the first and third trimester, respectively. The SASS demonstrated adequate validity and acceptable reliability (Cronbach's α = 0.72 during the third trimester). When the combined model consisting of SASS, age, BMI, and bedpartner-reported information was used, the area under the curve for AHI ≥ 5 for the first and third trimester was 0.781 (95%CI 0.648, 0.914) and 0.842 (95%CI 0.732, 0.952), respectively; the sensitivity/specificity was 76.9%/72.4% and 82.4%/78.0%, respectively. CONCLUSIONS: The SASS alone has acceptable reliability and validity, but limited predictive values. A new tool, combining the SASS and other patient characteristics (i.e., age, BMI, and bedpartner-reported snoring and breathing pauses), demonstrated improved sensitivity and specificity, and thus may have greater utility in clinical practice for predicting OSA in pregnant women.
PURPOSE: The Sleep Apnea Symptom Score (SASS) has been commonly used to assess obstructive sleep apnea (OSA). The aim of this study was to examine the psychometric properties of the SASS and the predictive value of SASS incorporating bedpartner-reported information in identifying OSA in pregnant women. METHODS: A cohort of healthy pregnant women completed the SASS and Pittsburgh Sleep Quality Index. Participants underwent overnight laboratory polysomnography (PSG) monitoring. Reliability and validity of the SASS were evaluated. A multivariable predictive model, incorporating the SASS score along with BMI, age, and bedpartner-reported information, was developed to assess the risk for OSA (AHI ≥ 5 events/h). Receiver operating characteristic curves for OSA were constructed to evaluate the sensitivity and specificity of the predictive model. RESULTS: A total of 126 and 105 participants completed the PSG during the first and third trimester, respectively. The SASS demonstrated adequate validity and acceptable reliability (Cronbach's α = 0.72 during the third trimester). When the combined model consisting of SASS, age, BMI, and bedpartner-reported information was used, the area under the curve for AHI ≥ 5 for the first and third trimester was 0.781 (95%CI 0.648, 0.914) and 0.842 (95%CI 0.732, 0.952), respectively; the sensitivity/specificity was 76.9%/72.4% and 82.4%/78.0%, respectively. CONCLUSIONS: The SASS alone has acceptable reliability and validity, but limited predictive values. A new tool, combining the SASS and other patient characteristics (i.e., age, BMI, and bedpartner-reported snoring and breathing pauses), demonstrated improved sensitivity and specificity, and thus may have greater utility in clinical practice for predicting OSA in pregnant women.
Authors: Bilgay Izci; Sascha E Martin; Kirsty C Dundas; Wang A Liston; Andrew A Calder; Neil J Douglas Journal: Sleep Med Date: 2005-03 Impact factor: 3.492
Authors: Francesca L Facco; Corette B Parker; Uma M Reddy; Robert M Silver; Matthew A Koch; Judette M Louis; Robert C Basner; Judith H Chung; Chia-Ling Nhan-Chang; Grace W Pien; Susan Redline; William A Grobman; Deborah A Wing; Hyagriv N Simhan; David M Haas; Brian M Mercer; Samuel Parry; Daniel Mobley; Shannon Hunter; George R Saade; Frank P Schubert; Phyllis C Zee Journal: Obstet Gynecol Date: 2017-01 Impact factor: 7.661
Authors: Bilgay Izci; James P McDonald; Emma L Coleman; Thomas W Mackay; Neil J Douglas; Heather M Engleman Journal: Respir Med Date: 2005-03 Impact factor: 3.415
Authors: Paul E Peppard; Terry Young; Jodi H Barnet; Mari Palta; Erika W Hagen; Khin Mae Hla Journal: Am J Epidemiol Date: 2013-04-14 Impact factor: 4.897
Authors: Grace W Pien; Allan I Pack; Nicholas Jackson; Greg Maislin; George A Macones; Richard J Schwab Journal: Thorax Date: 2013-11-21 Impact factor: 9.139
Authors: Bilgay Izci Balserak; Grace W Pien; Bharati Prasad; Dimitrios Mastrogiannis; Chang Park; Laurie T Quinn; James Herdegen; David W Carley Journal: Ann Am Thorac Soc Date: 2020-06