Validation of the ET-AHI: Effectiveness of Obstructive Sleep Apnea Treatment Index

Scott B. Boyd DDS, PhD, Department of Oral and Maxillofacial Surgery, Vanderbilt University School of Medicine, Nashville, TN
Raghu Upender MD, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN
Arthur Walters MD, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN
Rameela Chandrasekhar PhD, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN
Li Wang MS, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN
Statement of the Problem:  One of the major challenges in determining the comparative effectiveness of surgical interventions and continuous positive airway pressure (CPAP) for treatment of obstructive sleep apnea (OSA) comes from the complexity of comparing a treatment that requires adherence for clinical effectiveness to one that does not.  To address this challenge, we have developed an innovative measurement instrument, the Effectiveness of Treatment Apnea-Hypopnea Index (ET-AHI), for the purpose of determining the effective AHI for OSA treatment. The specific aims of this study were to validate the ET-AHI for CPAP therapy and to determine the levels of CPAP adherence that may be necessary to achieve equivalency with maxillomandibular advancement (MMA) surgery.    

 Materials and Methods:  The investigators conducted a prospective cohort study composed of patients with severe OSA who were currently undergoing treatment by CPAP.  To assess the full spectrum of adherence to CPAP, patients ranging from 0-100% adherence were recruited.  Each consented patient underwent a polysomnography (PSG) where they used their CPAP machine as they did at home.  The true effective AHI for the entire night was then calculated for each patient which included both the time when the patient did and did not use their CPAP machine.  ET-AHI calculations were then performed and compared to the true effective AHI to validate the accuracy of the ET-AHI.  These results were then compared to the PSG results of a second cohort of patients with severe OSA who had undergone MMA.  ET-AHI calculations were performed to estimate the level of CPAP adherence that would be necessary to achieve equivalence with the MMA surgical result.  

Method of Data Analysis:  Descriptive and bivariate statistics were computed.  Spearman rank correlation coefficients were calculated to assess the association between the true effective AHI and the calculated ET-AHI.  For all analyses, a p-value of <0.05 was considered statistically significant.

Results: The CPAP study group was composed of 28 adult patients (mean age, 50.9 ± 9.7 year; 75% men) with severe OSA (baseline AHI, 67.9 ± 29.0). The average hours of CPAP use during the study was 4.0 ± 2.8 with a range from 0 to 8.7 hours.   A high correlation was found between the true effective AHI and the ET-AHI calculation (r = 0.82) with a mean difference in the AHI of 2 events/hr.  The MMA comparator group was composed of 37 adult patients (mean age, 44.2 ± 9.0 years; 73% men) with severe OSA (baseline AHI, 56.3 ± 22.6). MMA produced a significant reduction in OSA (Post-MMA AHI, 11.6 ± 7.4).  ET-AHI calculations predicted that an average of nearly 5 hours of nightly CPAP use would be necessary to achieve equivalence with the AHI scores following MMA, which is greater than the observed 4 hours of use in the CPAP cohort in this study.

Conclusions:   The results of this study indicate that the calculated ET-AHI provides a very close approximation of the true effective AHI when patients use CPAP as they do at home.  Furthermore this study shows that MMA compares very favorably with CPAP for treatment of severe OSA as relatively high levels of nightly CPAP use may be necessary to achieve equivalency with MMA.

Support:  This investigation was supported in part by a Research Support Grant Award from the Oral and Maxillofacial Surgery Foundation and in part by CTSA award No.UL1TR000445 from the National Center for Advancing Translational Sciences.