Our study showed that use of total bedtime rather than sleeptime led to significant misclassification of OSA, with both underdiagnosis and with underestimation of severity. Age and BMI were identified as positive and negative predictors of misclassification respectively. In particular, patients who were aged 57 years and older, and who had a BMI < 32.3kg/m2 had increased odds of OSA misclassification. This was a novel finding that has otherwise not been reported prior.
The results of this study highlight that the use of bedtime (e.g. in home sleep studies)for the diagnosis of OSA will lead to considerable underdiagnosis and underestimation of OSA severity. Our finding is consistent with prior studies that also directly evaluated polysomnogram data.14 Reasons for this misclassification besides the expectedly higher denominator for total bed time includes the presence of concomitant sleep disturbances such as periodic limb movements of sleep, which may be more common in older persons.12,15 Such disturbances contribute to lack of sustained sleep, with resultant decreased sleep efficiency. The resultant decrease in total sleep time as compared to total bed time leads to a larger discrepancy between AHI scores calculated using the two.
One reason why misclassification is independently associated with increasing age could be that in older patients sleep latency can be increased.16 In addition, increasing age is associated with decreasing ability to maintain sleep as well.17 These findings were attributed in previous studies to be due to the overlap of increasing age with increasing medical and psychiatric disorders and related health burdens.18 These two factors contribute to a decrease in the ratio of total sleep time to total bed time, hence accounting for how increasing age may be associated with increased risk of misclassification.
Regarding the inverse association of misclassification with increasing BMI, this is explained by the raised respiratory arousal threshold in patients with increased BMI.19 In obese patients, there is a higher respiratory arousal threshold which protects against interrupted sleep. Conversely, in non-obese patients, this protective effect is lost. There would therefore be more interrupted sleep in the non-obese cohort with reduction in the ratio of total sleep time to total bed time, thereby explaining how increasing BMI is inversely associated with the risk of misclassification.
A strength of our study is that our study population consists of a multiethnic population which is representative of the diverse ethnicities present in Asia. This allows for our study to be applied in other healthcare settings across Asia and other populations with similar diversity. Furthermore, our study has gone on to evaluate for possible predictors for misclassification, which potentially may allow for clinicians to better select for patients who may be unsuitable for home sleep studies. In addition, as virtually all of our patients in the NUH sleep laboratory had in-lab sleep studies performed due to financial subsidies (compared to no subsidies for home sleep studies), we were able to comprehensively capture full polysomnographic data from a complete population of patients with suspected sleep disorders.
A limitation of our study is our lack of data on other comorbidities, in particular psychiatric comorbidities, which have been found previously to be contributory to poor sleep.18 It is possible that there may be other, unidentified comorbidities that could have contributed to misclassification of OSA as well. It could also be argued that a limitation of in-lab sleep studies includes a possible adverse effect on sleep quality, owing to the unfamiliar environment.20 Sleep latency and quality could be affected, which may result in a larger discordance between total bed time and sleep time. However, a prospective randomised study showed there was no evidence of a better quality of sleep and recording tolerance at home,21 which reduces the impact that this would have on our study.
The clinical implications of our study would be that the use of home sleep apnea testing needs to be done with caution, even in a patient population at high pretest risk of moderate-to-severe OSA, as misclassification may result in the appropriate therapies not being offered. Patients may also be lulled into thinking their OSA is less severe than it really is, and hence less motivated to adhere to therapy. Full polysomnography may be preferred in the population of age ≥ 57 years old with BMI < 32.3 given the presence of identified predictors of OSA misclassification.
Future research in this field could delve into affirming the results of this study with a randomised control trial of older patients with lower BMI undergoing either home sleep test or polysomnography. Other aspects to consider will include looking into how processes can be changed in the sleep clinic to flag up patients who may not be suitable for home sleep apnea testing.This study can also stimulate device manufacturers to innovate and create ways to more accurately detect sleep in home sleep devices.22
To conclude, home sleep apnea testing, a commonly used modality these days,23 may be associated with significant misclassification of OSA and underestimation of severity, which in turn may affect treatment. Predictors of misclassification included increasing age as well as lower BMI.