Physiology-Based Modeling May Predict Surgical Treatment Outcome for Obstructive Sleep Apnea

Abstract

Study objectives: To test whether the integration of both anatomical and nonanatomical parameters (ventilatory control, arousal threshold, muscle responsiveness) in a physiology-based model will improve the ability to predict outcomes after upper airway surgery for obstructive sleep apnea (OSA).

Methods: In 31 patients who underwent upper airway surgery for OSA, loop gain and arousal threshold were calculated from preoperative polysomnography (PSG). Three models were compared: (1) a multiple regression based on an extensive list of PSG parameters alone; (2) a multivariate regression using PSG parameters plus PSG-derived estimates of loop gain, arousal threshold, and other trait surrogates; (3) a physiological model incorporating selected variables as surrogates of anatomical and nonanatomical traits important for OSA pathogenesis.

Results: Although preoperative loop gain was positively correlated with postoperative apnea-hypopnea index (AHI) (P = .008) and arousal threshold was negatively correlated (P = .011), in both model 1 and 2, the only significant variable was preoperative AHI, which explained 42% of the variance in postoperative AHI. In contrast, the physiological model (model 3), which included AHIREM (anatomy term), fraction of events that were hypopnea (arousal term), the ratio of AHIREM and AHINREM (muscle responsiveness term), loop gain, and central/mixed apnea index (control of breathing terms), was able to explain 61% of the variance in postoperative AHI.

Conclusions: Although loop gain and arousal threshold are associated with residual AHI after surgery, only preoperative AHI was predictive using multivariate regression modeling. Instead, incorporating selected surrogates of physiological traits on the basis of OSA pathophysiology created a model that has more association with actual residual AHI.

Commentary: A commentary on this article appears in this issue on page 1023.

Clinical trial registration: ClinicalTrials.Gov; Title: The Impact of Sleep Apnea Treatment on Physiology Traits in Chinese Patients With Obstructive Sleep Apnea; Identifier: NCT02696629; URL: https://ichgcp.net/clinical-trials-registry/NCT02696629.

Keywords: critical pressure; loop gain; lung; obstructive sleep apnea; phenotyping; polysomnography; upper airway surgery.

© 2017 American Academy of Sleep Medicine

Figures

Figure 1. Scatterplots.

Scatter plots of model-derived AHI using regression value versus the actual postoperative AHI (A) from statistical model (r2 = .427) and (B) from physiological model (r2 = .607). Reference line: x = y. Note that the statistical model has both underestimated and overestimated surgical success. For example, in those predicted by the statistical model to have a residual AHI of about 30 events/h, the actual result is from 15–60 events/h. However, in the physiological model few patients are actually much worse than the model estimate. AHI = apnea-hypopnea index.

Figure 2. Receiver operating characteristic curves.

Dashed lines = receiver operating characteristic (ROC) curves using the statistical model to predict (A) postoperative AHI ≥ 10 events/h (failed to be cured), area under the curve (AUC) is 0.92 (0.82, 1.00); (B) postoperative AHI ≥ 20 events/h, AUC is 0.82 (0.67, 0.97); (C) postoperative AHI ≥ 30 events/h (patients who still had severe sleep apnea after surgery), AUC is 0.81 (0.66, 0.96). Solid lines = ROC curves using physiology model scores to predict (A) postoperative AHI ≥ 10 events/h, AUC is 0.97 (0.92, 1.00); (B) postoperative AHI ≥ 20 events/h, AUC is 0.88 (0.76, 1.00); (C) postoperative AHI ≥ 30 events/h, AUC is 0.90 (0.79, 1.00). AHI = apnea-hypopnea index.

Figure 3. The importance of nonanatomical traits is dependent on anatomy.

For the same given response to surgery (improvement in anatomy), the role of nonanatomical traits will be very different. For subject A, surgery is likely to improve obstructive sleep apnea (OSA) no matter the nonanatomical traits (ie, the patient has little airway collapsibility and surgery may cure OSA). For subject B, surgery has improved the anatomy but not enough to completely eliminate obstruction. Whether the subject has OSA after surgery will very much depend on the nonanatomical traits. Subject C has an improvement in anatomy, but the anatomy is still very poor. In this case, again, the nonanatomical traits will still contribute to the residual apnea-hypopnea index but not matter very much in deciding the success of surgery. Another difficulty with predication is the variable effect of surgery on the individual's anatomy. Pcrit = critical pressure.

Figure 4. Actual postoperative apnea-hypopnea index (AHI) versus model-derived AHI by PSG Multiple Regression model or PSG Plus Physiology model in selective patients.

Reference line: x = y. Four patients 1, 2, 3, and 4 with a similar preoperative AHI (50.3, 58.5, 65.2, and 51.3, respectively) had very different postoperative AHI. The estimated postoperative AHI of the same 4 patients are marked in the PSG Plus Physiology model figure as well (asterisks, with the patient's total physiological score in parenthesis; same patient's markers are linked with a dash line). Patients 1, 3, and 4 were all stratified to the same anatomy based on AHIREM (all bad anatomy). However, their scores from the nonanatomical surrogates were quite different (eg, Patient 1 had a total of 7 points from nonanatomy traits [high arousal threshold, bad upper airway muscle response and control of breathing]; Patient 3 only had 2 points from nonanatomy traits [“intermediate sleep stability, intermediate upper airway response, good control of breathing“]; and Patient 4 only had 1 point based on the nonanatomical trait surrogates [intermediate control of breathing, good upper airway response and low arousal threshold]). Although patient 2 had better (intermediate) anatomy, the nonanatomical surrogates of physiological traits score was 7 in total, thus the actual residual AHI was higher than estimated by multiple regression model. AHI = apneahypopnea index.