Analyzing Neck Circumference as an Indicator of CPAP Treatment Response in Obstructive Sleep Apnea with Network Medicine

Abstract

We explored the relationship between obstructive sleep apnea (OSA) patients' anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (D1, D2, D3) with 1046 patients from four sleep laboratories in Western Romania, including 145 subjects (D1) with one-night CPAP therapy. Using D1 data, we created a CPAP-response network of patients, and found neck circumference (NC) as the most significant qualitative indicator for apnea-hypopnea index (AHI) improvement. We also investigated a quantitative NC cutoff value for OSA screening on cohorts D2 (OSA-diagnosed) and D3 (control), using the area under the curve. As such, we confirmed the correlation between NC and AHI (ρ=0.35, p<0.001) and showed that 71% of diagnosed male subjects had bigger NC values than subjects with no OSA (area under the curve is 0.71, with 95% CI 0.63-0.79, p<0.001); the optimal NC cutoff is 41 cm, with a sensitivity of 0.8099, a specificity of 0.5185, positive predicted value (PPV) = 0.9588, negative predicted value (NPV) = 0.1647, and positive likelihood ratio (LR+) = 1.68. Our NC =41 cm threshold classified the D1 patients' CPAP responses-measured as the difference in AHI prior to and after the one-night use of CPAP-with a sensitivity of 0.913 and a specificity of 0.859.

Keywords: CPAP treatment response; anthropometric measures; network medicine; obstructive sleep apnea syndrome.

Figure 1

Overview of datasets and study design. The network-based analysis stage used cohort $D_1$ to model a CPAP patient network. By corroborating the community structure of this network with the CPAP treatment response of each patient (i.e., measured as AHI improvement), we extracted neck circumference (NC) as the most significant indicator of AHI improvement. We further used this information in the statistical analysis stage, in which used a larger $D_2+D_3$ supporting cohort to find an optimal NC threshold value for OSA-diagnosed patients. Cohort $D_3$ was the non-OSA control group. The study resulted in the definition of a rule of thumb guideline for CPAP treatment prioritization of patients with OSA (blue).

Figure 2

Ideal compatibility threshold of “at least 4 out of 6” common parameter classes used in the modeling of the CPAP patient network. If a lower threshold is used (i.e., less strict), too few, dense, and overlapping communities emerge. Conversely, if a higher threshold is used (i.e., more strict), too many non-representative communities emerge, and many nodes become completely disconnected from the giant component (GC) of the network.

Figure 3

The network of 145 patients with overnight CPAP treatment shows the mapping of the six measurements (age, gender, blood pressure, BMI, Epworth scale, and neck circumference) that are relevant for the four patient communities detected for OSA (central panel). The four communities ($C_1$—magenta, $C_2$—olive, $C_3$—orange, $C_4$—cyan) emerged from the modeled risk compatibility between patients and were used to study the associations between patient risk factors and CPAP treatment response.

Figure 4

The network of 145 OSA patients highlighting the improvement of AHI in terms of severity class, after the over-night CPAP treatment.

Figure 5

Receiver operator characteristic curve of neck circumference, for the differentiation between OSA and normal controls. The ROC curve illustrates the high OSA discriminatory performance of neck circumference—NC (area under curve AUC = 0.71, with a corresponding 95% confidence interval (CI) of 0.63–0.79, $p<0.001$).