English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Individuals at high risk for obstructive sleep apnea (OSA) may not access sleep clinics for reasons including immobility, transportation difficulties, or living in rural areas. An easy-to-administer OSA screening tool for different body types, independent of witnessed apneas or body mass index (BMI), is lacking to identify this group quickly. We compared the sensitivities (SNs), specificities (SPs), and receiving operator curves (ROCs) of the neck circumference/height ratio (NHR) and waist circumference/height ratio (WHR) in predicting moderate and severe OSA (apnea-hypopnea index [AHI] ≥15/hr) with the SN, SP, and ROC of the derived Stop-Bang Questionnaire (dSBQ), which was created from proxy variables from the Sleep Heart Health Study (SHHS). Methods Data from the SHHS baseline evaluation were used and included participants (N=5431) who completed polysomnograms and had neck and waist circumferences, height measurements, and the SHHS proxy variables. This data then was divided randomly into 1/3 for derivation and 2/3 for validation analyses. Results No statistical differences were seen for gender, age, or ethnicity between the derivation and validation samples. In the validation sample (n=3621), the NHR cut-point of 0.21 resulted in a SN of 91% and a SP of 26% for AHI ≥15/hr. The WHR cut-point of 0.51 resulted in a SN of 91% and a SP of 21% for AHI ≥15/hr. Comparing the validation NHR and the dSBQ ROC curves showed no significant difference (AUCs=0.69 and 0.70, respectively; p=0.22). However, the ROC curve for WHR was significantly lower than for the dSBQ (AUCs=0.63 and 0.70, respectively; p&amp;lt;0.0001). Comparing the derivation and validation ROCs showed no significant differences between NHR ROCs, p=0.81, or between WHR ROCs, p=0.67. Conclusion The NHR is a viable screening tool, independent of witnessed apneas and BMI, that can be used for different body types and is statistically comparable to the dSBQ. Support This work was supported by U01HL53938 and U01HL53938-07S (University of Arizona).

0572 Using Anthropometric Measures to Screen for Obstructive Sleep Apnea in the Sleep Heart Health Study Cohort