Zeitschrift für Schlafstörungen und Therapie
Offener Zugang

Abstrakt

Improving the identification and triage of patients with Obstructive Sleep Apnea who require treatment: The Merlin tool for high risk populations

Andrew Scott; Akke Vellinga, Miriam Geehan, Mohammad Ahmed, Eithne Mulloy, John Joseph Gilmartin

Aims and objectives: A number of validated questionnaires are routinely used to screen specific populations for obstructive sleep apnea (OSA) including the STOP, STOP-Bang, Berlin and Epworth sleepiness scales. These questionnaires depend on subjective questions which cannot be independently confirmed. The subjective questions also result in high sensitivity and low specificity as they are generally resulting from OSA. The aim of the study was to identify verifiable and independently measurable risk factors and increase specificity to limit the number of polysomnography evaluations (PE) and lower healthcare cost.

Methods: A retrospective data collection of patients (N=164) enrolled for PE was performed which included the results of STOP, STOP Bang, Berlin and Epworth questionnaires as well as demographic and health related variables. OSA was defined as an AHI>=15 obtained from an overnight PE. Sensitivity and specificity of each questionnaire as well as for combinations of other, independently verifiable factors (IVF) was calculated. A new questionnaire was devised including the IVFs and data was prospectively collected from patients undergoing PE (N=209).

Results: The retrospective analysis identified age>50, male, BMI>30, alcohol consumption >21 per week, collar circumference>16 inches (40 cm), diabetes, use of antidepressants and high blood pressure as the most influential factors. Prospective data collection was performed and analysis resulted in a new scale with a cut off of 3 based on the following equation: OSA=(2*BMI>30)+(Age>50)+(Male)+(neck>16)+(diabetes)+(alcohol>21unit/week). For every 100 patients with OSA, the total number enrolled for PE based on each screening tool were respectively for STOP 92 enrolled of whom 41 were diagnosed and 1 patient missed, for STOP-Bang 94 enrolled, 42 identified and 1 missed, Berlin 83 enrolled, 36 identified and 7 missed, Epworth 46 enrolled, 22 identified and 20 missed and our new screening tool 65 enrolled, 35 identified and 8 missed.

Conclusion: In a high risk population of patients referred for PE we identified independently verifiable factors associated with OSA and with only 2/3 of patients enrolled for PE, we identified most OSA cases while keeping the number of missed cases down.