• Stefan Mihaicuta, Mihai Udrescu, and Alexandru Topirceanu.
• Chest. 2014 Mar 1;145(3 Suppl):609A.

Session TitleSleepSESSION TYPE: Slide PresentationsPRESENTED ON: Monday, March 24, 2014 at 10:45 AM - 11:45 AMPURPOSE: Polysomnography (PSG) is a costly and time-consuming investigation for the evaluation of sleep apnea syndrome(SAS). Since it is not feasible to referred all individuals to PSG, it is useful to define predictors of OSA among these subjects. The aim is to identify specific patterns of developing apnea, by taking into consideration the multiple connections between risk factors in a relevant population of patients. Using a social network analysis pattern, we have developed incentives for predicting the apnea stage for any new patient by evaluating its network topological position and assigning a proposed ApnEa Risk score (AER)- a numerical predictor for the risk of severe apnea.Methods1348 patients from Timisoara "Victor Babes" Hospital (March 2005- December 2012), with over 100 measured criteria, were used to define a methodology which is inspired by the Network Medicine approach. Patients are nodes in a graph and are linked to other patients who have a risk compatibility of at least 4 out of 6 identical parameters: gender, age, blood pressure, obesity, neck circumference and mean de-saturationResultsFrom the generated graph, 7 distinct compatibility clusters were found. Each of these clusters corresponds to a specific patient profile which leads to a certain probability of developing the disease. The AER score predictor emerges from the statistical analysis of these clusters and helps easily and rapidly assess the risk of OSA of a new patient. Using it to prioritize patient treatment/evaluation we manage to improve to overall process efficacy by 53%, in terms of cumulative AHI diagnosed, as compared to the first-come, first-served (non-prioritized) method currently used.ConclusionsRelying on simple parameters, the AER score may pave the way for automatically predicting, with a high degree of accuracy, if a patient is prone to developing OSA, and thus classify and prioritize patients for diagnostic evaluation.Clinical ImplicationsThe predictive accuracy of the AER score facilitates an early prioritization of patients being appointed for PSG. This helps increase the overall efficiency of diagnosis and treatment by investigating more severe cases preemptively.DisclosureThe following authors have nothing to disclose: Mihai Udrescu, Alexandru Topirceanu, Razvan Avram, Stefan MihaicutaNo Product/Research Disclosure Information.

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