Sleep Disorders |

Predictive Performance of the STOP-Bang, Epworth Sleepiness Scale, and Modified Flemons Score in Identifying Sleep Center Patients With Obstructive Sleep Apnea FREE TO VIEW

Colin Smith; Richard Waldhorn; Anne O'Donnell
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Georgetown University School of Medicine, Washington, DC

Chest. 2014;146(4_MeetingAbstracts):939A. doi:10.1378/chest.1985313
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SESSION TITLE: Sleep Posters I

SESSION TYPE: Original Investigation Poster

PRESENTED ON: Wednesday, October 29, 2014 at 01:30 PM - 02:30 PM

PURPOSE: The purpose of this study is to evaluate the abilities of the STOP-Bang, Epworth Sleepiness Scale (ESS), and Modified Flemons Score (MFS) questionnaires in identifying patients at risk for obstructive sleep apnea (OSA), especially those at risk for moderate and severe OSA. The MFS is a four-item model that measures neck circumference with adjustment for a positive history of hypertension, snoring, and nocturnal choking or gasping.

METHODS: A convenience sample of 452 adult patients admitted to the sleep center at MedStar Georgetown University Hospital was used. Patients were asked to complete the STOP-Bang, ESS, and MFS questionnaires with help from sleep center technicians. Only those records in which all three scores were fully completed were used to allow for comparison of scores. The scores' predictive abilities were determined by comparing patients' predicted OSA risk to their apnea-hypopnea index, which was measured by overnight or split-night polysomnography.

RESULTS: The STOP-Bang questionnaire had the highest sensitivity to predict moderate-to-severe (93.4%) and severe (97.8%) OSA. The ESS had the highest specificity to predict moderate-to-severe (63.4%) and severe (60.7%) OSA. The MFS questionnaire had the highest positive predictive value for moderate-to-severe (83.6%) and severe (52.3%) OSA.

CONCLUSIONS: The STOP-Bang questionnaire had the highest sensitivity to predict patients at risk for OSA when compared to the ESS and MFS questionnaires. Anesthesiologists may prefer to use screening tools with high sensitivities like STOP-Bang in order to avoid missing cases that may lead to future complications and increased healthcare costs. Sleep center clinicians may prefer the MFS with the highest positive predictive value for use in diagnostic algorithms.

CLINICAL IMPLICATIONS: It is estimated that 87% of those with moderate-to-severe OSA have not been diagnosed. Since patients with OSA are known to have increased perioperative complications, it is now common to screen for patients who might be at risk for OSA prior to surgery. Sleep clinicians also use screening tools to help identify which patients might benefit from a formal sleep study. To meet these needs, many screening tools for predicting OSA have been proposed but there are few validation studies that compare their predictive abilities on the same population. In this study of the STOP-Bang, ESS, and MFS tools, STOP-Bang had the highest sensitivity and the ESS had the highest specificity in identifying individuals at risk for OSA.

DISCLOSURE: The following authors have nothing to disclose: Colin Smith, Richard Waldhorn, Anne O'Donnell

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