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Identification of patients with sleep disordered breathing: comparing the four-variable screening tool, STOP, STOP-Bang, and Epworth Sleepiness Scales.

TitleIdentification of patients with sleep disordered breathing: comparing the four-variable screening tool, STOP, STOP-Bang, and Epworth Sleepiness Scales.
Publication TypeJournal Article
Year of Publication2011
AuthorsSilva, GE, Vana, KD, Goodwin, JL, Sherrill, DL, Quan, SF
JournalJ Clin Sleep Med
Volume7
Issue5
Pagination467-72
Date Published2011 Oct 15
ISSN1550-9397
KeywordsBlood Pressure, Body Mass Index, Cohort Studies, Female, Humans, Male, Mass Screening, Middle Aged, Polysomnography, Predictive Value of Tests, Prospective Studies, Risk, ROC Curve, Sensitivity and Specificity, Severity of Illness Index, Sleep Apnea Syndromes, Snoring, Surveys and Questionnaires
Abstract<p><b>STUDY OBJECTIVE: </b>The Epworth Sleepiness Scale (ESS) has been used to detect patients with potential sleep disordered breathing (SDB). Recently, a 4-Variable screening tool was proposed to identify patients with SDB, in addition to the STOP and STOP-Bang questionnaires. This study evaluated the abilities of the 4-Variable screening tool, STOP, STOP-Bang, and ESS questionnaires in identifying subjects at risk for SDB.</p><p><b>METHODS: </b>A total of 4,770 participants who completed polysomnograms in the baseline evaluation of the Sleep Heart Health Study (SHHS) were included. Subjects with RDIs ≥ 15 and ≥ 30 were considered to have moderate-to-severe or severe SDB, respectively. Variables were constructed to approximate those in the questionnaires. The risk of SDB was calculated by the 4-Variable screening tool according to Takegami et al. The STOP and STOP-Bang questionnaires were evaluated including variables for snoring, tiredness/sleepiness, observed apnea, blood pressure, body mass index, age, neck circumference, and gender. Sleepiness was evaluated using the ESS questionnaire and scores were dichotomized into < 11 and ≥ 11.</p><p><b>RESULTS: </b>The STOP-Bang questionnaire had higher sensitivity to predict moderate-to-severe (87.0%) and severe (70.4%) SDB, while the 4-Variable screening tool had higher specificity to predict moderate-to-severe and severe SDB (93.2% for both).</p><p><b>CONCLUSIONS: </b>In community populations such as the SHHS, high specificities may be more useful in excluding low-risk patients, while avoiding false positives. However, sleep clinicians may prefer to use screening tools with high sensitivities, like the STOP-Bang, in order to avoid missing cases that may lead to adverse health consequences and increased healthcare costs.</p>
DOI10.5664/JCSM.1308
Alternate JournalJ Clin Sleep Med
PubMed ID22003341
PubMed Central IDPMC3190845
Grant ListU01HL53937 / HL / NHLBI NIH HHS / United States
U01 HL053916 / HL / NHLBI NIH HHS / United States
U01HL64360 / HL / NHLBI NIH HHS / United States
U01 HL063463 / HL / NHLBI NIH HHS / United States
U01HL53938-07S / HL / NHLBI NIH HHS / United States
U01HL53938 / HL / NHLBI NIH HHS / United States
U01 HL053938 / HL / NHLBI NIH HHS / United States
U01HL53934 / HL / NHLBI NIH HHS / United States
U01 HL064360 / HL / NHLBI NIH HHS / United States
U01 HL053941 / HL / NHLBI NIH HHS / United States
U01HL63429 / HL / NHLBI NIH HHS / United States
U01HL53931 / HL / NHLBI NIH HHS / United States
U01HL53941 / HL / NHLBI NIH HHS / United States
U01 HL053934 / HL / NHLBI NIH HHS / United States
U01HL53916 / HL / NHLBI NIH HHS / United States
U01 HL063429 / HL / NHLBI NIH HHS / United States
U01 HL053937 / HL / NHLBI NIH HHS / United States
U01HL53940 / HL / NHLBI NIH HHS / United States
U01HL63463 / HL / NHLBI NIH HHS / United States
U01 HL053931 / HL / NHLBI NIH HHS / United States