The STOP-Bang equivalent model and prediction of severity of obstructive sleep apnea: relation to polysomnographic measurements of the apnea/hypopnea index

J Clin Sleep Med. 2011 Oct 15;7(5):459-65B. doi: 10.5664/JCSM.1306.


Background: Various models and questionnaires have been developed for screening specific populations for obstructive sleep apnea (OSA) as defined by the apnea/hypopnea index (AHI); however, almost every method is based upon dichotomizing a population, and none function ideally. We evaluated the possibility of using the STOP-Bang model (SBM) to classify severity of OSA into 4 categories ranging from none to severe.

Methods: Anthropomorphic data and the presence of snoring, tiredness/sleepiness, observed apneas, and hypertension were collected from 1426 patients who underwent diagnostic polysomnography. Questionnaire data for each patient was converted to the STOP-Bang equivalent with an ordinal rating of 0 to 8. Proportional odds logistic regression analysis was conducted to predict severity of sleep apnea based upon the AHI: none (AHI < 5/h), mild (AHI ≥ 5 to < 15/h), moderate (≥ 15 to < 30/h), and severe (AHI ≥ 30/h).

Results: Linear, curvilinear, and weighted models (R(2) = 0.245, 0.251, and 0.269, respectively) were developed that predicted AHI severity. The linear model showed a progressive increase in the probability of severe (4.4% to 81.9%) and progressive decrease in the probability of none (52.5% to 1.1%). The probability of mild or moderate OSA initially increased from 32.9% and 10.3% respectively (SBM score 0) to 39.3% (SBM score 2) and 31.8% (SBM score 4), after which there was a progressive decrease in probabilities as more patients fell into the severe category.

Conclusions: The STOP-Bang model may be useful to categorize OSA severity, triage patients for diagnostic evaluation or exclude from harm.

Keywords: Berlin Questionnaire; STOP-Bang model; obstructive sleep apnea syndrome; polysomnography; proportional odds logistic regression; screening questionnaire.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Body Mass Index
  • Female
  • Humans
  • Linear Models*
  • Male
  • Middle Aged
  • Polysomnography / methods*
  • Polysomnography / statistics & numerical data*
  • Predictive Value of Tests
  • Severity of Illness Index
  • Sleep Apnea Syndromes / diagnosis
  • Sleep Apnea Syndromes / physiopathology
  • Sleep Apnea, Obstructive / diagnosis*
  • Sleep Apnea, Obstructive / physiopathology
  • Surveys and Questionnaires*
  • Young Adult