Correlation between the STOP-Bang Score and the Severity of Obstructive Sleep Apnea
Bibliographic record
Abstract
In the September 2014 letter to the editor, Corso et al.1 commented on preoperative screening for perioperative management of patients with obstructive sleep apnea (OSA) in the recently published Practice Guidelines.2 They stated that, “The STOP-Bang questionnaire has been shown to identify patients at risk with moderate-to-severe OSA, with reasonable certainty and can be easily implemented in the clinical setting.”1 In the reply by Gross et al.,3 the authors indicated that, “While the STOP-Bang scores were shown to correlate with the probability of sleep apnea, it was not established that they correlate with its severity.” This statement is not accurate based on recently published studies supporting a correlation between the STOP-Bang score and the severity of OSA.In 2012, we demonstrated that as the STOP-Bang score increased, the probability of having more severe OSA also increased. When the score rose from 0 to 2 till 7 to 8, the probability of having moderate-to-severe OSA (apnea-hypopnea index [AHI] > 15 event/h) increased from 18% (95% confidence interval [CI], 13 to 24%) to 60% (95% CI, 44 to 73%). The probability of severe OSA (AHI > 30 event/h) increased from 4% (95% CI, 2 to 8%) to 38% (95% CI, 29 to 53%).4 This indicates that the patients who have a higher score in the STOP-Bang questionnaire would have a greater probability of severe OSA.In 2011, Farney et al.5 evaluated the STOP-Bang score in patients referred to a sleep clinic and who underwent polysomnography. Although the predominant reason for referral was for suspected OSA, the study population consisted of patients with a variety of conditions, including insomnia, narcolepsy, and behavioral disorders. As the STOP-Bang score increased from 0 to 8, the probability of severe OSA increased from 4.4 to 81.9%. With any score greater than 4, the probability of severe OSA continuously increased with the increase of STOP-Bang score, whereas the probability having non-OSA, mild OSA, or moderate OSA decreased (fig. 1).5 A similar relation between the STOP-Bang score and the severity of OSA was also found in the Chinese patients referred to sleep clinics.6In summary, the currently available data in the literature support that a correlation exists between a higher STOP-Bang score and the severity of OSA. Accordingly, the STOP-Bang score can be used to not only identify cases with any degree of OSA but also prioritize those who are more likely to have moderate-to-severe disease. To the extent that the severity of sleep apnea characterized by the AHI is useful in clinical management, we would argue that the STOP-Bang questionnaire should be considered the optimal screening tool at the present time and that the score can be used for making more reasoned clinical decisions.The authors declare no competing interests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".