Review Club Minerva Anestesiologica
1) Pubblicata il 11/10/2016
Looking in the mouth of yawning patients
Department of Biopathology and Medical Biotechnologies (DIBIMED), Section of Anaesthesia, Analgesia, Intensive Care and Emergency, University Hospital Paolo Giaccone, University of Palermo, Italy.
Background and purposes of the study
Sleep-disordered breathing affects up to 25% of the general population, with a higher prevalence registered in surgical patients.1
Patients with obstructive sleep apnea (OSA) may be at increased perioperative risk due to potential difficult airway management and a higher rate of perioperative cardiovascular and respiratory complications.2 A proportion as high as 80% of men and 93% of women with moderate to severe OSA do not have a formal diagnosis in the community.3,4
Detection of patients with sleep-disordered breathing may have important implications for perioperative management (e.g. outpatient vs inpatient surgery management, adoption of measures for risk reduction, referral to a sleep medicine laboratory before surgery). Although
polysomnography is the gold-standard for diagnosis, it is time consuming and costly.
The loud snoring, tiredness, observed apnea, high blood pressure (STOP) – body mass index, age, neck circumference and gender (Bang), STOP-Bang questionnaire is one of the most commonly used screening tools for OSA.5,6
It consists of 8 dichotomous items related to sleep-disordered breathing signs and symptoms and patient's characteristics associated with OSA. Its ease-of use encouraged its adoption for screening of patients undergoing surgery and as such it has been recommended by the Italian Society of Anesthesia Analgesia Resuscitation and Intensive Care (SIAARTI) and the Italian Association of Sleep Medicine (AIMS).7
A score equal or higher than 3 yields a high sensitivity in the detection of moderate to severe OSA. However, the major shortcoming of the STOP-Bang questionnaire is its inadequate specificity (43% and 37% for moderate and severe OSA respectively), leading to a high number of false-positive results and a consequent unnecessary referral to a sleep medicine laboratory.
In the study we are reviewing, Dette et al.8 tried to improve the diagnostic performance of the STOP-Bang questionnaire by combining it with Mallampati classification.
Over a 24-month period, the authors studied 303 patients scheduled for surgery.
The association of a higher Mallampati score and OSA has been previously reported. When a STOP-Bang score > 3 was combined with a Mallampati score of > 3, the overall sensitivity increased in both male and female patients (respectively 92.3% and 93.3% sensitivity for detection of an oxygen desaturation index 4% of at least 15 per hour, ODI4%; similar results were detected when authors considered the apnea/hypopnea index, AHI). Unfortunately, specificity resulting from the combination was even worse (10.3% in men and 41.4% in women). Notably, specificity of Mallampati classification > 3 alone showed a higher specificity than the STOP-Bang questionnaire for detection of moderate to severe sleep disordered breathing, but a remarkably lower sensitivity (overall sensitivity: 26.9%, overall specificity 69.2% for AHI> 15).8
Upper airway crowding has been associated with OSA. In a study involving OSA patients who were matched with non-OSA controls, authors studied the morphological features of craniofacial structures and upper airway soft tissue through radiographs. Authors observed that tongue of OSA patients was significantly larger for a given maxillomandible space, and this morphological imbalance was not observed in matched non-OSA patients. Although authors did not report the Mallampati classification of patients, we may argue that it was on average higher in patients with OSA than in controls.9
We may argue that, despite anthropometric features may be involved in sleep disordered breathing, other, more complex mechanisms play a role. This is not the first attempt to optimize the diagnostic performance of the STOP-Bang tool by integration of additional variables.10 For instance, Serum bicarbonate added to STOP-Bang led to a higher specificity for detection of moderate to severe OSA patients.11
Take Home message
Dette et al. addressed the need for a tool to predict sleep-disordered breathing patients with high specificity. They performed a rigorous and well-conducted study enrolling unselected surgical patients. We believe their methodology led to highly consistent and reproducible results. Unfortunately, their study indicates that adding Mallampati classification to STOP-Bang questionnaire fails to improve its overall specificity and that their combination is not superior to STOP-Bang alone for preoperative detection of OSA. Contrarily, as the combination of Mallampati classification and STOP-Bang questionnaire has a high sensitivity, it may play role in the screening of specific populations of patients at higher risk of OSA: further clarifying studies on this topic are warranted.
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