Individuals with obstructive sleep apnea experience increased collapsibility of the upper airway. Patency of the upper airway is dependent on the activity of the upper airway muscles and lung volume which favor airway patency; extraluminal pressure and the intensity of negative inspiratory force which favor airway collapse. Patients with obstructive sleep apnea generate increased negative inspiratory force on inspiration. This coupled with often a reduction in lung volume and increased extraluminal pressure favor upper airway collapse. As a consequence, the activity of the pharyngeal dilator muscles, especially the genioglossus muscle, is primarily responsible for maintaining upper airway patency. Studies have demonstrated increased tonic activity in the genioglossus muscle in obstructive sleep apnea suggesting its singular importance in airway patency.

Sedatives, anesthetics, and analgesics (opioids) all impact upper airway function. There is a dose dependent reduction in upper airway muscle activity. Direct action on the phrenic nerve results in reduction in lung volume. There are alterations in central respiratory drive and apneic threshold. Patients with obstructive sleep apnea have a diminished ability to compensate for these alterations in respiratory function.

In patients with obstructive sleep, there is a progressive worsening of sleep apnea following surgery with the greatest increase in the severity index (apnea hypopnea index) observed during the third postoperative night. Importantly, the literature supports that the apnea hypopnea index does not return to baseline by the fifth postoperative night at which time many patients have already been discharged home. (Chung, In Press)

A retrospective case controlled study of orthopedic patients by Gupta published in 2001¹ showed that patients with obstructive sleep apnea had increased post operative complications, more frequent transfers to higher acuity care, and increased length of hospital stay. Kaw and colleagues² published a meta-analysis of 13 studies demonstrating similar results.

A comprehensive clinical management strategy should encompass screening, risk stratification, monitoring, and longitudinal care.

It is estimated that 80%-90% of individuals with obstructive sleep apnea are undiagnosed. This, coupled with the continuing increase in obesity, means that undiagnosed individuals will be presenting for surgery on a frequent basis. A mechanism for screening prior to surgery is needed to identify these undiagnosed patients. Singh³ evaluated 819 surgical patients with either an in-lab polysomnography or home sleep test. A total of 267 out of 708 (38%) of previously undiagnosed patients were found to have moderate/severe obstructive sleep apnea (AHI > 15). Of these patients, 92% were not identified preoperatively by surgeons; 60% were not identified by anesthesiologists. This suggests that routine clinical intake is often inadequate in identifying patients with obstructive sleep apnea.

The primary focus of screening is to reduce the frequency the unrecognized obstructive sleep apnea patient presents for surgery. This heightened awareness allows for an alteration in the approach to the perioperative management of these patients. This also provides an opportunity to intervene in poorly compliant or inadequately treated patients.

Important features of a screening tool should include: ease of understanding, ease of administration/scoring, concise, appropriate sensitivity/specificity through validation with sleep testing. A number of screening tools have been validated with sleep testing in the surgical population,  including the Berlin Questionnaire, STOP, STOP-BANG, ASA Checklist,^4-5 P-SAP Score⁶ and Sleep Apnea Clinical Score.⁷ There are strengths and weaknesses of each of these instruments; a detailed discussion is not feasible within the scope of this discussion,

The STOP and STOP-BANG were initially evaluated in the surgical population and have shown excellent sensitivity and negative predictive value with adequate specificity. The STOP-BANG is a series of eight questions; six are yes/no. Two questions require measurement of BMI and neck circumference. Three or more questions answered yes are consistent with high risk. More recently, Farney et al.⁸ demonstrated the greater probability of severe obstructive sleep apnea with a greater cumulative score on the STOP-BANG. This coupled with work from Chung⁹ has suggested a newer classification with 0-2 (low risk of OSA); 3-4 (intermediate risk of OSA); and 5-8 (high risk of OSA). Chung¹⁰ also demonstrated that the higher STOP-BANG score the higher the incidence of postoperative complications.

The Berlin Questionnaire, ASA Checklist, and STOP-BANG show no significant difference in predictive parameters, demonstrating approximately 25% to 30% of surgical patients will screen positive for obstructive sleep apnea (Chung 2008). This prevalence will vary depending on the surgical population studied with higher prevalence in bariatric and orthopedic surgery. Of these positive screens, the false positive rate is 15% to 20%.

There is no consensus regarding the optimal approach to patients with suspected sleep apnea. Patients may undergo diagnostic testing prior to surgery with treatment of moderate/severe sleep apnea. Additional factors such as urgency of surgery, severity of surgery and comorbid conditions influence this decision. Patients that screen positive could be treated with positive pressure therapy postoperatively. A third approach would be to monitor with evaluation and treatment provided after discharge. In this scenario, patients that experience difficulties postoperatively would be placed on positive pressure therapy.

Screening questionnaires show good sensitivity in identifying patients that are at risk for obstructive sleep apnea but do not identify patients at risk for postoperative complications. Peter Gali¹¹ has shown that screen positive patients that experience recurrent events in the PACU (hypoventilation, apnea, desaturation, or pain-sedation mismatch) were at higher risk for postoperative complications. This suggests that the course in the PACU may be most predictive of subsequent respiratory events. These patients may benefit from empiric treatment with positive pressure therapy although compliance is often problematic and there are no outcome studies demonstrating superiority of this approach. Higher scores on screening questionnaires and PACU course may improve risk stratification.

Postoperative monitoring is recommended although the intensity and duration of monitoring still needs to be determined. At present, oximetry alone is recommended until the patient is able to maintain oxygen saturation of greater than 90% on room air (ideally this should include a period of sleep).

Those patients that screen positive with complaints of non restorative sleep, fatigue, daytime sleepiness and/or those with cardiac, neurologic, or pulmonary comorbidities should be referred for sleep evaluation following discharge to determine if longitudinal care is required.

The implementation of a perioperative program requires the input of a number of stakeholders. Increased monitoring capability, alterations in flow and process of patient care, increased utilization of respiratory care practitioners, and determination of response strategies. Future challenges include improved ability to recognize at risk patients, determination of optimum monitoring protocols, improvement in compliance with positive pressure therapy when initiated in the postoperative period and seamless transition to outpatient management.

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References

1. Gupta, R. et al. Postoperative Complications in Patients With Obstructive Sleep Apnea Syndrome Undergoing Hip of Knee Replacement: A Case-Control Study. Mayo Clin Proc 2001; 76:897-905.
2. Kaw R, et al. Meta-analysis of the Association Between Obstructive Sleep Apnoea and Postoperative Outcome. Br J Anaesth 2012; 109:897-906.
3. Singh M, et al. Proportion of Surgical Patients with Undiagnosed Obstructive Sleep Apnoea. Br J Anaesth 2013; 110:629-36
4. Chung F, et al. STOP Questionnaire A Tool to Screen Patients for Obstructive Sleep Apnea. Anesthesiology 2008; 108: 812-821.
5. Chung, F, et al. Validation of the Berlin Questionnaire and American Society of Anesthesiologists Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients. Anesthesiology 2008; 108:822-830.
6. Ramachandran S, et al. Derivation and Validation of a Simple Perioperative Sleep Apnea Prediction Score. Anesth Analg 2010; 110:1007-15.
7. Gali B, et al. Identification of Patients at Risk for Postoperative Respiratory Complications Using a Preoperative Obstructive Sleep Apnea Screening Tool and Postanesthesia Care Assessment. Anesthesiology 2009; 110:869-877.
8. Farney RJ, et al. 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; 7:459-465.
9. Chung, F, et al. High STOP-BANG Score Indicates a High Probability of Obstructive Sleep Apnea. Br J Anaesth 2012; 108:768-775.
10. Chung F, et al. A Higher Score on STOP-BANG Questionnaire was Associated with a Higher Incidence of Postoperative Complications. American Thoracic Society: Abstract, A6063, 2011.
11. Gay PC. Sleep and Sleep Disordered Breathing in the Hospitalized Patient. Respir Care 2010; 55:1240-1254.

Keywords: Pharyngeal Muscles, Respiration, Sleep Apnea, Obstructive

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