Original ArticleObstructive sleep apnea screening and postoperative mortality in a large surgical cohort
Introduction
Obstructive sleep apnea (OSA) is associated with cardiovascular manifestations such as hypertension [1], congestive heart failure (CHF) [2], stroke [3], [4], coronary artery disease (CAD) [5], atrial fibrillation [6], and deep venous thrombosis [7]. OSA also is associated with sleepiness-related motor vehicle accidents [8]. Recent reports also demonstrate a high prevalence of chronic renal disease in patients with severe OSA without hypertension or diabetes mellitus (DM) [9], [10]. Furthermore, OSA has been associated with increased all-cause mortality [6]. Apart from the concerns relating to OSA itself, the frequent comorbidities associated with this condition are important considerations for all healthcare providers caring for patients with OSA [11].
There is a growing body of evidence suggesting that OSA may be an independent risk factor for perioperative morbidity. Patients with diagnosed OSA have an increased incidence of postoperative oxygen desaturation [12], cardiac ischemia, hemodynamic instability, and arrhythmias [13]. Furthermore, there are specific concerns that people with OSA might have increased sensitivity to the respiratory depressant effects of opioid analgesics, general anesthetics, and sedative medications [13], [14], [15]. Patients with OSA have been estimated to have twice the rate of hospitalization in the three years before OSA is diagnosed [16]. A recent investigation at Barnes-Jewish Hospital located in St. Louis, Missouri, found that an estimated 22% of adults presenting for inpatient surgery screened as high risk for OSA. Three quarters of these patients had not previously been diagnosed with OSA [17]. Therefore, the addition of a sleep apnea risk assessment to other screens commonly performed on hospital admission might be an appropriate public health initiative.
Many OSA screening tools that have been utilized in surgical patients, including the STOP (loud Snoring, daytime Tiredness, Observed apneas, and high blood Pressure) [18] STOP-BANG (STOP, plus body mass index [BMI], age, neck circumference, and gender) [18], [19], and American Society of Anesthesiologists (ASA) Checklist [20], and have been validated in this population against apnea–hypopnea index values from in-laboratory polysomnography. The Flemons [17], the Berlin [20], [21], and the Epworth Sleepiness Scale also have been used in this population [22]. As a whole, these screening tools are easy to use and vary in length, focus, and method of scoring. Presently, there is no convincing evidence to suggesting that any of these screening tools are superior in identifying patients at risk for perioperative morbidity or mortality. Because of the hypothesized potential for increased perioperative complications and treatment costs [23] associated with undiagnosed OSA, the ASA recommends preoperative evaluation for OSA prior to surgery [23]. The ASA further recommends that specific perioperative safety measures be implemented for patients with probable OSA.
In accordance with these ASA guidelines, routine preoperative screening for OSA was implemented and perioperative precautions were introduced at Barnes-Jewish Hospital for patients who screened as high risk. This initiative was followed by the B-J APNEAS (Barnes-Jewish Apnea Prevalence in Every Admission Study) investigation, which was designed as a prospective cohort study to test the hypothesis that either a prior diagnosis of OSA or a positive screen for OSA would be associated with an increased risk for early or intermediate postoperative morbidity and mortality from all causes. The primary purpose of our investigation was to compare the prognostic performance of the Berlin, Flemons, STOP, and STOP-BANG screening tools for sleep apnea among the B-J APNEAS patient population. Our study also examined the association of the performance of these four screening tools with key risk factors for postoperative morbidity and mortality. Specifically, we asked if screening positive on any of the four OSA screening tools was independently associated with an increased mortality rate up to one year post-operatively.
Section snippets
Study population
Unselected adult surgical patients at Barnes-Jewish Hospital between Feb 2006 and Apr 2010 who underwent preoperative OSA screening were prospectively enrolled. The Human Research Protection Office at Washington University School of Medicine (St. Louis, MO) approved the study. Because screening for OSA and the perioperative safety interventions were adopted as standard of care quality improvement initiatives, informed consent was not required. Obstetric patients and those under the age of 18
Results
Table 1 shows patient demographics and other health related information for the overall sample and by OSA risk status as defined by the four investigated screening tools. Overall, the sample included 14,962 patients. The mean age of the sample was 54.9 ± 15.7 years, the mean BMI was 30.4 ± 7.8 kg/m2, and 54.9% of the sample was female. The majority of patients were either white, n = 11,928 (80.2%) or African American, n = 2599 (17.4%). By all indicators, comorbidities were prevalent among these patients.
Discussion
Our study of unselected adult surgical patients supported previous reported findings that there is a high prevalence of undiagnosed OSA among patients presenting for surgery at Barnes Jewish Hospital [17], which is likely to be reflective of similar populations in the United States. Interestingly, 13% of patients presented with a prior diagnosis of OSA, suggesting that awareness in the medical community and the general population of OSA may be increasing. Depending on which screening tool is
Funding
Grant from the Barnes-Jewish Hospital Foundation # 01153-0308-01 to M. Avidan; TLRR024995, TL1 TR000449, UL1 TR000448 and UL1RR024992 to M. Willingham.
Conflict of Interest
The ICMJE Uniform Disclosure Form for Potential Conflicts of Interest associated with this article can be viewed by clicking on the following link: http://dx.doi.org/10.1016/j.sleep.2012.10.018.
Acknowledgment
The Institute of Quality Improvement, Research and Informatics (INQUIRI) at Washington University School of Medicine.
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These authors are contributed equally to this project.