Article

The use of practice guidelinesby the American Society ofAnesthesiologists for theidentification of surgical patientsat high risk of sleep apnea

Munish Munish1, Vandana Sharma1, Kaitlyn M Yarussi1,Andrew Sifain2, Jahan Porhomayon1 and Nader Nader1

AbstractAmerican Society of Anesthesiologists (ASA) has introduced a simple tool to assess the perioperative risk ofsurgery/anesthesia in patients with obstructive sleep apnea (OSA). We compared the surgical outcomes inpatients at high risk of OSA with the matched controls. This was a case–control study conducted on 3593surgical patients receiving a general anesthesia at a single institution. On the basis of a preoperative OSAscoring system using the ASA checklist, patients were classified as high-risk OSA (HR-OSA) or low-risk OSA(LR-OSA) groups. Apnea/hypopnea index of >5 h�1 during a formal preoperative sleep study was used toconfirm or rule out the diagnosis of OSA. Receiver operating characteristic curves were plotted to determinethe predictive values as well as sensitivity and specificity of the ASA tool in predicting HR-OSA. The HR-OSAgroup was matched with the patients in LR-OSA using the propensity scoring and logistic regression. Patientswere analyzed for premorbid conditions, intraoperative course and postoperative events using cross tabula-tion, logistic regression model and paired t test. The development of a composite respiratory complicationin the postoperative period was considered as the primary end point. The ASA risk tool was found to have95.1% sensitivity and 52.2% specificity. At a prevalence of 10%, the negative predictive value was 98.5%. Of the3593 patients, 306 were identified as HR-OSA. The HR-OSA group was found to have a higher incidence ofhypertension and diabetes preoperatively when compared with LR-OSA. Postoperatively, the HR-OSA grouphad higher incidence of hypoxia, reintubation, postoperative use of continuous positive airway pressure and alonger stay in the recovery room. The ASA checklist offers a highly sensitive tool to identify the patients at ahigher risk of OSA during the perioperative period. Patients at HR-OSA have a higher incidence of adverseevents in the postoperative period when compared with those with LR-OSA.

Introduction

Obstructive sleep apnea (OSA) is a clinical syndrome

characterized by repeated occlusions of upper airway

during sleep, resulting in sleep fragmentation and

nocturnal hypoxemia. Symptomatic OSA affects

approximately 2% and 4% of women and men,

respectively, but the overall prevalence of the sleep

disorder was estimated to be 9% for women and

24% for men between the ages of 30 and 60 years.1

In a survey study in elective surgical patients using

Berlin questionnaire,2 24% patients were found to

be at risk of OSA.3 Due to the associated airway

pathology and depressive effects of anesthetic

agents on respiration and pharyngeal muscle tone,

patients with OSA are at a high risk of respiratory

complications.4 In addition, airway management of

these patients has been shown to be challenging for

1 Department of Anesthesiology, University at Buffalo, Buffalo,NY, USA2 Department of Anesthesiology, University of Rochester,Rochester, NY, USA

Corresponding author:Nader Nader, University at Buffalo, VA Western NY HealthcareSystem, 3495 Bailey Ave, Buffalo NY 14215, USAEmail: nnader@buffalo.edu

Chronic Respiratory Disease9(4) 221–230ª The Author(s) 2012Reprints and permission:sagepub.co.uk/journalsPermissions.navDOI: 10.1177/1479972312458680crd.sagepub.com

the anesthesiologists in view of difficulty in secur-

ing the airway.5,6

Of concern is the fact that the majority of surgical

patients with OSA are undiagnosed. There are various

screening tools for the diagnosis of OSA in surgical

patients, but their validity for use in perioperative

setting is still under question. The Berlin question-

naire is a widely used tool for the detection of

OSA.2,3,7 The American Society of Anesthesiologists

(ASA) checklist8 is a consensus of the task force to

identify high-risk patients. This checklist consists of

12 items that include predisposing physical character-

istics, history of apparent airway obstruction during

sleep, daytime somnolence, snoring, tiredness,

observed stop breathing and blood pressure. STOP

questionnaire9 is also a concise and easy-to-use tool

to identify patients at risk of OSA.

An alternative scoring model combining both the

STOP questionnaire and BANG10,11 (body mass

index (BMI), age, neck circumference and gender)

further improves the sensitivity. Diagnostic sleep

studies, however, remain the gold standard for the

diagnosis of OSA,12 but can be inconvenient and time

consuming in the perioperative setting. Patients at

high risk of OSA may not actually carry a diagnosis

of OSA due to the lack of confirming sleep study and

sometimes the subtle symptoms, which the patients

may not recognize.

The primary objective of this study was to compare

the surgical outcomes in patients at high risk of OSA

with the control patients undergoing similar surgeries.

We hypothesized that the tool developed by the

ASAs’ task force8 reliably predicts the high-risk OSA

(HR-OSA), and thus, the incidence of postoperative

complications was higher among the high-risk

patients.

Methods

We conducted a retrospective case–control study on

patients who underwent surgery during the period

from September 2007 to September 2009. The study

was reviewed and approved by the Institutional

Review Board Committee at the VA Western New

York Healthcare System (VAWNYHCS), Buffalo,

New York. The approval number was 2010-00704.

Patient screening and risk assessment

All the ambulatory patients between the ages of 18

and 80 years arriving for an outpatient surgery or the

same day admission and who received general

anesthesia were included. Patients with regional

anesthesia or more than one surgery during this period

were excluded. At our institution, for the preoperative

evaluation of all the patients, we incorporated a preo-

perative protocol for annotating the OSA history with

the aid of a questionnaire based on the ASA checklist

(Appendix A). This preoperative evaluation was car-

ried out in a preoperative clinic by the anesthesia

nurse practitioners or an anesthesiologist, routinely

for the elective cases. In case of emergency surgeries,

the anesthesia residents or the anesthesiologists did

the evaluation before surgery. On the basis of ASA

checklist, the patients were assigned a risk score.

Patients with OSA risk score of �5 were identified

as HR-OSA and those with a score <5 were categor-

ized as low-risk OSA (LR-OSA). If a sleep study

(polysomnography) had been performed within the

past 5 years, the results were recorded and compared

with the ASA checklist scoring system. Additionally,

another sleep study was performed in symptomatic

patients with recent weight gain. The diagnosis of

OSA was confirmed if a patient had an apnea/hypop-

nea index (AHI) of >5 h�1. Patients who had a posi-

tive sleep study were recommended the continuous

positive airway pressure (CPAP) therapy, but the

compliance with this recommendation could not be

guaranteed. The patients already prescribed CPAP

were recommended to use their CPAP device during

their hospital stay. The respiratory therapist guaran-

teed their compliance.

Clinical data were collected by a detailed review of

the preexisting preoperative and clinical records by

the members of the research team (anesthesia resi-

dent, a research associate and a trained anesthesiolo-

gist) from the Computerized Patient Record System

database used at the VAWNYHCS. Demographic

data, ASA physical status (ASA-PS), airway assess-

ment on the basis of Mallampati et al. classification13

and existing comorbidities were obtained. From the

preoperative data, patients at HR-OSA and LR-OSA

were also identified. Intraoperative data include type,

invasiveness and duration of the surgical procedure,

type of anesthesia, type of airway method used and

the amount of opioids administered.

A composite respiratory complication includes

hypoxia, defined as one or more incidences of pulse

oximetry value of �90% on 2–3 L min�1 by nasal

cannula, in which reintubation and requirement of

mechanical ventilation during postoperative period

were considered as the primary end points. Addition-

ally, development of new onset atrial fibrillation for at

222 Chronic Respiratory Disease 9(4)

least 3 min; cardiac ischemia defined as ST-T wave

changes in the postoperative period; hemodynamic

instability defined as systolic blood pressure

<90 mm Hg or diastolic blood pressure <50 mm Hg

or a change >20% from the baseline; and myocardial

infarction, evident by electrocardiogram changes and

angina and confirmed by elevation of cardiac

enzymes, or evidence of cerebrovascular accident

on the basis of a new onset of neurological deficit

were recorded. Type of surgery was included in the

questionnaire for calculating the OSA risk and hence

was already considered for the classification of

patients. Since there were significantly more patients

in the ASA class 3/4 among the HR-OSA group com-

pared with the LR-OSA group (p ¼ 0.002), ASA-PS

was included as one the matching variables.

Duration of postanesthesia care unit (PACU),

1hospital stay and readmission rate within 24 h of dis-

charge from the ambulatory surgery unit were used as

the secondary outcome variables. The patients were

discharged from the PACU when they met the modi-

fied Aldrete scoring criteria.14 The patients who were

directly transferred to the intensive care unit (ICU) for

recovery were excluded from the analysis for the

duration of PACU stay but were included for other

variables. The anesthesia providers performing the

preoperative evaluation and assigning the risk score

were blinded to the clinical outcome.

Data measurement and statistical analysis

The preoperative comorbidities, intraoperative and

postoperative data were entered into the Microsoft

Excel Spreadsheet 2007 Inc. The NCSS Version

2007 (NCSS, LLC., Kaysville, Utah, USA) software

was used for the analysis. All continuous variables

were expressed as mean + SD and the categorical

variables were expressed as the percentage of patients

in the data. Receiver operating characteristic curves

were plotted to determine the predictive values, sensi-

tivity and specificity of the ASA tool in predicting

HR-OSA, using sleep studies with an AHI of >5 as the

gold standard diagnostic test. The complication rate

was compared between the two groups and a primary

outcome variable was defined as the occurrence of

composite postoperative respiratory event. All the

factors that had p < 0.1 on the basis of univariate anal-

ysis, age, airway surgery and ASA class were

included in calculating the propensity score. HR-

OSA patients were matched 1:1 with LR-OSA

patients using the propensity scores. Statistical

analyses were performed using Chi square test for

categorical variables, and two-sample paired t test

were performed for continuous variables before and

after data matching. Binary logistic regression was

used to find the predictive values of OSA in certain

comorbid conditions. Hazard ratio was calculated for

all comorbidities. A p < 0.05 was considered statisti-

cally significant.

Results

Of the 3593 patients studied, on the basis of patient

characteristics, 306 patients were identified as

HR-OSA and were compared with 3286 unmatched

patients in the LR-OSA group. After matching,

HR-OSA group was compared with an equal size of

matched LR-OSA controls. There was no significant

difference between the groups on the basis of gender,

age or race (Table 1).

In the HR-OSA group, 140 of 306 patients had an

AHI of >5 h�1 compared with 32 of 306 matched

LR-OSA patients with an AHI of >5 h�1. The area

under the curve was measured as 0.8 + 0.1

(p < 0.01). ASA risk assessment had 95.1% sensi-

tivity and 52.2% specificity. At a prevalence of

10%, the positive predictive value of this tool was

19%, while the negative predictive value was

98.5% (Figure 1).

HR-OSA patients had a higher prevalence of

comorbid conditions, that is, coronary artery disease,

hypertension and diabetes mellitus when compared

with the LR-OSA group (Figure 2). The incidence

of hypertension was 80.4% versus 68.6%,

(p < 0.001) and diabetes mellitus was 44.1% versus

27.1%, (p < 0.001) in HR-OSA group when compared

with the LR-OSA group (Table 2), respectively. How-

ever, no significant increase in the incidence of

chronic obstructive pulmonary disease (COPD)

among the HR-OSA patients was found. There were

more patients with higher Mallampati airway class13

(class 3 and 4) in the HR-OSA group compared with

the LR-OSA group (p < 0.01). Intraoperative airway

management was more likely to be attained by the tra-

cheal intubation in the HR-OSA group than the

matched LR-OSA group (73.4% vs. 62.2%; Table 3).

Postoperatively, the patients in the HR-OSA group

were found to have significantly higher incidence of

hypoxia (16.8% vs. 10.2%) and more frequently in

need of tracheal reintubation (4.9% vs. 0.9%) when

compared with those in the matched LR-OSA

controls (Table 4).

Munish et al. 223

Overall, the incidence of a composite adverse event

was 25.4% in the HR-OSA group and 17.4% in the

LR-OSA matched controls (p < 0.01). Multivariate

analysis was carried out using the composite respira-

tory event as the primary outcome. We found that

HR-OSA is an independent risk factor for the post-

operative respiratory event and increases the risk by

50%. Other than the OSA risk, the presence of COPDs

was also identified as an independent factor for the

development of hypoxia, postoperatively (Figure 3).

Fifteen patients from the HR-OSA group were reintu-

bated, while only two patients from the LR-OSA

group were reintubated in the postoperative period

(4.9% vs. 0.7%, p < 0.001) and transferred to the ICU

(Table 3). Additionally, there were more patients in

the HR-OSA group who needed postoperative use

of CPAP (7.2% vs. 1.3%, p ¼ 0.0003).

Patients in the HR-OSA group stayed in the PACU

for longer duration (113 + 54 min) when compared

with their matched cohort in the LR-OSA group

(99 + 52 min, p < 0.01). The likelihood of hospital

admission after surgery was similar in both the

groups. There was no difference between the

LR-OSA group and the HR-OSA group in overall

mortality, admission to hospital and the overall

lengths of hospital stay (11.3 + 18.6 days vs.

13.7 + 35.8 days).

Discussion

Our study demonstrates that the ASA checklist offers

a highly sensitive tool to identify the patients at high

risk of OSA during the perioperative period. This tool,

however, has a relatively low specificity that may lead

to false positive results. Our study showed that high

perioperative risk OSA translates into a greater

incidence of adverse events such as hypoxia in the

postoperative period.

Additionally, the incidence of reintubation was

higher in HR-OSA group. These patients were more

Table 1. Patient demographicsa

Before match After match

LR HRp Value

LR HRp ValueN ¼ 3286 N ¼ 307 N ¼ 306 N ¼ 306

Age 63.2 + 14.7 61.5 + 12.8 0.02 61.94 + 12.9 61.5 + 12.8 0.82GenderFemale 143 (4.4) 12 (3.9) 0.89 12 (3.9) 12 (3.9) 1.000Male 3142 (95.6) 295 (96.1) 294 (96.1) 294 (96.1)RaceBlack 418 (12.7) 36 (11.7) 45 (14.8) 36 (11.8)White 2830 (86.1) 267 (87.0) 0.86 256 (83.9) 265 (86.9) 0.670Othersb 38 (1.2) 4 (1.3) 4 (1.3) 4 (1.3)ASAPS-1 70 (2.1) 3 (1.0) 2 (0.7) 2 (0.7)PS-2 1033 (31.4) 68 (22.1) 62 (20.3) 68 (22.2)PS-3 1669 (50.8) 171 (55.7) 0.0020 167 (54.6) 171 (55.9) 0.498PS-4 504 (15.3) 63 (20.5) 75 (24.5) 63 (20.6)PS-5 10 (0.3) 2 (0.7) 0 (0.0) 2 (0.7)Airwayc

1 1952 (59.4) 140 (45.6) 167 (57.4) 133 (44.5)2 225 (6.8) 8 (2.6) 27 (9.3) 8 (2.7)3 960 (29.2) 133 (43.3) <0.001 80 (27.5) 132 (44.1) <0.0014 142 (4.3) 26 (8.5) 17 (5.8) 26 (8.7)CPAP use 34 (20.4) 133 (79.6) <0.001

HR: high risk; LR: low risk; CPAP: continuous positive airway pressure; ASA: American Society of Anesthesiologists; PS-1: physicalstatus 1 – a normal healthy patient; PS-2: physical status 2 – a patient with mild systemic disease; PS-3: physical status 3 – a patient withsevere systemic disease; PS-4: physical status 4 – a patient with severe systemic disease that is a constant threat to life; PS-5: physicalstatus 5 – a moribund patient who is not expected to survive without the operation.a Data are presented as mean + SD or N (%), as appropriate.b Others indicate Asians, Pacific islanders and Native Indians.c Airway indicates Mallampati classification of airway into four classes13.

224 Chronic Respiratory Disease 9(4)

likely to have a difficult airway, which has been

reported previously by other studies.6 This observa-

tion is probably due to the associated body habitus

and other physical characteristics. These reports,

however, failed to show any association with

increased incidence of reintubation. In the unmatched

data, more patients received tracheal intubation; this

could be due to the assumption that anesthesiologists

have a tendency for intubation in patients with an

anticipated difficult airway.

We found that hypertension, diabetes mellitus and

coronary artery diseases were more frequent among

the OSA population, and overall, the ASA-PS was

higher in OSA population due to the presence of these

comorbidities; therefore, we could not include these

in our matching criteria. Also with ASA-PS as a

matching criterion, we collectively included the

individual comorbidity variables. We also could not

match for BMI, as it was obviously higher in patients

at high risk of OSA. This is consistent with the liter-

ature as OSA has been linked to various comorbid-

ities and BMI tends to be higher in the OSA risk

patients.

There were two retrospective reviews on postopera-

tive complications in patients with an established

diagnosis of OSA. In a study by Liao and colleagues

on known OSA patients who underwent elective sur-

gery other than airway surgery, they found that

patients diagnosed with OSA have an increased inci-

dence of oxygen desaturation.15 Gupta et al. studied

patients with OSA undergoing orthopedic surgeries,

and found that OSA patients had higher incidence of

respiratory and cardiac complications in the post-

operative period. The length of hospital stay and

unplanned ICU admissions were also higher.16 We

were unable to demonstrate such an association

among our patients. Gupta and colleagues demon-

strated the length of stay at 6.8 + 2.8 days and

5.1 + 4.1 days for the OSA and the control groups,

respectively. We found no difference in the length

of stay between the HR-OSA and the LR-OSA

groups. The study by Gupta et al. was performed on

a smaller cohort of patients who only underwent

orthopedic surgeries, whereas in our study we

included all types of surgery including the airway.

The study by Gupta et al. was a fully retrospective

study, whereas we performed a retrospective review

on prospectively collected data. These may account

for a difference in the results attained.

Both the studies reported that the oxygen desatura-

tion is the most common respiratory complication in

the postoperative period. Sabers et al. showed that

Figure 1. ROC curves were plotted to determine the pre-dictive values, sensitivity and specificity of the ASA tool inpredicting HR-OSA and its related complications. The areaunder the curve was measured as 0.8 + 0.1(p < 0.01). ASArisk tool was found to have 95.1% sensitivity and 52.2% spe-cificity. At a prevalence of 10%, the positive predictive valueof this tool was 19%, while the negative predictive valuewas 98.5%. ROC: receiver operating characteristics; ASA:American Society of Anesthesiologists; HR-OSA: high riskobstructive sleep apnea.

Figure 2. Binary logistic regression analysis for predictivevalue of OSA for different comorbidities with odd ratiosand 95% confidence interval of OSA patients versus thosewith no OSA risk. CAD: coronary artery disease; CKD:chronic kidney disease; COPD: chronic obstructivepulmonary disease, DM: diabetes mellitus; OSA: obstruc-tive sleep apnea.

Munish et al. 225

Table 2. Preoperative comorbiditiesa

Before matching After matching

LR HRp Value

LR HRp ValueN ¼ 3286 N ¼ 307 N ¼ 306 N ¼ 306

CAD 837 (25.5) 101 (32.9) 0.004 83 (27.1) 101 (33.1) 0.106CKD 299 (9.1) 37 (12.1) 0.08 23 (7.5) 37 (12.1) 0.057A Fib 253 (7.7) 24 (7.8) 0.94 19 (6.2) 24 (7.8) 0.439HTN 2095 (63.8) 247 (80.5) <0.001 210 (68.6) 246 (80.4) <0.001Diabetes 862 (26.2) 136 (44.3) <0.001 83 (27.1) 135 (44.1) <0.001COPD 751 (22.9) 87 (28.3) 0.029 78 (25.5) 87 (28.5) 0.398

HR: high risk; LR: low risk; CAD: coronary artery disease; CKD: chronic kidney disease; A Fib: atrial fibrillation; HTN: hypertension;COPD: chronic airway obstructive disease.a Data are presented as N (%).

Table 3. Airway methoda

Before matching After matching

LR HRp Value

LR HRp ValueN ¼ 3286 N ¼ 307 N ¼ 306 N ¼ 306

Facemask 161 (4.9) 15 (4.9) 20 (6.6) 15 (4.9)ET Tube 2023 (62.2) 224 (73.4) <0.001b 202 (66.4) 223 (73.4) 0.17LMA 1071 (32.9) 66 (21.6) 82 (27.0) 66 (21.7)

LR: low risk; HR: high risk; ET: endotracheal; LMA: laryngeal mask airway.a Data are presented as N (%).b In the unmatched data, more patients received tracheal intubation; this could be due to the assumption that anesthesiologists have atendency for intubation in patients with anticipated difficult airway.

Table 4. Postoperative complicationsa

Before matching After matching

LR HRp Value

LR HRp ValueN ¼ 3286 N ¼ 307 N ¼ 306 N ¼ 306

CPAP use 22 (0.7) 23 (7.5) <0.001b 4 (1.3) 22 (7.2) <0.001b

Hypoxia 334 (10.2) 51 (16.6) <0.001b 31 (10.2) 51 (16.8) <0.01b

Reintubation 31 (0.9) 15 (4.9) <0.001b 2 (0.7) 15 (4.9) <0.001b

MI 15 (0.5) 0 (0.0) 0.24 3 (1.0) 0 (0.0) 0.08Ischemia 13 (0.4) 3 (1.0) 0.14 2 (0.7) 3 (1.0) 0.65A Fibrillation 67 (2.0) 9 (2.9) 0.30 5 (1.6) 9 (3.0) 0.28CVA 6 (0.2) 0 (0.0) 0.45 0 (0.0) 0 (0.0) NCInpatients 1955 (59.8) 209 (68.5) <0.001b 201 (65.9) 208 (68.4) 0.51Outpatients 1314 (40.2) 96 (31.5) 104 (34.1) 96 (31.6)Readmission 25 (0.8) 0 (0.0) 0.29 0 (0.0) 0 (0.0) NCICU admission 709 (21.6) 87 (28.3) <0.01b 85 (27.8) 87 (28.4) 0.89Death 471 (14.3) 49 (16.0) 0.43 56 (18.3) 49 (16) 0.45CMPEVENT 511 (15.6) 77 (25.1) <0.001b 53 (17.4) 77 (25.4) 0.01b

HR: high risk; LR: low risk; CPAP: continuous positive airway pressure; MI: myocardial infarction; A fib: atrial fibrillation; CVA:cerebrovascular accident; ICU: intensive care unit; CMPEVENT: composite respiratory event; NC: not calculated.a Data presented as mean + SD or N (%), as appropriate.b statistically significant.

226 Chronic Respiratory Disease 9(4)

in patients undergoing nonairway surgeries, the diag-

nosis of OSA was not a risk factor for the unplanned

admission.17 Since this study included less invasive

ambulatory procedures, projection of the results to the

general surgical procedures cannot be carried out. In

this study, we found that the patients at HR-OSA were

more likely to be admitted as inpatients when com-

pared with patients at LR-OSA; however, after match-

ing for comorbid conditions, this observation was not

significant.

Our study also supports the findings of Chung

et al., in which they found higher correlation between

the ASA checklist and the patients at high risk of

OSA.7 However, the majority of previous studies

including Chung et al. study enrolled the patients with

a confirmed diagnosis of OSA,7,15,16 whereas we used

the preoperative risk assessment tool developed by

the ASA to identify the relative risk of OSA during

perioperative period. We also observed that higher

number of patients in the HR-OSA group received

CPAP in the postoperative period. Considering the

fact that a higher number of HR-OSA patients were

using CPAP prior to their scheduled surgery, this

observation was not surprising.

An important limitation was the predominance of

male gender among the veterans. Preexisting litera-

ture suggests that OSA is a more prevalent condition

in males when compared with that of females.18 This

gender distribution may have contributed to higher

number of HR-OSA patients in our study. This was

a retrospective observational study and hence there

remain many limitations in the retrospective chart

review like incomplete or missing documentation,

poorly recorded information in certain cases and also

difficulty to ascertain the cause and effect relation-

ship. Another important limitation could be the fact

that the anesthesiologist was aware of the HR-OSA

patients preoperatively and therefore there is always

a chance for treatment bias in favor of the HR-OSA

patients regarding the postoperative CPAP use and

increased duration of PACU stay. From the HR group,

a higher number was already receiving CPAP in the

preoperative period and therefore continued in the

postoperative period.

We conclude that the patients with OSA have

higher incidence of perioperative adverse events,

which implies that we need to develop specific man-

agement strategies for OSA patients in the periopera-

tive period to reduce the economic burden on the

health care system. It is not feasible in the periopera-

tive period to get sleep studies done on every patient

due to the time constraints and inconvenience to the

patients. In this setting, screening the patients at the

time of preoperative visit, using simple questionnaires

as suggested by the ASA practice guidelines can help

identify the high risk patients and to take up specific

measures like early diagnosis and treatment initiation

and to reduced intra and postoperative opioid use;

alternative analgesic therapies can also be taken

beforehand to minimize the adverse perioperative out-

comes. More prospective studies on the perioperative

complications in OSA patients are needed. Also, the

efficacy of CPAP has not been established in the peri-

operative setting. We speculate that the utilization of

CPAP in high-risk patients will likely improve the

outcome and are highly warranted.

Figure 3. Hazard risk ratio for postoperative hypoxia with95% confidence intervals. Note that OSA risk and COPDare independent factors for a composite respiratory event(hypoxia, hypoventilation, reintubation and mechanicalventilation) but not any other comorbidity. CAD: coronaryartery disease, CKD: chronic kidney disease, COPD:chronic obstructive pulmonary disease, DM: diabetesmellitus; OSA: obstructive sleep apnea.

Munish et al. 227

Appendix A

Practice guidelines for the perioperative management of patients with obstructive sleep apnea:A report by the American Society of Anesthesiologists task force on perioperative managementof patients with obstructive sleep apnea8

Table 1. Identification and assessment of OSA: example

A. Clinical signs and symptoms suggesting the possibility of OSA1. Predisposing physical characteristics

a. BMI 35 kg/m2 [95th percentile for age and gender]a

b. Neck circumference 17 inches (men) or 16 inches (women)c. Craniofacial abnormalities affecting the airwayd. Anatomical nasal obstructione. Tonsils nearly touching or touching in the midline

2. History of apparent airway obstruction during sleep (two or more of the following are present; if patient lives aloneor sleep is not observed by another person, then only one of the following needs to be present)

a. Snoring (loud enough to be heard through closed door)b. Frequent snoringc. Observed pauses in breathing during sleepd. Awakens from sleep with choking sensatione. Frequent arousals from sleepf. [Intermittent vocalization during sleep]a

g. [Parental report of restless sleep, difficulty breathing, or struggling respiratory efforts during sleep]a

3. Somnolence (one or more of the following is present)a. Frequent somnolence or fatigue despite adequate ‘‘sleep’’b. Falls asleep easily in a nonstimulating environment (e.g., watching TV, reading, riding in or driving a car) despite

adequate ‘‘sleep’’c. [Parent or teacher comments that child appears sleepy during the day, is easily distracted, is overly aggressive, or

has difficulty concentrating]a

d. [Child is often difficult to arouse at usual awakening time]a

If a patient has signs or symptoms in two or more of the above categories, there is a significant probability that he or shehas OSA. The severity of OSA may be determined by a sleep study (see below). If a sleep study is not available, suchpatients should be treated as though they have moderate sleep apnea unless one or more of the signs or symptomsabove is severely abnormal (e.g. markedly increased BMI or neck circumference, respiratory pauses that are frighteningto the observer, patient regularly falls asleep within minutes after being left unstimulated), in which case they should betreated as though they have severe sleep apnea.

B. If a sleep study has been done, the results should be used to determine the perioperative anesthetic management of apatient. However, because sleep laboratories differ in their criteria for detecting episodes of apnea and hypopnea, theTask Force believes that the sleep laboratory’s assessment (none, mild, moderate or severe) should take precedenceover the actual AHI (the number of episodes of sleep disordered breathing per hour). If the overall severity is notindicated, it may be determined by using the table below:

Severity of OSA Adult AHI Pediatric AHINone 0–5 0Mild OSA 6–20 1–5Moderate OSA 21–40 6–10Severe OSA >40 >10

AHI: apnea-hypopnea index; BMI: body mass index; OSA: obstructive sleep apnea; TV: television.a Items in brackets refer to pediatric patients.

228 Chronic Respiratory Disease 9(4)

Funding

This research received no specific grant from any funding

agency in the public, commercial, or not-for-profit sectors.

References

1. Young T, Palta M, Dempsey J, et al. The occurrence of

sleep-disordered breathing among middle-aged adults.

New Engl J Med 1993; 328: 1230–1235.

2. Netzer NC, Stoohs RA, Netzer CM, et al. Using the

berlin questionnaire to identify patients at risk for the

sleep apnea syndrome. Ann Intern Med 1999; 131:

485–491.

3. Chung F, Ward B, Ho J, et al. Preoperative identifica-

tion of sleep apnea risk in elective surgical patients,

using the Berlin questionnaire. J Clin Anesth 2007;

19: 130–134.

4. Vasu TS, Doghramji K, Cavallazzi R, et al. Obstruc-

tive sleep apnea syndrome and postoperative compli-

cations: clinical use of the stop-bang questionnaire.

Arch Otolaryngol Head Neck Surg 2010; 136:

1020–1024.

5. Benumof JL. Obesity, sleep apnea, the airway and

anesthesia. Curr Opin Anaesthesiol 2004; 17: 21–30.

6. Hiremath AS, Hillman DR, James AL, et al. Relation-

ship between difficult tracheal intubation and obstruc-

tive sleep apnoea. Br J Anaesth 1998; 80: 606–611.

7. Chung F, Yegneswaran B, Liao P, et al. Validation of

the Berlin questionnaire and American society of

anesthesiologists checklist as screening tools for

Table 2. OSA scoring system: example

Points

A. Severity of sleep apnea based on sleep study (or clinical indicators if sleep study not available).Point score (0–3)a,b

Severity of OSA (Table 1)None 0Mild 1Moderate 2Severe 3

B. Invasiveness of surgery and anesthesia.Point score (0–3)Type of surgery and anesthesia

Superficial surgery under local or peripheral nerve block anesthesia without sedation 0Superficial surgery with moderate sedation or general anesthesia 1Peripheral surgery with spinal or epidural anesthesia (with no more than moderate sedation) 1Peripheral surgery with general anesthesia 2Airway surgery with moderate sedation 2Major surgery, general anesthesia 3Airway surgery, general anesthesia 3

C. Requirement for postoperative opioids.Point score (0–3)Opioid requirement

None 0Low-dose oral opioids 1High-dose oral opioids, parenteral or neuraxial opioids 3

D. Estimation of perioperative risk.Overall score ¼ the score for A plus the greater of the score for either B or C. Point score (0–6)c

A scoring system similar to this table may be used to estimate whether a patient is at increased perioperative risk ofcomplications from OSA. This example, which has not been clinically validated, is meant only as a guide, and clinicaljudgment should be used to assess the risk of an individual patient.

OSA: obstructive sleep apnea; CPAP: continuous positive airway pressure.a One point may be subtracted if a patient has been on CPAP or noninvasive positive-pressure ventilation before surgery and will beusing his or her appliance consistently during the postoperative period.b One point should be added if a patient with mild or moderate OSA also has a resting arterial carbon dioxide tension (PaCO2) greaterthan 50 mm Hg.c Patients with score of 4 may be at increased perioperative risk from OSA; patients with a score of 5 or 6 may be at significantlyincreased perioperative risk from OSA.

Munish et al. 229

obstructive sleep apnea in surgical patients. Anesthe-

siology 2008; 108: 822–830.

8. Gross JB, Bachenberg KL, Benumof JL, Caplan RA,

Connis RT, Cote CJ, et al. Practice guidelines for the

perioperative management of patients with obstructive

sleep apnea: a report by the american society of

anesthesiologists task force on perioperative manage-

ment of patients with obstructive sleep apnea. Anesthe-

siology 2006; 104: 1081–1093.

9. Chung F, Yegneswaran B, Liao P, et al. STOP ques-

tionnaire: a tool to screen patients for obstructive sleep

apnea. Anesthesiology 2008; 108: 812–821.

10. Gafsou B, Marsac L, Fournier JL, et al. Validation

of the STOP-bang questionnaire as screening tools

for obstructive sleep apnea in patients scheduled for

bariatric surgery: 1AP3-5. Eur J Anaesth 2010;

27(47): 13.

11. Ong T, Raudha S, Fook-Chong S, et al. Simplifying

STOP-bang: use of a simple questionnaire to screen for

OSA in an Asian population. Sleep Breath 2010; 14:

371–376.

12. Chung SAP, Yuan HP and Chung FF. A Systemic

review of obstructive sleep apnea and its implications

for anesthesiologists. Anesth Analg 2008; 107:

1543–1563

13. Mallampati S, Gatt S, Gugino L, et al. A clinical sign to

predict difficult tracheal intubation; a prospective

study. Can J Anesth 1985; 32: 429–434.

14. Aldrete JA and Kroulik D. A postanesthetic recovery

score. Anesth Analg 1970; 49: 924–934.

15. Liao P, Yegneswaran B, Vairavanathan S, et al. Post-

operative complications in patients with obstructive

sleep apnea: a retrospective matched cohort study. Can

J Anesth 2009; 56: 819–828.

16. Gupta RM, Parvizi J, Hanssen AD, et al. Postoperative

complications in patients with obstructive sleep apnea

syndrome undergoing hip or knee replacement: a

case-control study. Mayo Clin Proc 2001; 76: 897–905.

17. Sabers C, Plevak DJ, Schroeder DR, et al. The diagno-

sis of obstructive sleep apnea as a risk factor for unan-

ticipated admissions in outpatient surgery. Anesth

Analg 2003; 96: 1328–1335.

18. Redline S, Kump K, Tishler P, et al. Gender differ-

ences in sleep disordered breathing in a

community-based sample. Am J Respir Crit Care Med

1994; 149: 722–726.

230 Chronic Respiratory Disease 9(4)