The suitability of ambulatory surgery for a patient with obstructive sleep apnea (OSA) remains controversial because of concerns of increased perioperative complications including postdischarge death. A Society for Ambulatory Anesthesia task force on practice guidelines developed a consensus statement for the selection of patients with OSA scheduled for ambulatory surgery. A systematic review of the literature was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. There are 7 studies evaluating perioperative outcome in OSA patients undergoing ambulatory surgery and they are of limited quality.
Patients with a known diagnosis of OSA and optimized comorbid medical conditions can be considered for ambulatory surgery, if they are able to use a CPAP device in the postoperative period. Patients with a presumed diagnosis of OSA, based on screening tools such as the STOP-Bang questionnaire, and with optimized comorbid conditions, can be considered for ambulatory surgery, if postoperative pain can be managed predominantly with nonopioid analgesic techniques. On the other hand, OSA patients with nonoptimized comorbid medical conditions may not be good candidates for ambulatory surgery.
In this elegant study, Långsjö et al. use positron emission tomography (PET) imaging to identify the neuroanatomic sites that are activated during restoration of consciousness (ROC). ROC was tested using two different drugs (dexmedetomidine and propofol), and the study was carefully designed to distinguish between drug-induced epiphenomena and the actual neural correlates associated with ROC. For propofol anesthesia, the dose was decreased and the neural correlates of ROC were identified as the subjects regained consciousness. In contrast, the experiments with dexmedetomidine were performed without changing the drug dose, and gentle tactile and/or verbal stimulation were used to restore consciousness. Because the dose of dexmedetomidine was unchanged, this method allowed the investigators to tease apart the neural correlates associated with the behavioral state change vs. changes due to decreasing drug levels. In both cases, the areas of the brain that were ‘turned on’ during ROC were essentially the same: the anterior cingulate cortex, thalamus, hypothalamus, and brainstem. The implication is that emergence from general anesthesia occurs in a step-wise fashion, where only the activation of arousal-promoting deep brain structures is required for ROC, which apparently precedes the full recovery of neocortical processing.
This study sought to estimate the mortality risks associated with specific currently popular hypnotics in a matched cohort design of 10,529 pts who received hypnotic prescriptions and 23,676 matched controls that did not and followed for an average of 2.5 years. They used proportional hazards regression models and also tried to estimate the cancer risks associated with hypnotics. Data were adjusted for age, gender, smoking, body mass index, ethnicity, marital status, alcohol use and prior cancer. They found that pts prescribed any hypnotic had substantially elevated hazards of dying (mostly cardiovascular diseases) compared to those prescribed no hypnotics. Further, those in the upper third of regular hypnotic use had a significant elevation of incident cancer; HR=1.35 and were not attributable to pre-existing disease. The authors concluded that even when prescribed
This guideline is aimed to reduce the morbidity and mortality related to extubation by following a stepwise approach. From the fourth National Audit Project (NAP4) of the Royal College of Anaesthetists and the US closed claim study, it is vivid that extubation needs more attention. Compared to induction and intubation practice, lack of high grade clinical evidence in extubation practice has limited the authors to rely on expert opinion on many issues.
The guideline has three algorithms and each algorithm has four similar steps with different focus. The four steps are plan extubation, prepare for extubation, perform extubation and post extubation care. The core focus of the “basic algorithm” is stratification of extubation as “low risk” and “at risk”, based on the assessment of general and airway risk factors. The “low risk algorithm” mainly focusing on deep vs. awake extubation. The “at risk algorithm” has the key focus on awake vs. advanced techniques of extubation and postpone extubation vs. tracheostomy. The advanced techniques are laryngeal mask exchange, remifentanil technique and the airway exchange catheter.
This guideline has been formatted in such a way that would be useful in day to day practice. It is clearly emphasized that extubation is an elective process and planning is imperative.
This guideline provides otolaryngologists with evidence-based recommendations for using polysomnography (PSG) in assessing children, aged 2 to 18 years, with sleep-disordered breathing and are candidates for tonsillectomy, with or without adenoidectomy. The primary purpose of this guideline is to improve referral patterns for PSG among these patients.
The committee made the following recommendations: (1) before determining the need for tonsillectomy, the clinician should refer children with sleep-disordered breathing (SDB) for PSG if they exhibit certain complex medical conditions such as obesity, Down syndrome, craniofacial abnormalities, neuromuscular disorders, sickle cell disease, or mucopolysaccharidoses. (2) The clinician should advocate for PSG prior to tonsillectomy for SDB in children without any of the comorbidities listed in statement 1 for whom the need for surgery is uncertain or when there is discordance between tonsillar size on P.E. and the reported severity of SDB. (3) Clinicians should communicate PSG results to the anesthesiologist prior to the induction of anesthesia for tonsillectomy in a child with SDB. (4) Clinicians should admit children with OSA documented on PSG for inpatient, overnight monitoring after tonsillectomy if they are younger than age 3 or have severe OSA (AHI of 10 or more obstructive events/h, O2 saturation nadir <80%, or both). (5) In children for whom PSG is indicated to assess SDB prior to tonsillectomy, clinicians should obtain laboratory-based PSG, when available.
Can we identify a patient at high-risk for OSA by using a questionnaire? There are three questionnaires that have been validated in the surgical population to identify patients with underlying OSA: the Berlin questionnaire, STOP-Bang questionnaire, and ASA checklist.
The STOP-bang questionnaire consists of eight yes/no questions and is very easy to administer preoperatively. A score of ≥ 3 is very sensitive in identifying patients with moderate to severe OSA: 93% and 100% in identifying patients with moderate and severe OSA, respectively. However, at this cut-off, the questionnaire is not very specific and therefore includes many false positives.
In this study, Dr. Chung et al administered the STOP-bang questionnaire to patients undergoing elective inpatient surgery. These patients also underwent in-lab or type 2 home sleep studies. There were 746 patients with complete data for the analysis. The OSA was present in 68.4% with 29.9% mild, 20.5% moderate, and 18.0% severe OSA. For a STOP-Bang score of 5, the odds ratio (OR) for moderate/severe and severe OSA was 4.8 and 10.4, respectively. For STOP-Bang 6, the OR for moderate/ severe and severe OSA was 6.3 and 11.6, respectively. For STOP-Bang 7 and 8, the OR for moderate/severe and severe OSA was 6.9 and 14.9, respectively. Therefore, the STOP-bang questionnaire can be used to identify OSA in patients undergoing elective surgery. Interestingly, the likelihood of having moderate or severe OSA increased with each point increase in the STOP-bang score.
In this historical cohort study, the authors included patients undergoing non-cardiac surgery within 3 years of polysomnography. They excluded patients with age < 18 years, patients with history of upper airway surgery, and minor surgery under local or regional anesthesia. There were 471 patients who met the study criteria. The medical record of these patients was reviewed to identify postoperative complications including hypoxemia, respiratory failure, congestive heart failure, myocardial infarction, delirium, hospital length of stay, and death within 30 days.
There were 281 patients with OSA (AHI ≥ 5/hr) and 189 patients without OSA. For adjusting baseline differences in age, sex, race, BMI, type of anesthesia, American Society of Anesthesiology class and medical co-morbidities, the patients were classified into five quintiles according to a propensity score. Interestingly, OSA was associated with a higher incidence of postoperative hypoxemia (OR= 7.9), overall complications (OR= 6.9); ICU transfer (OR 4.43) and higher length of hospital stay, (OR= 1.65). There are many other studies that have shown OSA to be a risk factor for perioperative complications. Due to the increased prevalence of OSA in surgical population, it is very important to identify these patients preoperatively.
Studies on perioperative outcomes in patients with sleep apnea and pulmonary hypertension are rare and existing analyses are limited primarily by insufficient sample size. Utilizing nationally representative data collected for the Nationwide Inpatient Sample, the largest all-payer database in the U.S., we were able to perform two studies determining the impact of 1) obstructive sleep apnea (OSA) and 2) pulmonary hypertension on in-hospital complications.
We determined that both orthopedic and general surgical patients suffering from OSAhad increased risk of pulmonary adverse events, including adult respiratory distress syndrome (ORs 2.39 and 1.58), aspiration pneumonia (ORs1.41 and 1.37), and the need for mechanical ventilation (ORs 5.20 and 1.95) vs. non-OSA patients. OSApatients undergoing hip or knee arthroplasty were also more likely to suffer from perioperative pulmonary embolism compared to non-OSA patients (OR 1.22).
When matching patients with pulmonary hypertension with those without the disease, the former exhibited significantly higher perioperative rates of complications and mortality. These findings confirm the long held believe amongst clinicians, that patients with OSA and pulmonary hypertension indeed represent at risk populations in the surgical setting.
They further support the hypothesis, that increased rates of pulmonary hypertension and right heart dysfunction among OSA patients may explain worse outcomes, especially in the orthopedic patients. Here, embolization of bone marrow and cement during instrumention of the joint may lead to increased risk of lung injury, and worsening of right heart dysfunction resulting in chamber dilatation, venostasis and subsequently increased risk for thromboembolism.
Editorial: Bateman B, Eikermann M. Anesthesiology 2012;116: AprilDOI:10.1097/ALN.0b013e31824b96e11
Can we predict whether a patient will develop postoperative delirium? Specifically are there medical conditions that can help predict this condition? In the study, “Obstructive Sleep Apnea and Incidence of Postoperative Delirium after Elective Knee Replacement in the Nondemented Elderly” the authors studied 106 healthy patients ≥ 65 years undergoing elective knee replacement surgery. They excluded patients with dementia and other central nervous system disorders. Despite patient exclusion, 25% developed postoperative delirium (POD), a value similar to other studies that did not have such stringent entry criteria. Delirium incidence, of mild severity, was highest on the second day after surgery, though had recovered by day 3. Obstructive sleep apnea (OSA) was the only significant predictor using multivariate analysis. Patient with delirium also had lower hemoglobin values but hemoglobin value was not retained in the multivariate analysis. In the accompanying editorial, “Obstructive Sleep Apnea Predicts Adverse Perioperative Outcome. Evidence for an Association between Obstructive Sleep Apnea and Delirium”, those authors noted that the mechanisms for the association betweenOSA and POD was not directly assessed, though airway collapse leading to episodes of hypoxia may be the reason. If there is a relationship between OSA and POD, might strategies to decrease OSA decrease the incidence of POD? More research is needed.