Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes

Development and validation of an instrument to predict prolonged length of stay in the postanesthesia care unit following ambulatory surgery

PURPOSE

We sought to develop and validate an Anticipated Surveillance Requirement Prediction Instrument (ASRI) for prediction of prolonged postanesthesia care unit length of stay (PACU-LOS, more than four hours) after ambulatory surgery.

METHODS

We analyzed hospital registry data from patients who received anesthesia care in ambulatory surgery centres (ASCs) of university-affiliated hospital networks in New York, USA (development and internal validation cohort [n = 183,711]) and Massachusetts, USA (validation cohort [n = 148,105]). We used stepwise backwards elimination to create ASRI.

RESULTS

The model showed discriminatory ability in the development, internal, and external validation cohorts with areas under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI], 0.82 to 0.83), 0.82 (95% CI, 0.81 to 0.83), and 0.80 (95% CI, 0.79 to 0.80), respectively. In cases started in the afternoon, ASRI scores ≥ 43 had a total predicted risk for PACU stay past 8 p.m. of 32% (95% CI, 31.1 to 33.3) vs 8% (95% CI, 7.9 to 8.5) compared with low score values (P-for-interaction < 0.001), which translated to a higher direct PACU cost of care of USD 207 (95% CI, 194 to 2,019; model estimate, 1.68; 95% CI, 1.64 to 1.73; P < 0.001) The effects of using the ASRI score on PACU use efficiency were greater in a free-standing ASC with no limitations on PACU bed availability.

CONCLUSION

We developed and validated a preoperative prediction tool for prolonged PACU-LOS after ambulatory surgery that can be used to guide scheduling in ambulatory surgery to optimize PACU use during normal work hours, particularly in settings without limitation of PACU bed availability.

Diagnostic Value of Neutrophil to Lymphocyte Ratio for Assessing Obstructive Sleep Apnea Risk in Surgical Patients

PURPOSE

Obstructive sleep apnea (OSA) is an important risk factor leading to perioperative complications in surgical patients. Neutrophil-to-lymphocyte ratio (NLR) is an important biomarker of increasing interest in recent years, and is used in the determination of systemic inflammatory response.

DESIGN

The aim of this study was to evaluate the risk of OSA and the relationship between OSA risk and NLR in surgical patients.

METHODS

The study was conducted in a tertiary care hospital between November 2021 and May 2022. The cross-sectional study included 604 patients who underwent surgery. OSA risk was evaluated with the STOP-Bang questionnaire in the preoperative evaluation in all patients. NLR was calculated as the ratio of neutrophil count to lymphocyte count.

FINDINGS

According to the STOP-Bang questionnaire, 62.3% of the patients had a high risk of OSA in the preoperative period. Patients who were male, elderly, obese, had hypertension, diabetes, chronic lung disease, and heart disease and polypharmacy were at greater risk of OSA. Patients at high risk of OSA had significantly higher NLR than patients at low risk of OSA. (2.65 vs 2.92, P.ß=.ß.024). NLR of 2.40 or higher predicted OSA risk with 58.8% sensitivity and 51.0% specificity (AUC.ß=.ß0.561) CONCLUSIONS: Most patients who were to undergo surgery had a high risk of OSA. NLR was higher in patients at high risk of OSA. Although the diagnostic efficacy is not high, NLR can be used to detect high OSA risk because it is a low-cost and easy to obtain biomarker.

The CHANGED Score-A New Tool for the Prediction of Insulin Dependency in Gestational Diabetes

Gestational diabetes (GDM) is a frequent complication during pregnancy. We aimed to develop a score to predict future insulin dependency in gestational diabetes (GDM). Data from 1611 patients from Charité Berlins gestational diabetes clinic from 2015 to 2022 were utilized. A stepwise backwards regression, including patient characteristics obtained at the initial presentation, was performed. Predictors examined included age, fasting blood glucose level, blood glucose levels one and two hours after oral glucose tolerance test, pre-pregnancy BMI, number of previous pregnancies and births, and fetal sex. The ideal cutoff value between high and low risk for insulin dependency was assessed and the score was internally validated. There were 1249 (77.5%) women diagnosed with dietary GDM and 362 (22.5%) were diagnosed with insulin-dependent GDM. The CHarité AssessmeNt of GEstational Diabetes (CHANGED) Score achieved an area under the curve of 0.77 (95% confidence interval 0.75-0.80; 0.75 in internal validation). The optimal cutoff value was calculated at a score value of 9 (72% sensitivity, 69% specificity). We developed an easily applicable tool to accurately predict insulin dependency in gestational diabetes. The CHANGED Score is routinely available and can potentially improve maternal and fetal outcomes.

Discharge Prediction for Patients Undergoing Inpatient Surgery: Development and validation of the DEPENDENSE score

BACKGROUND

A substantial proportion of patients undergoing inpatient surgery each year is at risk for postoperative institutionalization and loss of independence. Reliable individualized preoperative prediction of adverse discharge can facilitate advanced care planning and shared decision making.

METHODS

Using hospital registry data from previously home-dwelling adults undergoing inpatient surgery, we retrospectively developed and externally validated a score predicting adverse discharge. Multivariable logistic regression analysis and bootstrapping were used to develop the score. Adverse discharge was defined as in-hospital mortality or discharge to a skilled nursing facility. The model was subsequently externally validated in a cohort of patients from an independent hospital.

RESULTS

In total, 106 164 patients in the development cohort and 92 962 patients in the validation cohort were included, of which 16 624 (15.7%) and 7717 (8.3%) patients experienced adverse discharge, respectively. The model was predictive of adverse discharge with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% CI 0.87-0.88) in the development cohort and an AUC of 0.86 (95% CI 0.86-0.87) in the validation cohort.

CONCLUSION

Using preoperatively available data, we developed and validated a prediction instrument for adverse discharge following inpatient surgery. Reliable prediction of this patient centered outcome can facilitate individualized operative planning to maximize value of care.

What Factors Predict Adverse Discharge Disposition in Patients Older Than 60 Years Undergoing Lower-extremity Surgery? The Adverse Discharge in Older Patients after Lower-extremity Surgery (ADELES) Risk Score

BACKGROUND

Adverse discharge disposition, which is discharge to a long-term nursing home or skilled nursing facility is frequent and devastating in older patients after lower-extremity orthopaedic surgery. Predicting individual patient risk allows for preventive interventions to address modifiable risk factors and helps managing expectations. Despite a variety of risk prediction tools for perioperative morbidity in older patients, there is no tool available to predict successful recovery of a patient's ability to live independently in this highly vulnerable population.

QUESTIONS/PURPOSES

In this study, we asked: (1) What factors predict adverse discharge disposition in patients older than 60 years after lower-extremity surgery? (2) Can a prediction instrument incorporating these factors be applied to another patient population with reasonable accuracy? (3) How does the instrument compare with other predictions scores that account for frailty, comorbidities, or procedural risk alone?

METHODS

In this retrospective study at two competing New England university hospitals and Level 1 trauma centers with 673 and 1017 beds, respectively; 83% (19,961 of 24,095) of patients 60 years or older undergoing lower-extremity orthopaedic surgery were included. In all, 5% (1316 of 24,095) patients not living at home and 12% (2797 of 24,095) patients with missing data were excluded. All patients were living at home before surgery. The mean age was 72 ± 9 years, 60% (11,981 of 19,961) patients were female, 21% (4155 of 19,961) underwent fracture care, and 34% (6882 of 19,961) underwent elective joint replacements. Candidate predictors were tested in a multivariable logistic regression model for adverse discharge disposition in a development cohort of all 14,123 patients from the first hospital, and then included in a prediction instrument that was validated in all 5838 patients from the second hospital by calculating the area under the receiver operating characteristics curve (ROC-AUC).Thirty-eight percent (5360 of 14,262) of patients in the development cohort and 37% (2184 of 5910) of patients in the validation cohort had adverse discharge disposition. Score performance in predicting adverse discharge disposition was then compared with prediction scores considering frailty (modified Frailty Index-5 or mFI-5), comorbidities (Charlson Comorbidity Index or CCI), and procedural risks (Procedural Severity Scores for Morbidity and Mortality or PSS).

RESULTS

After controlling for potential confounders like BMI, cardiac, renal and pulmonary disease, we found that the most prominent factors were age older than 90 years (10 points), hip or knee surgery (7 or 8 points), fracture management (6 points), dementia (5 points), unmarried status (3 points), federally provided insurance (2 points), and low estimated household income based on ZIP code (1 point). Higher score values indicate a higher risk of adverse discharge disposition. The score comprised 19 variables, including socioeconomic characteristics, surgical management, and comorbidities with a cutoff value of ≥ 23 points. Score performance yielded an ROC-AUC of 0.85 (95% confidence interval 0.84 to 0.85) in the development and 0.72 (95% CI 0.71 to 0.73) in the independent validation cohort, indicating excellent and good discriminative ability. Performance of the instrument in predicting adverse discharge in the validation cohort was superior to the mFI-5, CCI, and PSS (ROC-AUC 0.72 versus 0.58, 0.57, and 0.57, respectively).

CONCLUSION

The Adverse Discharge in Older Patients after Lower Extremity Surgery (ADELES) score predicts adverse discharge disposition after lower-extremity surgery, reflecting loss of the ability to live independently. Its discriminative ability is better than instruments that consider frailty, comorbidities, or procedural risk alone. The ADELES score identifies modifiable risk factors, including general anesthesia and prolonged preoperative hospitalization, and should be used to streamline patient and family expectation management and improve shared decision making. Future studies need to evaluate the score in community hospitals and in institutions with different rates of adverse discharge disposition and lower income. A non-commercial calculator can be accessed at www.adeles-score.org.

LEVEL OF EVIDENCE

Level III, diagnostic study.

Effects of laparoscopic vs open abdominal surgery on costs and hospital readmission rate and its effect modification by surgeons' case volume

BACKGROUND

Laparoscopy provides a minimally invasive alternative to open abdominal surgery. Current data describing its association with hospital readmission and costs in relation to surgeon laparoscopic case volume is limited to smaller databases and subsets of operations.

METHODS

This retrospective cohort study of 23,285 adult abdominal operations from 2007 to 2015 compares 30-day readmission rate and costs between laparoscopic and open abdominal operations and examines effect modification by surgeon laparoscopic case volume. Outcomes were all-cause hospital readmission within 30 days after discharge and index hospital admission cost.

RESULTS

All-cause hospital readmission rates were significantly lower after laparoscopic abdominal operations compared with open operations (adjusted odds ratio [aOR] 0.56, 95% CI 0.46-0.69, p < 0.001) with a difference in readmission risk attributable to laparoscopic approach of - 4.0% (95% CI - 5.4 to - 2.6%) in complete-case analysis. Among surgeons with a high laparoscopic case volume, the estimated difference in readmission risk through laparoscopy was magnified (- 5.8%, 95% CI - 7.5 to - 4.1%) compared to low surgeon laparoscopic case volume (- 2.9%, 95% CI - 4.8 to -1.1%, p for interaction = 0.005). The estimated difference in costs of the index hospital admission attributable to laparoscopic approach was - $3869 (95% CI - $4200 to - $3538; adjusted incidence rate ratio 0.77, 95% CI 0.75-0.79, p < 0.001). Laparoscopy was followed by significantly lower rates of readmissions related to gastrointestinal (aOR 0.68, 95% CI 0.55-0.85, p = 0.001), wound complications (infection: aOR 0.33, 95% CI 0.23-0.47, p < 0.001; non-infectious: aOR 0.47, 95% CI 0.30-0.74, p = 0.001), and malignancy (aOR 0.68, 95% CI 0.55-0.85, p < 0.001). The findings remain robust after multiple imputation and sensitivity analyses.

CONCLUSIONS

Laparoscopy versus open abdominal surgery is associated with reduced hospital readmissions related to malignancy, gastrointestinal, and wound complications. Effect modification by higher laparoscopy case volume argues for continued proliferation of laparoscopy in abdominal surgeries.

Development of an Instrument for Preoperative Prediction of Adverse Discharge in Patients Scheduled for Cardiac Surgery

OBJECTIVE

Inability of home discharge occurs in nearly a third of patients undergoing cardiac surgery and is associated with increased mortality. The authors aimed to evaluate the incidence and risk factors for adverse discharge disposition (ADD) after cardiac surgery and develop a prediction tool for preoperative risk assessment.

DESIGN

This retrospective cohort study included adult patients undergoing cardiac surgery between 2010 and 2018. The primary outcome was ADD, defined as in-hospital mortality, discharge to a skilled nursing facility, or transfer to a long-term care hospital. The authors created a prediction tool using stepwise backward logistic regression and used 5-fold and leave-one-out cross-validation.

SETTING

University hospital network.

PARTICIPANTS

Adult patients living at home prior to surgery, who underwent coronary artery bypass grafting and/or valve procedures at the authors' institution.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A total of 3,760 patients were included in the final study cohort. The observed rate of ADD was 33.3%. The prediction model showed good discrimination and accuracy, with C-statistic of 0.78 (95% confidence interval [CI] 0.76-0.79) and unmodified Brier score of 0.177 (reliability 0.001). The final model comprised 14 predictors. Patients who experienced ADD were more likely to be older, of female sex, to have had higher length of hospital stay prior to surgery, and to have undergone emergency surgery.

CONCLUSIONS

The authors present an instrument for prediction of loss of the ability to live independently in patients undergoing cardiac surgery. The authors' score may be useful in identifying high-risk patients such that earlier coordination of care can be initiated in this vulnerable patient population.

The Impact of Postoperative Intensive Care Unit Admission on Postoperative Hospital Length of Stay and Costs: A Prespecified Propensity-Matched Cohort Study

BACKGROUND

In this prespecified cohort study, we investigated the influence of postoperative admission to the intensive care unit versus surgical ward on health care utilization among patients undergoing intermediate-risk surgery.

METHODS

Of adult surgical patients who underwent general anesthesia without an absolute indication for postoperative intensive care unit admission, 3530 patients admitted postoperatively to an intensive care unit were matched to 3530 patients admitted postoperatively to a surgical ward using a propensity score based on 23 important preoperative and intraoperative predictor variables. Postoperative hospital length of stay and hospital costs were defined as primary and secondary end points, respectively.

RESULTS

Among patients with low propensity for postoperative intensive care unit admission, initial triage to an intensive care unit was associated with increased postoperative length of stay (incidence rate ratio, 1.69 [95% CI, 1.59-1.79]; P < .001) and hospital costs (incidence rate ratio, 1.92 [95% CI, 1.81-2.03]; P < .001). By contrast, postoperative intensive care unit admission of patients with high propensity was associated with decreased postoperative length of stay (incidence rate ratio, 0.90 [95% CI, 0.85-0.95]; P < .001) and costs (incidence rate ratio, 0.92 [95% CI, 0.88-0.97]; P = .001). Decisions regarding postoperative intensive care unit resource utilization were influenced by individual preferences of anesthesiologists and surgeons.

CONCLUSIONS

In patients with an unclear indication for postoperative critical care, intensive care unit admission may negatively impact postoperative hospital length of stay and costs. Postoperative discharge disposition varies substantially based on anesthesia and surgical provider preferences but should optimally be driven by an objective assessment of a patient's status at the end of surgery.

The development and validation of the Score for the Prediction of Postoperative Respiratory Complications (SPORC-2) to predict the requirement for early postoperative tracheal re-intubation: a hospital registry study

Postoperative pulmonary complications are associated with an increase in mortality, morbidity and healthcare utilisation. The Agency for Healthcare Research and Quality recommends risk assessment for postoperative respiratory complications in patients undergoing surgery. In this hospital registry study of adult patients undergoing non-cardiac surgery between 2005 and 2017 at two independent healthcare networks, a prediction instrument for early postoperative tracheal re-intubation was developed and externally validated. This was based on the development of the Score for Prediction Of Postoperative Respiratory Complications. For predictor selection, stepwise backward logistic regression and bootstrap resampling were applied. Development and validation cohorts were represented by 90,893 patients at Partners Healthcare and 67,046 patients at Beth Israel Deaconess Medical Center, of whom 699 (0.8%) and 587 (0.9%) patients, respectively, had their tracheas re-intubated. In addition to five pre-operative predictors identified in the Score for Prediction Of Postoperative Respiratory Complications, the final model included seven additional intra-operative predictors: early post-tracheal intubation desaturation; prolonged duration of surgery; high fraction of inspired oxygen; high vasopressor dose; blood transfusion; the absence of volatile anaesthetic use; and the absence of lung-protective ventilation. The area under the receiver operating characteristic curve for the new score was significantly greater than that of the original Score for Prediction Of Postoperative Respiratory Complications (0.84 [95%CI 0.82-0.85] vs. 0.76 [95%CI 0.75-0.78], respectively; p < 0.001). This may allow clinicians to develop and implement strategies to decrease the risk of early postoperative tracheal re-intubation.

Effects of Opioids Given to Facilitate Mechanical Ventilation on Sleep Apnea After Extubation in the Intensive Care Unit

Study Objectives

Following extubation in the intensive care unit (ICU), upper airway (UA) edema and respiratory depressants may promote UA dysfunction. We tested the hypothesis that opioids increase the risk of sleep apnea early after extubation.

Methods

Fifty-six ICU patients underwent polysomnography the night after extubation. Airflow limitation during wakefulness was identified using bedside spirometry. Correlation and ordinal regression analyses were used to quantify the effects of preextubation opioid dose on postextubation apnea-hypopnea index (AHI) and severity of sleep apnea and whether or not inspiratory airway obstruction (ratio of maximum expiratory and inspiratory airflows at 50% of vital capacity [MEF50/MIF50] ≥ 1) during wakefulness predicts airway obstruction during sleep. Data were adjusted for age, gender, body mass index, as well as a generalized propensity score balanced for APACHE II, score for preoperative prediction of obstructive sleep apnea, duration of mechanical ventilation, chronic obstructive pulmonary disease, and a procedural severity score for morbidity.

Results

Sleep apnea (AHI ≥ 5) was present in 40 (71%) of the 56 patients. Morphine equivalent dose given 24 hours prior extubation predicted obstructive respiratory events during sleep (r = 0.35, p = .01) and sleep apnea (odds ratio [OR] 1.17; 95% confidence interval [CI] 1.02-1.34). Signs of inspiratory UA obstruction (MEF50/MIF50 ≥ 1) assessed by bedside spirometry were strongly associated with sleep apnea (OR 5.93; 95% CI 1.16-30.33).

Conclusions

High opioid dose given 24 hours prior to extubation increases the likelihood of postextubation sleep apnea in the ICU, particularly in patients with anatomical vulnerability following extubation.

Effects of low-dose intraoperative fentanyl on postoperative respiratory complication rate: a pre-specified, retrospective analysis

BACKGROUND

Fentanyl is one of the most frequently administered intraoperative drugs and may increase the risk of postoperative respiratory complications (PRCs).

METHODS

We performed a pre-specified analysis of 145 735 adult non-cardiac surgical cases under general anaesthesia. Using multivariable logistic regression, we evaluated the association of intraoperative fentanyl dose and PRCs within 3 days after surgery (defined as reintubation, respiratory failure, pneumonia, pulmonary oedema, or atelectasis). We examined effect modification by patient characteristics, surgical site, and anaesthetics used.

RESULTS

PRCs within 3 days after surgery occurred in 18 839 (12.9%) patients. In comparison with high intraoperative fentanyl doses [median: 3.85; inter-quartile range (IQR): 3.42-4.50 μg kg^-1, quartile 4 (Q4)], low intraoperative fentanyl dose [median: 0.80, IQR: 0.00-1.14 μg kg^-1, quartile 1 (Q1)] was significantly associated with lower odds of PRCs [Q1 vs Q4: 10.9% vs 16.2%; adjusted odds ratio (aOR) 0.79; 95% confidence intervals (CI) 0.75-0.84; P<0.001; adjusted absolute risk difference (aARD) -1.7%]. This effect was augmented by thoracic surgery (P for interaction <0.001; aARD -6.2%), high doses of inhalation anaesthetics (P for interaction=0.016; aARD -2.2%) and neuromuscular blocking agents (NMBAs) (P for interaction=0.001; aARD -3.4%). Exploratory analysis demonstrated that compared with no fentanyl, low-dose fentanyl was associated with lower rates of PRCs (decile 2 vs decile 1: aOR 0.82, CI 0.75-0.89, P<0.001).

CONCLUSIONS

Intraoperative low-dose fentanyl (about 60-120 μg for a 70 kg patient) was associated with lower risk of postoperative respiratory complications compared with both no fentanyl and high-dose fentanyl. Beneficial effects of low-dose fentanyl were magnified in specific patient subgroups.

CLINICAL TRIAL REGISTRATION

NCT03198208.

Preoperative Evaluation: Estimation of Pulmonary Risk Including Obstructive Sleep Apnea Impact

One in 4 deaths occurring within a week of surgery are related to pulmonary complications, making it the second most common serious morbidity after cardiovascular events. The most significant predictors of the postoperative pulmonary complications (PPCs) are American Society of Anesthesiologists physical status, advanced age, dependent functional status, surgical site, and duration of surgery. The overall risk of PPCs can be predicted using scores that incorporate readily available clinical data.

A narrative review of interventions for improving sleep and reducing circadian disruption in medical inpatients

Sleep and circadian disruptions are frequently observed in patients across hospital wards. This is alarming, since impaired nocturnal sleep and disruption of a normal circadian rhythm can compromise health and disturb processes involved in recovery from illness (eg, immune functions). With this in mind, the present narrative review discusses how patient characteristics (sleep disorders, anxiety, stress, chronotype, and disease), hospital routines (pain management, timing of medication, nocturnal vital sign monitoring, and physical inactivity), and hospital environment (light and noise) may all contribute to sleep disturbances and circadian misalignment in patients. We also propose hospital-based strategies that may help reduce sleep and circadian disruptions in patients admitted to the hospital.

Evaluation of Epworth Sleepiness Scale to Predict Obstructive Sleep Apnea in Morbidly Obese Patients and Increasing Its Utility

INTRODUCTION

Studies have shown that Epworth sleepiness scale (ESS) is not a good tool to predict obstructive sleep apnea (OSA). However, data regarding the accuracy of ESS in the prediction of OSA among morbidly obese patients are scarce.

METHODS

The study involved a retrospective review of the charts of the consecutive patients who underwent bariatric surgery at a tertiary care teaching hospital. All the patients underwent polysomnography (PSG) and undertook the ESS questionnaire. The sensitivity and specificity of ESS were calculated based on its correlation with the PSG findings. Furthermore, a new score was devised to improve the utility of ESS to predict OSA.

RESULTS

A total of 232 consecutive patients from January 2014 to July 2017 were included in the study. The mean age and body mass index (BMI) were 40.5 ± 11.8 years and 47.6 ± 7.3 kg/m², respectively. Among the 162 patients who had an ESS <10, 57.4% had moderate-to-severe OSA. The sensitivity of ESS to predict moderate-to-severe OSA was found to be 38.8% and the positive predictive value was 84.2% (positive likelihood ratio 2.82, 95% confidence interval = 1.57-5.06). A predictive score was identified as 0.031Age (years) +0.039BMI (kg/m²) + 0.038ESS + Gender (1 for male, 0 for female). The score had a sensitivity of 80% at a cutoff of 3.3.

CONCLUSIONS

Among the morbidly obese, ESS is a poor predictor of OSA. Its utility as a tool for prediction of moderate-to-severe OSA can be improved by use of a new formula incorporating age, gender, and BMI beside ESS.

Knowledge Gaps in the Perioperative Management of Adults with Obstructive Sleep Apnea and Obesity Hypoventilation Syndrome. An Official American Thoracic Society Workshop Report

The purpose of this workshop was to identify knowledge gaps in the perioperative management of obstructive sleep apnea (OSA) and obesity hypoventilation syndrome (OHS). A single-day meeting was held at the American Thoracic Society Conference in May, 2016, with representation from many specialties, including anesthesiology, perioperative medicine, sleep, and respiratory medicine. Further research is urgently needed as we look to improve health outcomes for these patients and reduce health care costs. There is currently insufficient evidence to guide screening and optimization of OSA and OHS in the perioperative setting to achieve these objectives. Patients who are at greatest risk of respiratory or cardiac complications related to OSA and OHS are not well defined, and the effectiveness of monitoring and other interventions remains to be determined. Centers involved in sleep research need to develop collaborative networks to allow multicenter studies to address the knowledge gaps identified below.

The obesity conundrum in sepsis

While the long-term negative effects of obesity on health is a well-studied phenomenon, its effects on acute illnesses seem to be the contrary. Several studies have indicated the possibility of an 'obesity paradox' in sepsis - where overweight and obese patients have better outcomes than normal weight patients. These meta-analyses including large numbers of patients across different countries raised an interesting but debatable topic. Results from meta-analyses of observational studies should be interpreted with caution, and a prove of association not be mistaken as prove of causality. Limitations common to such studies include inadequate adjustment for confounding and selection bias. More rigorous investigations to clarify any causal relationship between obesity and mortality in sepsis are needed.

The association of postoperative pulmonary complications in 109,360 patients with pressure-controlled or volume-controlled ventilation

We thought that the rate of postoperative pulmonary complications might be higher after pressure-controlled ventilation than after volume-controlled ventilation. We analysed peri-operative data recorded for 109,360 adults, whose lungs were mechanically ventilated during surgery at three hospitals in Massachusetts, USA. We used multivariable regression and propensity score matching. Postoperative pulmonary complications were more common after pressure-controlled ventilation, odds ratio (95%CI) 1.29 (1.21-1.37), p < 0.001. Tidal volumes and driving pressures were more varied with pressure-controlled ventilation compared with volume-controlled ventilation: mean (SD) variance from the median 1.61 (1.36) ml.kg^-1 vs. 1.23 (1.11) ml.kg^-1 , p < 0.001; and 3.91 (3.47) cmH₂ O vs. 3.40 (2.69) cmH₂ O, p < 0.001. The odds ratio (95%CI) of pulmonary complications after pressure-controlled ventilation compared with volume-controlled ventilation at positive end-expiratory pressures < 5 cmH₂ O was 1.40 (1.26-1.55) and 1.20 (1.11-1.31) when ≥ 5 cmH₂ O, both p < 0.001, a relative risk ratio of 1.17 (1.03-1.33), p = 0.023. The odds ratio (95%CI) of pulmonary complications after pressure-controlled ventilation compared with volume-controlled ventilation at driving pressures of < 19 cmH₂ O was 1.37 (1.27-1.48), p < 0.001, and 1.16 (1.04-1.30) when ≥ 19 cmH₂ O, p = 0.011, a relative risk ratio of 1.18 (1.07-1.30), p = 0.016. Our data support volume-controlled ventilation during surgery, particularly for patients more likely to suffer postoperative pulmonary complications.

Perioperative sleep apnea: a real problem or did we invent a new disease?

Depending on the subpopulation, obstructive sleep apnea (OSA) can affect more than 75% of surgical patients. An increasing body of evidence supports the association between OSA  and perioperative complications, but some data indicate important perioperative outcomes do not differ between patients with and without OSA. In this review we will provide an overview of the pathophysiology of sleep apnea and the risk factors for perioperative complications related to sleep apnea. We also discuss a clinical algorithm for the identification and management of OSA patients facing surgery.