Nontechnical Skills for Intraoperative Team Members.

Nontechnical skills, defined as the set of cognitive and social skills used by individuals and teams to reduce error and improve performance in complex systems, have become increasingly recognized as a key contributor to patient safety. Efforts to characterize, quantify, and teach nontechnical skills in the context of perioperative care continue to evolve. This review article summarizes the essential behaviors for safety, described in taxonomies for nontechnical skills assessments developed for intraoperative clinical team members (eg, surgeons, anesthesiologists, scrub practitioners, perfusionists). Furthermore, the authors describe emerging methods to advance understanding of the impact of nontechnical skills on perioperative outcomes.

Applying AI and Guidelines to Assist Medical Students in Recognizing Patients With Heart Failure: Protocol for a Randomized Trial.

BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is transforming both clinical practice and medical education. AI-based systems aim to improve the efficacy of clinical tasks, enhancing diagnostic accuracy and tailoring treatment delivery. As it becomes increasingly prevalent in health care for high-quality patient care, it is critical for health care providers to use the systems responsibly to mitigate bias, ensure effective outcomes, and provide safe clinical practices. In this study, the clinical task is the identification of heart failure (HF) prior to surgery with the intention of enhancing clinical decision-making skills. HF is a common and severe disease, but detection remains challenging due to its subtle manifestation, often concurrent with other medical conditions, and the absence of a simple and effective diagnostic test. While advanced HF algorithms have been developed, the use of these AI-based systems to enhance clinical decision-making in medical education remains understudied. OBJECTIVE: This research protocol is to demonstrate our study design, systematic procedures for selecting surgical cases from electronic health records, and interventions. The primary objective of this study is to measure the effectiveness of interventions aimed at improving HF recognition before surgery, the second objective is to evaluate the impact of inaccurate AI recommendations, and the third objective is to explore the relationship between the inclination to accept AI recommendations and their accuracy. METHODS: Our study used a 3 × 2 factorial design (intervention type × order of prepost sets) for this randomized trial with medical students. The student participants are asked to complete a 30-minute e-learning module that includes key information about the intervention and a 5-question quiz, and a 60-minute review of 20 surgical cases to determine the presence of HF. To mitigate selection bias in the pre- and posttests, we adopted a feature-based systematic sampling procedure. From a pool of 703 expert-reviewed surgical cases, 20 were selected based on features such as case complexity, model performance, and positive and negative labels. This study comprises three interventions: (1) a direct AI-based recommendation with a predicted HF score, (2) an indirect AI-based recommendation gauged through the area under the curve metric, and (3) an HF guideline-based intervention. RESULTS: As of July 2023, 62 of the enrolled medical students have fulfilled this study's participation, including the completion of a short quiz and the review of 20 surgical cases. The subject enrollment commenced in August 2022 and will end in December 2023, with the goal of recruiting 75 medical students in years 3 and 4 with clinical experience. CONCLUSIONS: We demonstrated a study protocol for the randomized trial, measuring the effectiveness of interventions using AI and HF guidelines among medical students to enhance HF recognition in preoperative care with electronic health record data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49842.

Differences between patients in whom physicians agree versus disagree about the preoperative diagnosis of heart failure.

STUDY OBJECTIVE: To quantify preoperative heart failure (HF) diagnostic agreement and identify characteristics of patients in whom physicians agreed versus disagreed about the diagnosis. DESIGN: Observational cohort study. SETTING: Patients undergoing major non-cardiac surgery at an academic center between 2015 and 2019. PATIENTS: 40,659 patients undergoing major non-cardiac surgery, among which a stratified subsample of 1018 patients with and without documented HF was reviewed. INTERVENTIONS: Via a panel of physicians frequently managing patients with HF (cardiologists, cardiac anesthesiologists, intensivists), detailed chart reviews were performed (two per patient; median review time 32 min per reviewer per patient) to render adjudicated HF diagnoses. MEASUREMENTS: Adjudicated diagnostic agreement measures (percent agreement, Krippendorf's alpha) and univariate comparisons (standardized differences) between patients in whom physicians agreed versus disagreed about the preoperative HF diagnosis. MAIN RESULTS: Among patients with documented HF, physicians agreed about the diagnosis in 80.0% of cases (consensus positive), disagreed in 13.8% (disagreement), and refuted the diagnosis in 6.3% (consensus negative). Conversely, among patients without documented HF, physicians agreed about the diagnosis in 88.0% (consensus negative), disagreed in 8.4% (disagreement), and refuted the diagnosis in 3.6% (consensus positive). The estimated agreement for the 40,659 cases was 91.1% (95% CI 88.3%-93.9%); Krippendorff's alpha was 0.77 (0.75-0.80). Compared to patients in whom physicians agreed about a HF diagnosis, patients in whom physicians disagreed exhibited fewer guideline-defined HF diagnostic criteria. CONCLUSIONS: Physicians usually agree about HF diagnoses adjudicated via chart review, although disagreement is not uncommon and may be partly explained by heterogeneous clinical presentations. Our findings inform preoperative screening processes by identifying patients whose characteristics contribute to physician disagreement via chart review. Clinical Trial Number / Registry URL: Not applicable.

Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis.

BACKGROUND: Acute kidney injury (AKI) is a frequent yet understudied postoperative total joint arthroplasty complication. This study aimed to describe cardiometabolic disease co-occurrence using latent class analysis, and associated postoperative AKI risk. METHODS: This retrospective analysis examined patients ≥18 years old undergoing primary total knee or hip arthroplasties within the US Multicenter Perioperative Outcomes Group of hospitals from 2008 to 2019. AKI was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Latent classes were constructed from eight cardiometabolic diseases including hypertension, diabetes, and coronary artery disease, excluding obesity. A mixed-effects logistic regression model was constructed for the outcome of any AKI and the exposure of interaction between latent class and obesity status adjusting for preoperative and intraoperative covariates. RESULTS: Of 81 639 cases, 4007 (4.9%) developed AKI. Patients with AKI were more commonly older and non-Hispanic Black, with more significant comorbidity. A latent class model selected three groups of cardiometabolic patterning, labelled 'hypertension only' (n=37 223), 'metabolic syndrome (MetS)' (n=36 503), and 'MetS+cardiovascular disease (CVD)' (n=7913). After adjustment, latent class/obesity interaction groups had differential risk of AKI compared with those in 'hypertension only'/non-obese. Those 'hypertension only'/obese had 1.7-fold increased odds of AKI (95% confidence interval [CI]: 1.5-2.0). Compared with 'hypertension only'/non-obese, those 'MetS+CVD'/obese had the highest odds of AKI (odds ratio 3.1, 95% CI: 2.6-3.7), whereas 'MetS+CVD'/non-obese had 2.2 times the odds of AKI (95% CI: 1.8-2.7; model area under the curve 0.76). CONCLUSIONS: The risk of postoperative AKI varies widely between patients. The current study suggests that the co-occurrence of metabolic conditions (diabetes mellitus, hypertension), with or without obesity, is a more important risk factor for acute kidney injury than individual comorbid diseases.

Leveraging observational data to identify targeted patient populations for future randomized trials.

Randomized controlled trials reported in the literature are often affected by poor generalizability, and pragmatic trials have become an increasingly utilized workaround approach to overcome logistical limitations and explore routine interventions demonstrating equipoise in clinical practice. Intravenous albumin, for example, is commonly administered in the perioperative setting despite lacking supportive evidence. Given concerns for cost, safety, and efficacy, randomized trials are needed to explore the clinical equipoise of albumin therapy in this setting, and we therefore present an approach to identifying populations exposed to perioperative albumin to encourage clinical equipoise in patient selection and optimize study design for clinical trials.

Patient-, Clinician-, and Institution-level Variation in Inotrope Use for Cardiac Surgery: A Multicenter Observational Analysis.

BACKGROUND: Conflicting evidence exists regarding the risks and benefits of inotropic therapies during cardiac surgery, and the extent of variation in clinical practice remains understudied. Therefore, the authors sought to quantify patient-, anesthesiologist-, and hospital-related contributions to variation in inotrope use. METHODS: In this observational study, nonemergent adult cardiac surgeries using cardiopulmonary bypass were reviewed across a multicenter cohort of academic and community hospitals from 2014 to 2019. Patients who were moribund, receiving mechanical circulatory support, or receiving preoperative or home inotropes were excluded. The primary outcome was an inotrope infusion (epinephrine, dobutamine, milrinone, dopamine) administered for greater than 60 consecutive min intraoperatively or ongoing upon transport from the operating room. Institution-, clinician-, and patient-level variance components were studied. RESULTS: Among 51,085 cases across 611 attending anesthesiologists and 29 hospitals, 27,033 (52.9%) cases received at least one intraoperative inotrope, including 21,796 (42.7%) epinephrine, 6,360 (12.4%) milrinone, 2,000 (3.9%) dobutamine, and 602 (1.2%) dopamine (non-mutually exclusive). Variation in inotrope use was 22.6% attributable to the institution, 6.8% attributable to the primary attending anesthesiologist, and 70.6% attributable to the patient. The adjusted median odds ratio for the same patient receiving inotropes was 1.73 between 2 randomly selected clinicians and 3.55 between 2 randomly selected institutions. Factors most strongly associated with increased likelihood of inotrope use were institutional medical school affiliation (adjusted odds ratio, 6.2; 95% CI, 1.39 to 27.8), heart failure (adjusted odds ratio, 2.60; 95% CI, 2.46 to 2.76), pulmonary circulation disorder (adjusted odds ratio, 1.72; 95% CI, 1.58 to 1.87), loop diuretic home medication (adjusted odds ratio, 1.55; 95% CI, 1.42 to 1.69), Black race (adjusted odds ratio, 1.49; 95% CI, 1.32 to 1.68), and digoxin home medication (adjusted odds ratio, 1.48; 95% CI, 1.18 to 1.86). CONCLUSIONS: Variation in inotrope use during cardiac surgery is attributable to the institution and to the clinician, in addition to the patient. Variation across institutions and clinicians suggests a need for future quantitative and qualitative research to understand variation in inotrope use affecting outcomes and develop evidence-based, patient-centered inotrope therapies.

Intraoperative Use of Albumin in Major Noncardiac Surgery: Incidence, Variability, and Association With Outcomes.

BACKGROUND: The impact of albumin use during major surgery is unknown, and a dearth of evidence governing its use in major noncardiac surgery has long precluded its standardization in clinical guidelines. OBJECTIVE: In this study, we investigate institutional variation in albumin use among medical centers in the United States during major noncardiac surgery and explore the association of intraoperative albumin administration with important postoperative outcomes. METHODS: The study is an observational retrospective cohort analysis performed among 54 U.S. hospitals in the Multicenter Perioperative Outcomes Group and includes adult patients who underwent major noncardiac surgery under general anesthesia between January 2014 and June 2020. The primary endpoint was the incidence of albumin administration. Secondary endpoints are acute kidney injury (AKI), net-positive fluid balance, pulmonary complications, and 30-day mortality. Albumin-exposed and albumin-unexposed cases were compared within a propensity score-matched cohort to evaluate associations of albumin use with outcomes. RESULTS: Among 614,215 major surgeries, predominantly iso-oncotic albumin was administered in 15.3% of cases and featured significant inter-institutional variability in use patterns. Cases receiving intraoperative albumin involved patients of higher American Society of Anesthesiologists physical status and featured larger infused crystalloid volumes, greater blood loss, and vasopressor use. Overall, albumin was most often administered at high-volume surgery centers with academic affiliation, and within a propensity score-matched cohort (n=153,218), the use of albumin was associated with AKI (aOR 1.24, 95% CI 1.20-1.28, P <0.001), severe AKI (aOR 1.45, 95% CI 1.34-1.56, P <0.001), net-positive fluid balance (aOR 1.18, 95% CI 1.16-1.20, P <0.001), pulmonary complications (aOR 1.56, 95% CI 1.30-1.86, P <0.001), and 30-day all-cause mortality (aOR 1.37, 95% CI 1.26-1.49, P <0.001). CONCLUSIONS: Intravenous albumin is commonly administered among noncardiac surgeries with significant inter-institutional variability in use in the United States. Albumin administration was associated with an increased risk of postoperative complications.

Postoperative Acute Kidney Injury by Age and Sex: A Retrospective Cohort Association Study.

BACKGROUND: Acute kidney injury (AKI) after noncardiac surgery is common and has substantial health impact. Preclinical and clinical studies examining the influence of sex on AKI have yielded conflicting results, although they typically do not account for age-related changes. The objective of the study was to determine the association of age and sex groups on postoperative AKI. The authors hypothesized that younger females would display lower risk of postoperative AKI than males of similar age, and the protection would be lost in older females. METHODS: This was a multicenter retrospective cohort study across 46 institutions between 2013 and 2019. Participants included adult inpatients without pre-existing end-stage kidney disease undergoing index major noncardiac, nonkidney/urologic surgeries. The authors' primary exposure was age and sex groups defined as females 50 yr or younger, females older than 50 yr, males 50 yr or younger, and males older than 50 yr. The authors' primary outcome was development of AKI by Kidney Disease-Improving Global Outcomes serum creatinine criteria. Exploratory analyses included associations of ascending age groups and hormone replacement therapy home medications with postoperative AKI. RESULTS: Among 390,382 patients, 25,809 (6.6%) developed postoperative AKI (females 50 yr or younger: 2,190 of 58,585 [3.7%]; females older than 50 yr: 9,320 of 14,4047 [6.5%]; males 50 yr or younger: 3,289 of 55,503 [5.9%]; males older than 50 yr: 11,010 of 132,447 [8.3%]). When adjusted for AKI risk factors, compared to females younger than 50 yr (odds ratio, 1), the odds of AKI were higher in females older than 50 yr (odds ratio, 1.51; 95% CI, 1.43 to 1.59), males younger than 50 yr (odds ratio, 1.90; 95% CI, 1.79 to 2.01), and males older than 50 yr (odds ratio, 2.06; 95% CI, 1.96 to 2.17). CONCLUSIONS: Younger females display a lower odds of postoperative AKI that gradually increases with age. These results suggest that age-related changes in women should be further studied as modifiers of postoperative AKI risk after noncardiac surgery.

Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study.

BACKGROUND: The automated acquisition of intraoperative patient temperature data via temperature probes leads to the possibility of producing a number of artifacts related to probe positioning that may impact these probes' utility for observational research. OBJECTIVE: We sought to compare the performance of two de novo algorithms for filtering such artifacts. METHODS: In this observational retrospective study, the intraoperative temperature data of adults who received general anesthesia for noncardiac surgery were extracted from the Multicenter Perioperative Outcomes Group registry. Two algorithms were developed and then compared to the reference standard-anesthesiologists' manual artifact detection process. Algorithm 1 (a slope-based algorithm) was based on the linear curve fit of 3 adjacent temperature data points. Algorithm 2 (an interval-based algorithm) assessed for time gaps between contiguous temperature recordings. Sensitivity and specificity values for artifact detection were calculated for each algorithm, as were mean temperatures and areas under the curve for hypothermia (temperatures below 36 C) for each patient, after artifact removal via each methodology. RESULTS: A total of 27,683 temperature readings from 200 anesthetic records were analyzed. The overall agreement among the anesthesiologists was 92.1%. Both algorithms had high specificity but moderate sensitivity (specificity: 99.02% for algorithm 1 vs 99.54% for algorithm 2; sensitivity: 49.13% for algorithm 1 vs 37.72% for algorithm 2; F-score: 0.65 for algorithm 1 vs 0.55 for algorithm 2). The areas under the curve for time × hypothermic temperature and the mean temperatures recorded for each case after artifact removal were similar between the algorithms and the anesthesiologists. CONCLUSIONS: The tested algorithms provide an automated way to filter intraoperative temperature artifacts that closely approximates manual sorting by anesthesiologists. Our study provides evidence demonstrating the efficacy of highly generalizable artifact reduction algorithms that can be readily used by observational studies that rely on automated intraoperative data acquisition.

Limited clinical utility for GWAS or polygenic risk score for postoperative acute kidney injury in non-cardiac surgery in European-ancestry patients.

BACKGROUND: Prior studies support a genetic basis for postoperative acute kidney injury (AKI). We conducted a genome-wide association study (GWAS), assessed the clinical utility of a polygenic risk score (PRS), and estimated the heritable component of AKI in patients who underwent noncardiac surgery. METHODS: We performed a retrospective large-scale genome-wide association study followed by a meta-analysis of patients who underwent noncardiac surgery at the Vanderbilt University Medical Center ("Vanderbilt" cohort) or Michigan Medicine, the academic medical center of the University of Michigan ("Michigan" cohort). In the Vanderbilt cohort, the relationship between polygenic risk score for estimated glomerular filtration rate and postoperative AKI was also tested to explore the predictive power of aggregating multiple common genetic variants associated with AKI risk. Similarly, in the Vanderbilt cohort genome-wide complex trait analysis was used to estimate the heritable component of AKI due to common genetic variants. RESULTS: The study population included 8248 adults in the Vanderbilt cohort (mean [SD] 58.05 [15.23] years, 50.2% men) and 5998 adults in Michigan cohort (56.24 [14.76] years, 49% men). Incident postoperative AKI events occurred in 959 patients (11.6%) and in 277 patients (4.6%), respectively. No loci met genome-wide significance in the GWAS and meta-analysis. PRS for estimated glomerular filtration rate explained a very small percentage of variance in rates of postoperative AKI and was not significantly associated with AKI (odds ratio 1.050 per 1 SD increase in polygenic risk score [95% CI, 0.971-1.134]). The estimated heritability among common variants for AKI was 4.5% (SE = 4.5%) suggesting low heritability. CONCLUSION: The findings of this study indicate that common genetic variation minimally contributes to postoperative AKI after noncardiac surgery, and likely has little clinical utility for identifying high-risk patients.

Identification of intraoperative management strategies that have a differential effect on patients with reduced left ventricular ejection fraction: a retrospective cohort study.

BACKGROUND: There are few data to guide the intraoperative management of patients with reduced left ventricular ejection fraction (LVEF). This study aimed to describe how patients with reduced LVEF are managed differently and to identify and treatments had a different risk profile in this population. METHODS: We performed a retrospective cohort study of adult patients who underwent general anesthesia for non-cardiac surgery. The effect of anesthesia medications and fluid balance was compared between those with and without a reduced preoperative LVEF. The primary outcome was a composite of acute kidney injury, myocardial injury, pulmonary complications, and 30-day mortality. Multivariable logistic regression was used to adjust for confounders. Treatments that affected patients with reduced LVEF differently were defined as those associated with the primary outcome that also had a significant interaction with LVEF. RESULTS: A total of 9420 patients were included. Patients with reduced LVEF tended to have a less positive fluid balance. Etomidate, calcium, and phenylephrine were use more frequently, while propofol and remifentanil were used less frequently. Remifentanil affected patients with reduced LVEF differently than those without (interaction term OR 2.71, 95% CI 1.30-5.68, p = 0.008). While the use of remifentanil was associated with fewer complications in patients with normal systolic function (OR 0.54, 95% CI 0.42-0.68, p < 0.001), it was associated with an increase in complications in patients with reduced LVEF (OR = 3.13, 95% CI 3.06-5.98, p = 0.026). CONCLUSIONS: Patients with a reduced preoperative LVEF are treated differently than those with a normal LVEF when undergoing non-cardiac surgery. An association was found between the use of remifentanil and an increase in postoperative adverse events that was unique to this population. Future research is needed to determine if this relationship is secondary to the medication itself or reflects a difference in how remifentanil is used in patients with reduced LVEF.

Prediction of Postoperative Deterioration in Cardiac Surgery Patients Using Electronic Health Record and Physiologic Waveform Data.

BACKGROUND: Postoperative hemodynamic deterioration among cardiac surgical patients can indicate or lead to adverse outcomes. Whereas prediction models for such events using electronic health records or physiologic waveform data are previously described, their combined value remains incompletely defined. The authors hypothesized that models incorporating electronic health record and processed waveform signal data (electrocardiogram lead II, pulse plethysmography, arterial catheter tracing) would yield improved performance versus either modality alone. METHODS: Intensive care unit data were reviewed after elective adult cardiac surgical procedures at an academic center between 2013 and 2020. Model features included electronic health record features and physiologic waveforms. Tensor decomposition was used for waveform feature reduction. Machine learning-based prediction models included a 2013 to 2017 training set and a 2017 to 2020 temporal holdout test set. The primary outcome was a postoperative deterioration event, defined as a composite of low cardiac index of less than 2.0 ml min-1 m-2, mean arterial pressure of less than 55 mmHg sustained for 120 min or longer, new or escalated inotrope/vasopressor infusion, epinephrine bolus of 1 mg or more, or intensive care unit mortality. Prediction models analyzed data 8 h before events. RESULTS: Among 1,555 cases, 185 (12%) experienced 276 deterioration events, most commonly including low cardiac index (7.0% of patients), new inotrope (1.9%), and sustained hypotension (1.4%). The best performing model on the 2013 to 2017 training set yielded a C-statistic of 0.803 (95% CI, 0.799 to 0.807), although performance was substantially lower in the 2017 to 2020 test set (0.709, 0.705 to 0.712). Test set performance of the combined model was greater than corresponding models limited to solely electronic health record features (0.641; 95% CI, 0.637 to 0.646) or waveform features (0.697; 95% CI, 0.693 to 0.701). CONCLUSIONS: Clinical deterioration prediction models combining electronic health record data and waveform data were superior to either modality alone, and performance of combined models was primarily driven by waveform data. Decreased performance of prediction models during temporal validation may be explained by data set shift, a core challenge of healthcare prediction modeling.

Prediction of postoperative cardiac events in multiple surgical cohorts using a multimodal and integrative decision support system.

Postoperative patients are at risk of life-threatening complications such as hemodynamic decompensation or arrhythmia. Automated detection of patients with such risks via a real-time clinical decision support system may provide opportunities for early and timely interventions that can significantly improve patient outcomes. We utilize multimodal features derived from digital signal processing techniques and tensor formation, as well as the electronic health record (EHR), to create machine learning models that predict the occurrence of several life-threatening complications up to 4 hours prior to the event. In order to ensure that our models are generalizable across different surgical cohorts, we trained the models on a cardiac surgery cohort and tested them on vascular and non-cardiac acute surgery cohorts. The best performing models achieved an area under the receiver operating characteristic curve (AUROC) of 0.94 on training and 0.94 and 0.82, respectively, on testing for the 0.5-hour interval. The AUROCs only slightly dropped to 0.93, 0.92, and 0.77, respectively, for the 4-hour interval. This study serves as a proof-of-concept that EHR data and physiologic waveform data can be combined to enable the early detection of postoperative deterioration events.

Optimizing the Design and Analysis of Future AKI Trials.

AKI is a complex clinical syndrome associated with an increased risk of morbidity and mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical trials have been inconclusive, failing to detect clinically important treatment effects at predetermined statistical thresholds. Heterogeneity in the pathobiology, etiology, presentation, and clinical course of AKI remains a key challenge in successfully testing new approaches for AKI prevention and treatment. This article, derived from the "AKI" session of the "Kidney Disease Clinical Trialists" virtual workshop held in October 2021, reviews barriers to and strategies for improving the design and implementation of clinical trials in patients with, or at risk of, developing AKI. The novel approaches to trial design included in this review span adaptive trial designs that increase the knowledge gained from each trial participant; pragmatic trial designs that allow for the efficient enrollment of sufficiently large numbers of patients to detect small, but clinically significant, treatment effects; and platform trial designs that use one trial infrastructure to answer multiple clinical questions simultaneously. This review also covers novel approaches to clinical trial analysis, such as Bayesian analysis and assessing heterogeneity in the response to therapies among trial participants. We also propose a road map and actionable recommendations to facilitate the adoption of the reviewed approaches. We hope that the resulting road map will help guide future clinical trial planning, maximize learning from AKI trials, and reduce the risk of missing important signals of benefit (or harm) from trial interventions.

Multicentre analysis of practice patterns regarding benzodiazepine use in cardiac surgery.

BACKGROUND: There is controversy regarding optimal use of benzodiazepines during cardiac surgery, and it is unknown whether and to what extent there is variation in practice. We sought to describe benzodiazepine use and sources of variation during cardiac surgeries across patients, clinicians, and institutions. METHODS: We conducted an analysis of adult cardiac surgeries across a multicentre consortium of USA academic and private hospitals from 2014 to 2019. The primary outcome was administration of a benzodiazepine from 2 h before anaesthesia start until anaesthesia end. Institutional-, clinician-, and patient-level variables were analysed via multilevel mixed-effects models. RESULTS: Of 65 508 patients cared for by 825 anaesthesiology attending clinicians (consultants) at 33 institutions, 58 004 patients (88.5%) received benzodiazepines with a median midazolam-equivalent dose of 4.0 mg (inter-quartile range [IQR], 2.0-6.0 mg). Variation in benzodiazepine dosage administration was 54.7% attributable to institution, 14.7% to primary attending anaesthesiology clinician, and 30.5% to patient factors. The adjusted median odds ratio for two similar patients receiving a benzodiazepine was 2.68 between two randomly selected clinicians and 4.19 between two randomly selected institutions. Factors strongly associated (adjusted odds ratio, <0.75, or >1.25) with significantly decreased likelihoods of benzodiazepine administration included older age (>80 vs ≤50 yr; adjusted odds ratio=0.04; 95% CI, 0.04-0.05), university affiliation (0.08, 0.02-0.35), recent year of surgery (0.42, 0.37-0.49), and low clinician case volume (0.44, 0.25-0.75). Factors strongly associated with significantly increased likelihoods of benzodiazepine administration included cardiopulmonary bypass (2.26, 1.99-2.55), and drug use history (1.29, 1.02-1.65). CONCLUSIONS: Two-thirds of the variation in benzodiazepine administration during cardiac surgery are associated with institutions and attending anaesthesiology clinicians (consultants). These data, showing wide variations in administration, suggest that rigorous research is needed to guide evidence-based and patient-centred benzodiazepine administration.

Opportunities Beyond the Anesthesiology Department: Broader Impact Through Broader Thinking.

Ensuring a productive clinical and research workforce requires bringing together physicians and communities to improve health, by strategic targeting of initiatives with clear and significant public health relevance. Within anesthesiology, the traditional perspective of the field's health impact has focused on providing safe and effective intraoperative care, managing critical illness, and treating acute and chronic pain. However, there are limitations to such a framework for anesthesiology's public health impact, including the transient nature of acute care episodes such as the intraoperative period and critical illness, and a historical focus on analgesia alone-rather than the complex psychosocial milieu-for pain management. Due to the often episodic nature of anesthesiologists' interactions with patients, it remains challenging for anesthesiologists to achieve their full potential for broad impact and leadership within increasingly integrated health systems. To unlock this potential, anesthesiologists should cultivate new clinical, research, and administrative roles within the health system-transcending traditional missions, seeking interdepartmental collaborations, and taking measures to elevate anesthesiologists as dynamic and trusted leaders. This special article examines 3 core themes for how anesthesiologists can enhance their impact within the health care system and pursue new collaborative health missions with nonanesthesiologist clinicians, researchers, and administrative leaders. These themes include (1) reframing of traditional anesthesiologist missions toward a broader health system-wide context; (2) leveraging departmental and institutional support for professional career development; and (3) strategically prioritizing leadership attributes to enhance system-wide anesthesiologist contributions to improving overall patient health.

Airway driving pressure is associated with postoperative pulmonary complications after major abdominal surgery: a multicentre retrospective observational cohort study.

Background: High airway driving pressure is associated with adverse outcomes in critically ill patients receiving mechanical ventilation, but large multicentre studies investigating airway driving pressure during major surgery are lacking. We hypothesised that increased driving pressure is associated with postoperative pulmonary complications in patients undergoing major abdominal surgery. Methods: In this preregistered multicentre retrospective observational cohort study, the authors reviewed major abdominal surgical procedures in 11 hospitals from 2004 to 2018. The primary outcome was a composite of postoperative pulmonary complications, defined as postoperative pneumonia, unplanned tracheal intubation, or prolonged mechanical ventilation for more than 48 h. Associations between intraoperative dynamic driving pressure and outcomes, adjusted for patient and procedural factors, were evaluated. Results: Among 14 218 qualifying cases, 389 (2.7%) experienced postoperative pulmonary complications. After adjustment, the mean dynamic driving pressure was associated with postoperative pulmonary complications (adjusted odds ratio for every 1 cm H2O increase: 1.04; 95% confidence interval [CI], 1.02-1.06; P<0.001). Neither tidal volume nor PEEP was associated with postoperative pulmonary complications. Increased BMI, shorter height, and female sex were predictors for higher dynamic driving pressure (ß=0.35, 95% CI 0.32-0.39, P<0.001; ß=-0.01, 95% CI -0.02 to 0.00, P=0.005; and ß=0.74, 95% CI 0.63-0.86, P<0.001, respectively). Conclusions: Dynamic airway driving pressure, but not tidal volume or PEEP, is associated with postoperative pulmonary complications in models controlling for a large number of risk predictors and covariates. Such models are capable of risk prediction applicable to individual patients.