2023 American Society of Anesthesiologists Practice Guidelines for Monitoring and Antagonism of Neuromuscular Blockade: A Report by the American Society of Anesthesiologists Task Force on Neuromuscular Blockade.

These practice guidelines provide evidence-based recommendations on the management of neuromuscular monitoring and antagonism of neuromuscular blocking agents during and after general anesthesia. The guidance focuses primarily on the type and site of monitoring and the process of antagonizing neuromuscular blockade to reduce residual neuromuscular blockade.

Five Decades of Trauma Anesthesiology.

We present a brief history of the scientific and educational development of trauma anesthesiology. Key milestones from the past 50 years are noted, as well as the current standing of the subspecialty and prospects for the future.

Scaling up quality in an anesthesia practice.

The resources necessary to improve anesthesia quality and meet reimbursement and regulatory thresholds are scarce, particularly for smaller practices. We examined how small practice integration into a firm with greater resources can facilitate improvements. A mixed-methods analysis was conducted using the data from the US Anesthesia Partners data warehouse, Merit-based Incentive Payment System (MIPS), commercial insurers' surgery length of stay (LOS) databases, anesthesia-specific patient satisfaction surveys, and interviews with practice leadership before and after integration. All integrated practices improved their quality improvement infrastructure and achieved higher MIPS scores, with increased clinician and leadership satisfaction. Patient satisfaction exceeded national benchmarks in all groups, based on 398 392 returned surveys in 2021. Hospital LOS for common operations was shorter, based on a statewide database. This case study demonstrates that partnership with an organization with greater resources can advance anesthesia quality.

In control or along for the ride? Lessons for anesthesiologists from air traffic control.

PURPOSE OF REVIEW: Anesthesia professionals work in an unpredictable, rapidly changing environment in which they are quickly diagnose and manage uncommon and life-threatening critical events. The perioperative environment has traditionally been viewed as a deterministic system in which outcomes can be predicted, but recent studies suggest that the operating room behaves more like a complex adaptive system, in which events can interact and connect with each other in unpredictable and unplanned ways. RECENT FINDINGS: The increasing complexity of the healthcare environment suggests that the complete elimination of human error is not possible. Complex clinical situations predispose to errors that are the result of high workload, decision making under stress, and poor team coordination. The theory behind complex adaptive systems differs from medicine's traditional approach to safety and highlights the importance of an institutional safety culture that encourages flexibility, adaptability, reporting and learning from errors. Instead of focusing on standardization and strict adherence to procedures, clinicians can improve safety by recognizing that unpredictable changes routinely occur in the work environment and learning how resilience can prevent adverse events. SUMMARY: A better understanding of automation, complexity, and resilience in a changing environment are essential steps toward the safe practice of anesthesia.

2022 American Society of Anesthesiologists Practice Guidelines for Management of the Difficult Airway.

The American Society of Anesthesiologists; All India Difficult Airway Association; European Airway Management Society; European Society of Anaesthesiology and Intensive Care; Italian Society of Anesthesiology, Analgesia, Resuscitation and Intensive Care; Learning, Teaching and Investigation Difficult Airway Group; Society for Airway Management; Society for Ambulatory Anesthesia; Society for Head and Neck Anesthesia; Society for Pediatric Anesthesia; Society of Critical Care Anesthesiologists; and the Trauma Anesthesiology Society present an updated report of the Practice Guidelines for Management of the Difficult Airway.

December Is Coming: A Time Trend Analysis of Monthly Variation in Adult Elective Anesthesia Caseload across Florida and Texas Locations of a Large Multistate Practice.

BACKGROUND: Anesthesia staffing models rely on predictable surgical case volumes. Previous studies have found no relationship between month of the year and surgical volume. However, seasonal events and greater use of high-deductible health insurance plans may cause U.S. patients to schedule elective surgery later in the calendar year. The hypothesis was that elective anesthesia caseloads would be higher in December than in other months. METHODS: This review analyzed yearly adult case data in Florida and Texas locations of a multistate anesthesia practice from 2017 to 2019. To focus on elective caseload, the study excluded obstetric, weekend, and holiday cases. Time trend decomposition analysis was used with seasonal variation to assess differences between December and other months in daily caseload and their relationship to age and insurance subgroups. RESULTS: A total of 3,504,394 adult cases were included in the analyses. Overall, daily caseloads increased by 2.5 ± 0.1 cases per day across the 3-yr data set. After adjusting for time trends, the average daily December caseload in 2017 was 5,039 cases (95% CI, 4,900 to 5,177), a 20% increase over the January-to-November baseline (4,196 cases; 95% CI, 4,158 to 4,235; P < 0.0001). This increase was replicated in 2018: 5,567 cases in December (95% CI, 5,434 to 5,700) versus 4,589 cases at baseline (95% CI, 4,538 to 4,641), a 21.3% increase; and in 2019: 6,103 cases in December (95% CI, 5,871 to 6,334) versus 5,045 cases at baseline (95% CI, 4,984 to 5,107), a 21% increase (both P < 0.001). The proportion of commercially insured patients and those aged 18 to 64 yr was also higher in December than in other months. CONCLUSIONS: In this 3-yr retrospective analysis, it was observed that, after accounting for time trends, elective anesthesia caseloads were higher in December than in other months of the year. Proportions of commercially insured and younger patients were also higher in December. When compared to previous studies finding no increase, this pattern suggests a recent shift in elective surgical scheduling behavior.

Impact of the Choice of Risk Model for Identifying Low-risk Patients Using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines.

WHAT WE ALREADY KNOW ABOUT THIS TOPIC: WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: The 2014 American College of Cardiology Perioperative Guideline recommends risk stratifying patients scheduled to undergo noncardiac surgery using either: (1) the Revised Cardiac Index; (2) the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator; or (3) the Myocardial Infarction or Cardiac Arrest calculator. The aim of this study is to determine how often these three risk-prediction tools agree on the classification of patients as low risk (less than 1%) of major adverse cardiac event. METHODS: This is a retrospective observational study using a sample of 10,000 patient records. The risk of cardiac complications was calculated for the Revised Cardiac Index and the Myocardial Infarction or Cardiac Arrest models using published coefficients, and for the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator using the publicly available website. The authors used the intraclass correlation coefficient and kappa analysis to quantify the degree of agreement between these three risk-prediction tools. RESULTS: There is good agreement between the American College of Surgeons National Surgical Quality Improvement Program and Myocardial Infarction or Cardiac Arrest estimates of major adverse cardiac events (intraclass correlation coefficient = 0.68, 95% CI: 0.66 to 0.70), while only poor agreement between (1) American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator and the Revised Cardiac Index (intraclass correlation coefficient = 0.37; 95% CI: 0.34 to 0.40), and (2) Myocardial Infarction or Cardiac Arrest and Revised Cardiac Index (intraclass correlation coefficient = 0.26; 95% CI: 0.23 to 0.30). The three prediction models disagreed 29% of the time on which patients were low risk. CONCLUSIONS: There is wide variability in the predicted risk of cardiac complications using different risk-prediction tools. Including more than one prediction tool in clinical guidelines could lead to differences in decision-making for some patients depending on which risk calculator is used.

Use of Survey and Delphi Process to Understand Trauma Anesthesia Care Practices.

BACKGROUND: Few trauma guidelines evaluate and recommend anesthesiology practices and there are no trauma anesthesia-specific guidelines. There is no information on how anesthesiologists perceive clinical practice patterns. Our objective was to understand the perceptions of anesthesiologists regarding trauma anesthesia practices. METHODS: A survey assessing anesthesia management of trauma patients was distributed to 21,491 anesthesiologists. A subset of 10 of these questions was subsequently reviewed by a trauma anesthesiology focus group through a 3-round web-based Delphi process. A question was deemed to have respondent consensus if the response with the highest percentage of agreement was unchanged between rounds 1 and 2. RESULTS: A total of 2360 anesthesiologists (11% response rate) responded to the survey. Results demonstrated that the practitioners' answers conflicted with existing surgical trauma society recommendations (ie, when to transfuse component therapy), and several areas that lacked any guidelines, resulted in response variability among anesthesiologists where not 1 answer achieved >75% agreement (ie, intubation technique of choice for patients with uncleared cervical spine). Thirteen trauma anesthesiologists participated in round 1 (response rate 100%), and 12 responded in rounds 2 and 3 (response rate 92%) of the Delphi process. None of the questions received 100% agreement. Consensus was achieved on 9 of 10 statements pertaining to trauma anesthesia care. Consensus was not reached on the intubating technique in a hemodynamically unstable patient with an uncleared cervical spine with deficits. Delphi participant opinion conflicted with existing guidelines on 2 statements: the use of cricoid pressure, and when to begin blood component therapy. CONCLUSIONS: There are several important areas of trauma anesthesia practice where guidelines do not exist and several where existing guidelines are not endorsed by the majority of practitioners who completed our survey. The lack of consensus on trauma anesthesia management and the variation in survey responses demonstrate a need to develop evidence-based trauma anesthesia guidelines.

Variability in Case Durations for Common Surgical Procedures.

BACKGROUND: Under the Merit-based Incentive Payment System, physician payment will be adjusted using a composite performance score that has 4 components, one of which is resource use. The objective of this exploratory study is to quantify the facility-level variation in surgical case duration for common surgeries to examine the feasibility of using surgical case duration as a performance metric. METHODS: We used data from the National Anesthesia Clinical Outcomes Registry on 404,987 adult patients undergoing one of 6 general surgical or orthopedic procedures: laparoscopic appendectomy, laparoscopic cholecystectomy, laparoscopic cholecystectomy with intraoperative cholangiogram, knee arthroscopy, laminectomy, and total hip replacement. We constructed separate mixed-effects multivariable time-to-event models (survival analysis) for each of the 6 procedures to model surgical case duration. RESULTS: We identified performance outliers, based on surgical case duration, using 2013 data and then quantified the gap between high- and low-performance outliers using 2014 data. After adjusting for patient risk, patients undergoing surgery at high-performance facilities were between 54% and 79% more likely to exit the operating room (OR) per unit time compared to average-performing facilities, depending on the procedure. For example, patients undergoing a laparoscopic appendectomy at high-performance facilities were 68% more likely to exit the OR per unit time (hazard ratio, 1.68; 95% CI, 1.40-2.02; P < .001) compared to average-performing facilities. Patients undergoing a laparoscopic appendectomy at low-performance facilities were 41% less likely to exit the OR per unit time (hazard ratio, 0.59; 95% CI, 0.47-0.74; P < .001) compared to average-performing facilities. The adjusted median surgical case duration for patients undergoing laparoscopic appendectomy was 69 minutes at high-performance centers and 92 minutes at low-performance centers. Similar results were obtained for the other procedures. CONCLUSIONS: There was wide variation in surgery case duration for patients undergoing common general surgical and orthopedic surgeries. This variability in care delivery may represent an important opportunity to promote more efficient use of health care resources.

Incidence and Operative Factors Associated With Discretional Postoperative Mechanical Ventilation After General Surgery.

BACKGROUND: Mechanical ventilation after general surgery is associated with worse outcomes, prolonged hospital stay, and increased health care cost. Postoperatively, patients admitted to the intensive care unit (ICU) may be categorized into 1 of 3 groups: extubated patients (EXT), patients with objective medical indications to remain ventilated (MED), and patients not meeting these criteria, called "discretional postoperative mechanical ventilation" (DPMV). The objectives of this study were to determine the incidence of DPMV in general surgery patients and identify the associated operative factors. METHODS: At a large, tertiary medical center, we reviewed all surgical cases performed under general anesthesia from April 1, 2008 to February 28, 2015 and admitted to the ICU postoperatively. Patients were categorized into 1 of 3 cohorts: EXT, MED, or DPMV. Operative factors related to the American Society of Anesthesiologists Physical Status (ASA PS), duration of surgery, surgery end time, difficult airway management, intraoperative blood and fluid administration, vasopressor infusions, intraoperative arterial blood gasses, and ventilation data were collected. Additionally, anesthesia records were reviewed for notes indicating a reason or rationale for postoperative ventilation. Categorical variables were compared by χ test, and continuous variables by analysis of variance or Kruskal-Wallis H test. Categorical variables are presented as n (%), and continuous variables as mean ± standard deviation or median (interquartile range) as appropriate. Significance level was set at P≤ .05. RESULTS: Sixteen percent of the 3555 patients were categorized as DPMV and 12.2% as MED. Compared to EXT patients, those classified as DPMV had received significantly less fluid (2757 ± 2728 mL vs 3868 ± 1885 mL; P < .001), lost less blood during surgery (150 [20-625] mL vs 300 [150-600] mL; P< .001), underwent a shorter surgery (199 ± 215 minutes vs 276 ± 143 minutes; P< .001), but received more blood products, 900 (600-1800) mL vs 600 (300-900) mL. The DPMV group had more patients with high ASA PS (ASA III-V) than the EXT group: 508 (90.4%) vs 1934 (75.6%); P< .001. Emergency surgery (ASA E modifier) was more common in the DPMV group than the EXT group: 145 (25.8%) vs 306 (12%), P< .001, respectively. Surgery end after regular working hours was not significantly higher with DPMV status compared to EXT. DPMV cohort had fewer cases with difficult airway when compared to EXT or MED. When compared to MED patients, those classified as DPMV received less fluid (2757 ± 2728 mL vs 4499 ± 2830 mL; P< .001), lost less blood (150 [20-625] mL vs 500 [200-1350] mL; P < .001), but did not differ in blood products transfused or duration of surgery. CONCLUSIONS: In our tertiary medical center, patients often admitted to the ICU on mechanical ventilation without an objective medical indication. When compared to patients admitted to the ICU extubated, those mechanically ventilated but without an objective indication had a higher ASA PS class and were more likely to have an ASA E modifier. A surgery end time after regular working hours or difficult airway management was not associated with higher incidence of DPMV.

A Retrospective Analysis of the Variability in Case Duration for Aortic Valve Replacement and Association With Hospital Facility Types.

OBJECTIVE: Currently, there are no large-scale studies that compare differences in case duration of aortic valve replacements (AVRs). The primary objective of this study was to determine associations of hospital facility type, geographic location, case volume per year, and time of day with duration of valve replacement surgery. DESIGN: Retrospective. SETTING: Data from the National Anesthesia Clinical Outcomes Registry. PARTICIPANTS: National data from university and non-university hospitals. INTERVENTIONS: No interventions. MEASUREMENTS AND MAIN RESULTS: All AVRs from the National Anesthesia Clinical Outcomes Registry were identified from 2010 to 2014. Mean case duration for all AVRs was 360.8 ± 95.8 minutes and was presented based on facility type (university hospital, large community hospital, medium-sized community hospital, and other); US geographic region; time of day (cases performed after 5 pm and before 7 am v day shift); and case volume per year. A multivariable linear regression model was built to determine the association of various patient, procedural, and facility characteristics with case duration. University hospitals were associated with increased case duration for AVRs (p < 0.0001). CONCLUSIONS: With this large national database, the authors demonstrated that academic hospitals, time of day of the surgery, US region, and case volume per year for a facility are related to the case duration of AVRs.

Variation in Frequency of Intraoperative Arterial, Central Venous and Pulmonary Artery Catheter Placement During Kidney Transplantation: An Analysis of Invasive Monitoring Trends.

The rapidly increasing number of kidney transplantations warrants assessment of anesthesia care in this patient population. We explored the frequency of arterial catheter (AC), central venous catheter (CVC) and pulmonary artery catheter (PAC) placement during kidney transplantation in the USA using data from the National Anesthesia Clinical Outcomes Registry (NACOR) and assessed the between-facility variation in the frequency of catheter placement. We defined cases of kidney transplantation using Agency for Healthcare Research and Quality Clinical Classification Software. Placement of AC, CVC and PAC was defined by respective Current Procedural Terminology codes. The frequency of vascular catheter placement across facility types was compared using Pearson χ2 test. We identified 10,580 cases of kidney transplantation performed in 100 facilities from January 1, 2010 to December 31, 2014. Placement of an AC was reported in 1700 (16.1%), CVC in 2580 (24.4%) and PAC in 50 (0.5%) of cases. The frequency of placement of specific types of catheters was statistically different across facility types (p < 0.001). Within individual facilities that reported at least 50 cases of kidney transplantation, the percentages of cases performed with AC, CVC and PAC ranged from 0% to 86%, 0% to 90% and 0% to 3%, respectively. Considerable between-facility variation in the frequency of AC, CVC and PAC placement during kidney transplantation raises concerns about the need for better practice standardization. Excess invasive monitoring may represent a safety risk as well as unnecessary additional cost. If kidney transplantation can be safely performed without an AC, CVC or PAC in most patients, facilities with above-average catheter placement rates may have an opportunity for measurable reduction in catheter-related perioperative complications. Optimizing perioperative monitoring is an important component of ensuring high functioning, high-value medical systems.

Analysis of Unplanned Intensive Care Unit Admissions in Postoperative Pediatric Patients.

BACKGROUND: Currently, there are only a few retrospective, single-institution studies that have addressed the prevalence and risk factors associated with unplanned admissions to the pediatric intensive care unit (ICU) after surgery. Based on the limited amount of studies, it appears that airway and respiratory complications put a child at increased risk for unplanned ICU admission. A more extensive and diverse analysis of unplanned postoperative admissions to the ICU is needed to address risk factors that have yet to be revealed by the current literature. AIM: To establish a rate of unplanned postoperative ICU admissions in pediatric patients using a large, multi-institution data set and to further characterize the associated risk factors. METHODS: Data from the National Anesthesia Clinical Outcomes Registry were analyzed. We recorded the overall risk of unplanned postoperative ICU admission in patients younger than 18 years and performed univariate and multivariate logistic regression analysis to identify the associated patient, surgical, and anesthetic-related characteristics. RESULTS: Of the 324 818 cases analyzed, 211 reported an unexpected ICU admission. There was an increased likelihood of unplanned postoperative ICU in infants (age <1 year) and children who were classified as American Society of Anesthesiologists physical status classification of III or IV. Likewise, longer case duration and cases requiring general anesthesia were also associated with unplanned ICU admissions. CONCLUSION: This study establishes a rate of unplanned ICU admission following surgery in the heterogeneous pediatric population. This is the first study to utilize such a large data set encompassing a wide range of practice environments to identify risk factors leading to unplanned postoperative ICU admissions. Our study revealed that patient, surgical, and anesthetic complexity each contributed to an increased number of unplanned ICU admissions in the pediatric population.

Analysis of Unplanned Postoperative Admissions to the Intensive Care Unit.

PURPOSE: To investigate factors associated with unplanned postoperative admissions to the intensive care unit (ICU). METHODS: Data from the National Anesthesia Clinical Outcomes Registry (NACOR) were analyzed. We performed univariate and multivariate logistic regression to identify patient- and surgery-specific characteristics associated with unplanned postoperative ICU admission. We also recorded the prevalence of Current Procedural Terminology (CPT) and International Classification of Diseases, ninth revision ( ICD-9) billing codes and outcomes for unplanned postoperative ICU admissions. RESULTS: Of 23 341 130 records in the database, 2 910 738 records met our inclusion criteria. A higher American Society of Anesthesiologists physical status (ASA PS) class, case duration greater than 4 hours, and advanced age were associated with a greater likelihood of unplanned ICU admission. Vascular and thoracic surgery patients were more likely to have an unplanned ICU admission. The most common CPT and ICD-9 codes involved repair of femur/hip fracture, bowel resection, and acute postoperative pain. Large community hospitals were more likely than university hospitals to have unplanned postoperative ICU admissions. Patients in the unplanned postoperative ICU admission group were more likely to have experienced intraoperative cardiac arrest, hemodynamic instability, or respiratory failure and were more likely to die in the immediate perioperative period. CONCLUSION: Our study is the first diverse analysis of unplanned postoperative ICU admissions in the literature across multiple specialties and practice models. We found an association of advanced age, higher ASA PS class, and duration of procedure with unplanned ICU admission after surgery. Surgical specialties and procedures with the most unplanned ICU admissions could be areas for quality improvement and clinical pathways in the future.

Growth of Nonoperating Room Anesthesia Care in the United States: A Contemporary Trends Analysis.

BACKGROUND: Although previous publications suggest an increasing demand and volume of nonoperating room anesthesia (NORA) cases in the United States, there is little factual information on either volume or characteristics of NORA cases at a national level. Our goal was to assess the available data using the National Anesthesia Clinical Outcomes Registry (NACOR). METHODS: We performed a retrospective analysis of NORA volume and case characteristics using NACOR data for the period 2010-2014. Operating room (OR) and NORA cases were assessed for patient, provider, procedural, and facility characteristics. NACOR may indicate general trends, since it collects data on about 25% of all anesthetics in the United States each year. We examined trends in the annual proportion of NORA cases, the annual mean age of patients, the annual proportions of American Society of Anesthesiologists physical status (ASA PS) III-V patients, and outpatient cases. Regression analyses for trends included facility type and urban/rural location as covariables. The most frequently reported procedures were identified. RESULTS: The proportion of NORA cases overall increased from 28.3% in 2010 to 35.9% in 2014 (P < .001). The mean age of NORA patients was 3.5 years higher compared with OR patients (95% CI 3.5-3.5, P < .001). The proportion of patients with ASA PS class III-V was higher in the NORA group compared with OR group, 37.6% and 33.0%, respectively (P < .001). The median (quartile 1, 3) duration of NORA cases was 40 (25, 70) minutes compared with 86 (52, 141) minutes for OR cases (P < .001). In comparison to OR cases, more NORA cases were started after normal working hours (9.9% vs 16.7%, P < .001). Colonoscopy was the most common procedure that required NORA. There was a significant upward trend in the mean age of NORA patients in the multivariable analysis-the estimated increase in mean age was 1.06 years of age per year of study period (slope 1.06; 95% confidence interval [CI] 1.05-1.07, P < .001). Multivariable analysis demonstrated that the mean age of NORA patients increased significantly faster compared with OR patients (difference in slopes 0.39; 95% CI 0.38-0.41, P < .001). The annual increase in ordinal ASA PS of NORA patients was small in magnitude, but statistically significant (odds ratio 1.03; 95% CI 1.03-1.03, P < .001). The proportion of outpatient NORA cases increased from 69.7% in 2010 to 73.3% in 2014 (P < .001). CONCLUSIONS: Our results demonstrate that NORA is a growing component of anesthesiology practice. The proportion of cases performed outside of the OR increased during the study period. In addition, we identified an upward trend in the age of patients receiving NORA care. NORA cases were different from OR cases in a number of aspects. Data collected by NACOR in the coming years will further characterize the trends identified in this study.