Closing the Chasm: Understanding and Addressing the Anesthesia Workforce Supply and Demand Imbalance.

The imbalance in anesthesia workforce supply and demand has been exacerbated post-COVID due to a surge in demand for anesthesia care, especially in non-operating room anesthetizing sites, at a faster rate than the increase in anesthesia clinicians. The consequences of this imbalance or labor shortage compromise healthcare facilities, adversely affect the cost of care, worsen anesthesia workforce burnout, disrupt procedural and surgical schedules, and threaten academic missions and the ability to educate future anesthesiologists. In developing possible solutions, one must examine emerging trends that are affecting the anesthesia workforce, new technologies that will transform anesthesia care and the workforce, and financial considerations, including governmental payment policies. Possible practice solutions to this imbalance will require both short- and long-term multifactorial approaches that include increasing training positions and retention policies, improving capacity through innovations, leveraging technology, and addressing financial constraints.

Restrictive versus Decision Support Guided Fluid Therapy during Major Hepatic Resection Surgery: A Randomized Controlled Trial.

BACKGROUND: Fluid therapy during major hepatic resection aims at minimizing fluids during the dissection phase to reduce central venous pressure, retrograde liver blood flow, and venous bleeding. This strategy, however, may lead to hyperlactatemia. The Acumen assisted fluid management system uses novel decision support software, the algorithm of which helps clinicians optimize fluid therapy. The study tested the hypothesis that using this decision support system could decrease arterial lactate at the end of major hepatic resection when compared to a more restrictive fluid strategy. METHODS: This two-arm, prospective, randomized controlled, assessor- and patient-blinded superiority study included consecutive patients undergoing major liver surgery equipped with an arterial catheter linked to an uncalibrated stroke volume monitor. In the decision support group, fluid therapy was guided throughout the entire procedure using the assisted fluid management software. In the restrictive fluid group, clinicians were recommended to restrict fluid infusion to 1 to 2 ml · kg-1 · h-1 until the completion of hepatectomy. They then administered fluids based on advanced hemodynamic variables. Noradrenaline was titrated in all patients to maintain a mean arterial pressure greater than 65 mmHg. The primary outcome was arterial lactate level upon completion of surgery (i.e., skin closure). RESULTS: A total of 90 patients were enrolled over a 7-month period. The primary outcome was lower in the decision support group than in the restrictive group (median [quartile 1 to quartile 3], 2.5 [1.9 to 3.7] mmol · l-1vs. 4.6 [3.1 to 5.4] mmol · l-1; median difference, -2.1; 95% CI, -2.7 to -1.2; P < 0.001). Among secondary exploratory outcomes, there was no difference in blood loss (median [quartile 1 to quartile 3], 450 [300 to 600] ml vs. 500 [300 to 800] ml; P = 0.727), although central venous pressure was higher in the decision support group (mean ± SD of 7.7 ± 2.0 mmHg vs. 6.6 ± 1.1 mmHg; P < 0.002). CONCLUSIONS: Patients managed using a clinical decision support system to guide fluid administration during major hepatic resection had a lower arterial lactate concentration at the end of surgery when compared to a more restrictive fluid strategy. Future trials are necessary to make conclusive recommendations that will change clinical practice.

Comparison of Differences in Cohort (Forward) and Case Control (Backward) Methodologic Approaches for Validation of the Hypotension Prediction Index.

BACKGROUND: The Hypotension Prediction Index (the index) software is a machine learning algorithm that detects physiologic changes that may lead to hypotension. The original validation used a case control (backward) analysis that has been suggested to be biased. This study therefore conducted a cohort (forward) analysis and compared this to the original validation technique. METHODS: A retrospective analysis of data from previously reported studies was conducted. All data were analyzed identically with two different methodologies, and receiver operating characteristic curves were constructed. Both backward and forward analyses were performed to examine differences in area under the receiver operating characteristic curves for the Hypotension Prediction Index and other hemodynamic variables to predict a mean arterial pressure (MAP) less than 65 mmHg for at least 1 min 5, 10, and 15 min in advance. RESULTS: The analysis included 2,022 patients, yielding 4,152,124 measurements taken at 20-s intervals. The area under the curve for the index predicting hypotension analyzed by backward and forward methodologies respectively was 0.957 (95% CI, 0.947 to 0.964) versus 0.923 (95% CI, 0.912 to 0.933) 5 min in advance, 0.933 (95% CI, 0.924 to 0.942) versus 0.923 (95% CI, 0.911 to 0.933) 10 min in advance, and 0.929 (95% CI, 0.918 to 0.938) versus 0.926 (95% CI, 0.914 to 0.937) 15 min in advance. No variable other than MAP had an area under the curve greater than 0.7. The areas under the curve using forward analysis for MAP predicting hypotension 5, 10, and 15 min in advance were 0.932 (95% CI, 0.920 to 0.940), 0.929 (95% CI, 0.918 to 0.938), and 0.932 (95% CI, 0.921 to 0.940), respectively. The R2 for the variation in the index due to MAP was 0.77. CONCLUSIONS: Using an updated methodology, the study found that the utility of the Hypotension Prediction Index to predict future hypotensive events is high, with an area under the receiver operating characteristics curve similar to that of the original validation method.

Clinical Knowledge and Reasoning Abilities of AI Large Language Models in Anesthesiology: A Comparative Study on the American Board of Anesthesiology Examination.

BACKGROUND: Over the past decade, artificial intelligence (AI) has expanded significantly with increased adoption across various industries, including medicine. Recently, AI-based large language models such as Generative Pretrained Transformer-3 (GPT-3), Bard, and Generative Pretrained Transformer-3 (GPT-4) have demonstrated remarkable language capabilities. While previous studies have explored their potential in general medical knowledge tasks, here we assess their clinical knowledge and reasoning abilities in a specialized medical context. METHODS: We studied and compared the performance of all 3 models on both the written and oral portions of the comprehensive and challenging American Board of Anesthesiology (ABA) examination, which evaluates candidates' knowledge and competence in anesthesia practice. RESULTS: Our results reveal that only GPT-4 successfully passed the written examination, achieving an accuracy of 78% on the basic section and 80% on the advanced section. In comparison, the less recent or smaller GPT-3 and Bard models scored 58% and 47% on the basic examination, and 50% and 46% on the advanced examination, respectively. Consequently, only GPT-4 was evaluated in the oral examination, with examiners concluding that it had a reasonable possibility of passing the structured oral examination. Additionally, we observe that these models exhibit varying degrees of proficiency across distinct topics, which could serve as an indicator of the relative quality of information contained in the corresponding training datasets. This may also act as a predictor for determining which anesthesiology subspecialty is most likely to witness the earliest integration with AI. CONCLUSIONS: GPT-4 outperformed GPT-3 and Bard on both basic and advanced sections of the written ABA examination, and actual board examiners considered GPT-4 to have a reasonable possibility of passing the real oral examination; these models also exhibit varying degrees of proficiency across distinct topics.

A Prospective Observational Cohort Study of Language Preference and Preoperative Cognitive Screening in Older Adults: Do Language Disparities Exist in Cognitive Screening and Does the Association Between Test Results and Postoperative Delirium Differ Based on Language Preference?

BACKGROUND: A greater percentage of surgical procedures are being performed each year on patients 65 years of age or older. Concurrently, a growing proportion of patients in English-speaking countries such as the United States, United Kingdom, Australia, and Canada have a language other than English (LOE) preference. We aimed to measure whether patients with LOE underwent cognitive screening at the same rates as their English-speaking counterparts when routine screening was instituted. We also aimed to measure the association between preoperative Mini-Cog and postoperative delirium (POD) in both English-speaking and LOE patients. METHODS: We conducted a single-center, observational cohort study in patients 65 years old or older, scheduled for surgery and evaluated in the preoperative clinic. Cognitive screening of older adults was recommended as an institutional program for all patients 65 and older presenting to the preoperative clinic. We measured program adherence for cognitive screening. We also assessed the association of preoperative impairment on Mini-Cog and POD in both English-speaking and LOE patients, and whether the association differed for the 2 groups. A Mini-Cog score ≤2 was considered impaired. Postoperatively, patients were assessed for POD using the Confusion Assessment Method (CAM) and by systematic chart review. RESULTS: Over a 3-year period (February 2019-January 2022), 2446 patients 65 years old or older were assessed in the preoperative clinic prior. Of those 1956 patients underwent cognitive screening. Eighty-nine percent of English-speaking patients underwent preoperative cognitive screening, compared to 58% of LOE patients. The odds of having a Mini-Cog assessment were 5.6 times higher (95% confidence interval [CI], 4.6-7.0) P < .001 for English-speaking patients compared to LOE patients. In English-speaking patients with a positive Mini-Cog screen, the odds of having postop delirium were 3.5 times higher (95% CI, 2.6-4.8) P < .001 when compared to negative Mini-Cog. In LOE patients, the odds of having postop delirium were 3.9 times higher (95% CI, 2.1-7.3) P < .001 for those with a positive Mini-Cog compared to a negative Mini-Cog. The difference between these 2 odds ratios was not significant ( P = .753). CONCLUSIONS: We observed a disparity in the rates LOE patients were cognitively screened before surgery, despite the Mini-Cog being associated with POD in both English-speaking and LOE patients. Efforts should be made to identify barriers to cognitive screening in limited English-proficient older adults.

Assisted Fluid Management and Sublingual Microvascular Flow During High-Risk Abdominal Surgery: A Randomized Controlled Trial.

BACKGROUND: Implementation of goal-directed fluid therapy (GDFT) protocols remains low. Protocol compliance among anesthesiologists tends to be suboptimal owing to the high workload and the attention required for implementation. The assisted fluid management (AFM) system is a novel decision support tool designed to help clinicians apply GDFT protocols. This system predicts fluid responsiveness better than anesthesia practitioners do and achieves higher stroke volume (SV) and cardiac index values during surgery. We tested the hypothesis that an AFM-guided GDFT strategy would also be associated with better sublingual microvascular flow compared to a standard GDFT strategy. METHODS: This bicenter, parallel, 2-arm, prospective, randomized controlled, patient and assessor-blinded, superiority study considered for inclusion all consecutive patients undergoing high-risk abdominal surgery who required an arterial catheter and uncalibrated SV monitoring. Patients having standard GDFT received manual titration of fluid challenges to optimize SV while patients having an AFM-guided GDFT strategy received fluid challenges based on recommendations from the AFM software. In all patients, fluid challenges were standardized and titrated per 250 mL and vasopressors were administered to maintain a mean arterial pressure >70 mm Hg. The primary outcome (average of each patient's intraoperative microvascular flow index (MFI) across 4 intraoperative time points) was analyzed using a Mann-Whitney U test and the treatment effect was estimated with a median difference between groups with a 95% confidence interval estimated using the bootstrap percentile method (with 1000 replications). Secondary outcomes included SV, cardiac index, total amount of fluid, other microcirculatory variables, and postoperative lactate. RESULTS: A total of 86 patients were enrolled over a 7-month period. The primary outcome was significantly higher in patients with AFM (median [Q1-Q3]: 2.89 [2.84-2.94]) versus those having standard GDFT (2.59 [2.38-2.78] points, median difference 0.30; 95% confidence interval [CI], 0.19-0.49; P < .001). Cardiac index and SVI were higher (3.2 ± 0.5 vs 2.7 ± 0.7 l.min-1.m-2; P = .001 and 42 [35-47] vs 36 [32-43] mL.m-2; P = .018) and arterial lactate concentration was lower at the end of the surgery in patients having AFM-guided GDFT (2.1 [1.5-3.1] vs 2.9 [2.1-3.9] mmol.L-1; P = .026) than patients having standard GDFT strategy. Patients having AFM received a higher fluid volume but 3 times less norepinephrine than those receiving standard GDFT (P < .001). CONCLUSIONS: Use of an AFM-guided GDFT strategy resulted in higher sublingual microvascular flow during surgery compared to use of a standard GDFT strategy. Future trials are necessary to make conclusive recommendations that will change clinical practice.

Closing the loop: automation in anesthesiology is coming.

Anesthesiology and intensive care medicine provide fertile ground for innovation in automation, but to date we have only achieved preliminary studies in closed-loop intravenous drug administration. Anesthesiologists have yet to implement these tools on a large scale despite clear evidence that they outperform manual titration. Closed-loops continuously assess a predefined variable as input into a controller and then attempt to establish equilibrium by administering a treatment as output. The aim is to decrease the error between the closed-loop controller's input and output. In this editorial we consider the available intravenous anesthesia closed-loop systems, try to clarify why they have not yet been implemented on a large scale, see what they offer, and propose the future steps towards automation in anesthesia.

Control of mean arterial pressure using a closed-loop system for norepinephrine infusion in severe brain injury patients: the COMAT randomized controlled trial.

Brain injury patients require precise blood pressure (BP) management to maintain cerebral perfusion pressure (CPP) and avoid intracranial hypertension. Nurses have many tasks and norepinephrine titration has been shown to be suboptimal. This can lead to limited BP control in patients that are in critical need of cerebral perfusion optimization. We have designed a closed-loop vasopressor (CLV) system capable of maintaining mean arterial pressure (MAP) in a narrow range and we aimed to assess its performance when treating severe brain injury patients. Within the first 48 h of intensive care unit (ICU) admission, 18 patients with a severe brain injury underwent either CLV or manual norepinephrine titration. In both groups, the objective was to maintain MAP in target (within ± 5 mmHg of a predefined target MAP) to achieve optimal CPP. Fluid administration was standardized in the two groups. The primary objective was the percentage of time patients were in target. Secondary outcomes included time spent over and under target. Over the four-hour study period, the mean percentage of time with MAP in target was greater in the CLV group than in the control group (95.8 ± 2.2% vs. 42.5 ± 27.0%, p < 0.001). Severe undershooting, defined as MAP < 10 mmHg of target value was lower in the CLV group (0.2 ± 0.3% vs. 7.4 ± 14.2%, p < 0.001) as was severe overshooting defined as MAP > 10 mmHg of target (0.0 ± 0.0% vs. 22.0 ± 29.0%, p < 0.001). The CLV system can maintain MAP in target better than nurses caring for severe brain injury patients.

A review of machine learning methods for non-invasive blood pressure estimation.

Blood pressure is a very important clinical measurement, offering valuable insights into the hemodynamic status of patients. Regular monitoring is crucial for early detection, prevention, and treatment of conditions like hypotension and hypertension, both of which increasing morbidity for a wide variety of reasons. This monitoring can be done either invasively or non-invasively and intermittently vs. continuously. An invasive method is considered the gold standard and provides continuous measurement, but it carries higher risks of complications such as infection, bleeding, and thrombosis. Non-invasive techniques, in contrast, reduce these risks and can provide intermittent or continuous blood pressure readings. This review explores modern machine learning-based non-invasive methods for blood pressure estimation, discussing their advantages, limitations, and clinical relevance.

Tight control of mean arterial pressure using a closed loop system for norepinephrine infusion after high-risk abdominal surgery: a randomized controlled trial.

Intensive care unit (ICU) nurses frequently manually titrate norepinephrine to maintain a predefined mean arterial pressure (MAP) target after high-risk surgery. However, achieving this task is often suboptimal. We have developed a closed-loop vasopressor (CLV) controller to better maintain MAP within a narrow range. After ethical committee approval, fifty-three patients admitted to the ICU following high-risk abdominal surgery were randomized to CLV or manual norepinephrine titration. In both groups, the aim was to maintain MAP in the predefined target of 80-90 mmHg. Fluid administration was standardized in the two groups using an advanced hemodynamic monitoring device. The primary outcome of our study was the percentage of time patients were in the MAP target. Over the 2-hour study period, the percentage of time with MAP in target was greater in the CLV group than in the control group (median: IQR25-75: 80 [68-88]% vs. 42 [22-65]%), difference 37.2, 95% CI (23.0-49.2); p < 0.001). Percentage time with MAP under 80 mmHg (1 [0-5]% vs. 26 [16-75]%, p < 0.001) and MAP under 65 mmHg (0 [0-0]% vs. 0 [0-4]%, p = 0.017) were both lower in the CLV group than in the control group. The percentage of time with a MAP > 90 mmHg was not statistically different between groups. In patients admitted to the ICU after high-risk abdominal surgery, closed-loop control of norepinephrine infusion better maintained a MAP target of 80 to 90 mmHg and significantly decreased postoperative hypotensive when compared to manual norepinephrine titration.

Laboratory Result Reference Ranges Stratified for Patient-Reported Sex and Ethnicity Are More Closely Associated With Postoperative Outcomes Than Currently Used Reference Ranges: A Retrospective Data Analysis.

BACKGROUND: A single laboratory range for all individuals may fail to take into account underlying physiologic differences based on sex and genetic factors. We hypothesized that laboratory distributions differ based on self-reported sex and ethnicity and that ranges stratified by these factors better correlate with postoperative mortality and acute kidney injury (AKI). METHODS: Results from metabolic panels, complete blood counts, and coagulation panels for patients in outpatient encounters were identified from our electronic health record. Patients were grouped based on self-reported sex (2 groups) and ethnicity (6 groups). Stratified ranges were set to be the 2.5th/97.5th percentile for each sex/ethnic group. For patients undergoing procedures, each patient/laboratory result was classified as normal/abnormal using the stratified and nonstratified (traditional) ranges; overlap in the definitions was assessed between the 2 classifications by looking for the percentage of agreement in result classifications of normal/abnormal using the 2 methods. To assess which definitions of normal are most associated with adverse postoperative outcomes, the odds ratio (OR) for each outcome/laboratory result pair was assessed, and the frequency that the confidence intervals of ORs for the stratified versus nonstratified range did not overlap was examined. RESULTS: Among the 300 unique combinations (race × sex × laboratory type), median proportion overlap (meaning patient was either "normal" or "abnormal" for both methodologies) was 0.86 [q1, 0.80; q3, 0.89]. All laboratory results except 6 overlapped at least 80% of the time. The frequency of overlap did not differ among the racial/ethnic groups. In cases where the ORs were different, the stratified range was better associated with both AKI and mortality (P < .001). There was no trend of bias toward any specific sex/ethnic group. CONCLUSIONS: Baseline "normal" laboratory values differ across sex and ethnic groups, and ranges stratified by these groups are better associated with postoperative AKI and mortality as compared to the standard reference ranges.

Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.

BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discriminative features from the electronic health record (EHR), machine-learning algorithms can create digital phenotypes among heterogenous populations, representing distinct patient subpopulations grouped by shared characteristics, from which we can personalize care, anticipate clinical care trajectories, and explore therapies. We hypothesized that digital phenotypes in preoperative settings are associated with postoperative adverse events including in-hospital and 30-day mortality, 30-day surgical redo, intensive care unit (ICU) admission, and hospital length of stay (LOS). METHODS: We identified all laminectomies, colectomies, and thoracic surgeries performed over a 9-year period from a large hospital system. Seventy-seven readily extractable preoperative features were first selected from clinical consensus, including demographics, medical history, and lab results. Three surgery-specific datasets were built and split into derivation and validation cohorts using chronological occurrence. Consensus k -means clustering was performed independently on each derivation cohort, from which phenotypes' characteristics were explored. Cluster assignments were used to train a random forest model to assign patient phenotypes in validation cohorts. We reconducted descriptive analyses on validation cohorts to confirm the similarity of patient characteristics with derivation cohorts, and quantified the association of each phenotype with postoperative adverse events by using the area under receiver operating characteristic curve (AUROC). We compared our approach to American Society of Anesthesiologists (ASA) alone and investigated a combination of our phenotypes with the ASA score. RESULTS: A total of 7251 patients met inclusion criteria, of which 2770 were held out in a validation dataset based on chronological occurrence. Using segmentation metrics and clinical consensus, 3 distinct phenotypes were created for each surgery. The main features used for segmentation included urgency of the procedure, preoperative LOS, age, and comorbidities. The most relevant characteristics varied for each of the 3 surgeries. Low-risk phenotype alpha was the most common (2039 of 2770, 74%), while high-risk phenotype gamma was the rarest (302 of 2770, 11%). Adverse outcomes progressively increased from phenotypes alpha to gamma, including 30-day mortality (0.3%, 2.1%, and 6.0%, respectively), in-hospital mortality (0.2%, 2.3%, and 7.3%), and prolonged hospital LOS (3.4%, 22.1%, and 25.8%). When combined with the ASA score, digital phenotypes achieved higher AUROC than the ASA score alone (hospital mortality: 0.91 vs 0.84; prolonged hospitalization: 0.80 vs 0.71). CONCLUSIONS: For 3 frequently performed surgeries, we identified 3 digital phenotypes. The typical profiles of each phenotype were described and could be used to anticipate adverse postoperative events.

Preoperative Point-of-Care Ultrasound to Identify Frailty and Predict Postoperative Outcomes: A Diagnostic Accuracy Study.

BACKGROUND: Frailty is increasingly being recognized as a public health issue, straining healthcare resources and increasing costs to care for these patients. Frailty is the decline in physical and cognitive reserves leading to increased vulnerability to stressors such as surgery or disease states. The goal of this pilot diagnostic accuracy study was to identify whether point-of-care ultrasound measurements of the quadriceps and rectus femoris muscles can be used to discriminate between frail and not-frail patients and predict postoperative outcomes. This study hypothesized that ultrasound could discriminate between frail and not-frail patients before surgery. METHODS: Preoperative ultrasound measurements of the quadriceps and rectus femoris were obtained in patients with previous computed tomography scans. Using the computed tomography scans, psoas muscle area was measured in all patients for comparative purposes. Frailty was identified using the Fried phenotype assessment. Postoperative outcomes included unplanned intensive care unit admission, delirium, intensive care unit length of stay, hospital length of stay, unplanned skilled nursing facility admission, rehospitalization, falls within 30 days, and all-cause 30-day and 1-yr mortality. RESULTS: A total of 32 patients and 20 healthy volunteers were included. Frailty was identified in 18 of the 32 patients. Receiver operating characteristic curve analysis showed that quadriceps depth and psoas muscle area are able to identify frailty (area under the curve-receiver operating characteristic, 0.80 [95% CI, 0.64 to 0.97] and 0.88 [95% CI, 0.76 to 1.00], respectively), whereas the cross-sectional area of the rectus femoris is less promising (area under the curve-receiver operating characteristic, 0.70 [95% CI, 0.49 to 0.91]). Quadriceps depth was also associated with unplanned postoperative skilled nursing facility discharge disposition (area under the curve 0.81 [95% CI, 0.61 to 1.00]) and delirium (area under the curve 0.89 [95% CI, 0.77 to 1.00]). CONCLUSIONS: Similar to computed tomography measurements of psoas muscle area, preoperative ultrasound measurements of quadriceps depth shows promise in discriminating between frail and not-frail patients before surgery. It was also associated with skilled nursing facility admission and postoperative delirium.

A Century of Technology in Anesthesia & Analgesia.

Technological innovation has been closely intertwined with the growth of modern anesthesiology as a medical and scientific discipline. Anesthesia & Analgesia, the longest-running physician anesthesiology journal in the world, has documented key technological developments in the specialty over the past 100 years. What began as a focus on the fundamental tools needed for effective anesthetic delivery has evolved over the century into an increasing emphasis on automation, portability, and machine intelligence to improve the quality, safety, and efficiency of patient care.

Control of Postoperative Hypotension Using a Closed-Loop System for Norepinephrine Infusion in Patients After Cardiac Surgery: A Randomized Trial.

BACKGROUND: Vasopressors are a cornerstone for the management of vasodilatory hypotension. Vasopressor infusions are currently adjusted manually to achieve a predefined arterial pressure target. We have developed a closed-loop vasopressor (CLV) controller to help correct hypotension more efficiently during the perioperative period. We tested the hypothesis that patients managed using such a system postcardiac surgery would present less hypotension compared to patients receiving standard management. METHODS: A total of 40 patients admitted to the intensive care unit (ICU) after cardiac surgery were randomized into 2 groups for a 2-hour study period. In all patients, the objective was to maintain mean arterial pressure (MAP) between 65 and 75 mm Hg using norepinephrine. In the CLV group, the norepinephrine infusion was controlled via the CLV system; in the control group, it was adjusted manually by the ICU nurse. Fluid administration was standardized in both groups using an assisted fluid management system linked to an advanced hemodynamic monitoring system. The primary outcome was the percentage of time patients were hypotensive, defined as MAP <65 mm Hg, during the study period. RESULTS: Over the 2-hour study period, the percentage of time with hypotension was significantly lower in the CLV group than that in the control group (1.4% [0.9-2.3] vs 12.5% [9.9-24.3]; location difference, -9.8% [95% CI, -5.4 to -15.9]; P < .001). The percentage of time with MAP between 65 and 75 mm Hg was also greater in the CLV group (95% [89-96] vs 66% [59-77]; location difference, 27.6% [95% CI, 34.3-19.0]; P < .001). The percentage of time with an MAP >75 mm Hg (and norepinephrine still being infused) was also significantly lower in patients in the CLV group than that in the control group (3.2% [1.9-5.4] vs 20.6% [8.9-32.5]; location difference, -17% [95% CI, -10 to -24]; P < .001).The number of norepinephrine infusion rate modifications over the study period was greater in the CLV group than that in the control group (581 [548-597] vs 13 [11-14]; location difference, 568 [578-538]; P < .001). No adverse event occurred during the study period in both groups. CONCLUSIONS: Closed-loop control of norepinephrine infusion significantly decreases postoperative hypotension compared to manual control in patients admitted to the ICU after cardiac surgery.

Outcomes and risk factors for delayed-onset postoperative respiratory failure: a multi-center case-control study by the University of California Critical Care Research Collaborative (UC3RC).

BACKGROUND: Few interventions are known to reduce the incidence of respiratory failure that occurs following elective surgery (postoperative respiratory failure; PRF). We previously reported risk factors associated with PRF that occurs within the first 5 days after elective surgery (early PRF; E-PRF); however, PRF that occurs six or more days after elective surgery (late PRF; L-PRF) likely represents a different entity. We hypothesized that L-PRF would be associated with worse outcomes and different risk factors than E-PRF. METHODS: This was a retrospective matched case-control study of 59,073 consecutive adult patients admitted for elective non-cardiac and non-pulmonary surgical procedures at one of five University of California academic medical centers between October 2012 and September 2015. We identified patients with L-PRF, confirmed by surgeon and intensivist subject matter expert review, and matched them 1:1 to patients who did not develop PRF (No-PRF) based on hospital, age, and surgical procedure. We then analyzed risk factors and outcomes associated with L-PRF compared to E-PRF and No-PRF. RESULTS: Among 95 patients with L-PRF, 50.5% were female, 71.6% white, 27.4% Hispanic, and 53.7% Medicare recipients; the median age was 63 years (IQR 56, 70). Compared to 95 matched patients with No-PRF and 319 patients who developed E-PRF, L-PRF was associated with higher morbidity and mortality, longer hospital and intensive care unit length of stay, and increased costs. Compared to No-PRF, factors associated with L-PRF included: preexisiting neurologic disease (OR 4.36, 95% CI 1.81-10.46), anesthesia duration per hour (OR 1.22, 95% CI 1.04-1.44), and maximum intraoperative peak inspiratory pressure per cm H20 (OR 1.14, 95% CI 1.06-1.22). CONCLUSIONS: We identified that pre-existing neurologic disease, longer duration of anesthesia, and greater maximum intraoperative peak inspiratory pressures were associated with respiratory failure that developed six or more days after elective surgery in adult patients (L-PRF). Interventions targeting these factors may be worthy of future evaluation.

Computer-assisted Individualized Hemodynamic Management Reduces Intraoperative Hypotension in Intermediate- and High-risk Surgery: A Randomized Controlled Trial.

BACKGROUND: Individualized hemodynamic management during surgery relies on accurate titration of vasopressors and fluids. In this context, computer systems have been developed to assist anesthesia providers in delivering these interventions. This study tested the hypothesis that computer-assisted individualized hemodynamic management could reduce intraoperative hypotension in patients undergoing intermediate- to high-risk surgery. METHODS: This single-center, parallel, two-arm, prospective randomized controlled single blinded superiority study included 38 patients undergoing abdominal or orthopedic surgery. All included patients had a radial arterial catheter inserted after anesthesia induction and connected to an uncalibrated pulse contour monitoring device. In the manually adjusted goal-directed therapy group (N = 19), the individualized hemodynamic management consisted of manual titration of norepinephrine infusion to maintain mean arterial pressure within 10% of the patient's baseline value, and mini-fluid challenges to maximize the stroke volume index. In the computer-assisted group (N = 19), the same approach was applied using a closed-loop system for norepinephrine adjustments and a decision-support system for the infusion of mini-fluid challenges (100 ml). The primary outcome was intraoperative hypotension defined as the percentage of intraoperative case time patients spent with a mean arterial pressure of less than 90% of the patient's baseline value, measured during the preoperative screening. Secondary outcome was the incidence of minor postoperative complications. RESULTS: All patients were included in the analysis. Intraoperative hypotension was 1.2% [0.4 to 2.0%] (median [25th to 75th] percentiles) in the computer-assisted group compared to 21.5% [14.5 to 31.8%] in the manually adjusted goal-directed therapy group (difference, -21.1 [95% CI, -15.9 to -27.6%]; P < 0.001). The incidence of minor postoperative complications was not different between groups (42 vs. 58%; P = 0.330). Mean stroke volume index and cardiac index were both significantly higher in the computer-assisted group than in the manually adjusted goal-directed therapy group (P < 0.001). CONCLUSIONS: In patients having intermediate- to high-risk surgery, computer-assisted individualized hemodynamic management significantly reduces intraoperative hypotension compared to a manually controlled goal-directed approach.

Risk Factors Associated With Early Postoperative Respiratory Failure: A Matched Case-Control Study.

BACKGROUND: Postoperative respiratory failure is the most common serious postoperative pulmonary complication, yet little is known about factors that can reduce its incidence. We sought to elucidate modifiable factors associated with respiratory failure that developed within the first 5 d after an elective operation. MATERIALS AND METHODS: Matched case-control study of adults who had an operation at five academic medical centers between October 1, 2012 and September 30, 2015. Cases were identified using administrative data and confirmed via chart review by critical care clinicians. Controls were matched 1:1 to cases based on hospital, age, and surgical procedure. RESULTS: Our total sample (n = 638) was 56.4% female, 71.3% white, and had a median age of 62 y (interquartile range 51, 70). Factors associated with early postoperative respiratory failure included male gender (odds ratio [OR] 1.72, 95% confidence interval [CI] 1.12-2.63), American Society of Anesthesiologists class III or greater (OR 2.85, 95% CI 1.74-4.66), greater number of preexisting comorbidities (OR 1.14, 95% CI 1.004-1.30), increased operative duration (OR 1.14, 95% CI 1.06-1.22), increased intraoperative positive end-expiratory pressure (OR 1.23, 95% CI 1.13-1.35) and tidal volume (OR 1.13, 95% CI 1.004-1.27), and greater net fluid balance at 24 h (OR 1.17, 95% CI 1.07-1.28). CONCLUSIONS: We found greater intraoperative ventilator volume and pressure and 24-h fluid balance to be potentially modifiable factors associated with developing early postoperative respiratory failure. Further studies are warranted to independently verify these risk factors, explore their role in development of early postoperative respiratory failure, and potentially evaluate targeted interventions.

Automated closed-loop versus manually controlled norepinephrine infusion in patients undergoing intermediate- to high-risk abdominal surgery: a randomised controlled trial.

BACKGROUND: Hypotension occurs frequently during surgery and may be associated with adverse complications. Vasopressor titration is frequently used to correct hypotension, but requires considerable time and attention, potentially reducing the time available for other clinical duties. To overcome this issue, we have developed a closed-loop vasopressor (CLV) controller to help correct hypotension more efficiently. The aim of this randomised controlled study was to evaluate whether the CLV controller was superior to traditional vasopressor management at minimising hypotension in patients undergoing abdominal surgery. METHODS: Thirty patients scheduled for elective intermediate-to high-risk abdominal surgery were randomised into two groups. In the CLV group, hypotension was corrected automatically via the CLV controller system, which adjusted the rate of a norepinephrine infusion according to MAP values recorded using an advanced haemodynamic device. In the control group, management of hypotension consisted of standard, manual adjustment of the norepinephrine infusion. The primary outcome was the percentage of time that a patient was hypotensive, defined as MAP <90% of their baseline value, during surgery. RESULTS: The percentage of time patients were hypotensive during surgery was 10 times less in the CVL group than in the control group (1.6 [0.9-2.3]% vs 15.4 [9.9-24.3]%; difference: 13 [95% confidence interval: 9-19]; P<0.0001). The CVL group also spent much less time with MAP <65 mm Hg (0.2 [0.0-0.4]% vs 4.5 [1.1-7.9]%; P<0.0001). CONCLUSIONS: In patients undergoing intermediate- to high-risk surgery under general anaesthesia, computer-assisted adjustment of norepinephrine infusion significantly decreases the incidence of hypotension compared with manual control. CLINICAL TRIAL REGISTRATION: NCT04089644.

Acute Kidney Injury and Outcomes in Children Undergoing Noncardiac Surgery: A Propensity-Matched Analysis.

BACKGROUND: Acute kidney injury (AKI) has been well documented in adults after noncardiac surgery and demonstrated to be associated with adverse outcomes. We report the prevalence of AKI after pediatric noncardiac surgery, the perioperative factors associated with postoperative AKI, and the association of AKI with postoperative outcomes in children undergoing noncardiac surgery. METHODS: Patients ≤18 years of age who underwent noncardiac surgery with serum creatinine during the 12 months preceding surgery and no history of end-stage renal disease were included in this retrospective observational study at a single tertiary academic hospital. Patients were evaluated during the first 7 days after surgery for development of any stage of AKI, according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patients were classified into stages of KDIGO AKI for the purposes of describing prevalence. For further analyses, patients were grouped into those who developed any stage of AKI postoperatively and those who did not. Additionally, the time point at which each patient was first diagnosed with stage I AKI or greater was also assessed. Pre-, intra-, and postoperative factors were compared between the 2 groups. A multivariable Cox proportional hazards regression model was created to examine the time to first diagnosis of AKI using all nonredundant covariates. Analysis of the association of AKI with postoperative outcomes, mortality and 30-day readmission, was undertaken utilizing propensity score-matched controls and a multivariable Cox proportional hazards regression model. RESULTS: A total of 25,203 cases between 2013 and 2018 occurred; 8924 met inclusion criteria. Among this cohort, the observed prevalence of postoperative AKI was 3.2% (288 cases; confidence interval [CI], 2.9-3.6). The multivariable Cox model showed American Society of Anesthesiologists (ASA) status to be associated with the development of postoperative AKI. Several other factors, including intraoperative hypotension, were significantly associated with postoperative AKI in univariable models but found not to be significantly associated after adjustment. The multivariable Cox analyses with propensity-matched controls showed an estimated hazard ratio of 3.28 for mortality (CI, 1.71-6.32, P < .001) and 1.55 for 30-day readmission (CI, 1.08-2.23, P = .018) in children who developed AKI versus those who did not. CONCLUSIONS: In children undergoing noncardiac surgery, postoperative AKI occurred in 3.2% of patients. Several factors, including intraoperative hypotension, were significantly associated with postoperative AKI in univariable models. After adjustment, only ASA status was found to be significantly associated with AKI in children after noncardiac surgery. Postoperative AKI was found to be associated with significantly higher rates of mortality and 30-day readmission in multivariable, time-varying models with propensity-matched controls.