The effect of intra-operative hypotension on acute kidney injury, postoperative mortality and length of stay following emergency hip fracture surgery.

The association between intra-operative hypotension and postoperative acute kidney injury, mortality and length of stay has not been comprehensively evaluated in a large single-centre hip fracture population. We analysed electronic anaesthesia records of 1063 patients undergoing unilateral hip fracture surgery, collected from 2015 to 2018. Acute kidney injury, 3-, 30- and 365-day mortality and length of stay were evaluated to assess the relationship between intra-operative hypotension absolute values (≤ 55, 60, 65, 70 and 75 mmHg) and duration of hypotension. The rate of acute kidney injury was 23.7%, mortality at 3-, 30- and 365 days was 3.7%, 8.0% and 25.3%, respectively, and median (IQR [range]) length of stay 8 (6-12 [0-99]) days. Median (IQR [range]) time ≤ MAP 55, 60, 65, 70 and 75 mmHg was 0 (0-0.5[0-72.1]); 0 (0-4.4 [0-104.9]); 2.2 (0-8.7 [0-144.2]); 6.6 (2.2-19.7 [0-198.8]); 17.5 (6.6-37.1 [0-216.3]) minutes, and percentage of surgery time below these thresholds was 1%, 2.5%, 7.9%, 12% and 21% respectively. There were some univariate associations between hypotension and mortality; however, these were no longer evident in multivariable analysis. Multivariable analysis found no association between hypotension and acute kidney injury. Acute kidney injury was associated with male sex, antihypertensive medications and cardiac/renal comorbidities. Three-day mortality was associated with delay to surgery ? 48 hours, whilst 30-day and 365-day mortality was associated with delay to surgery ≥ 48 hours, impaired cognition and cardiac/renal comorbidities. While the rate of acute kidney injury was similar to other studies, use of vasopressors and fluids to reduce the time spent at hypotensive levels failed to reduce this complication. Intra-operative hypotension at the levels observed in this cohort may not be an important determinant of acute kidney injury, postoperative mortality and length of stay.

Quantitative Neuromuscular Monitoring and Postoperative Outcomes: A Narrative Review.

Over the past five decades, quantitative neuromuscular monitoring devices have been used to examine the incidence of postoperative residual neuromuscular block in international clinical practices, and to determine their role in reducing the risk of residual neuromuscular block and associated adverse clinical outcomes. Several clinical trials and a recent meta-analysis have documented that the intraoperative application of quantitative monitoring significantly reduces the risk of residual neuromuscular blockade in the operating room and postanesthesia care unit. In addition, emerging data show that quantitative monitoring minimizes the risk of adverse clinical events, such as unplanned postoperative reintubations, hypoxemia, and postoperative episodes of airway obstruction associated with incomplete neuromuscular recovery, and may improve postoperative respiratory outcomes. Several international anesthesia societies have recommended that quantitative monitoring be performed whenever a neuromuscular blocking agent is administered. Therefore, a comprehensive review of the literature was performed to determine the potential benefits of quantitative monitoring in the perioperative setting.

Deep learning models for the prediction of intraoperative hypotension.

BACKGROUND: Intraoperative hypotension is associated with a risk of postoperative organ dysfunction. In this study, we aimed to present deep learning algorithms for real-time predictions 5, 10, and 15 min before a hypotensive event. METHODS: In this retrospective observational study, deep learning algorithms were developed and validated using biosignal waveforms acquired from patient monitoring of noncardiac surgery. The classification model was a binary classifier of a hypotensive event (MAP <65 mm Hg) or a non-hypotensive event by analysing biosignal waveforms. The regression model was developed to directly estimate the MAP. The primary outcome was area under the receiver operating characteristic (AUROC) curve and the mean absolute error (MAE). RESULTS: In total, 3301 patients were included. For invasive models, the multichannel model with an arterial pressure waveform, electrocardiography, photoplethysmography, and capnography showed greater AUROC than the arterial-pressure-only models (AUROC15-min, 0.897 [95% confidence interval {CI}: 0.894-0.900] vs 0.891 [95% CI: 0.888-0.894]) and lesser MAE (MAE15-min, 7.76 mm Hg [95% CI: 7.64-7.87 mm Hg] vs 8.12 mm Hg [95% CI: 8.02-8.21 mm Hg]). For the noninvasive models, the multichannel model showed greater AUROCs than that of the photoplethysmography-only models (AUROC15-min, 0.762 [95% CI: 0.756-0.767] vs 0.694 [95% CI: 0.686-0.702]) and lesser MAEs (MAE15-min, 11.68 mm Hg [95% CI: 11.57-11.80 mm Hg] vs 12.67 [95% CI: 12.56-12.79 mm Hg]). CONCLUSIONS: Deep learning models can predict hypotensive events based on biosignals acquired using invasive and noninvasive patient monitoring. In addition, the model shows better performance when using combined rather than single signals.

Effect of fluid strategy on stroke volume, cardiac output, and fluid responsiveness in adult patients undergoing major abdominal surgery: a sub-study of the Restrictive versus Liberal Fluid Therapy in Major Abdominal Surgery (RELIEF) trial.

BACKGROUND: We designed a prospective sub-study of the larger Restrictive versus Liberal Fluid Therapy in Major Abdominal Surgery (RELIEF) trial to measure differences in stroke volume and other haemodynamic parameters at the end of the intraoperative fluid protocols. The haemodynamic effects of the two fluid regimens may increase our understanding of the observed perioperative outcomes. METHODS: Stroke volume and cardiac output were measured with both an oesophageal Doppler ultrasound monitor and arterial pressure waveform analysis. Stroke volume variation, pulse pressure variation, and plethysmographic variability index were also obtained. A passive leg raise manoeuvre was performed to identify fluid responsiveness. RESULTS: Analysis of 105 patients showed that the primary outcome, Doppler monitor-derived stroke volume index, was higher in the liberal group: restrictive 38.5 (28.6-48.8) vs liberal 44.0 (34.9-61.9) ml m-2; P=0.043. Similarly, there was a higher cardiac index in the liberal group: 2.96 (2.32-4.05) vs 2.42 (1.94-3.26) L min-1 m-2; P=0.015. Arterial-pressure-based stroke volume and cardiac index did not differ, nor was there a significant difference in stroke volume variation, pulse pressure variation, or plethysmographic variability index. The passive leg raise manoeuvre showed fluid responsiveness in 40% of restrictive and 30% of liberal protocol patients (not significant). CONCLUSIONS: The liberal fluid group from the RELIEF trial had significantly higher Doppler ultrasound monitor-derived stroke volume and cardiac output compared with the restrictive fluid group at the end of the intraoperative period. Measures of fluid responsiveness did not differ significantly between groups. CLINICAL TRIAL REGISTRATION: ACTRN12615000125527.

A Forensic Disassembly of the BIS Monitor.

BACKGROUND: The bispectral index (BIS) monitor has been available for clinical use for >20 years and has had an immense impact on academic activity in Anesthesiology, with >3000 articles referencing the bispectral index. Despite attempts to infer its algorithms by external observation, its operation has nevertheless remained undescribed, in contrast to the algorithms of other less commercially successful monitors of electroencephalogram (EEG) activity under anesthesia. With the expiration of certain key patents, the time is therefore ripe to examine the operation of the monitor on its own terms through careful dismantling, followed by extraction and examination of its internal software. METHODS: An A-2000 BIS Monitor (gunmetal blue case, amber monochrome display) was purchased on the secondary market. After identifying the major data processing and storage components, a set of free or inexpensive tools was used to retrieve and disassemble the monitor's onboard software. The software executes primarily on an ARMv7 microprocessor (Sharp/NXP LH77790B) and a digital signal processor (Texas Instruments TMS320C32). The device software can be retrieved directly from the monitor's hardware by using debugging interfaces that have remained in place from its original development. RESULTS: Critical numerical parameters such as the spectral edge frequency (SEF), total power, and BIS values were retraced from external delivery at the device's serial port back to the point of their calculation in the extracted software. In doing so, the locations of the critical algorithms were determined. To demonstrate the validity of the technique, the algorithms for SEF and total power were disassembled, comprehensively annotated and compared to their theoretically ideal behaviors. A bug was identified in the device's implementation of the SEF algorithm, which can be provoked by a perfectly isoelectric EEG. CONCLUSIONS: This article demonstrates that the electronic design of the A-2000 BIS Monitor does not pose any insuperable obstacles to retrieving its device software in hexadecimal machine code form directly from the motherboard. This software can be reverse engineered through disassembly and decompilation to reveal the methods by which the BIS monitor implements its algorithms, which ultimately must form the definitive statement of its function. Without further revealing any algorithms that might be considered trade secrets, the manufacturer of the BIS monitor should be encouraged to release the device software in its original format to place BIS-related academic literature on a firm theoretical foundation and to promote further academic development of EEG monitoring algorithms.

The cumulative duration of bispectral index less than 40 concurrent with hypotension is associated with 90-day postoperative mortality: a retrospective study.

BACKGROUND: The relationship between intraoperative low bispectral index (BIS) values and poor clinical outcomes has been controversial. Intraoperative hypotension is associated with postoperative complication. The purpose of this study was to investigate the influence of intraoperative low BIS values and hypotension on postoperative mortality in patients undergoing major abdominal surgery. METHODS: This retrospective study analyzed 1862 cases of general anesthesia. We collected the cumulative time of BIS values below 20 and 40 as well as electroencephalographic suppression and documented the incidences in which these states were maintained for at least 5 min. Durations of intraoperative mean arterial pressures (MAP) less than 50 mmHg were also recorded. Multivariable logistic regression was used to evaluate the association between suspected risk factors and postoperative mortality. RESULTS: Ninety-day mortality and 180-day mortality were 1.5 and 3.2% respectively. The cumulative time in minutes for BIS values falling below 40 coupled with MAP falling below 50 mmHg was associated with 90-day mortality (odds ratio, 1.26; 95% confidence interval, 1.04-1.53; P = .019). We found no association between BIS related values and 180-day mortality. CONCLUSIONS: The cumulative duration of BIS values less than 40 concurrent with MAP less than 50 mmHg was associated with 90-day postoperative mortality, not 180-day postoperative mortality.

Forecasting a Crisis: Machine-Learning Models Predict Occurrence of Intraoperative Bradycardia Associated With Hypotension.

BACKGROUND: Predictive analytics systems may improve perioperative care by enhancing preparation for, recognition of, and response to high-risk clinical events. Bradycardia is a fairly common and unpredictable clinical event with many causes; it may be benign or become associated with hypotension requiring aggressive treatment. Our aim was to build models to predict the occurrence of clinically significant intraoperative bradycardia at 3 time points during an operative course by utilizing available preoperative electronic medical record and intraoperative anesthesia information management system data. METHODS: The analyzed data include 62,182 scheduled noncardiac procedures performed at the University of Washington Medical Center between 2012 and 2017. The clinical event was defined as severe bradycardia (heart rate <50 beats per minute) followed by hypotension (mean arterial pressure <55 mm Hg) within a 10-minute window. We developed models to predict the presence of at least 1 event following 3 time points: induction of anesthesia (TP1), start of the procedure (TP2), and 30 minutes after the start of the procedure (TP3). Predictor variables were based on data available before each time point and included preoperative patient and procedure data (TP1), followed by intraoperative minute-to-minute patient monitor, ventilator, intravenous fluid, infusion, and bolus medication data (TP2 and TP3). Machine-learning and logistic regression models were developed, and their predictive abilities were evaluated using the area under the ROC curve (AUC). The contribution of the input variables to the models were evaluated. RESULTS: The number of events was 3498 (5.6%) after TP1, 2404 (3.9%) after TP2, and 1066 (1.7%) after TP3. Heart rate was the strongest predictor for events after TP1. Occurrence of a previous event, mean heart rate, and mean pulse rates before TP2 were the strongest predictor for events after TP2. Occurrence of a previous event, mean heart rate, mean pulse rates before TP2 (and their interaction), and 15-minute slopes in heart rate and blood pressure before TP2 were the strongest predictors for events after TP3. The best performing machine-learning models including all cases produced an AUC of 0.81 (TP1), 0.87 (TP2), and 0.89 (TP3) with positive predictive values of 0.30, 0.29, and 0.15 at 95% specificity, respectively. CONCLUSIONS: We developed models to predict unstable bradycardia leveraging preoperative and real-time intraoperative data. Our study demonstrates how predictive models may be utilized to predict clinical events across multiple time intervals, with a future goal of developing real-time, intraoperative, decision support.

Anesthetic Management Using Multiple Closed-loop Systems and Delayed Neurocognitive Recovery: A Randomized Controlled Trial.

BACKGROUND: Cognitive changes after anesthesia and surgery represent a significant public health concern. We tested the hypothesis that, in patients 60 yr or older scheduled for noncardiac surgery, automated management of anesthetic depth, cardiac blood flow, and protective lung ventilation using three independent controllers would outperform manual control of these variables. Additionally, as a result of the improved management, patients in the automated group would experience less postoperative neurocognitive impairment compared to patients having standard, manually adjusted anesthesia. METHODS: In this single-center, patient-and-evaluator-blinded, two-arm, parallel, randomized controlled, superiority study, 90 patients having noncardiac surgery under general anesthesia were randomly assigned to one of two groups. In the control group, anesthesia management was performed manually while in the closed-loop group, the titration of anesthesia, analgesia, fluids, and ventilation was performed by three independent controllers. The primary outcome was a change in a cognition score (the 30-item Montreal Cognitive Assessment) from preoperative values to those measures 1 week postsurgery. Secondary outcomes included a battery of neurocognitive tests completed at both 1 week and 3 months postsurgery as well as 30-day postsurgical outcomes. RESULTS: Forty-three controls and 44 closed-loop patients were assessed for the primary outcome. There was a difference in the cognition score compared to baseline in the control group versus the closed-loop group 1 week postsurgery (-1 [-2 to 0] vs. 0 [-1 to 1]; difference 1 [95% CI, 0 to 3], P = 0.033). Patients in the closed-loop group spent less time during surgery with a Bispectral Index less than 40, had less end-tidal hypocapnia, and had a lower fluid balance compared to the control group. CONCLUSIONS: Automated anesthetic management using the combination of three controllers outperforms manual control and may have an impact on delayed neurocognitive recovery. However, given the study design, it is not possible to determine the relative contribution of each controller on the cognition score.

Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence in anesthesiology: (1) depth of anesthesia monitoring, (2) control of anesthesia, (3) event and risk prediction, (4) ultrasound guidance, (5) pain management, and (6) operating room logistics. Based on papers identified in the review, several topics within artificial intelligence were described and summarized: (1) machine learning (including supervised, unsupervised, and reinforcement learning), (2) techniques in artificial intelligence (e.g., classical machine learning, neural networks and deep learning, Bayesian methods), and (3) major applied fields in artificial intelligence.The implications of artificial intelligence for the practicing anesthesiologist are discussed as are its limitations and the role of clinicians in further developing artificial intelligence for use in clinical care. Artificial intelligence has the potential to impact the practice of anesthesiology in aspects ranging from perioperative support to critical care delivery to outpatient pain management.

End of year summary 2019: anaesthesia and airway management.

This end of the year summary reviews anesthesia related manuscripts that have been published in the Journal of Clinical Monitoring and Computing in 2019. Anesthesia is currently defined as being composed of unconsciousness, immobility, and autonomic nervous system (ANS) control (Br J Anaesth;122:e127-e135135, Egan 2019). Pain is a postoperative issue, because by definition unconsciousness implies pain cannot be experienced. We first review work related to these aspect of the profession: unconsciousness (EEG, target control), immobility (muscle relaxants), and ANS control. Regaining consciousness has to be accompanied by pain control, and it is important to ensure that the patient regains baseline cognitive function. Anesthesia machine equipment, drug administration, and airway related topics make up the rest of published manuscripts.

Best practice & research clinical anaesthesiology: Advances in haemodynamic monitoring for the perioperative patient: Perioperative cardiac output monitoring.

Less invasive or even completely non-invasive haemodynamic monitoring technologies have evolved during the last decades. Even established, invasive devices such as the pulmonary artery catheter and transpulmonary thermodilution have still an evidence-based place in the perioperative setting, albeit only in special patient populations. Accumulating evidence suggests to use continuous haemodynamic monitoring, especially flow-based variables such as stroke volume or cardiac output to prevent occult hypoperfusion and, consequently, decrease morbidity and mortality perioperatively. However, there is still a substantial gap between evidence provided by randomised trials and the implementation of haemodynamic monitoring in daily clinical routine. Given the fact that perioperative morbidity and mortality are higher than anticipated and anaesthesiologists are in charge to deal with this problem, the recent advances in minimally invasive and non-invasive monitoring technologies may facilitate more widespread use in the operating theatre, as in addition to costs, the degree of invasiveness of any monitoring tool determines the frequency of its application, at least perioperatively. This review covers the currently available invasive, non-invasive and minimally invasive techniques and devices and addresses their indications and limitations.

Perioperative goal-directed therapy - What is the evidence?

Perioperative goal-directed therapy aims at optimizing global hemodynamics during the perioperative period by titrating fluids, vasopressors, and/or inotropes to predefined hemodynamic goals. There is evidence on the benefit of perioperative goal-directed therapy, but its adoption into clinical practice is slow and incomprehensive. Current evidence indicates that treating patients according to perioperative goal-directed therapy protocols reduces morbidity and mortality, particularly in patients having high-risk surgery. Perioperative goal-directed therapy protocols need to be started early, should include vasoactive agents in addition to fluids, and should target blood flow related variables. Future promising developments in the field of perioperative goal-directed therapy include personalized hemodynamic management and closed-loop system management.

Predictors of Atherosclerotic Change in Unruptured Intracranial Aneurysms and Parent Arteries During Clipping.

OBJECTIVES: To identify predictors of atherosclerotic change in aneurysms and parent arteries, and to retrospectively analyze outcomes from clipped aneurysms that showed atherosclerotic changes. METHODS: Between May 2017 and April 2018, we collected a total of 151 clipping cases and reviewed records of operation videos to classify atherosclerosis by location (dome, neck of aneurysm, or parent artery). To identify predictors of atherosclerotic change in aneurysms, we analyzed baseline demographic characteristics, preoperative images, and Framingham Risk Scores (FRS). We also analyzed incomplete clipping cases according to atherosclerosis presence and location. RESULT: This study cohort included 110 women (mean age, 59.3 ± 7.1 years) and 41 men (mean age, 55.9 ± 9.6 years). Atherosclerotic change was seen in 77 cases. FRS, diabetes mellitus, and aneurysm size were identified as independent risk factors for atherosclerotic change in multivariate logistic regression analysis. There were 11 incomplete clipping cases (7.2%). Among the 30 cases with atherosclerotic change in the neck were 10 cases of incomplete clipping (P < 0.001). CONCLUSIONS: FRS, diabetes mellitus, and aneurysm size as predictors of atherosclerosis in patients undergoing aneurysm surgery can help guide surgical decisions and performance.

Intraoperative Neuromonitoring: Principles and Considerations for Perioperative Nurses.

Intraoperative neuromonitoring (IONM) is a method used to warn the surgeon of impending neurological damage while it can still be corrected, ideally preventing a permanent neurological deficit in the surgical patient. It was originally used in neurosurgery, but now also applies to other surgical specialties. Comprehensive monitoring of a patient's neurological status requires using a variety of approaches. The IONM tests most frequently used in the OR are somatosensory evoked potentials; transcranial electrical motor evoked potentials; electromyography, including cranial nerve monitoring; and electroencephalography. With its increased use during a variety of operative and other invasive procedures, most perioperative nurses will be exposed to IONM at some point in their careers. This article provides perioperative nurses with a basic understanding of IONM, including the framework, purpose, associated terminology, and nursing implications.