The Current State of Combined Pediatric Anesthesiology-Critical Care Practice: A Survey of Dual-Trained Practitioners in the United States

BACKGROUND

Combined practice in pediatric anesthesiology (PA) and pediatric critical care medicine (PCCM) was historically common but has declined markedly with time. The reasons for this temporal shift are unclear, but existing evidence suggests that length of training is a barrier to contemporary trainees. Among current practitioners, restriction in dual-specialty practice also occurs, for reasons that are unknown at present. We sought to describe the demographics of this population, investigate their perceptions about the field, and consider factors that lead to attrition.

METHODS

We conducted a cross-sectional, observational study of physicians in the United States with a combined practice in PA and PCCM. The survey was distributed electronically and anonymously to the distribution list of the Pediatric Anesthesia Leadership Council (PALC) of the Society for Pediatric Anesthesia (SPA), directing the recipients to forward the link to their faculty meeting our inclusion criteria. Attending-level respondents (n = 62) completed an anonymous, 40-question multidomain survey.

RESULTS

Forty-seven men and 15 women, with a median age of 51, completed the survey. Major leadership positions are held by 44%, and 55% are externally funded investigators. A minority (26%) have given up one or both specialties, citing time constraints and politics as the dominant reasons. Duration of training was cited as the major barrier to entry by 77%. Increasing age and faculty rank and lack of a comparably trained institutional colleague were associated with attrition from dual-specialty practice. The majority (88%) reported that they would do it all again.

CONCLUSIONS

The current cohort of pediatric anesthesiologist-intensivists in the United States is a small but accomplished group of physicians. Efforts to train, recruit, and retain such providers must address systematic barriers to completion of the requisite training and continued practice.

Probabilistic forecasting of surgical case duration using machine learning: model development and validation

OBJECTIVE

Accurate estimations of surgical case durations can lead to the cost-effective utilization of operating rooms. We developed a novel machine learning approach, using both structured and unstructured features as input, to predict a continuous probability distribution of surgical case durations.

MATERIALS AND METHODS

The data set consisted of 53 783 surgical cases performed over 4 years at a tertiary-care pediatric hospital. Features extracted included categorical (American Society of Anesthesiologists [ASA] Physical Status, inpatient status, day of week), continuous (scheduled surgery duration, patient age), and unstructured text (procedure name, surgical diagnosis) variables. A mixture density network (MDN) was trained and compared to multiple tree-based methods and a Bayesian statistical method. A continuous ranked probability score (CRPS), a generalized extension of mean absolute error, was the primary performance measure. Pinball loss (PL) was calculated to assess accuracy at specific quantiles. Performance measures were additionally evaluated on common and rare surgical procedures. Permutation feature importance was measured for the best performing model.

RESULTS

MDN had the best performance, with a CRPS of 18.1 minutes, compared to tree-based methods (19.5-22.1 minutes) and the Bayesian method (21.2 minutes). MDN had the best PL at all quantiles, and the best CRPS and PL for both common and rare procedures. Scheduled duration and procedure name were the most important features in the MDN.

CONCLUSIONS

Using natural language processing of surgical descriptors, we demonstrated the use of ML approaches to predict the continuous probability distribution of surgical case durations. The more discerning forecast of the ML-based MDN approach affords opportunities for guiding intelligent schedule design and day-of-surgery operational decisions.

Abnormal preoperative cognitive screening in aged surgical patients: a retrospective cohort analysis

BACKGROUND

Preoperative cognitive dysfunction has been associated with adverse postoperative outcomes. There are limited data characterising the epidemiology of preoperative cognitive dysfunction in older surgical patients.

METHODS

This retrospective cohort included all patients ≥65 yr old seen at the Washington University preoperative clinic between January 2013 and June 2018. Cognitive screening was performed using the Short-Blessed Test (SBT) and Eight-Item Interview to Differentiate Aging and Dementia (AD8) screen. The primary outcome of abnormal cognitive screening was defined as SBT score ≥5 or AD8 score ≥2. Multivariable logistic regression was used to identify associated factors.

RESULTS

Overall, 21 666 patients ≥65 yr old completed screening during the study period; 23.5% (n=5099) of cognitive screens were abnormal. Abnormal cognitive screening was associated with increasing age, decreasing BMI, male sex, non-Caucasian race, decreased functional independence, and decreased metabolic functional capacity. Patients with a history of stroke or transient ischaemic attack, chronic obstructive pulmonary disease, diabetes mellitus, hepatic cirrhosis, and heavy alcohol use were also more likely to have an abnormal cognitive screen. Predictive modelling showed no combination of patient factors was able to reliably identify patients who had a <10% probability of abnormal cognitive screening.

CONCLUSIONS

Routine preoperative cognitive screening of unselected aged surgical patients often revealed deficits consistent with cognitive impairment or dementia. Such deficits were associated with increased age, decreased function, decreased BMI, and several common medical comorbidities. Further research is necessary to characterise the clinical implications of preoperative cognitive dysfunction and identify interventions that may reduce related postoperative complications.

Preoperative Cognitive Abnormality, Intraoperative Electroencephalogram Suppression, and Postoperative Delirium: A Mediation Analysis

BACKGROUND

Postoperative delirium is a common complication that hinders recovery after surgery. Intraoperative electroencephalogram suppression has been linked to postoperative delirium, but it is unknown if this relationship is causal or if electroencephalogram suppression is merely a marker of underlying cognitive abnormalities. The hypothesis of this study was that intraoperative electroencephalogram suppression mediates a nonzero portion of the effect between preoperative abnormal cognition and postoperative delirium.

METHODS

This is a prespecified secondary analysis of the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) randomized trial, which enrolled patients age 60 yr or older undergoing surgery with general anesthesia at a single academic medical center between January 2015 and May 2018. Patients were randomized to electroencephalogram-guided anesthesia or usual care. Preoperative abnormal cognition was defined as a composite of previous delirium, Short Blessed Test cognitive score greater than 4 points, or Eight Item Interview to Differentiate Aging and Dementia score greater than 1 point. Duration of intraoperative electroencephalogram suppression was defined as number of minutes with suppression ratio greater than 1%. Postoperative delirium was detected via Confusion Assessment Method or chart review on postoperative days 1 to 5.

RESULTS

Among 1,113 patients, 430 patients showed evidence of preoperative abnormal cognition. These patients had an increased incidence of postoperative delirium (151 of 430 [35%] vs.123 of 683 [18%], P < 0.001). Of this 17.2% total effect size (99.5% CI, 9.3 to 25.1%), an absolute 2.4% (99.5% CI, 0.6 to 4.8%) was an indirect effect mediated by electroencephalogram suppression, while an absolute 14.8% (99.5% CI, 7.2 to 22.5%) was a direct effect of preoperative abnormal cognition. Randomization to electroencephalogram-guided anesthesia did not change the mediated effect size (P = 0.078 for moderation).

CONCLUSIONS

A small portion of the total effect of preoperative abnormal cognition on postoperative delirium was mediated by electroencephalogram suppression. Study precision was too low to determine if the intervention changed the mediated effect.

High-Sensitivity Cardiac Troponin After Cardiac Stress Test: A Systematic Review and Meta-Analysis

Background The recent introduction of high-sensitivity cardiac troponin (hs-cTn) assays has allowed clinicians to measure hs-cTn before and after cardiac stress testing, but the hs-cTn release pattern and potential utility in identifying inducible myocardial ischemia are unclear. We thus conducted a systematic review and meta-analysis to improve our understanding of hs-cTn release associated with exercise and pharmacological stress testing. Methods and Results Studies published between January 2008 and July 2016 that reported hs-cTn change values (high-sensitivity cardiac troponin T [hs-cTnT] or high-sensitivity cardiac troponin I [hs-cTnI]) in relation to cardiac stress testing were searched and reviewed by 2 independent screeners. Primary outcomes were pooled estimates of absolute and relative hs-cTn changes after cardiac stress test, stratified by the presence of inducible myocardial ischemia. This meta-analysis included 11 studies (n=2432 patients). After exercise stress testing, hs-cTnT increased by 0.5 ng/L or 11% (6 studies, n=406) and hs-cTnI by 2.4 ng/L or 41% (4 studies, n=365) in patients with inducible myocardial ischemia versus hs-cTnT by 1.1 ng/L or 18% (8 studies, n=629; P=0.29) and hs-cTnI by 1.8 ng/L or 72% (4 studies, n=831; P=0.61) in patients who did not develop inducible myocardial ischemia. After pharmacological stress test, hs-cTnT changed by -0.1 ng/L or -0.4% (6 studies, n=251) and hs-cTnI by 2.4 ng/L or 32% (2 studies, n=108) in patients with inducible myocardial ischemia versus hs-cTnT by 0.7 ng/L or 11% (5 studies, n=443, P=0.44) and hs-cTnI by 1.7 ng/L or 38% (2 studies, n=116; P=0.62) in patients who did not develop inducible myocardial ischemia. Conclusions hs-cTn rising patterns after exercise and pharmacological stress testing appear inconsistent and comparably small, and do not appear to be correlated with inducible myocardial ischemia.

Practical Training of Anesthesia Clinicians in Electroencephalogram-Based Determination of Hypnotic Depth of General Anesthesia

BACKGROUND

Electroencephalographic (EEG) brain monitoring during general anesthesia provides information on hypnotic depth. We hypothesized that anesthesia clinicians could be trained rapidly to recognize typical EEG waveforms occurring with volatile-based general anesthesia.

METHODS

This was a substudy of a trial testing the hypothesis that EEG-guided anesthesia prevents postoperative delirium. The intervention was a 35-minute training session, summarizing typical EEG changes with volatile-based anesthesia. Participants completed a preeducational test, underwent training, and completed a posteducational test. For each question, participants indicated whether the EEG was consistent with (1) wakefulness, (2) non-slow-wave anesthesia, (3) slow-wave anesthesia, or (4) burst suppression. They also indicated whether the processed EEG (pEEG) index was discordant with the EEG waveforms. Four clinicians, experienced in intraoperative EEG interpretation, independently evaluated the EEG waveforms, resolved disagreements, and provided reference answers. Ten questions were assessed in the preeducational test and 9 in the posteducational test.

RESULTS

There were 71 participants; 13 had previous anesthetic-associated EEG interpretation training. After training, the 58 participants without prior training improved at identifying dominant EEG waveforms (median 60% with interquartile range [IQR], 50%-70% vs 78% with IQR, 67%-89%; difference: 18%; 95% confidence interval [CI], 8-27; P < .001). In contrast, there was no significant improvement following the training for the 13 participants who reported previous training (median 70% with IQR, 60%-80% vs 67% with IQR, 67%-78%; difference: -3%; 95% CI, -18 to 11; P = .88). The difference in the change between the pre- and posteducational session for the previously untrained versus previously trained was statistically significant (difference in medians: 21%; 95% CI, 2-28; P = .005). Clinicians without prior training also improved in identifying discordance between the pEEG index and the EEG waveform (median 60% with IQR, 40%-60% vs median 100% with IQR, 75%-100%; difference: 40%; 95% CI, 30-50; P < .001). Clinicians with prior training showed no significant improvement (median 60% with IQR, 60%-80% vs 75% with IQR, 75%-100%; difference: 15%; 95% CI, -16 to 46; P = .16). Regarding the identification of discordance, the difference in the change between the pre- and posteducational session for the previously untrained versus previously trained was statistically significant (difference in medians: 25%; 95% CI, 5-45; P = .012).

CONCLUSIONS

A brief training session was associated with improvements in clinicians without prior EEG training in (1) identifying EEG waveforms corresponding to different hypnotic depths and (2) recognizing when the hypnotic depth suggested by the EEG was discordant with the pEEG index.

Protocol for the Effectiveness of an Anesthesiology Control Tower System in Improving Perioperative Quality Metrics and Clinical Outcomes: the TECTONICS randomized, pragmatic trial

Introduction: Perioperative morbidity is a public health priority, and surgical volume is increasing rapidly. With advances in technology, there is an opportunity to research the utility of a telemedicine-based control center for anesthesia clinicians that assess risk, diagnoses negative patient trajectories, and implements evidence-based practices. Objectives: The primary objective of this trial is to determine whether an anesthesiology control tower (ACT) prevents clinically relevant adverse postoperative outcomes including 30-day mortality, delirium, respiratory failure, and acute kidney injury. Secondary objectives are to determine whether the ACT improves perioperative quality of care metrics including management of temperature, mean arterial pressure, mean airway pressure with mechanical ventilation, blood glucose, anesthetic concentration, antibiotic redosing, and efficient fresh gas flow. Methods and analysis: We are conducting a single center, randomized, controlled, phase 3 pragmatic clinical trial. A total of 58 operating rooms are randomized daily to receive support from the ACT or not. All adults (eighteen years and older) undergoing surgical procedures in these operating rooms are included and followed until 30 days after their surgery. Clinicians in operating rooms randomized to ACT support receive decision support from clinicians in the ACT. In operating rooms randomized to no intervention, the current standard of anesthesia care is delivered. The intention-to-treat principle will be followed for all analyses. Differences between groups will be presented with 99% confidence intervals; p-values <0.005 will be reported as providing compelling evidence, and p-values between 0.05 and 0.005 will be reported as providing suggestive evidence. Registration: TECTONICS is registered on ClinicalTrials.gov, NCT03923699; registered on 23 April 2019.

Deep-learning model for predicting 30-day postoperative mortality

BACKGROUND

Postoperative mortality occurs in 1-2% of patients undergoing major inpatient surgery. The currently available prediction tools using summaries of intraoperative data are limited by their inability to reflect shifting risk associated with intraoperative physiological perturbations. We sought to compare similar benchmarks to a deep-learning algorithm predicting postoperative 30-day mortality.

METHODS

We constructed a multipath convolutional neural network model using patient characteristics, co-morbid conditions, preoperative laboratory values, and intraoperative numerical data from patients undergoing surgery with tracheal intubation at a single medical centre. Data for 60 min prior to a randomly selected time point were utilised. Model performance was compared with a deep neural network, a random forest, a support vector machine, and a logistic regression using predetermined summary statistics of intraoperative data.

RESULTS

Of 95 907 patients, 941 (1%) died within 30 days. The multipath convolutional neural network predicted postoperative 30-day mortality with an area under the receiver operating characteristic curve of 0.867 (95% confidence interval [CI]: 0.835-0.899). This was higher than that for the deep neural network (0.825; 95% CI: 0.790-0.860), random forest (0.848; 95% CI: 0.815-0.882), support vector machine (0.836; 95% CI: 0.802-870), and logistic regression (0.837; 95% CI: 0.803-0.871).

CONCLUSIONS

A deep-learning time-series model improves prediction compared with models with simple summaries of intraoperative data. We have created a model that can be used in real time to detect dynamic changes in a patient's risk for postoperative mortality.

Frailty Phenotypes and Relations With Surgical Outcomes: A Latent Class Analysis

BACKGROUND

Frailty is an important concept in the care of older adults although controversy remains regarding its defining features and clinical utility. Both the Fried phenotype and the Rockwood deficit accumulation approaches cast frailty as a "burden" without exploring the relative salience of its cardinal markers and their relevance to the patient. New multifactorial perspectives require a reliable assessment of frailty that can validly predict postoperative health outcomes.

METHODS

In a retrospective study of 2828 unselected surgical patients, we used item response theory to examine the ability of 32 heterogeneous markers capturing limitations in physical, functional, emotional, and social activity domains to indicate severity of frailty as a latent continuum. Eighteen markers efficiently indicated frailty severity and were then subject to latent class analysis to derive discrete phenotypes. Next, we validated the obtained frailty phenotypes against patient-reported 30-day postoperative outcomes using multivariable logistic regression. Models were adjusted for demographics, comorbidity, type and duration of surgery, and cigarette and alcohol consumption.

RESULTS

The 18 markers provided psychometric evidence of a single reliable continuum of frailty severity. Latent class analyses produced 3 distinct subtypes, based on patients' endorsement probabilities of the frailty indicators: not frail (49.7%), moderately frail (33.5%), and severely frail (16.7%). Unlike the moderate class, severely frail endorsed emotional health problems in addition to physical burdens and functional limitations. Models adjusting for age, sex, type of anesthesia, and intraoperative factors indicated that severely frail (odds ratio, 1.89; 95% confidence interval, 1.42-2.50) and moderately frail patients (odds ratio, 1.31; 95% confidence interval, 1.03-1.67) both had higher odds of experiencing postoperative complications compared to not frail patients. In a 3-way comparison, a higher proportion of severely frail patients (10.7%) reported poorer quality of life after surgery compared to moderately frail (9.2%) and not frail (8.3%) patients (P < .001). There was no significant difference among these groups in proportions reporting hospital readmission (5.6%, 5.1%, and 3.8%, respectively; P = .067).

CONCLUSIONS

Self-report frailty items can accurately discern 3 distinct phenotypes differing in composition and their relations with surgical outcomes. Systematically assessing a wider set of domains including limitations in functional, emotional, and social activities can inform clinicians on what precipitates loss of physiological reserve and profoundly influences patients' lives. This information can help guide the current discussion on frailty and add meaningful clinical tools to the surgical practice.

Somatosensory predictors of response to pregabalin in painful chemotherapy-induced peripheral neuropathy: a randomized, placebo-controlled, crossover study

Painful chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating and treatment-resistant sequela of many chemotherapeutic medications. Ligands of α2δ subunits of voltage-gated Ca channels, such as pregabalin, have shown efficacy in reducing mechanical sensitivity in animal models of neuropathic pain. In addition, some data suggest that pregabalin may be more efficacious in relieving neuropathic pain in subjects with increased sensitivity to pinprick. We hypothesized that greater mechanical sensitivity, as quantified by decreased mechanical pain threshold at the feet, would be predictive of a greater reduction in average daily pain in response to pregabalin vs placebo. In a prospective, randomized, double-blinded study, 26 patients with painful CIPN from oxaliplatin, docetaxel, or paclitaxel received 28-day treatment with pregabalin (titrated to maximum dose 600 mg per day) and placebo in crossover design. Twenty-three participants were eligible for efficacy analysis. Mechanical pain threshold was not significantly correlated with reduction in average pain (P = 0.97) or worst pain (P = 0.60) in response to pregabalin. There was no significant difference between pregabalin and placebo in reducing average daily pain (22.5% vs 10.7%, P = 0.23) or worst pain (29.2% vs 16.0%, P = 0.13) from baseline. Post hoc analysis of patients with CIPN caused by oxaliplatin (n = 18) demonstrated a larger reduction in worst pain with pregabalin than with placebo (35.4% vs 14.6%, P = 0.04). In summary, baseline mechanical pain threshold tested on dorsal feet did not meaningfully predict the analgesic response to pregabalin in painful CIPN.

Effect of Electroencephalography-Guided Anesthetic Administration on Postoperative Delirium Among Older Adults Undergoing Major Surgery: The ENGAGES Randomized Clinical Trial

IMPORTANCE

Intraoperative electroencephalogram (EEG) waveform suppression, often suggesting excessive general anesthesia, has been associated with postoperative delirium.

OBJECTIVE

To assess whether EEG-guided anesthetic administration decreases the incidence of postoperative delirium.

DESIGN, SETTING, AND PARTICIPANTS

Randomized clinical trial of 1232 adults aged 60 years and older undergoing major surgery and receiving general anesthesia at Barnes-Jewish Hospital in St Louis. Recruitment was from January 2015 to May 2018, with follow-up until July 2018.

INTERVENTIONS

Patients were randomized 1:1 (stratified by cardiac vs noncardiac surgery and positive vs negative recent fall history) to receive EEG-guided anesthetic administration (n = 614) or usual anesthetic care (n = 618).

MAIN OUTCOMES AND MEASURES

The primary outcome was incident delirium during postoperative days 1 through 5. Intraoperative measures included anesthetic concentration, EEG suppression, and hypotension. Adverse events included undesirable intraoperative movement, intraoperative awareness with recall, postoperative nausea and vomiting, medical complications, and death.

RESULTS

Of the 1232 randomized patients (median age, 69 years [range, 60 to 95]; 563 women [45.7%]), 1213 (98.5%) were assessed for the primary outcome. Delirium during postoperative days 1 to 5 occurred in 157 of 604 patients (26.0%) in the guided group and 140 of 609 patients (23.0%) in the usual care group (difference, 3.0% [95% CI, -2.0% to 8.0%]; P = .22). Median end-tidal volatile anesthetic concentration was significantly lower in the guided group than the usual care group (0.69 vs 0.80 minimum alveolar concentration; difference, -0.11 [95% CI, -0.13 to -0.10), and median cumulative time with EEG suppression was significantly less (7 vs 13 minutes; difference, -6.0 [95% CI, -9.9 to -2.1]). There was no significant difference between groups in the median cumulative time with mean arterial pressure below 60 mm Hg (7 vs 7 minutes; difference, 0.0 [95% CI, -1.7 to 1.7]). Undesirable movement occurred in 137 patients (22.3%) in the guided and 95 (15.4%) in the usual care group. No patients reported intraoperative awareness. Postoperative nausea and vomiting was reported in 48 patients (7.8%) in the guided and 55 patients (8.9%) in the usual care group. Serious adverse events were reported in 124 patients (20.2%) in the guided and 130 (21.0%) in the usual care group. Within 30 days of surgery, 4 patients (0.65%) in the guided group and 19 (3.07%) in the usual care group died.

CONCLUSIONS AND RELEVANCE

Among older adults undergoing major surgery, EEG-guided anesthetic administration, compared with usual care, did not decrease the incidence of postoperative delirium. This finding does not support the use of EEG-guided anesthetic administration for this indication.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02241655.

Predicting Hospital Readmission via Cost-Sensitive Deep Learning

With increased use of electronic medical records (EMRs), data mining on medical data has great potential to improve the quality of hospital treatment and increase the survival rate of patients. Early readmission prediction enables early intervention, which is essential to preventing serious or life-threatening events, and act as a substantial contributor to reduce healthcare costs. Existing works on predicting readmission often focus on certain vital signs and diseases by extracting statistical features. They also fail to consider skewness of class labels in medical data and different costs of misclassification errors. In this paper, we recur to the merits of convolutional neural networks (CNN) to automatically learn features from time series of vital sign, and categorical feature embedding to effectively encode feature vectors with heterogeneous clinical features, such as demographics, hospitalization history, vital signs, and laboratory tests. Then, both learnt features via CNN and statistical features via feature embedding are fed into a multilayer perceptron (MLP) for prediction. We use a cost-sensitive formulation to train MLP during prediction to tackle the imbalance and skewness challenge. We validate the proposed approach on two real medical datasets from Barnes-Jewish Hospital, and all data is taken from historical EMR databases and reflects the kinds of data that would realistically be available at the clinical prediction system in hospitals. We find that early prediction of readmission is possible and when compared with state-of-the-art existing methods used by hospitals, our methods perform significantly better. For example, using the general hospital wards data for 30-day readmission prediction, the area under the curve (AUC) for the proposed model was 0.70, significantly higher than all the baseline methods. Based on these results, a system is being deployed in hospital settings with the proposed forecasting algorithms to support treatment.

Study protocol for the Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: a pilot randomized controlled trial in intraoperative telemedicine

Background: Each year, over 300 million people undergo surgical procedures worldwide. Despite efforts to improve outcomes, postoperative morbidity and mortality are common. Many patients experience complications as a result of either medical error or failure to adhere to established clinical practice guidelines. This protocol describes a clinical trial comparing a telemedicine-based decision support system, the Anesthesiology Control Tower (ACT), with enhanced standard intraoperative care. Methods: This study is a pragmatic, comparative effectiveness trial that will randomize approximately 12,000 adult surgical patients on an operating room (OR) level to a control or to an intervention group. All OR clinicians will have access to decision support software within the OR as a part of enhanced standard intraoperative care. The ACT will monitor patients in both groups and will provide additional support to the clinicians assigned to intervention ORs. Primary outcomes include blood glucose management and temperature management. Secondary outcomes will include surrogate, clinical, and economic outcomes, such as incidence of intraoperative hypotension, postoperative respiratory compromise, acute kidney injury, delirium, and volatile anesthetic utilization. Ethics and dissemination: The ACTFAST-3 study has been approved by the Human Resource Protection Office (HRPO) at Washington University in St. Louis and is registered at clinicaltrials.gov ( NCT02830126). Recruitment for this protocol began in April 2017 and will end in December 2018. Dissemination of the findings of this study will occur via presentations at academic conferences, journal publications, and educational materials.

Study protocol for the Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: a pilot randomized controlled trial in intraoperative telemedicine

Background: Each year, over 300 million people undergo surgical procedures worldwide. Despite efforts to improve outcomes, postoperative morbidity and mortality are common. Many patients experience complications as a result of either medical error or failure to adhere to established clinical practice guidelines. This protocol describes a clinical trial comparing a telemedicine-based decision support system, the Anesthesiology Control Tower (ACT), with enhanced standard intraoperative care. Methods: This study is a pragmatic, comparative effectiveness trial that will randomize approximately 12,000 adult surgical patients on an operating room (OR) level to a control or to an intervention group. All OR clinicians will have access to decision support software within the OR as a part of enhanced standard intraoperative care. The ACT will monitor patients in both groups and will provide additional support to the clinicians assigned to intervention ORs. Primary outcomes include blood glucose management and temperature management. Secondary outcomes will include surrogate, clinical, and economic outcomes, such as incidence of intraoperative hypotension, postoperative respiratory compromise, acute kidney injury, delirium, and volatile anesthetic utilization. Ethics and dissemination: The ACTFAST-3 study has been approved by the Human Resource Protection Office (HRPO) at Washington University in St. Louis and is registered at clinicaltrials.gov ( NCT02830126). Recruitment for this protocol began in April 2017 and will end in December 2018. Dissemination of the findings of this study will occur via presentations at academic conferences, journal publications, and educational materials.

Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study

INTRODUCTION

Mortality and morbidity following surgery are pressing public health concerns in the USA. Traditional prediction models for postoperative adverse outcomes demonstrate good discrimination at the population level, but the ability to forecast an individual patient's trajectory in real time remains poor. We propose to apply machine learning techniques to perioperative time-series data to develop algorithms for predicting adverse perioperative outcomes.

METHODS AND ANALYSIS

This study will include all adult patients who had surgery at our tertiary care hospital over a 4-year period. Patient history, laboratory values, minute-by-minute intraoperative vital signs and medications administered will be extracted from the electronic medical record. Outcomes will include in-hospital mortality, postoperative acute kidney injury and postoperative respiratory failure. Forecasting algorithms for each of these outcomes will be constructed using density-based logistic regression after employing a Nadaraya-Watson kernel density estimator. Time-series variables will be analysed using first and second-order feature extraction, shapelet methods and convolutional neural networks. The algorithms will be validated through measurement of precision and recall.

ETHICS AND DISSEMINATION

This study has been approved by the Human Research Protection Office at Washington University in St Louis. The successful development of these forecasting algorithms will allow perioperative healthcare clinicians to predict more accurately an individual patient's risk for specific adverse perioperative outcomes in real time. Knowledge of a patient's dynamic risk profile may allow clinicians to make targeted changes in the care plan that will alter the patient's outcome trajectory. This hypothesis will be tested in a future randomised controlled trial.

Obstructive sleep apnea as an independent predictor of postoperative delirium and pain: protocol for an observational study of a surgical cohort

Introduction: Postoperative delirium and pain are common complications in adults, and are difficult both to prevent and treat. Obstructive sleep apnea (OSA) is prevalent in surgical patients, and has been suggested to be a risk factor for postoperative delirium and pain. OSA also might impact pain perception, and alter pain medication requirements. This protocol describes an observational study, with the primary aim of testing whether OSA is an independent predictor of postoperative complications, focusing on (i) postoperative incident delirium and (ii) acute postoperative pain severity. We secondarily hypothesize that compliance with prescribed treatment for OSA (typically continuous positive airway pressure or CPAP) might decrease the risk of delirium and the severity of pain. Methods and analysis: We will include data from patients who have been enrolled into three prospective studies: ENGAGES, PODCAST, and SATISFY-SOS. All participants underwent general anesthesia for a non-neurosurgical inpatient operation, and had a postoperative hospital stay of at least one day at Barnes Jewish Hospital in St. Louis, Missouri, from February 2013 to May 2018.  Patients included in this study have been assessed for postoperative delirium and pain severity as part of the parent studies. In the current study, determination of delirium diagnosis will be based on the Confusion Assessment Method, and the Visual Analogue Pain Scale will be used for pain severity. Data on OSA diagnosis, OSA risk and compliance with treatment will be obtained from the preoperative assessment record. Other variables that are candidate risk factors for delirium and pain will also be extracted from this record. We will use logistic regression to test whether OSA independently predicts postoperative delirium and linear regression to assess OSAs relationship to acute pain severity. We will conduct secondary analyses with subgroups to explore whether these relationships are modified by compliance with OSA treatment.

Building a collaborative culture in cardiothoracic operating rooms: pre and postintervention study protocol for evaluation of the implementation of teamSTEPPS training and the impact on perceived psychological safety

INTRODUCTION

The importance of effective communication, a key component of teamwork, is well recognised in the healthcare setting. Establishing a culture that encourages and empowers team members to speak openly in the cardiothoracic (CT) operating room (OR) is necessary to improve patient safety in this high-risk environment.

METHODS AND ANALYSIS

This study will take place at Barnes-Jewish Hospital, an academic hospital in affiliation with Washington University School of Medicine located in the USA. All team members participating in cardiac and thoracic OR cases during this 17-month study period will be identified by the primary surgical staff attending on the OR schedule.TeamSTEPPS (Team Strategies and Tools to Enhance Performance and Patient Safety) training course will be taught to all CT OR staff. Before TeamSTEPPS training, staff will respond to a 39-item questionnaire that includes constructs from the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture, Edmondson's 'Measure of psychological safety' questionnaire, and questionnaires on turnover intentions, job satisfaction and 'burnout'. The questionnaires will be readministered at 6 and 12 months.The primary outcomes to be assessed include the perceived psychological safety of CT OR team members, the overall effect of TeamSTEPPS on burnout and job satisfaction, and observed turnover rate among the OR nurses. As secondary outcomes, we will be assessing self-reported rates of medical error and near misses in the ORs with a questionnaire at the end of each case.

ETHICS AND DISSEMINATION

Ethics approval is not indicated as this project does not meet the federal definitions of research requiring the oversight of the Institutional Review Board (IRB). Patient health information (PHI) will not be generated during the implementation of this project. Results of the trial will be made accessible to the public when published in a peer-reviewed journal following the completion of the study.

Changes in quality of life after elective surgery: an observational study comparing two measures

PURPOSE

Our main objective was to compare the change in a validated quality of life measure to a global assessment measure. The secondary objectives were to estimate the minimum clinically important difference (MCID) and to describe the change in quality of life by surgical specialty.

METHODS

This prospective cohort study included 7902 adult patients undergoing elective surgery. Changes in the Veterans RAND 12-Item Health Survey (VR-12), composed of a physical component summary (PCS) and a mental component summary (MCS), were calculated using preoperative and postoperative questionnaires. The latter also contained a global assessment question for quality of life. We compared PCS and MCS to the global assessment using descriptive statistics and weighted kappa. MCID was calculated using an anchor-based approach. Analyses were pre-specified and registered (NCT02771964).

RESULTS

By the change in VR-12 scores, an equal proportion of patients experienced improvement and deterioration in quality of life (28% for PCS, 25% for MCS). In contrast, by the global assessment measure, 61% reported improvement, while only 10% reported deterioration. Agreement with the global assessment was slight for both PCS (kappa = 0.20, 57% matched) and MCS (kappa = 0.10, 54% matched). The MCID for the overall VR-12 score was approximately 2.5 points. Patients undergoing orthopedic surgery showed the most improvement in quality of life measures, while patients undergoing gastrointestinal/hepatobiliary or urologic surgery showed the most deterioration.

CONCLUSIONS

Subjective global quality of life report does not agree well with a validated quality of life instrument, perhaps due to patient over-optimism.

Intraoperative ketamine for prevention of postoperative delirium or pain after major surgery in older adults: an international, multicentre, double-blind, randomised clinical trial

BACKGROUND

Delirium is a common and serious postoperative complication. Subanaesthetic ketamine is often administered intraoperatively for postoperative analgesia, and some evidence suggests that ketamine prevents delirium. The primary purpose of this trial was to assess the effectiveness of ketamine for prevention of postoperative delirium in older adults.

METHODS

The Prevention of Delirium and Complications Associated with Surgical Treatments [PODCAST] study is a multicentre, international randomised trial that enrolled adults older than 60 years undergoing major cardiac and non-cardiac surgery under general anaesthesia. Using a computer-generated randomisation sequence we randomly assigned patients to one of three groups in blocks of 15 to receive placebo (normal saline), low-dose ketamine (0·5 mg/kg), or high dose ketamine (1·0 mg/kg) after induction of anaesthesia, before surgical incision. Participants, clinicians, and investigators were blinded to group assignment. Delirium was assessed twice daily in the first 3 postoperative days using the Confusion Assessment Method. We did analyses by intention-to-treat and assessed adverse events. This trial is registered with clinicaltrials.gov, number NCT01690988.

FINDINGS

Between Feb 6, 2014, and June 26, 2016, 1360 patients were assessed, and 672 were randomly assigned, with 222 in the placebo group, 227 in the 0·5 mg/kg ketamine group, and 223 in the 1·0 mg/kg ketamine group. There was no difference in delirium incidence between patients in the combined ketamine groups and the placebo group (19·45% vs 19·82%, respectively; absolute difference 0·36%, 95% CI -6·07 to 7·38, p=0·92). There were more postoperative hallucinations (p=0·01) and nightmares (p=0·03) with increasing ketamine doses compared with placebo. Adverse events (cardiovascular, renal, infectious, gastrointestinal, and bleeding), whether viewed individually (p value for each >0·40) or collectively (36·9% in placebo, 39·6% in 0·5 mg/kg ketamine, and 40·8% in 1·0 mg/kg ketamine groups, p=0·69), did not differ significantly across groups.

INTERPRETATION

A single subanaesthetic dose of ketamine did not decrease delirium in older adults after major surgery, and might cause harm by inducing negative experiences.

FUNDING

National Institutes of Health and Cancer Center Support.

Characterizing psychosis risk traits in Africa: A longitudinal study of Kenyan adolescents

The schizophrenia prodrome has not been extensively studied in Africa. Identification of prodromal behavioral symptoms holds promise for early intervention and prevention of disorder onset. Our goal was to investigate schizophrenia risk traits in Kenyan adolescents and identify predictors of psychosis progression. 135 high-risk (HR) and 142 low-risk (LR) adolescents were identified from among secondary school students in Machakos, Kenya, using the structured interview of psychosis-risk syndromes (SIPS) and the Washington early recognition center affectivity and psychosis (WERCAP) screen. Clinical characteristics were compared across groups, and participants followed longitudinally over 0-, 4-, 7-, 14- and 20-months. Potential predictors of psychosis conversion and severity change were studied using multiple regression analyses. More psychiatric comorbidities and increased psychosocial stress were observed in HR compared to LR participants. HR participants also had worse attention and better abstraction. The psychosis conversion rate was 3.8%, with only disorganized communication severity at baseline predicting conversion (p=0.007). Decreasing psychotic symptom severity over the study period was observed in both HR and LR participants. ADHD, bipolar disorder, and major depression diagnoses, as well as poor occupational functioning and avolition were factors relating to lesser improvement in psychosis severity. Our results indicate that psychopathology and disability occur at relatively high rates in Kenyan HR adolescents. Few psychosis conversions may reflect an inadequate time to conversion, warranting longer follow-up studies to clarify risk predictors. Identifying disorganized communication and other risk factors could be useful for developing preventive strategies for HR youth in Kenya.

Ability of preoperative falls to predict postsurgical outcomes in non-selected patients undergoing elective surgery at an academic medical centre: protocol for a prospective cohort study

INTRODUCTION

Falls are increasingly recognised for their ability to herald impending health decline. Despite the likely susceptibility of postsurgical patients to falls, a detailed description of postoperative falls in an unselected surgical population has never been performed. One study suggests that preoperative falls may forecast postoperative complications. However, a larger study with non-selected surgical patients and patient-centred outcomes is needed to provide the generalisability and justification necessary to implement preoperative falls assessment into routine clinical practice. The aims of this study are therefore twofold. First, we aim to describe the main features of postoperative falls in a population of unselected surgical patients. Second, we aim to test the hypothesis that a history of falls in the 6 months prior to surgery predicts postoperative falls, poor quality of life, functional dependence, complications and readmission.

METHODS AND ANALYSIS

To achieve these goals, we study adult patients who underwent elective surgery at our academic medical centre and were recruited to participate in a prospective, survey-based cohort study called Systematic Assessment and Targeted Improvement of Services Following Yearlong Surgical Outcomes Surveys (SATISFY-SOS) (NCT02032030). Patients who reported falling in the 6 months prior to surgery will be considered 'exposed.' The primary outcome of interest is postoperative falls within 30 days of surgery. Secondary outcomes include postoperative functional dependence, quality of life (both physical and mental), in-hospital complications and readmission. Regression models will permit controlling for important confounders.

ETHICS AND DISSEMINATION

The home institution's Institutional Review Board approved this study (IRB ID number 201505035). The authors will publish the findings, regardless of the results.