Effect of Telemedicine Support for Intraoperative Anaesthesia Care on Postoperative Outcomes: The TECTONICS Randomised Clinical Trial.

Background: Novel applications of telemedicine can improve care quality and patient outcomes. Telemedicine for intraoperative decision support has not been rigorously studied. Methods: This single centre randomised clinical trial ( clinicaltrials.gov NCT03923699 ) of unselected adult surgical patients was conducted between July 1, 2019 and January 31, 2023. Patients received usual care or decision support from a telemedicine service, the Anesthesiology Control Tower (ACT). The ACT provided real-time recommendations to intraoperative anaesthesia clinicians based on case reviews, machine-learning forecasting, and physiologic alerts. ORs were randomised 1:1. Co-primary outcomes of 30-day all-cause mortality, respiratory failure, acute kidney injury (AKI), and delirium were analysed as intention-to-treat. Results: The trial completed planned enrolment with 71927 surgeries (35956 ACT; 35971 usual care). After multiple testing correction, there was no significant effect of the ACT vs. usual care on 30-day mortality [641/35956 (1.8%) vs 638/35971 (1.8%), risk difference 0.0% (95% CI -0.2% to 0.3%), p=0.96], respiratory failure [1089/34613 (3.1%) vs 1112/34619 (3.2%), risk difference -0.1% (95% CI -0.4% to 0.3%), p=0.96], AKI [2357/33897 (7%) vs 2391/33795 (7.1%), risk difference -0.1% (-0.6% to 0.4%), p=0.96], or delirium [1283/3928 (32.7%) vs 1279/3989 (32.1%), risk difference 0.6% (-2.0% to 3.2%), p=0.96]. There were no significant differences in secondary outcomes or in sensitivity analyses. Conclusions: In this large RCT of a novel application of telemedicine-based remote monitoring and decision support using real-time alerts and case reviews, we found no significant differences in postoperative outcomes. Large-scale intraoperative telemedicine is feasible, and we suggest future avenues where it may be impactful.

Effect of Machine Learning on Anaesthesiology Clinician Prediction of Postoperative Complications: The Perioperative ORACLE Randomised Clinical Trial.

BACKGROUND: Anaesthesiology clinicians can implement risk mitigation strategies if they know which patients are at greatest risk for postoperative complications. Although machine learning models predicting complications exist, their impact on clinician risk assessment is unknown. METHODS: This single-centre randomised clinical trial enrolled patients age ≥18 undergoing surgery with anaesthesiology services. Anaesthesiology clinicians providing remote intraoperative telemedicine support reviewed electronic health records with (assisted group) or without (unassisted group) also reviewing machine learning predictions. Clinicians predicted the likelihood of postoperative 30-day all-cause mortality and postoperative acute kidney injury within 7 days. Area under the receiver operating characteristic curve (AUROC) for the clinician predictions was determined. RESULTS: Among 5,071 patient cases reviewed by 89 clinicians, the observed incidence was 2% for postoperative death and 11% for acute kidney injury. Clinician predictions agreed with the models more strongly in the assisted versus unassisted group (weighted kappa 0.75 versus 0.62 for death [difference 0.13, 95%CI 0.10-0.17] and 0.79 versus 0.54 for kidney injury [difference 0.25, 95%CI 0.21-0.29]). Clinicians predicted death with AUROC of 0.793 in the assisted group and 0.780 in the unassisted group (difference 0.013, 95%CI -0.070 to 0.097). Clinicians predicted kidney injury with AUROC of 0.734 in the assisted group and 0.688 in the unassisted group (difference 0.046, 95%CI -0.003 to 0.091). CONCLUSIONS: Although there was evidence that the models influenced clinician predictions, clinician performance was not statistically significantly different with and without machine learning assistance. Further work is needed to clarify the role of machine learning in real-time perioperative risk stratification. TRIAL REGISTRATION: ClinicalTrials.gov NCT05042804.

An Intraoperative Telemedicine Program to Improve Perioperative Quality Measures: The ACTFAST-3 Randomized Clinical Trial.

Importance: Telemedicine for clinical decision support has been adopted in many health care settings, but its utility in improving intraoperative care has not been assessed. Objective: To pilot the implementation of a real-time intraoperative telemedicine decision support program and evaluate whether it reduces postoperative hypothermia and hyperglycemia as well as other quality of care measures. Design, Setting, and Participants: This single-center pilot randomized clinical trial (Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments [ACTFAST-3]) was conducted from April 3, 2017, to June 30, 2019, at a large academic medical center in the US. A total of 26 254 adult surgical patients were randomized to receive either usual intraoperative care (control group; n = 12 980) or usual care augmented by telemedicine decision support (intervention group; n = 13 274). Data were initially analyzed from April 22 to May 19, 2021, with updates in November 2022 and February 2023. Intervention: Patients received either usual care (medical direction from the anesthesia care team) or intraoperative anesthesia care monitored and augmented by decision support from the Anesthesiology Control Tower (ACT), a real-time, live telemedicine intervention. The ACT incorporated remote monitoring of operating rooms by a team of anesthesia clinicians with customized analysis software. The ACT reviewed alerts and electronic health record data to inform recommendations to operating room clinicians. Main Outcomes and Measures: The primary outcomes were avoidance of postoperative hypothermia (defined as the proportion of patients with a final recorded intraoperative core temperature >36 °C) and hyperglycemia (defined as the proportion of patients with diabetes who had a blood glucose level ≤180 mg/dL on arrival to the postanesthesia recovery area). Secondary outcomes included intraoperative hypotension, temperature monitoring, timely antibiotic redosing, intraoperative glucose evaluation and management, neuromuscular blockade documentation, ventilator management, and volatile anesthetic overuse. Results: Among 26 254 participants, 13 393 (51.0%) were female and 20 169 (76.8%) were White, with a median (IQR) age of 60 (47-69) years. There was no treatment effect on avoidance of hyperglycemia (7445 of 8676 patients [85.8%] in the intervention group vs 7559 of 8815 [85.8%] in the control group; rate ratio [RR], 1.00; 95% CI, 0.99-1.01) or hypothermia (7602 of 11 447 patients [66.4%] in the intervention group vs 7783 of 11 672 [66.7.%] in the control group; RR, 1.00; 95% CI, 0.97-1.02). Intraoperative glucose measurement was more common among patients with diabetes in the intervention group (RR, 1.07; 95% CI, 1.01-1.15), but other secondary outcomes were not significantly different. Conclusions and Relevance: In this randomized clinical trial, anesthesia care quality measures did not differ between groups, with high confidence in the findings. These results suggest that the intervention did not affect the targeted care practices. Further streamlining of clinical decision support and workflows may help the intraoperative telemedicine program achieve improvement in targeted clinical measures. Trial Registration: ClinicalTrials.gov Identifier: NCT02830126.

Reducing perioperative red blood cell unit issue orders, returns, and waste using failure modes and effects analysis.

BACKGROUND: Surgical transfusion has an outsized impact on hospital-based transfusion services, leading to blood product waste and unnecessary costs. The objective of this study was to design and implement a streamlined, reliable process for perioperative blood issue ordering and delivery to reduce waste. STUDY DESIGN AND METHODS: To address the high rates of surgical blood issue requests and red blood cell (RBC) unit waste at a large academic medical center, a failure modes and effects analysis was used to systematically examine perioperative blood management practices. Based on identified failure modes (e.g., miscommunication, knowledge gaps), a multi-component action plan was devised involving process changes, education, electronic clinical decision support, audit, and feedback. Changes in RBC unit issue requests, returns, waste, labor, and cost were measured pre- and post-intervention. RESULTS: The number of perioperative RBC unit issue requests decreased from 358 per month (SD 24) pre-intervention to 282 per month (SD 16) post-intervention (p < .001), resulting in an estimated savings of 8.9 h per month in blood bank staff labor. The issue-to-transfusion ratio decreased from 2.7 to 2.1 (p < .001). Perioperative RBC unit waste decreased from 4.5% of units issued pre-intervention to 0.8% of units issued post-intervention (p < .001), saving an estimated $148,543 in RBC unit acquisition costs and $546,093 in overhead costs per year. DISCUSSION: Our intervention, designed based on a structured failure modes analysis, achieved sustained reductions in perioperative RBC unit issue orders, returns, and waste, with associated benefits for blood conservation and transfusion program costs.

Postoperative Delirium Severity and Recovery Correlate With Electroencephalogram Spectral Features.

BACKGROUND: Delirium is an acute syndrome characterized by inattention, disorganized thinking, and an altered level of consciousness. A reliable biomarker for tracking delirium does not exist, but oscillations in the electroencephalogram (EEG) could address this need. We evaluated whether the frequencies of EEG oscillations are associated with delirium onset, severity, and recovery in the postoperative period. METHODS: Twenty-six adults enrolled in the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES; ClinicalTrials.gov NCT02241655) study underwent major surgery requiring general anesthesia, and provided longitudinal postoperative EEG recordings for this prespecified substudy. The presence and severity of delirium were evaluated with the confusion assessment method (CAM) or the CAM-intensive care unit. EEG data obtained during awake eyes-open and eyes-closed states yielded relative power in the delta (1-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) bands. Discriminability for delirium presence was evaluated with c-statistics. To account for correlation among repeated measures within patients, mixed-effects models were generated to assess relationships between: (1) delirium severity and EEG relative power (ordinal), and (2) EEG relative power and time (linear). Slopes of ordinal and linear mixed-effects models are reported as the change in delirium severity score/change in EEG relative power, and the change in EEG relative power/time (days), respectively. Bonferroni correction was applied to confidence intervals (CIs) to account for multiple comparisons. RESULTS: Occipital alpha relative power during eyes-closed states offered moderate discriminability (c-statistic, 0.75; 98% CI, 0.58-0.87), varying inversely with delirium severity (slope, -0.67; 98% CI, -1.36 to -0.01; P = .01) and with severity of inattention (slope, -1.44; 98% CI, -2.30 to -0.58; P = .002). Occipital theta relative power during eyes-open states correlated directly with severity of delirium (slope, 1.28; 98% CI, 0.12-2.44; P = .007), inattention (slope, 2.00; 98% CI, 0.48-3.54; P = .01), and disorganized thinking (slope, 3.15; 98% CI, 0.66-5.65; P = .01). Corresponding frontal EEG measures recapitulated these relationships to varying degrees. Severity of altered level of consciousness correlated with frontal theta relative power during eyes-open states (slope, 11.52; 98% CI, 6.33-16.71; P < .001). Frontal theta relative power during eyes-open states correlated inversely with time (slope, -0.05; 98% CI, -0.12 to -0.04; P = .002). CONCLUSIONS: Presence, severity, and core features of postoperative delirium covary with spectral features of the EEG. The cost and accessibility of EEG facilitate the translation of these findings to future mechanistic and interventional trials.

Predicting Postoperative Troponin in Patients Undergoing Elective Hip or Knee Arthroplasty: A Comparison of Five Cardiac Risk Prediction Tools.

Background: Elderly patients undergoing hip or knee arthroplasty are at a risk for myocardial injury after noncardiac surgery (MINS). We evaluated the ability of five common cardiac risk scores, alone or combined with baseline high-sensitivity cardiac troponin I (hs-cTnI), in predicting MINS and postoperative day 2 (POD2) hs-cTnI levels in patients undergoing elective total hip or knee arthroplasty. Methods: This study is ancillary to the Genetics-InFormatics Trial (GIFT) of Warfarin Therapy to Prevent Deep Venous Thrombosis, which enrolled patients 65 years and older undergoing elective total hip or knee arthroplasty. The five cardiac risk scores evaluated were the atherosclerotic cardiovascular disease calculator (ASCVD), the Framingham risk score (FRS), the American College of Surgeon's National Surgical Quality Improvement Program (ACS-NSQIP) calculator, the revised cardiac risk index (RCRI), and the reconstructed RCRI (R-RCRI). Results: None of the scores predicted MINS in women. Among men, the ASCVD (C-statistic of 0.66; p=0.04), ACS-NSQIP (C-statistic of 0.69; p=0.01), and RCRI (C-statistic of 0.64; p=0.04) predicted MINS. Among all patients, spearman correlations (r s) of the risk scores with the POD2 hs-cTnI levels were 0.24, 0.20, 0.11, 0.11, and 0.08 for the ASCVD, Framingham, ACS-NSQIP, RCRI, and R-RCRI scores, respectively, with p values of <0.001, <0.001, <0.001, 0.006, and 0.025. Baseline hs-cTnI predicted MINS (C-statistics: 0.63 in women and 0.72 in men) and postoperative hs-cTnI (r s = 0.51, p=0.001). Conclusion: In elderly patients undergoing elective hip or knee arthroplasty, several of the scores modestly predicted MINS in men and correlated with POD2 hs-cTnI.

Personalized Surgical Transfusion Risk Prediction Using Machine Learning to Guide Preoperative Type and Screen Orders.

BACKGROUND: Accurate estimation of surgical transfusion risk is essential for efficient allocation of blood bank resources and for other aspects of anesthetic planning. This study hypothesized that a machine learning model incorporating both surgery- and patient-specific variables would outperform the traditional approach that uses only procedure-specific information, allowing for more efficient allocation of preoperative type and screen orders. METHODS: The American College of Surgeons National Surgical Quality Improvement Program Participant Use File was used to train four machine learning models to predict the likelihood of red cell transfusion using surgery-specific and patient-specific variables. A baseline model using only procedure-specific information was created for comparison. The models were trained on surgical encounters that occurred at 722 hospitals in 2016 through 2018. The models were internally validated on surgical cases that occurred at 719 hospitals in 2019. Generalizability of the best-performing model was assessed by external validation on surgical cases occurring at a single institution in 2020. RESULTS: Transfusion prevalence was 2.4% (73,313 of 3,049,617), 2.2% (23,205 of 1,076,441), and 6.7% (1,104 of 16,053) across the training, internal validation, and external validation cohorts, respectively. The gradient boosting machine outperformed the baseline model and was the best- performing model. At a fixed 96% sensitivity, this model had a positive predictive value of 0.06 and 0.21 and recommended type and screens for 36% and 30% of the patients in internal and external validation, respectively. By comparison, the baseline model at the same sensitivity had a positive predictive value of 0.04 and 0.144 and recommended type and screens for 57% and 45% of the patients in internal and external validation, respectively. The most important predictor variables were overall procedure-specific transfusion rate and preoperative hematocrit. CONCLUSIONS: A personalized transfusion risk prediction model was created using both surgery- and patient-specific variables to guide preoperative type and screen orders and showed better performance compared to the traditional procedure-centric approach.

Effect of electroencephalogram-guided anaesthesia administration on 1-yr mortality: follow-up of a randomised clinical trial.

BACKGROUND: Intraoperative EEG suppression duration has been associated with postoperative delirium and mortality. In a clinical trial testing anaesthesia titration to avoid EEG suppression, the intervention did not decrease the incidence of postoperative delirium, but was associated with reduced 30-day mortality. The present study evaluated whether the EEG-guided anaesthesia intervention was also associated with reduced 1-yr mortality. METHODS: This manuscript reports 1 yr follow-up of subjects from a single-centre RCT, including a post hoc secondary outcome (1-yr mortality) in addition to pre-specified secondary outcomes. The trial included subjects aged 60 yr or older undergoing surgery with general anaesthesia between January 2015 and May 2018. Patients were randomised to receive EEG-guided anaesthesia or usual care. The previously reported primary outcome was postoperative delirium. The outcome of the current study was all-cause 1-yr mortality. RESULTS: Of the 1232 subjects enrolled, 614 subjects were randomised to EEG-guided anaesthesia and 618 subjects to usual care. One-year mortality was 57/591 (9.6%) in the guided group and 62/601 (10.3%) in the usual-care group. No significant difference in mortality was observed (adjusted absolute risk difference, -0.7%; 99.5% confidence interval, -5.8% to 4.3%; P=0.68). CONCLUSIONS: An EEG-guided anaesthesia intervention aiming to decrease duration of EEG suppression during surgery did not significantly decrease 1-yr mortality. These findings, in the context of other studies, do not provide supportive evidence for EEG-guided anaesthesia to prevent intermediate term postoperative death. CLINICAL TRIAL REGISTRATION: NCT02241655.

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.

Protocol for the Prognosticating Delirium Recovery Outcomes Using Wakefulness and Sleep Electroencephalography (P-DROWS-E) study: a prospective observational study of delirium in elderly cardiac surgical patients.

INTRODUCTION: Delirium is a potentially preventable disorder characterised by acute disturbances in attention and cognition with fluctuating severity. Postoperative delirium is associated with prolonged intensive care unit and hospital stay, cognitive decline and mortality. The development of biomarkers for tracking delirium could potentially aid in the early detection, mitigation and assessment of response to interventions. Because sleep disruption has been posited as a contributor to the development of this syndrome, expression of abnormal electroencephalography (EEG) patterns during sleep and wakefulness may be informative. Here we hypothesise that abnormal EEG patterns of sleep and wakefulness may serve as predictive and diagnostic markers for postoperative delirium. Such abnormal EEG patterns would mechanistically link disrupted thalamocortical connectivity to this important clinical syndrome. METHODS AND ANALYSIS: P-DROWS-E (Prognosticating Delirium Recovery Outcomes Using Wakefulness and Sleep Electroencephalography) is a 220-patient prospective observational study. Patient eligibility criteria include those who are English-speaking, age 60 years or older and undergoing elective cardiac surgery requiring cardiopulmonary bypass. EEG acquisition will occur 1-2 nights preoperatively, intraoperatively, and up to 7 days postoperatively. Concurrent with EEG recordings, two times per day postoperative Confusion Assessment Method (CAM) evaluations will quantify the presence and severity of delirium. EEG slow wave activity, sleep spindle density and peak frequency of the posterior dominant rhythm will be quantified. Linear mixed-effects models will be used to evaluate the relationships between delirium severity/duration and EEG measures as a function of time. ETHICS AND DISSEMINATION: P-DROWS-E is approved by the ethics board at Washington University in St. Louis. Recruitment began in October 2018. Dissemination plans include presentations at scientific conferences, scientific publications and mass media. TRIAL REGISTRATION NUMBER: NCT03291626.

Protocol for a proof-of-concept observational study evaluating the potential utility and acceptability of a telemedicine solution for the post-anesthesia care unit.

Introduction: The post-anesthesia care unit (PACU) is a clinical area designated for patients recovering from invasive procedures. There are typically several geographically dispersed PACUs within hospitals. Patients in the PACU can be unstable and at risk for complications. However, clinician coverage and patient monitoring in PACUs is not well regulated and might be sub-optimal. We hypothesize that a telemedicine center for the PACU can improve key PACU functions. Objectives: The objective of this study is to demonstrate the potential utility and acceptability of a telemedicine center to complement the key functions of the PACU. These include participation in hand-off activities to and from the PACU, detection of physiological derangements, identification of symptoms requiring treatment, recognition of situations requiring emergency medical intervention, and determination of patient readiness for PACU discharge. Methods and analysis: This will be a single center prospective before-and-after proof-of-concept study. Adults (18 years and older) undergoing elective surgery and recovering in two selected PACU bays will be enrolled. During the initial three-month observation phase, clinicians in the telemedicine center will not communicate with clinicians in the PACU, unless there is a specific patient safety concern. During the subsequent three-month interaction phase, clinicians in the telemedicine center will provide structured decision support to PACU clinicians. The primary outcome will be time to PACU discharge readiness determination in the two study phases. The attitudes of key stakeholders towards the telemedicine center will be assessed. Other outcomes will include detection of physiological derangements, complications, adverse symptoms requiring treatments, and emergencies requiring medical intervention. Registration: This trial is registered on clinicaltrials.gov, NCT04020887 (16 th July 2019).

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.

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.

Association between postoperative complications and lingering post-surgical pain: an observational cohort study.

BACKGROUND: Post-surgical pain that lingers beyond the initial few-week period of tissue healing is a major predictor of pain chronification, which leads to substantial disability and new persistent opioid analgesic use. We investigated whether postoperative medical complications increase the risk of lingering post-surgical pain. METHODS: The study population consisted of patients undergoing diverse elective surgical procedures in an academic referral centre in the USA, between September 2013 and May 2017. Multivariable logistic regression, adjusting for confounding variables and patient-specific risk factors, was used to test for an independent association between any major postoperative complication and functionally limiting lingering pain 1-3 months after surgery, as obtained from patient self-reports. RESULTS: The cohort included 11 986 adult surgical patients; 10 562 with complete data. At least one complication (cardiovascular, respiratory, renal/gastrointestinal, wound, thrombotic, or neural) was reported by 13.3% (95% confidence interval: 12.7-14.0) of patients, and 19.7% (19.0-20.5%) reported functionally limiting lingering post-surgical pain. After adjusting for known risk factors, the patients were twice as likely (odds ratio: 2.04; 1.78-2.35) to report lingering post-surgical pain if they also self-reported a postoperative complication. Experiencing a complication was also independently predictive of lingering post-surgical pain (odds ratio: 1.95; 1.26-3.04) when complication data were extracted from the National Surgical Quality Improvement Program registry, instead of being obtained from patient self-report. CONCLUSIONS: Medical complications were associated with a two-fold increase in functionally limiting pain 1-3 months after surgery. Understanding the mechanisms that link complications to pathological persistence of pain could help develop future approaches to prevent persistent post-surgical pain.

Intraoperative Awareness With Recall: A Descriptive, Survey-Based, Cohort Study.

BACKGROUND: Unintended intraoperative awareness with recall (AWR) is a potential complication of general anesthesia. Patients typically report recollections of (1) hearing sounds or conversations, (2) being unable to breathe or move, (3), feeling pain, and/or (4) experiencing emotional distress. The purpose of the current study was to identify and further characterize AWR experiences identified through postoperative surveys of a large unselected adult surgical cohort. METHODS: This is a substudy of a prospective registry study, which surveys patients on their health and well-being after surgery. Responses to 4 questions focusing on AWR were analyzed. Patients who reported AWR with pain, paralysis, and/or distress were contacted by telephone to obtain more information about their AWR experience. The interview results for patients who received general anesthesia were sent to 3 anesthesiologists, who adjudicated the reported AWR episodes. RESULTS: Of 48,151 surveys sent, 17,875 patient responses were received. Of these respondents, 622 reported a specific memory from the period between going to sleep and waking up from perceived general anesthesia and 282 of these reported related pain, paralysis, and/or distress. An attempt was made to contact these 282 patients, and 149 participated in a telephone survey. Among the 149 participants, 87 endorsed their prior report of AWR. However, only 22 of these patients had received general anesthesia, while 51 received only sedation and 14 received regional anesthesia. Three anesthesiologists independently adjudicated the survey results of the 22 general anesthesia cases and assigned 6 as definite AWR, 8 as possible AWR, and 8 as not AWR episodes. Of the 65 patients who confirmed their report of AWR after regional or sedation anesthesia, 37 (31 with sedation and 6 with regional anesthesia) had not expected to be conscious during surgery. CONCLUSIONS: The complication of AWR continues to occur during intended general anesthesia. Many reports of AWR episodes occur in patients receiving sedation or regional anesthesia and relate to incorrect expectations regarding anesthetic techniques and conscious experiences, representing a potential target for intervention.

Association of Preoperative Functional Performance With Outcomes After Surgical Treatment of Head and Neck Cancer: A Clinical Severity Staging System.

Importance: Patients with head and neck cancers have comorbidities and other constitutional symptoms known to be associated with adverse postoperative outcomes, but the role of functional performance is not well studied. Objective: To explore the addition of functional performance to other clinical factors for association with 3 patient outcomes: 30-day unplanned readmission (UR), 90-day medical complications, and overall survival (OS). Design, Setting, and Participants: This retrospective cohort study was conducted in a single tertiary care center with patients surgically treated for squamous cell cancer of the lip, oral cavity, pharynx, or larynx from January 2012 to December 2016. All analysis took place between January 2018 and November 2018. Data from 2 registries were analyzed, supplemented with medical record review. Logistic regression analysis was used to explore association of preoperative functional performance with outcomes. Conjunctive consolidation was used to create a useful clinical severity staging system, which included functional performance (estimated from metabolic equivalent [MET] score: <4, light-intensity activities; ≥4 at least moderate-intensity activities); overall comorbidity severity; preoperative weight loss; and TNM tumor staging. Logistic regression was used to assess the prognostic accuracy of the clinical severity staging system for 30-day UR and 90-day complications, and Cox proportional hazard regression for OS. Exposures: All patients underwent surgical treatment for head and neck cancer. Main Outcomes and Measures: The primary outcomes were 30-day UR and 90-day complications; the secondary outcome was OS. Results: For the 657 patients included, the mean (SD) age was 62.0 (11.3) years; 73% were men (n = 477), and 88% were white (n = 580). A total of 75 (11%) had a 30-day UR; 204 (31%) developed a 90-day complication; and 127 (19%) patients died during the observation period. Individually, poor functional performance (<4 METs), high comorbidity burden, preoperative weight loss, and advanced TNM stage were associated with all 3 outcomes; the increased risk for each outcome ranged from 1.5 to 3.0 times the reference range. Using these 4 variables in combination, the 4-category clinical severity staging system demonstrated a strong association between severity stage and all 3 adverse outcomes: 30-day UR (C statistic, 0.63), 90-day complications (C statistic, 0.63), and OS (C statistic, 0.68). Conclusions and Relevance: Poor preoperative functional performance, high comorbidity burden, preoperative weight loss, and advanced tumor stage were all associated with worse patient outcomes after head and neck cancer surgery. The model incorporating all 4 of these factors developed in this study may facilitate patient-centered risk assessment and patient-physician shared preoperative decision making.

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.