Prediction Model Performance With Different Imputation Strategies: A Simulation Study Using a North American ICU Registry.

OBJECTIVES: To evaluate the performance of pragmatic imputation approaches when estimating model coefficients using datasets with varying degrees of data missingness. DESIGN: Performance in predicting observed mortality in a registry dataset was evaluated using simulations of two simple logistic regression models with age-specific criteria for abnormal vital signs (mentation, systolic blood pressure, respiratory rate, WBC count, heart rate, and temperature). Starting with a dataset with complete information, increasing degrees of biased missingness of WBC and mentation were introduced, depending on the values of temperature and systolic blood pressure, respectively. Missing data approaches evaluated included analysis of complete cases only, assuming missing data are normal, and multiple imputation by chained equations. Percent bias and root mean square error, in relation to parameter estimates obtained from the original data, were evaluated as performance indicators. SETTING: Data were obtained from the Virtual Pediatric Systems, LLC, database (Los Angeles, CA), which provides clinical markers and outcomes in prospectively collected records from 117 PICUs in the United States and Canada. PATIENTS: Children admitted to a participating PICU in 2017, for whom all required data were available. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Simulations demonstrated that multiple imputation by chained equations is an effective strategy and that even a naive implementation of multiple imputation by chained equations significantly outperforms traditional approaches: the root mean square error for model coefficients was lower using multiple imputation by chained equations in 90 of 99 of all simulations (91%) compared with discarding cases with missing data and lower in 97 of 99 (98%) compared with models assuming missing values are in the normal range. Assuming missing data to be abnormal was inferior to all other approaches. CONCLUSIONS: Analyses of large observational studies are likely to encounter the issue of missing data, which are likely not missing at random. Researchers should always consider multiple imputation by chained equations (or similar imputation approaches) when encountering even only small proportions of missing data in their work.

Blood pressure nomograms for children undergoing general anesthesia, stratified by age and anesthetic type, using data from a retrospective cohort at a tertiary pediatric center.

Reference values for non-invasive blood pressure (NIBP) are available for children undergoing general anesthesia, but have not been analyzed by type of anesthetic. This study establishes age-specific pediatric NIBP reference values, stratified by anesthetic type: inhalational anesthesia (IHA), total intravenous anesthesia (TIVA), and mostly intravenous anesthesia (MIVA, an inhalational induction followed by intravenous maintenance of anesthesia). NIBP measurements were extracted from a de-identified vital signs database for children < 19 years undergoing anesthesia between Jan/2013-Dec/2016, excluding cardiac surgery. We automatically rejected artifacts and randomly sampled 20 NIBP values per case. Anesthetic phase (induction/maintenance) was identified using operating room booking times for procedure start, and anesthetic types were identified based on intraoperative minimum alveolar concentration values in the different phases of the anesthetic. From 36,347 cases in our operating room booking system, we matched 24,457 cases with available vital signs. Of these, 20,613 (84%) had valid NIBP data and could be assigned to one anesthetic type: TIVA 11,819 [57%], IHA 4,752 [23%], and MIVA 4,042 [20%]. Mean NIBP during anesthesia increased with age, from median values of 48 mmHg (TIVA), 45 mmHg (IHA), and 41 mmHg (MIVA) in neonates, to 70 mmHg (TIVA), 68 mmHg (IHA), and 64 mmHg (MIVA) in 18-year-olds, respectively. In children < 1 year, mean NIBP values were 4 mmHg higher with TIVA than IHA (p < 0.001). These pediatric NIBP reference values contribute to ongoing debate about alarm limits based on age and anesthetic type, and may motivate prospective studies into the effects of different anesthesia regimes on vital signs.

The Effect of Carbetocin Dose on Transmural Dispersion of Myocardial Repolarization in Healthy Parturients Scheduled for Elective Cesarean Delivery Under Spinal Anesthesia: A Prospective, Randomized Clinical Trial.

BACKGROUND: QT interval prolongation is associated with torsade de pointes but remains a poor predictor of drug torsadogenicity. Increased transmural dispersion of myocardial repolarization (TDR), measured as the time interval between the peak and end of the T wave (Tp-e), is a more reliable predictor. Carbetocin is recommended as an uterotonic in patients undergoing cesarean delivery (CD), but its effect on Tp-e is unknown. We evaluated the effect of carbetocin dose on Tp-e and Bazett-corrected QT intervals (QTc) during elective CD under spinal anesthesia. METHODS: On patient consent, 50 healthy parturients undergoing elective CD with a standardized spinal anesthetic and phenylephrine infusion were randomized to receive an intravenous (IV) bolus of carbetocin 50 µg (C50) or 100 µg (C100) via an infusion pump over 1 minute. A 12-lead electrocardiogram (ECG) was obtained at baseline, 5 minutes after spinal anesthesia, then 5 and 10 minutes after carbetocin administration. A cardiologist blinded to group and timing of ECGs measured QTc and Tp-e using Emori's criteria. Primary outcome was the change in Tp-e at 5 minutes after carbetocin administration between the C50 and C100 groups and within each group compared to baseline values. Secondary outcomes included occurrence of arrhythmias, changes in QTc at 5 and 10 minutes after carbetocin, changes in both QTc and Tp-e after spinal anesthesia compared to baseline between and within groups. RESULTS: Data from 41 parturients with a mean (standard deviation [SD]) age of 39.0 (0.7) years and weight of 75.0 (12.0) kg were analyzed. Between groups, at 5 minutes after carbetocin administration, Tp-e in C100 was 4.1 milliseconds longer compared to C50 (95% confidence interval [CI], 0.8-7.5; P = .01). Within groups, at 5 minutes after carbetocin administration, C50 did not significantly increase Tp-e compared to baseline (mean difference [MD] 1.9 milliseconds; 95% CI, -0.95 to 4.81 milliseconds; P = .42) but C100 did (MD 5.1 milliseconds; 95% CI, 2.1-8.1; P = .003). QTc increased significantly within C50 and C100 groups at 5 and 10 minutes after carbetocin administration (all P < .001), with no between-group differences. There were no arrhythmias. CONCLUSIONS: Tp-e was unaffected by C50 IV given after CD in healthy parturients under spinal anesthesia, but minimally prolonged by C100. The increase in QTc after carbetocin administration was statistically significant, but with no apparent dose-dependent effect. The minimal Tp-e prolongation at the higher dose is unlikely to have any clinically significant impact on TDR and therefore the risk of inducing torsade de pointes is low.

The Effect of Low-Dose Intraoperative Ketamine on Closed-Loop-Controlled General Anesthesia: A Randomized Controlled Equivalence Trial.

BACKGROUND: Closed-loop control of propofol-remifentanil anesthesia using the processed electroencephalography depth-of-hypnosis index provided by the NeuroSENSE monitor (WAVCNS) has been previously described. The purpose of this placebo-controlled study was to evaluate the performance (percentage time within ±10 units of the setpoint during the maintenance of anesthesia) of a closed-loop propofol-remifentanil controller during induction and maintenance of anesthesia in the presence of a low dose of ketamine. METHODS: Following ethical approval and informed consent, American Society of Anesthesiologist (ASA) physical status I-II patients aged 19-54 years, scheduled for elective orthopedic surgery requiring general anesthesia for >60 minutes duration, were enrolled in a double-blind randomized, placebo-controlled, 2-group equivalence trial. Immediately before induction of anesthesia, participants in the ketamine group received a 0.25 mg·kg-1 bolus of intravenous ketamine over 60 seconds followed by a continuous 5 µg·kg-1·min-1 infusion for up to 45 minutes. Participants in the control group received an equivalent volume of normal saline. After the initial study drug bolus, closed-loop induction of anesthesia was initiated; propofol and remifentanil remained under closed-loop control until the anesthetic was tapered and turned off at the anesthesiologist's discretion. An equivalence range of ±8.99% was assumed for comparing controller performance. RESULTS: Sixty patients participated: 41 males, 54 ASA physical status I, with a median (interquartile range [IQR]) age of 29 [23, 38] years and weight of 82 [71, 93] kg. Complete data were available from 29 cases in the ketamine group and 27 in the control group. Percentage time within ±10 units of the WAVCNS setpoint was median [IQR] 86.6% [79.7, 90.2] in the ketamine group and 86.4% [76.5, 89.8] in the control group (median difference, 1.0%; 95% confidence interval [CI] -3.6 to 5.0). Mean propofol dose during maintenance of anesthesia for the ketamine group was higher than for the control group (median difference, 24.9 µg·kg-1·min-1; 95% CI, 6.5-43.1; P = .005). CONCLUSIONS: Because the 95% CI of the difference in controller performance lies entirely within the a priori equivalence range, we infer that this analgesic dose of ketamine did not alter controller performance. Further study is required to confirm the finding that mean propofol dosing was higher in the ketamine group, and to investigate the implication that this dose of ketamine may have affected the WAVCNS.

Characteristics and Timing of Mortality in Children Dying With Infections in North American PICUs.

OBJECTIVES: To investigate the characteristics and timing of death of children with severe infections who die during PICU admission. DESIGN: We analyzed demographics, timing of death, diagnoses, and common procedures in a large cohort obtained from the Virtual Pediatrics Systems database, focusing on early deaths (< 1 d). SETTING: Clinical records were prospectively collected in 130 PICUs across North America. PATIENTS: Children admitted between January 2009 and December 2014 with at least one infection-related diagnosis at time of death. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Analysis included data from 106,464 children admitted to PICUs. The 4,240 children (4%) who died were older than PICU survivors. The median (interquartile range) duration in PICU prior to death was 7.1 days (2.1-21.3 d), with 635 children (15%) dying early (< 1 d of PICU admission). Children who died early were older, more likely to have septic shock, and more likely to have received cardiopulmonary resuscitation than those who died later. Withdrawal of care was less likely in early deaths compared with later deaths. After adjusting for age, sex, sepsis severity, procedures (including cardiopulmonary resuscitation and heart, lung, and renal support), and number of admissions contributed per PICU, it was found that children admitted from the emergency department, inpatient floors, or referring hospitals had significantly greater risk of early death compared with children admitted from the operating room. CONCLUSIONS: A substantial proportion of children admitted to PICU with severe infections die early and differ from those dying later in diagnoses, procedures, and admitting location. The emergency department is a key source of critically ill patients. Understanding characteristics of early deaths may yield recruitment considerations for clinical trials enrolling children at high risk of early death.

Anesthesia in the modern world of apps and technology: Implications and impact on wellness.

Recent decades have seen an unprecedented leap in digital innovation, with far-reaching implications in healthcare. Anesthesiologists have historically championed the adoption of new technologies. However, the rapid evolution of these technologies has outpaced attempts at studying their potential impact on healthcare providers' well-being. This document introduces several categories of workplace technologies commonly encountered by the anesthesiologist. We examine examples of novel technology and the impact of these digital interventions on the anesthesiologist's well-being. We also review popular personalized technology aimed at improving wellness and the impact on well-being examined. Finally, technology acceptance models are introduced to improve technology adoption, which, when appropriately applied, may minimize the negative impacts of technology on anesthesiologists' well-being. Incorporating quantitative, serial assessments of well-being as part of technology implementation are proposed as a future direction for examining the wellness impact of technology on anesthesiologists.

Association of dexmedetomidine with recovery room and hospital discharge times: A retrospective cohort analysis.

BACKGROUND: Dexmedetomidine is a useful anesthetic adjunct, increasingly popular during pediatric surgery and procedural sedation. Its half-life of 2-3 hours might prolong recovery and discharge times when compared with an un-supplemented propofol anesthetic. This may create an additional burden in a busy post-anesthetic care unit (PACU). AIM: To investigate whether intraoperative adjuvant dexmedetomidine delays PACU discharge in patients undergoing propofol anesthesia for day surgery or procedural investigations with minimal anticipated post-procedural pain. METHODS: We conducted a retrospective review of outpatient procedures performed during a six-month period including pediatric patients, ASA physical status I-III, who underwent intravenous anesthesia with propofol and remifentanil for magnetic resonance imaging (MRI), strabismus repair, upper gastrointestinal endoscopy, or combined upper/lower gastrointestinal endoscopy. Patients receiving a sedative premedication, long-acting opioids, or volatile anesthetics for maintenance of anesthesia, were excluded. Duration of PACU stay was compared for patients who did or did not receive intraoperative dexmedetomidine in the four procedure groups. RESULTS: Charts were reviewed for 359 patients; 130 (36%) received dexmedetomidine. Median differences in duration of PACU stay for dexmedetomidine versus non-dexmedetomidine cases were: 5 minutes (95%CI 0 to 10, p=0.037) for MRI; 5 minutes (95%CI -3 to 15, p=0.258) for strabismus surgery; 7 minutes (95%CI 3 to 10, p<0.001) for upper endoscopy; and 5 minutes (95%CI 1 to 12, p=0.021) for combined upper/lower endoscopy. Linear regression (F=61.1, adjusted R2 =0.40) indicated a significant relationship between dexmedetomidine dose (estimate 14.6 minutes per µg/kg, 95%CI 8.2 to 21.1, p<0.001) and duration of PACU stay. CONCLUSION: We found evidence for a small association of intraoperative dexmedetomidine with duration of recovery from propofol anesthesia for a set of common outpatient procedures, with a potential dose relationship equivalent to approximately 15 minutes delay per µg/kg dexmedetomidine administered. Future research into the benefits of dexmedetomidine in pediatric anesthesia should further evaluate this relationship.

Effect of ketamine on the NeuroSENSE WAVCNS during propofol anesthesia; a randomized feasibility trial.

Dose-dependent effects of ketamine on processed electroencephalographic depth-of-hypnosis indices have been reported. Limited data are available for the NeuroSENSE WAVCNS index. Our aim was to establish the feasibility of closed-loop propofol-remifentanil anesthesia guided by the WAVCNS index in the presence of an analgesic dose of ketamine. Thirty ASA I-II adults, 18-54 years, requiring general anesthesia for anterior cruciate ligament surgery were randomized to receive: full-dose [ketamine, 0.5 mg kg-1 initial bolus, 10 mcg kg-1 min-1 infusion] (recommended dose for postoperative pain management); half-dose [ketamine, 0.25 mg kg-1 bolus, 5 mcg kg-1 min-1 infusion]; or control [no ketamine]. After the ketamine bolus, patients received 1.0 mcg kg-1 remifentanil over 30 s, then 1.5 mg kg-1 propofol over 30 s, followed by manually-adjusted propofol-remifentanil anesthesia. The WAVCNS was > 60 for 7/9 patients in the full-dose group at 7 min after starting the propofol infusion. This was inconsistent with clinical observations of depth-of-hypnosis and significantly higher than control (median difference [MD] 17.0, 95% confidence interval [CI] 11.4-26.8). WAVCNS was median [interquartile range] 49.3 [42.2-62.6] in the half-dose group, and not different to control (MD 5.1, 95% CI - 4.9 to 17.9). During maintenance of anesthesia, the WAVCNS was higher in the full-dose group compared to control (MD 14.7, 95% CI 10.2-19.2) and in the half-dose group compared to control (MD 11.4, 95% CI 4.7-20.4). The full-dose of ketamine recommended for postoperative pain management had a significant effect on the WAVCNS. This effect should be considered when using the WAVCNS to guide propofol-remifentanil dosing.Trial Registration ClinicalTrails.gov No. NCT02908945.

The effect of ketamine on depth of hypnosis indices during total intravenous anesthesia-a comparative study using a novel electroencephalography case replay system.

Ketamine may affect the reliability of electroencephalographic (EEG) depth-of-hypnosis indices as it affects power in high-frequency EEG components. The purpose of this study was to compare the effects of ketamine on three commonly-used depth-of-hypnosis indices by extending our EEG simulator to allow replay of previously-recorded EEG. Secondary analysis of previously-collected data from a randomized controlled trial of intravenous anesthesia with ketamine: Group 0.5 [ketamine, 0.5 mg kg-1 bolus followed by a 10 mcg kg-1 min-1 infusion], Group 0.25 [ketamine, 0.25 mg kg-1 bolus, 5 mcg kg-1 min-1 infusion], and Control [no ketamine]. EEG data were replayed to three monitors: NeuroSENSE (WAV), Bispectral Index (BIS), and Entropy (SE). Differences in depth-of-hypnosis indices during the initial 15 min after induction of anesthesia were compared between monitors, and between groups. Monitor agreement was evaluated using Bland-Altman analysis. Available data included 45.6 h of EEG recordings from 27 cases. Ketamine was associated with higher depth-of-hypnosis index values measured at 10 min (BIS, χ2 = 8.01, p = 0.018; SE, χ2 = 11.44, p = 0.003; WAV, χ2 = 9.19, p = 0.010), and a higher proportion of index values > 60 for both ketamine groups compared to the control group. Significant differences between monitors were not observed, except between BIS and SE in the control group. Ketamine did not change agreement between monitors. The ketamine-induced increase in depth-of-hypnosis indices was observed consistently across the three EEG monitoring algorithms evaluated. The observed increase was likely caused by a power increase in the beta and gamma bands. However, there were no lasting differences in depth-of-hypnosis reported between the three compared indices.

Evaluating NeuroSENSE for assessing depth of hypnosis during desflurane anesthesia: an adaptive, randomized-controlled trial.

PURPOSE: Processed electroencephalography (EEG) monitors support depth-of-hypnosis assessment during anesthesia. This randomized-controlled trial investigated the performance of the NeuroSENSE electroencephalography (EEG) monitor to determine whether its wavelet anesthetic value for central nervous system (WAVCNS) index distinguishes consciousness from unconsciousness during induction of anesthesia (as assessed by the anesthesiologist) and emergence from anesthesia (indicated by patient responsiveness), and whether it correlates with changes in desflurane minimum alveolar concentration (MAC) during maintenance of anesthesia. METHODS: EEG was collected using a fronto-temporal bilateral montage. The WAVCNS was continuously recorded by the NeuroSENSE monitor, to which the anesthesiologist was blinded. Anesthesia was induced with propofol/remifentanil and maintained with desflurane, with randomized changes of -0.4, 0, or +0.4 MAC every 7.5 min within the 0.8-1.6 MAC range, if clinically acceptable to the anesthesiologist. During emergence from anesthesia, desflurane was stepped down by 0.2 MAC every five minutes. RESULTS: Data from 75 patients with a median [interquartile range] age of 41[35-52] yr were obtained. The WAVCNS distinguished consciousness from unconsciousness as assessed by the anesthesiologist, with area under the receiver operating characteristic curve of 99.5% (95% confidence interval [CI], 98.5 to 100.0) at loss of consciousness and 99.4% (95% CI, 98.5 to 100.0) at return of consciousness. Bilateral WAVCNS changes correlated with desflurane concentrations, with -8.0 and -8.6 WAVCNS units, respectively, per 1 MAC change in the 0.8-1.6 MAC range during maintenance of anesthesia and -10.0 and -10.5 WAVCNS units, respectively, in the 0.4-1.6 MAC range including emergence from anesthesia. CONCLUSION: The NeuroSENSE monitor can reliably discriminate between consciousness and unconsciousness, as assessed by the anesthesiologist, during induction of anesthesia and with a lower level of reliability during emergence from anesthesia. The WAVCNS correlates with desflurane concentration but plateaus at higher concentrations, similar to other EEG monitors, which suggests limited utility to titrate higher concentrations of anesthetic vapour. TRIAL REGISTRATION: clinicaltrials.gov, NCT02088671; registered 17 March, 2014.

Reducing preoperative anxiety with Child Life preparation prior to intravenous induction of anesthesia: A randomized controlled trial.

BACKGROUND: Induction of anesthesia can be stressful: Up to 60% of children suffer significant anxiety immediately before surgery. Anxiety is associated with higher postoperative analgesia requirements, higher incidence of emergence delirium, and detrimental effects on sleep and behavior. Child Life preparation includes role-play, expectation-setting, and teaching coping strategies. AIM : The aim of this trial was to determine whether preoperative Child Life preparation reduces anxiety prior to intravenous induction of anesthesia. METHODS: Children aged 3-10 years, with no known preexisting anxiety and no preoperative anxiolytics, undergoing elective day surgery lasting ≤ 2 hours, were enrolled in a randomized controlled trial. Each child's baseline anxiety was assessed in the anesthetic care unit, using the modified Yale Preoperative Anxiety Scale-Short Form (mYPAS-SF, observational scores from 22.9, minimal anxiety, to 100, maximal anxiety) as the primary outcome. The child was randomly assigned to intervention (minimum 15 minutes Child Life preparation) or control (standard practice without Child Life preparation). Participants entered the operating room with one parent. A researcher (blinded to group allocation) scored the child's operating room anxiety using mYPAS-SF, up to the first attempt at intravenous cannulation. RESULTS: Fifty-nine children completed the study, aged median [interquartile range] 5 [3-7] years. Baseline mYPAS-SF anxiety was 29.2 [22.9-37.5] for all children, and operating room anxiety was 29.2 [22.9-49.0]. Operating room anxiety was higher than baseline in 16/31 (52%) children in the control group and 6/28 (21%) in the Child Life preparation group. ANCOVA revealed a significant effect of baseline mYPAS-SF anxiety and group on operating room anxiety (F = 10.31, P < .001, adjusted R2  = .24); individual parameter estimates indicated that Child Life preparation reduced operating room anxiety by 13.8 (95% CI 4.4-23.1) points compared to control, P = .005. CONCLUSION: A brief, targeted Child Life preparation session had a statistically significant effect on reducing preoperative anxiety prior to intravenous induction of anesthesia in young children, with no known preexisting anxiety. This effect may be clinically important and suggests that Child Life can be a valuable component of pediatric surgical care. Further research is required in specific populations.

Intravenous cannula placement in children for induction of general anesthesia: Prospective audit and identification of success factors.

BACKGROUND: Approaches to pediatric induction of anesthesia vary widely. While oral sedative premedication and inhalational induction are common, total intravenous anesthesia is becoming increasingly popular. Total intravenous anesthesia without anxiolytic premedication, which is the most commonly used technique in our hospital, requires intravenous (IV) cannula placement in an awake child. AIMS: To quantify the success rate of IV cannula placement in 1 or 2 attempts and to identify success factors and barriers. METHODS: With ethical approval and written informed consent from participating anesthesiologists, a prospective audit of IV cannulation was undertaken over a 1-month period. The attending anesthesiologist captured basic demographics, IV insertion characteristics, setting, distraction techniques, the behavior of the child, number of attempts, and success/failure. A logistic regression model for successful IV cannulation was created. Anesthesiologists and procedural suite nurses participated in semi-structured interviews to identify success factors, barriers, and teaching approaches. RESULTS: Data from 984 cases were analyzed. IV induction was planned in 562 cases, and IV cannulation was successful in 90% of these patients. Anxiolytic premedication was given in 6% of cases. Observations indicated that 64% of children were pain- and reaction-free, and 90% experienced minimal or no reaction. Predictors for success included older child's age and child behavior at first encounter. Qualitative interview data from 13 participants suggested success factors included effective distraction, preparing the family for IV induction, parental presence, support of the operating room team, effective use of local analgesic cream, adapting the approach to the individual child, and the anesthesiologist's efficiency. Barriers included needle phobia, uncooperative child, anxious parents, ineffective use of analgesic cream, and unfavorable anatomy. Distraction techniques varied by age and developmental stage of the child. CONCLUSIONS: Cannulation for planned IV induction is feasible for most children, enabling increased use of total intravenous anesthesia as an institutional anesthetic strategy.

Zero-heat-flux core temperature monitoring system: an observational secondary analysis to evaluate agreement with naso-/oropharyngeal probe during anesthesia.

General anesthesia impairs thermoregulation and contributes to perioperative hypothermia; core body temperature monitoring is recommended during surgical procedures lasting > 30 min. Zero-heat-flux core body temperature measurement systems enable continuous non-invasive perioperative monitoring. During a previous trial evaluating the benefits of preoperative forced-air warming, intraoperative temperatures were measured with both a zero-heat-flux sensor and a standard naso-/oropharyngeal temperature probe. The aim of this secondary analysis is to evaluate their agreement. ASA I-III patients, scheduled for elective, non-cardiac surgery under general anesthesia, were enrolled. A zero-heat-flux sensor was placed on the participant's forehead preoperatively. Following induction of anesthesia, a "clinical" temperature probe was placed in the nasopharynx or oropharynx at the anesthesiologist's discretion. Temperature measurements from both sensors were recorded every 10 s. Agreement was analyzed using the Bland-Altman method, corrected for repeated measurements, and Lin's concordance correlation coefficient, and compared with existing studies. Data were collected in 194 patients with a median (interquartile range) age of 60 (49-69) years, during surgical procedures lasting 120 (89-185) min. The zero-heat-flux measurements had a mean bias of - 0.05 °C (zero-heat-flux lower) with 95% limits of agreement within - 0.68 to + 0.58 °C. Lin's concordance correlation coefficient was 0.823. The zero-heat-flux sensor demonstrated moderate agreement with the naso-/oropharyngeal temperature probe, which was not fully within the generally accepted ± 0.5 °C limit. This is consistent with previous studies. The zero-heat-flux system offers clinical utility for non-invasive and continuous core body temperature monitoring throughout the perioperative period using a single sensor.

Augmented intelligence in pediatric anesthesia and pediatric critical care.

PURPOSE OF REVIEW: Acute care technologies, including novel monitoring devices, big data, increased computing capabilities, machine-learning algorithms and automation, are converging. This enables the application of augmented intelligence for improved outcome predictions, clinical decision-making, and offers unprecedented opportunities to improve patient outcomes, reduce costs, and improve clinician workflow. This article briefly explores recent work in the areas of automation, artificial intelligence and outcome prediction models in pediatric anesthesia and pediatric critical care. RECENT FINDINGS: Recent years have yielded little published research into pediatric physiological closed loop control (a type of automation) beyond studies focused on glycemic control for type 1 diabetes. However, there has been a greater range of research in augmented decision-making, leveraging artificial intelligence and machine-learning techniques, in particular, for pediatric ICU outcome prediction. SUMMARY: Most studies focusing on artificial intelligence demonstrate good performance on prediction or classification, whether they use traditional statistical tools or novel machine-learning approaches. Yet the challenges of implementation, user acceptance, ethics and regulation cannot be underestimated. Areas in which there is easy access to routinely labeled data and robust outcomes, such as those collected through national networks and quality improvement programs, are likely to be at the forefront of the adoption of these advances.

Effects of Dexmedetomidine on Myocardial Repolarization in Children Undergoing General Anesthesia: A Randomized Controlled Trial.

BACKGROUND: Dexmedetomidine is a highly selective α2-adrenergic agonist, which is increasingly used in pediatric anesthesia and intensive care. Potential adverse effects that have not been rigorously evaluated in children include its effects on myocardial repolarization, which is important given that the drug is listed as a possible risk factor for torsades de pointes. We investigated the effect of 3 different doses of dexmedetomidine on myocardial repolarization and transmural dispersion in children undergoing elective surgery with total IV anesthesia. METHODS: Sixty-four American Society of Anesthesiologists I-II children 3-10 years of age were randomized to receive dexmedetomidine 0.25 µg/kg, 0.5 µg/kg, 0.75 µg/kg, or 0 µg/kg (control), as a bolus administered over 60 seconds, after induction of anesthesia. Pre- and postintervention 12-lead electrocardiograms were recorded. The interval between the peak and the end of the electrocardiogram T wave (Tp-e; transmural dispersion) and heart rate-corrected QT intervals (myocardial repolarization) were measured by a pediatric electrophysiologist blinded to group allocation. Data were analyzed using an analysis of covariance regression model. The study was powered to detect a 25-millisecond difference in Tp-e. RESULTS: Forty-eight children completed the study, with data analyzed from 12 participants per group. There were no instances of dysrhythmias. Tp-e values were unaffected by dexmedetomidine administration at any of the studied doses (F = 0.09; P = .96). Mean (99% CI) within-group differences were all <2 milliseconds (-5 to 8). Postintervention, corrected QT interval increased in the control group, but decreased in some dexmedetomidine groups (F = 7.23; P < .001), specifically the dexmedetomidine 0.5 and 0.75 µg/kg doses. Within groups, the mean (99% CI) differences between pre- and postintervention corrected QT interval were 12.4 milliseconds (-5.8 to 30.6) in the control group, -9.0 milliseconds (-24.9 to 6.9) for dexmedetomidine 0.25 µg/kg, -18.6 milliseconds (-33.7 to -3.5) for dexmedetomidine 0.5 µg/kg, and -14.1 milliseconds (-27.4 to -0.8) for dexmedetomidine 0.75 µg/kg. CONCLUSIONS: Of the bolus doses of dexmedetomidine studied, none had an effect on Tp-e and the dexmedetomidine 0.5 and 0.75 µg/kg doses shortened corrected QT intervals when measured at 1 minute after dexmedetomidine bolus injection during total IV anesthesia. There is no evidence for an increased risk of torsades de pointes in this context.

Effects of Dexmedetomidine on Blood Glucose and Serum Potassium Levels in Children Undergoing General Anesthesia: A Secondary Analysis of Safety Endpoints During a Randomized Controlled Trial.

BACKGROUND: Dexmedetomidine is a highly selective α2-adrenergic agonist, which is increasingly used in pediatric anesthesia and intensive care. Potential adverse effects that have not been rigorously evaluated in children include its effects on blood glucose and serum potassium concentrations, which are relevant due to the associations of derangements of both parameters with undesired outcomes. We investigated the effects of 3 different doses of dexmedetomidine on these outcomes in a randomized controlled trial in children undergoing elective surgery. METHODS: Sixty-four American Society of Anesthesiologists I-II children were randomized to receive either dexmedetomidine 0.25 µg/kg, dexmedetomidine 0.5 µg/kg, dexmedetomidine 0.75 µg/kg, or 0 µg/kg (control), as a bolus administered over 60 seconds after induction of anesthesia. Changes in plasma glucose and serum potassium concentrations were measured in venous blood sampled before and at 15 and 30 minutes after study drug administration. Data were plotted within and between groups and analyzed using a constrained longitudinal data approach. RESULTS: Forty-nine children completed the study. Mean glucose levels at 15 and 30 minutes were elevated with estimated changes from baseline of 0.37 mmol/L (95% CI, 0.29-0.45 mmol/L) and 0.05 mmol/L (95% CI, 0.00-0.10 mmol/L), respectively. At 15 minutes, there was a linear dose-response relationship (1.07 mmol/L/µg/kg [95% CI, 0.57-1.58 mmol/L/µg/kg]), but there was no appreciable effect of dexmedetomidine at 30 minutes (0.15 mmol/L/µg/kg [95% CI, -0.40 to 0.70 mmol/L/µg/kg]). Potassium levels were depressed relative to baseline, with a mean difference at 15 minutes of -0.20 mEq/L (95% CI, -0.28 to -0.12 mEq/L) and at 30 minutes of -0.12 mEq/L (95% CI, -0.15 to -0.08 mEq/L), but there was no appreciable effect of dexmedetomidine at either time. CONCLUSIONS: Small elevations in glucose and decreases in potassium were observed after induction of anesthesia in children. The elevation in glucose at 15 minutes depended on the dose of dexmedetomidine administered. These preliminary data warrant further investigation.

Integrating intraoperative physiology data into outcome analysis for the ACS Pediatric National Surgical Quality Improvement Program.

BACKGROUND: The Pediatric National Surgical Quality Improvement Program (P-NSQIP) samples surgical procedures for benchmarking and quality improvement. While generally comprehensive, P-NSQIP does not collect intraoperative physiologic data, despite potential impact on outcomes. AIMS: The aims of this study were (a) to describe a methodology to augment P-NSQIP with vital signs data and (b) demonstrate its utility by exploring relationships that intraoperative hypothermia and hypotension have with P-NSQIP outcomes. METHODS: Vital signs from 2012 to 2016 were available in a research databank. Episodes of hypotension and hypothermia were extracted and recorded alongside local P-NSQIP data. Multivariable regression analyses were performed to explore associations with undesired outcomes, including: surgical site infection, wound disruption, unplanned return to the operating room, and blood transfusion. Model variables were selected with the Akaike information criterion using 2012-2014 as the training set and validated with receiver operating characteristics analysis using 2015-2016 as the testing set. RESULTS: Data from 6737 patients were analyzed, with 43.9% female, median [interquartile range] age 5.8 [1.3-12.4] years, undergoing procedures lasting 118 [75-193] minutes. Hypothermia, observed in 45% of cases, was associated with wound disruption (odds ratio 1.75, 95% CI 1.1-2.83). Hypotension, observed in 60% of cases, was associated with unplanned returns (odds ratio 1.58, 95% CI 1.02-2.51), and transfusions (odds ratio 1.95, 95% CI 1.14-3.52). Surgical site infection, wound disruption, unplanned return, and transfusion models had areas under the receiver operating characteristic curve of 0.69/0.67, 0.59/0.63, 0.78/0.79, and 0.92/0.93 for validation models including hypothermia/hypotension respectively. CONCLUSION: Adding intraoperative vital signs to P-NSQIP data allowed identification of two modifiable risk factors: hypothermia was associated with increased wound disruption, and hypotension with increased blood transfusions and unplanned returns to the operating room. These findings may motivate prospective studies and prompt other centers and P-NSQIP to augment outcome data with intraoperative physiological data.

Design and Evaluation of a Closed-Loop Anesthesia System With Robust Control and Safety System.

BACKGROUND: Closed-loop control of anesthesia involves continual adjustment of drug infusion rates according to measured clinical effect. The NeuroSENSE monitor provides an electroencephalographic measure of depth of hypnosis (wavelet-based anesthetic value for central nervous system monitoring [WAVCNS]). It has previously been used as feedback for closed-loop control of propofol, in a system designed using robust control engineering principles, which implements features specifically designed to ensure patient safety. Closed-loop control of a second drug, remifentanil, may be added to improve WAVCNS stability in the presence of variable surgical stimulation. The objective of this study was to design and evaluate the feasibility of a closed-loop system for robust control of propofol and remifentanil infusions using WAVCNS feedback, with an infusion safety system based on the known pharmacological characteristics of these 2 drugs. METHODS: With Health Canada authorization, research ethics board approval, and informed consent, American Society of Anesthesiologists I-III adults, requiring general anesthesia for elective surgery, were enrolled in a 2-phase study. In both phases, infusion of propofol was controlled in closed loop during induction and maintenance of anesthesia, using WAVCNS feedback, but bounded by upper- and lower-estimated effect-site concentration limits. In phase I, remifentanil was administered using an adjustable target-controlled infusion and a controller was designed based on the collected data. In phase II, remifentanil was automatically titrated to counteract rapid increases in WAVCNS. RESULTS: Data were analyzed for 127 patients, of median (range) age 64 (22-86) years, undergoing surgical procedures lasting 105 (9-348) minutes, with 52 participating in phase I and 75 in phase II. The overall control performance indicator, global score, was a median (interquartile range) 18.3 (14.2-27.7) in phase I and 14.6 (11.6-20.7) in phase II (median difference, -3.25; 95% confidence interval, -6.35 to -0.52). The WAVCNS was within ±10 of the setpoint for 84.3% (76.6-90.6) of the maintenance of anesthesia in phase I and 88.2% (83.1-93.4) in phase II (median difference, 3.7; 95% confidence interval, 0.1-6.9). The lower propofol safety bound was activated during 30 of 52 (58%) cases in phase I and 51 of 75 (68%) cases in phase II. CONCLUSIONS: Adding closed-loop control of remifentanil improved overall controller performance. This controller design offers a robust method to optimize the control of 2 drugs using a single sensor. The infusion safety system is an important component of a robust automated anesthesia system, but further research is required to determine the optimal constraints for these safe conditions.

External Validation of the "Quick" Pediatric Logistic Organ Dysfunction-2 Score Using a Large North American Cohort of Critically Ill Children With Suspected Infection.

OBJECTIVES: A quick Pediatric Logistic Organ Dysfunction 2 score on day 1, consisting of tachycardia, hypotension, and altered mentation, was shown to predict mortality with an area under the receiver operating characteristic curve of 82% (95% CI, 76-87%) in children admitted to a PICU with suspected infection. We performed an external validation of the quick Pediatric Logistic Organ Dysfunction 2, including its performance in predicting mortality in specific age groups. DESIGN: Analysis of retrospective data obtained from the Virtual Pediatric Systems PICU registry. SETTING: Prospectively collected clinical records from 130 participating PICUs in North America. PATIENTS: Children admitted between January 2009 and December 2014, with a diagnosis of infection at discharge, for whom all required data were available. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Systolic blood pressures, heart rates, and Glasgow Coma Scale scores were used to evaluate the quick Pediatric Logistic Organ Dysfunction 2 using area under the receiver operating characteristic curve analysis. Performance was compared with Pediatric Risk of Mortality 3 and Pediatric Index of Mortality 2 risk scores. Data from 42,196 children with complete data were analyzed, with median age 2.7 years (interquartile range, 0.7-8.8 yr; range 0-18 yr) and a 4.27% mortality rate. Mortality was 13.4% for quick Pediatric Logistic Organ Dysfunction 2 greater than or equal to 2 and 2.5% for quick Pediatric Logistic Organ Dysfunction 2 less than 2, representing a false-negative rate of 49.5%. Also 311 children (17%) who died had a quick Pediatric Logistic Organ Dysfunction 2 score of 0. The area under the receiver operating characteristic curve was 72.6% (95% CI, 71.4-73.8%) for quick Pediatric Logistic Organ Dysfunction 2, compared with 85.0% (95% CI, 84.0-86.0%) for Pediatric Risk of Mortality 3 and 81.5% (95% CI, 80.5-82.5%) for Pediatric Index of Mortality 2. Performance of quick Pediatric Logistic Organ Dysfunction 2 was worst in the greater than 12 years age group (area under the receiver operating characteristic curve, 67.8%; 95% CI, 65-70.5) and best in the less than 1 month age group (area under the receiver operating characteristic curve, 78.9%; 95% CI, 75.3-82.4). CONCLUSIONS: Quick Pediatric Logistic Organ Dysfunction 2 performed markedly worse in our cohort, compared with the original study, and the high rate of false negatives limits its clinical utility in our population. Further work is needed to develop a robust quick pediatric sepsis diagnostic tool for both research and clinical care.

Mortality Risk Using a Pediatric Quick Sequential (Sepsis-Related) Organ Failure Assessment Varies With Vital Sign Thresholds.

OBJECTIVES: We evaluated adapting the quick Sequential (Sepsis-Related) Organ Failure Assessment score (fast respiratory rate, altered mental status, low blood pressure) for pediatric use by selecting thresholds from three commonly used definitions: Pediatric Logistic Organ Dysfunction 2, Pediatric Advanced Life Support, and International Pediatric Sepsis Consensus Conference. We examined their respective performance in identifying children who had a discharge diagnosis of infection at high risk of mortality using PICU registry data, with additional focus on the influence of age on performance. DESIGN: Analysis of retrospective data obtained from the Virtual Pediatric Systems PICU database. The performance in predicting observed mortality was assessed for the three candidate approaches using receiver operating characteristics analysis, including age group effects. SETTING: The Virtual Pediatric Systems database contains data on diagnosis, clinical markers, and outcomes in prospectively collected clinical records from 130 participating PICUs in the United States and Canada. PATIENTS: Children who had a discharge diagnosis of infection in a participating PICU between 2009 and 2014, for which all required data were available. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data from 40,228 children revealed an overall mortality of 4.22%. Area under the receiver operating characteristics curve (95% CI) was 0.760 (0.749-0.771) for Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation, 0.700 (0.689-0.712) for Pediatric Advanced Life Support, and 0.709 (0.696-0.721) for International Pediatric Sepsis Consensus Conference. When split by age group, the performance of Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation was lowest in the youngest neonates (under 1 wk old), with an area under the receiver operating characteristics curve (95% CI) of 0.724 (0.656-0.791), and in the teenagers (13-18 yr), with an area under the receiver operating characteristics curve of 0.710 (0.682-0.738), yet it still outperformed Pediatric Advanced Life Support and International Pediatric Sepsis Consensus Conference in both groups. CONCLUSIONS: Among critically ill children who had a discharge diagnosis of infection in the PICU, quick Sequential (Sepsis-Related) Organ Failure Assessment score performs best when using the Pediatric Logistic Organ Dysfunction 2 age thresholds with mechanical ventilation, while all definitions performed worse at extremes of pediatric age. Thus, mortality risk varies with vital sign thresholds, and although Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation performed marginally better, it is unlikely to be of use to clinicians. More work is needed to develop a robust and relevant pediatric sepsis risk score.