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 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.

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.

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.

In-hospital usability and feasibility evaluation of Panda, an app for the management of pain in children at home.

BACKGROUND: Postoperative pain in children is often poorly managed at home, leading to slower functional recovery, poor oral intake, sleep disturbances, and behavioral changes. Panda is a smartphone application (app) designed to support parents in assessing their child's pain and managing medications. AIMS: The aim of this study was to evaluate the Panda app's usability and feasibility in hospital prior to testing the app at home. METHODS: The study comprised two phases. Phase I evaluated Panda's usability with nurses, parents, and adolescents using simulated scenarios. Usability was measured by task completion rate, user error rates, and the Computer Systems Usability Questionnaire. Phase II evaluated Panda's feasibility by observing parents/guardians of pediatric patients using the app on the postsurgical ward. Feasibility was measured using response frequency and delay following app notifications from an audit trail of app function, and parental satisfaction from an interview. Feedback was used to guide iterative app improvements. RESULTS: In Phase I, 13 nurses, 12 parents, and 5 adolescents evaluated the app. A total of 103 usability issues were identified, analyzed, and addressed. In Phase II, 29 parents responded to a total of 151 app notifications, with 84% responding within 1 hour in the final round of testing; 93% of participants reported the app was easy to use, and rated the app with a median [interquartile range] Computer Systems Usability Questionnaire score of 2 [1-4]. Significant barriers to use included lack of flexibility in the medication scheduling, low volume of alert sounds, and the extra time spent on medication safety checks. CONCLUSION: Panda's usability was improved and its feasibility demonstrated in the controlled hospital environment. The next step is to evaluate its feasibility for use at home.

Using physiological monitoring data for performance feedback: an initiative using thermoregulation metrics.

BACKGROUND: Feedback of performance data can improve professional practice and outcomes. Vital signs are not routinely used for quality improvement because of their limited access. Intraoperative hypothermia has been associated with deleterious effects, including surgical site infections and bleeding. We speculated that providing feedback could help keep temperature monitoring and management a priority in the anesthesiologist's mind, thereby improving perioperative temperature management. We hypothesized that feedback on thermoregulation metrics, without changes in policy, could reduce temperature-monitoring delays at the start of scoliosis correction surgery. METHODS: Although our tertiary pediatric centre does not have an anesthesia information management system, vital signs for all surgical cases are recorded in real time. Temperature data from children undergoing spine surgery are extracted from a vital signs databank and analyzed using MATLAB. Spine team anesthesiologists are provided with both team and individualized feedback regarding two variables: the percentage of time that patients are hypothermic and the time delay from the start of the case to the first temperature monitoring (our primary outcome). These data are shared every six months as run charts for the entire group and as anonymized (coded) box-and-whisker plots for each anesthesiologist. RESULTS: This feedback of temperature-delay data reduced the median [interquartile range] delay from 39.0 [18.7-61.5] min to 14.4 [10.8-22.9] min (median reduction, 21.8 min; 95% confidence interval, 14.9 to 28.2; P < 0.001). It did not, however, further reduce the percentage of time patients remained hypothermic beyond the improvements already achieved with prewarming. CONCLUSION: Feedback of intraoperative thermoregulation management improved both group and individual performances as measured by significant, sustained reductions in temperature-monitoring delays. Thus, intraoperative vital signs data may improve the quality of, and reduce the variability in, anesthetic practice.

An Ethnographic Observational Study to Evaluate and Optimize the Use of Respiratory Acoustic Monitoring in Children Receiving Postoperative Opioid Infusions.

BACKGROUND: Respiratory depression in children receiving postoperative opioid infusions is a significant risk because of the interindividual variability in analgesic requirement. Detection of respiratory depression (or apnea) in these children may be improved with the introduction of automated acoustic respiratory rate (RR) monitoring. However, early detection of adverse events must be balanced with the risk of alarm fatigue. Our objective was to evaluate the use of acoustic RR monitoring in children receiving opioid infusions on a postsurgical ward and identify the causes of false alarm and optimal alarm thresholds. METHODS: A video ethnographic study was performed using an observational, mixed methods approach. After surgery, an acoustic RR sensor was placed on the participant's neck and attached to a Rad87 monitor. The monitor was networked with paging for alarms. Vital signs data and paging notification logs were obtained from the central monitoring system. Webcam videos of the participant, infusion pump, and Rad87 monitor were recorded, stored on a secure server, and subsequently analyzed by 2 research nurses to identify the cause of the alarm, response, and effectiveness. Alarms occurring within a 90-second window were grouped into a single-alarm response opportunity. RESULTS: Data from 49 patients (30 females) with median age 14 (range, 4.4-18.8) years were analyzed. The 896 bedside vital sign threshold alarms resulted in 160 alarm response opportunities (44 low RR, 74 high RR, and 42 low SpO2). In 141 periods (88% of total), for which video was available, 65% of alarms were deemed effective (followed by an alarm-related action within 10 minutes). Nurses were the sole responders in 55% of effective alarms and the patient or parent in 20%. Episodes of desaturation (SpO2 < 90%) were observed in 9 patients: At the time of the SpO2 paging trigger, the RR was >10 bpm in 6 of 9 patients. Based on all RR samples observed, the default alarm thresholds, to serve as a starting point for each patient, would be a low RR of 6 (>10 years of age) and 10 (4-9 years of age). CONCLUSIONS: In this study, the use of RR monitoring did not improve the detection of respiratory depression. An RR threshold, which would have been predictive of desaturations, would have resulted in an unacceptably high false alarm rate. Future research using a combination of variables (e.g., SpO2 and RR), or the measurement of tidal volumes, may be needed to improve patient safety in the postoperative ward.

Preoperative warming and undesired surgical and anesthesia outcomes in pediatric spinal surgery-a retrospective cohort study.

BACKGROUND: Underbody forced air warming is a method commonly used for intraoperative temperature maintenance in children. We previously reported that preoperative forced air warming of children undergoing spinal surgery substantially reduces the incidence and duration of intraoperative hypothermia (<36°C). OBJECTIVE: The aim of this study was to evaluate the effects of preoperative warming before spinal deformity surgery on surgical site infection rate, length of hospitalization, and bleeding (estimated blood loss and incidence of cell salvaged and/or allogeneic packed red blood cell transfusions). METHODS: Demographic, anesthetic, and surgical data of all patients who underwent spinal deformity surgery between December 2009 and December 2012 were obtained by retrospective chart review. Temperature data were abstracted from an existing repository; the incidence and duration of hypothermic episodes were identified. For each outcome, logistic regression models and propensity score analysis were used to estimate the effect of prewarming, adjusted for potential confounders. The issue of missing data was handled by a multiple imputation method. Data from 334 procedures were used in modeling and propensity score stratification. RESULTS: Adjusted odds ratios for the effects of prewarming were 0.47 (95% CI 0.15-1.49) for surgical site infections; 0.89 (95% CI 0.55-1.41) for cell salvaged blood transfusion; 0.43 (95% CI 0.22-0.83) for allogeneic packed red blood cell transfusion; and 1.24 (95% CI 0.77-1.99) for a length of hospitalization >6 days. Adjusted mean decrease in estimated blood loss for prewarming was 72 (95% CI -29 to 173) ml. CONCLUSION: In this study, prewarming was associated with a reduction in allogeneic packed red blood cell transfusion. However, no causal relationship between prewarming and reduced allogeneic blood transfusion should be assumed. Prewarming was not associated with reductions in estimated blood loss, length of hospitalization, or the incidence of surgical site infection.

Developing an objective method for analyzing vital signs changes in neonates during general anesthesia.

BACKGROUND: Commonly used general anesthetics are considered to be neurotoxic to the developing rodent brain, leading to poor long-term outcome. However, it is unclear whether these rodent studies can be extrapolated to the human neonate. Given that anesthesia for urgent neonatal surgery cannot be avoided, it is vitally important to assess other factors that may impact neurological outcome following anesthesia and surgery. OBJECTIVE: The purpose of this study is to identify thresholds for detecting vital sign deviations, which may have the potential for affecting neurological outcome following anesthesia and surgery in neonates. These data may be suitable to identify targets for prospective quality improvement projects and guide future research for strategies to reduce detrimental neurocognitive outcomes. METHODS: A retrospective analysis of vital sign data was performed for neonates (age ≤28 days), undergoing noncardiac surgery over a 4-year period (2010-2013). Thresholds for detecting bradycardia, tachycardia, hypothermia, hyperthermia, hypertension, hypotension, hypocarbia, hypoxemia, significant changes in mean arterial blood pressure, and periods of high inspired oxygen concentration, were proposed. Selected chart review, to identify additional risk factors, and identify sources of data artifact, was performed for 224 cases. RESULTS: Data from 435 procedures in neonates, with median (IQR [range]) ages of 6 (2-16 [0-28]) days were available for analysis. Five (3-6 [0-12]) rule deviations per case were observed; only 11 cases had no rule deviations. Hypothermia was observed in 285/435 (70%), moderate hypocapnia in 298/430 (69%), and severe hypotension in 270/435 (62%) cases. CONCLUSION: An objective method of comparing cases has been created with a method to automatically identify neonatal vital sign deviations. With further validation the method has the potential to be a powerful tool to drive future quality improvement projects in neonatal anesthesia.

Postsurgical Pain Risk Stratification to Enhance Pain Management Workflow in Adult Patients: Design, Implementation, and Pilot Evaluation.

BACKGROUND: Exposure to opioids after surgery is the initial contact for some people who develop chronic opioid use disorder. Hence, effective postoperative pain management, with less reliance on opioids, is critical. The Perioperative Opioid Quality Improvement (POQI) program developed (1) a digital health platform leveraging patient-survey-reported risk factors and (2) a postsurgical pain risk stratification algorithm to personalize perioperative care by integrating several commercially available digital health solutions into a combined platform. Development was reduced in scope by the COVID-19 pandemic. OBJECTIVE: This pilot study aims to assess the screening performance of the risk algorithm, quantify the use of the POQI platform, and evaluate clinicians' and patients' perceptions of its utility and benefit. METHODS: A POQI platform prototype was implemented in a quality improvement initiative at a Canadian tertiary care center and evaluated from January to September 2022. After surgical booking, a preliminary risk stratification algorithm was applied to health history questionnaire responses. The estimated risk guided the patient assignment to a care pathway based on low or high risk for persistent pain and opioid use. Demographic, procedural, and medication administration data were extracted retrospectively from the electronic medical record. Postoperative inpatient opioid use of >90 morphine milligram equivalents per day was the outcome used to assess algorithm performance. Data were summarized and compared between the low- and high-risk groups. POQI use was assessed by completed surveys on postoperative days 7, 14, 30, 60, 90, and 120. Semistructured patient and clinician interviews provided qualitative feedback on the platform. RESULTS: Overall, 276 eligible patients were admitted for colorectal procedures. The risk algorithm stratified 203 (73.6%) as the low-risk group and 73 (26.4%) as the high-risk group. Among the 214 (77.5%) patients with available data, high-risk patients were younger than low-risk patients (age: median 53, IQR 40-65 years, vs median 59, IQR 49-69 years, median difference five years, 95% CI 1-9; P=.02) and were more often female patients (45/73, 62% vs 80/203, 39.4%; odds ratio 2.5, 95% CI 1.4-4.5; P=.002). The risk stratification was reasonably specific (true negative rate=144/200, 72%) but not sensitive (true positive rate=10/31, 32%). Only 39.7% (85/214) patients completed any postoperative quality of recovery questionnaires (only 14, 6.5% patients beyond 60 days after surgery), and 22.9% (49/214) completed a postdischarge medication survey. Interviewed participants welcomed the initiative but noted usability issues and poor platform education. CONCLUSIONS: An initial POQI platform prototype was deployed operationally; the risk algorithm had reasonable specificity but poor sensitivity. There was a significant loss to follow-up in postdischarge survey completion. Clinicians and patients appreciated the potential impact of preemptively addressing opioid exposure but expressed shortcomings in the platform's design and implementation. Iterative platform redesign with additional features and reevaluation are required before broader implementation.

An Individualized Postoperative Pain Risk Communication Tool for Use in Pediatric Surgery: Co-Design and Usability Evaluation.

BACKGROUND: Risk identification and communication tools have the potential to improve health care by supporting clinician-patient or family discussion of treatment risks and benefits and helping patients make more informed decisions; however, they have yet to be tailored to pediatric surgery. User-centered design principles can help to ensure the successful development and uptake of health care tools. OBJECTIVE: We aimed to develop and evaluate the usability of an easy-to-use tool to communicate a child's risk of postoperative pain to improve informed and collaborative preoperative decision-making between clinicians and families. METHODS: With research ethics board approval, we conducted web-based co-design sessions with clinicians and family participants (people with lived surgical experience and parents of children who had recently undergone a surgical or medical procedure) at a tertiary pediatric hospital. Qualitative data from these sessions were analyzed thematically using NVivo (Lumivero) to identify design requirements to inform the iterative redesign of an existing prototype. We then evaluated the usability of our final prototype in one-to-one sessions with a new group of participants, in which we measured mental workload with the National Aeronautics and Space Administration (NASA) Task Load Index (TLX) and user satisfaction with the Post-Study System Usability Questionnaire (PSSUQ). RESULTS: A total of 12 participants (8 clinicians and 4 family participants) attended 5 co-design sessions. The 5 requirements were identified: (A) present risk severity descriptively and visually; (B) ensure appearance and navigation are user-friendly; (C) frame risk identification and mitigation strategies in positive terms; (D) categorize and describe risks clearly; and (E) emphasize collaboration and effective communication. A total of 12 new participants (7 clinicians and 5 family participants) completed a usability evaluation. Tasks were completed quickly (range 5-17 s) and accurately (range 11/12, 92% to 12/12, 100%), needing only 2 requests for assistance. The median (IQR) NASA TLX performance score of 78 (66-89) indicated that participants felt able to perform the required tasks, and an overall PSSUQ score of 2.1 (IQR 1.5-2.7) suggested acceptable user satisfaction with the tool. CONCLUSIONS: The key design requirements were identified, and that guided the prototype redesign, which was positively evaluated during usability testing. Implementing a personalized risk communication tool into pediatric surgery can enhance the care process and improve informed and collaborative presurgical preparation and decision-making between clinicians and families of pediatric patients.

Dashboard of Short-Term Postoperative Patient Outcomes for Anesthesiologists: Development and Preliminary Evaluation.

BACKGROUND: Anesthesiologists require an understanding of their patients' outcomes to evaluate their performance and improve their practice. Traditionally, anesthesiologists had limited information about their surgical outpatients' outcomes due to minimal contact post discharge. Leveraging digital health innovations for analyzing personal and population outcomes may improve perioperative care. BC Children's Hospital's postoperative follow-up registry for outpatient surgeries collects short-term outcomes such as pain, nausea, and vomiting. Yet, these data were previously not available to anesthesiologists. OBJECTIVE: This quality improvement study aimed to visualize postoperative outcome data to allow anesthesiologists to reflect on their care and compare their performance with their peers. METHODS: The postoperative follow-up registry contains nurse-reported postoperative outcomes, including opioid and antiemetic administration in the postanesthetic care unit (PACU), and family-reported outcomes, including pain, nausea, and vomiting, within 24 hours post discharge. Dashboards were iteratively co-designed with 5 anesthesiologists, and a department-wide usability survey gathered anesthesiologists' feedback on the dashboards, allowing further design improvements. A final dashboard version has been deployed, with data updated weekly. RESULTS: The dashboard contains three sections: (1) 24-hour outcomes, (2) PACU outcomes, and (3) a practice profile containing individual anesthesiologist's case mix, grouped by age groups, sex, and surgical service. At the time of evaluation, the dashboard included 24-hour data from 7877 cases collected from September 2020 to February 2023 and PACU data from 8716 cases collected from April 2021 to February 2023. The co-design process and usability evaluation indicated that anesthesiologists preferred simpler designs for data summaries but also required the ability to explore details of specific outcomes and cases if needed. Anesthesiologists considered security and confidentiality to be key features of the design and most deemed the dashboard information useful and potentially beneficial for their practice. CONCLUSIONS: We designed and deployed a dynamic, personalized dashboard for anesthesiologists to review their outpatients' short-term postoperative outcomes. This dashboard facilitates personal reflection on individual practice in the context of peer and departmental performance and, hence, the opportunity to evaluate iterative practice changes. Further work is required to establish their effect on improving individual and department performance and patient outcomes.

Competency-Based Medical Education: Are Canadian Pediatric Anesthesiologists Ready?

Background With the introduction of Competency-Based Medical Education (CBME), the Canadian Pediatric Anesthesia Society (CPAS) surveyed its members to assess their awareness of and prior experience with CBME concepts and evaluation tools, and identify methods for faculty development of CBME teaching strategies for pediatric anesthesia residents and fellows. Methods An online survey was sent to CPAS members. Outcomes included respondents' previous exposure to CBME and the educational support they had received in anticipation of the curriculum. Questions used multi-item Likert scales and a general feedback question.  Results The response rate was 39% (60/155). Eighty-eight percent of respondents spent ≥50% of their time practicing pediatric anesthesia; 78% and 45% spent at least a quarter of their time teaching residents and fellows respectively. Eighty-three percent were familiar with CBME concepts, and 58% were familiar with Milestones, Competencies, and Entrustable Professional Activities (EPAs). However, 64% had not received any formal training and 52% had not used any CBME evaluation tools. Learning preferences included small group discussions (72%), lectures with questions and answers (Q&A) (62%), seminars (50%), and workshops (50%). Conclusions Despite widespread awareness of CBME concepts, there is a need to educate Canadian pediatric anesthesiologists regarding CBME evaluation tools. Faculty development support will increase the utilization of these tools in teaching practice.

Identifying Risk Factors, Patient-Reported Experience and Outcome Measures, and Data Capture Tools for an Individualized Pain Prediction Tool in Pediatrics: Focus Group Study.

BACKGROUND: The perioperative period is a data-rich environment with potential for innovation through digital health tools and predictive analytics to optimize patients' health with targeted prehabilitation. Although some risk factors for postoperative pain following pediatric surgery are already known, the systematic use of preoperative information to guide personalized interventions is not yet widespread in clinical practice. OBJECTIVE: Our long-term goal is to reduce the incidence of persistent postsurgical pain (PPSP) and long-term opioid use in children by developing personalized pain risk prediction models that can guide clinicians and families to identify targeted prehabilitation strategies. To develop such a system, our first objective was to identify risk factors, outcomes, and relevant experience measures, as well as data collection tools, for a future data collection and risk modeling study. METHODS: This study used a patient-oriented research methodology, leveraging parental/caregiver and clinician expertise. We conducted virtual focus groups with participants recruited at a tertiary pediatric hospital; each session lasted approximately 1 hour and was composed of clinicians or family members (people with lived surgical experience and parents of children who had recently undergone a procedure requiring general anesthesia) or both. Data were analyzed thematically to identify potential risk factors for pain, as well as relevant patient-reported experience and outcome measures (PREMs and PROMs, respectively) that can be used to evaluate the progress of postoperative recovery at home. This guidance was combined with a targeted literature review to select tools to collect risk factor and outcome information for implementation in a future study. RESULTS: In total, 22 participants (n=12, 55%, clinicians and n=10, 45%, family members) attended 10 focus group sessions; participants included 12 (55%) of 22 persons identifying as female, and 12 (55%) were under 50 years of age. Thematic analysis identified 5 key domains: (1) demographic risk factors, including both child and family characteristics; (2) psychosocial risk factors, including anxiety, depression, and medical phobias; (3) clinical risk factors, including length of hospital stay, procedure type, medications, and pre-existing conditions; (4) PREMs, including patient and family satisfaction with care; and (5) PROMs, including nausea and vomiting, functional recovery, and return to normal activities of daily living. Participants further suggested desirable functional requirements, including use of standardized and validated tools, and longitudinal data collection, as well as delivery modes, including electronic, parent proxy, and self-reporting, that can be used to capture these metrics, both in the hospital and following discharge. Established PREM/PROM questionnaires, pain-catastrophizing scales (PCSs), and substance use questionnaires for adolescents were subsequently selected for our proposed data collection platform. CONCLUSIONS: This study established 5 key data domains for identifying pain risk factors and evaluating postoperative recovery at home, as well as the functional requirements and delivery modes of selected tools with which to capture these metrics both in the hospital and after discharge. These tools have been implemented to generate data for the development of personalized pain risk prediction models.

Identification of Requirements for a Postoperative Pediatric Pain Risk Communication Tool: Focus Group Study With Clinicians and Family Members.

BACKGROUND: Pediatric surgery is associated with a risk of postoperative pain that can impact the family's quality of life. Although some risk factors for postoperative pain are known, these are often not consistently communicated to families. In addition, although tools for risk communication exist in other domains, none are tailored to pediatric surgery. OBJECTIVE: As part of a larger project to develop pain risk prediction tools, we aimed to design an easy-to-use tool to effectively communicate a child's risk of postoperative pain to both clinicians and family members. METHODS: With research ethics board approval, we conducted virtual focus groups (~1 hour each) comprising clinicians and family members (people with lived surgical experience and parents of children who had recently undergone surgery/medical procedures) at a tertiary pediatric hospital to understand and evaluate potential design approaches and strategies for effectively communicating and visualizing postoperative pain risk. Data were analyzed thematically to generate design requirements and to inform iterative prototype development. RESULTS: In total, 19 participants (clinicians: n=10, 53%; family members: n=9, 47%) attended 6 focus group sessions. Participants indicated that risk was typically communicated verbally by clinicians to patients and their families, with severity indicated using a descriptive or a numerical representation or both, which would only occasionally be contextualized. Participants indicated that risk communication tools were seldom used but that families would benefit from risk information, time to reflect on the information, and follow-up with questions. In addition, 9 key design requirements and feature considerations for effective risk communication were identified: (1) present risk information clearly and with contextualization, (2) quantify the risk and contextualize it, (3) include checklists for preoperative family preparation, (4) provide risk information digitally to facilitate recall and sharing, (5) query the family's understanding to ensure comprehension of risk, (6) present the risk score using multimodal formats, (7) use color coding that is nonthreatening and avoids limitations with color blindness, (8) present the most significant factors contributing to the risk prediction, and (9) provide risk mitigation strategies to potentially decrease the patient's level of risk. CONCLUSIONS: Key design requirements for a pediatric postoperative pain risk visualization tool were established and guided the development of an initial prototype. Implementing a risk communication tool into clinical practice has the potential to bridge existing gaps in the accessibility, utilization, and comprehension of personalized risk information between health care professionals and family members. Future iterative codesign and clinical evaluation of this risk communication tool are needed to confirm its utility in practice.

An Artificial Neural Network-Based Pediatric Mortality Risk Score: Development and Performance Evaluation Using Data From a Large North American Registry.

BACKGROUND: In the pediatric intensive care unit (PICU), quantifying illness severity can be guided by risk models to enable timely identification and appropriate intervention. Logistic regression models, including the pediatric index of mortality 2 (PIM-2) and pediatric risk of mortality III (PRISM-III), produce a mortality risk score using data that are routinely available at PICU admission. Artificial neural networks (ANNs) outperform regression models in some medical fields. OBJECTIVE: In light of this potential, we aim to examine ANN performance, compared to that of logistic regression, for mortality risk estimation in the PICU. METHODS: The analyzed data set included patients from North American PICUs whose discharge diagnostic codes indicated evidence of infection and included the data used for the PIM-2 and PRISM-III calculations and their corresponding scores. We stratified the data set into training and test sets, with approximately equal mortality rates, in an effort to replicate real-world data. Data preprocessing included imputing missing data through simple substitution and normalizing data into binary variables using PRISM-III thresholds. A 2-layer ANN model was built to predict pediatric mortality, along with a simple logistic regression model for comparison. Both models used the same features required by PIM-2 and PRISM-III. Alternative ANN models using single-layer or unnormalized data were also evaluated. Model performance was compared using the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPRC) and their empirical 95% CIs. RESULTS: Data from 102,945 patients (including 4068 deaths) were included in the analysis. The highest performing ANN (AUROC 0.871, 95% CI 0.862-0.880; AUPRC 0.372, 95% CI 0.345-0.396) that used normalized data performed better than PIM-2 (AUROC 0.805, 95% CI 0.801-0.816; AUPRC 0.234, 95% CI 0.213-0.255) and PRISM-III (AUROC 0.844, 95% CI 0.841-0.855; AUPRC 0.348, 95% CI 0.322-0.367). The performance of this ANN was also significantly better than that of the logistic regression model (AUROC 0.862, 95% CI 0.852-0.872; AUPRC 0.329, 95% CI 0.304-0.351). The performance of the ANN that used unnormalized data (AUROC 0.865, 95% CI 0.856-0.874) was slightly inferior to our highest performing ANN; the single-layer ANN architecture performed poorly and was not investigated further. CONCLUSIONS: A simple ANN model performed slightly better than the benchmark PIM-2 and PRISM-III scores and a traditional logistic regression model trained on the same data set. The small performance gains achieved by this two-layer ANN model may not offer clinically significant improvement; however, further research with other or more sophisticated model designs and better imputation of missing data may be warranted.

Feasibility of Using a Single Heart Rate-Based Measure for Real-time Feedback in a Voluntary Deep Breathing App for Children: Data Collection and Algorithm Development.

BACKGROUND: Deep diaphragmatic breathing, also called belly breathing, is a popular behavioral intervention that helps children cope with anxiety, stress, and their experience of pain. Combining physiological monitoring with accessible mobile technology can motivate children to comply with this intervention through biofeedback and gaming. These innovative technologies have the potential to improve patient experience and compliance with strategies that reduce anxiety, change the experience of pain, and enhance self-regulation during distressing medical procedures. OBJECTIVE: The aim of this paper was to describe a simple biofeedback method for quantifying breathing compliance in a mobile smartphone app. METHODS: A smartphone app was developed that combined pulse oximetry with an animated protocol for paced deep breathing. We collected photoplethysmogram data during spontaneous and subsequently paced deep breathing in children. Two measures, synchronized respiratory sinus arrhythmia (RSAsync) and the corresponding relative synchronized inspiration/expiration heart rate ratio (HR-I:Esync), were extracted from the photoplethysmogram. RESULTS: Data collected from 80 children aged 5-17 years showed a positive RSAsync effect in all participants during paced deep breathing, with a median (IQR; range) HR-I:Esync ratio of 1.26 (1.16-1.35; 1.01-1.60) during paced deep breathing compared to 0.98 (0.96-1.02; 0.82-1.18) during spontaneous breathing (median difference 0.25, 95% CI 0.23-0.30; P<.001). The measured HR-I:Esync values appeared to be independent of age. CONCLUSIONS: An HR-I:Esync level of 1.1 was identified as an age-independent threshold for programming the breathing pattern for optimal compliance in biofeedback.

Development and Implementation of the Portable Operating Room Tracker App With Vital Signs Streaming Infrastructure: Operational Feasibility Study.

BACKGROUND: In the perioperative environment, a multidisciplinary clinical team continually observes and evaluates patient information. However, data availability may be restricted to certain locations, cognitive workload may be high, and team communication may be constrained by availability and priorities. We developed the remote Portable Operating Room Tracker app (the telePORT app) to improve information exchange and communication between anesthesia team members. The telePORT app combines a real-time feed of waveforms and vital signs from the operating rooms with messaging, help request, and reminder features. OBJECTIVE: The aim of this paper is to describe the development of the app and the back-end infrastructure required to extract monitoring data, facilitate data exchange and ensure privacy and safety, which includes results from clinical feasibility testing. METHODS: telePORT's client user interface was developed using user-centered design principles and workflow observations. The server architecture involves network-based data extraction and data processing. Baseline user workload was assessed using step counters and communication logs. Clinical feasibility testing analyzed device usage over 11 months. RESULTS: telePORT was more commonly used for help requests (approximately 4.5/day) than messaging between team members (approximately 1/day). Passive operating room monitoring was frequently utilized (34% of screen visits). Intermittent loss of wireless connectivity was a major barrier to adoption (decline of 0.3%/day). CONCLUSIONS: The underlying server infrastructure was repurposed for real-time streaming of vital signs and their collection for research and quality improvement. Day-to-day activities of the anesthesia team can be supported by a mobile app that integrates real-time data from all operating rooms.