OBJECTIVE Injury is the leading cause of death in children and adolescents. Understanding the association between social determinants of health and pediatric injury is paramount for targeted intervention. We aimed to measure the association between Child Opportunity Index (COI) 2.0 and mortality for injured patients requiring pediatric intensive care unit (PICU) admission, hypothesizing that lower COI is associated with higher mortality. METHODS This was a retrospective, multicenter study of children (aged <18 years) admitted between January 1, 2019 and December 31, 2020 to 15 US PICUs with injury, inclusive of trauma, nonaccidental injury, drowning, ingestion/poisoning, burn/inhalational injury, and suffocation. We measured the association between COI 2.0 (area-based index of social determinants of health for children) and in-hospital mortality (primary outcome) and PICU readmission (secondary outcome) using multivariable logistic regression. RESULTS We included 3778 critically injured children, of whom 235 (6.2%) died. Distribution by COI was: 29% Very Low, 19% Low, 20% Moderate, 16% High, and 16% Very High. After adjustment for age, sex, mechanism, complex chronic condition, and severity of illness, the adjusted odds of mortality were approximately 2.5 times greater for patients with Very Low (aOR 2.4 [1.02–6.05]) and Moderate COI (aOR 2.6 [1.1–6.61]) compared with Very High COI. Low and High COI were associated with nearly 3 times odds of readmission (low aOR 3.18 [1.31–8.94]; high aOR 3.01 [1.23–8.46]). CONCLUSION Very Low and Moderate COI was associated with increased mortality of critically injured children. Further investigation is needed to identify modifiable determinants of child opportunity to decrease pediatric injury.

BACKGROUND:Blunt cerebrovascular injury (BCVI), defined as an injury occurring to the carotid and/or vertebral arteries, occurs in ~1% of pediatric blunt trauma patients and is associated with morbidity and mortality. Our objective was to evaluate the sensitivity and specificity of the McGovern score, a pediatric-specific screening tool for BCVI, and describe the effect of its implementation on the use of additional imaging for BCVI and the detection of BCVI. METHODS:This was a retrospective cohort study of patients below 16 years old presenting with blunt trauma to the Pediatric Emergency Department of a tertiary care level 1 pediatric trauma center pre- (July 1, 2020, to November 30, 2021) and post- (December 1, 2021, to December 31, 2022) implementation of McGovern scoring into the clinical decision algorithm for blunt trauma. Patient characteristics, diagnostic studies used [including computed tomography angiography (CTA) or magnetic resonance angiography (MRA) of the neck vessels], and outcomes (BCVI, stroke, mortality), were obtained from the medical record and compared pre-McGovern versus post-McGovern score implementation. RESULTS:A total of 1189 patients were included in the study; 664 p reimplementation of the McGovern scoring and 525 postimplementation. Median age was 6 years (IQR 2 to 11), and 668 (56%) were trauma activations (leveled traumas), with no significant differences in patient characteristics between the 2 cohorts. Imaging for BCVI was performed in 13 (2.0%) patients in the preimplementation group and 27 (5.0%) patients in the postimplementation group ( P =0.003). BCVI was detected in 12/1189 patients overall (1.0%); 2 in the preimplementation group (0.3%), and 10 (1.9%) in the postimplementation group ( P =0.007). In the postimplementation group, the sensitivity of the McGovern score was 90% while the specificity was 96.7%. CONCLUSIONS:The implementation of the McGovern score into the pediatric trauma decision algorithm was associated with the detection of an increased number of BCVIs compared to the preimplementation group, with good sensitivity and specificity, but a significant increase in the use of imaging.

OBJECTIVES:To describe medical management surrounding withdrawal of life-sustaining therapy (WLST) in nine U.S. PICUs. DESIGN:Retrospective, secondary analysis of the "Death One Hour After Terminal Extubation" (DONATE) cohort (2009-2021) assessing usage patterns of: 1) analgesics and sedatives; 2) vasoactive infusions; 3) neuromuscular blockade; and 4) post-extubation respiratory support. SETTING:Nine U.S. PICUs. PATIENTS:Children and adolescents 0-21 years old, who had died after WLST (discontinuation of invasive mechanical ventilation). INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Of 905 patients, 680 (75.1%) died within 1 hour of WLST. Opioids were administered in 721 of 905 patients (79.7%); across sites the range was 68-89% ( p < 0.001). We did not observe a temporal trend. Benzodiazepines were used in 507 of 905 patients (56.0%; site range, 41-66%; p < 0.001), with lower odds of usage per year (odds ratio [OR], 0.95 per year; 95% CI, 0.90-0.99 per year; p = 0.04). Dexmedetomidine was used in 140 of 905 patients (15.5%; sites range, 4-21%; p = 0.002), with greater odds of usage per year (OR, 1.16 per year; 95% CI, 1.05-1.27 per year; p = 0.004). Vasoactive infusions were discontinued in 458 of 520 patients (88.1%) receiving this medication (site range, 59-100%; p < 0.001), with greater odds of discontinuation per year (OR, 1.15 per year; 95% CI, 1.04-1.26 per year; p = 0.007). Neuromuscular blockade was used in 46 of 905 patients (5.1%; sites range, 0-13%; p < 0.001), with greater odds of usage per year (OR, 1.23 per year; 95% CI, 1.08-1.40 per year; p = 0.002). Use of any post-extubation respiratory support occurred in 50 of 905 patients (5.5%), and we did not identify an association with site or year-on-year trend. CONCLUSIONS:The 2009-2021 DONATE dataset shows substantial institutional and temporal variability in WLST practices across our nine collaborating PICUs in the United States. Future studies should focus on understanding the drivers of variability to improve the consistency and quality of end-of-life management.

Objectives: To observe the mean daily dose of fentanyl required for adequate sedation in critically ill, mechanically ventilated children randomized to receive dexmedetomidine or placebo. Methods: We conducted Dexmedetomidine Opioid Sparing Effect in Mechanically Ventilated Children (DOSE), a multicenter, double-blind, randomized, placebo-controlled, dose-escalating trial. We enrolled children aged 35 weeks post-menstrual to 17 years (inclusive) admitted across 13 pediatric multidisciplinary and cardiac intensive care units. Adequate sedation was based on a State Behavioral Score and Richmond Agitation-Sedation Scale of-1 or lower. Only the first two dexmedetomidine dosing cohorts opened for enrollment, due to early trial closure during the coronavirus 2019 pandemic. Thirty children were randomized over 13 months and included in the analyses. Results: Demographic and baseline characteristics were not different between dexmedetomidine and placebo cohorts. Similarly, mean daily fentanyl use was not different, using an unadjusted mixed regression model that considered treatment, time, and a treatment-by-time interaction. Adverse events and safety events of special interest were not different between cohorts. Conclusions: The DOSE trial revealed that dexmedetomidine added to fentanyl does not impact safety and may not spare fentanyl use in critically ill children, although the trial did not meet its recruitment goals, due to early closure during the coronavirus 2019 pandemic. More rigorous inpatient pediatric trials like DOSE that study critically ill, mechanically ventilated children are needed. Despite the many obstacles faced, the DOSE trial presents challenges from which the greater research community can learn and use to optimize future therapeutic trials in children.

ABSTRACT Background Inhaled epoprostenol (iEpo) may improve oxygenation in adults with hypoxic respiratory failure, but any effect in children with pediatric acute respiratory distress syndrome (pARDS) is unknown. Methods Retrospective observational cohort study 2017–2022 at a single pediatric intensive care unit (PICU) of children who met criteria for pARDS and received iEpo for ≥ 6 h. Results 18 children were included, with a median age of 2.9 years (IQR 1.4–7.9), severe pARDS in 14/18 (78%), and pulmonary hypertension in 8/18 (44%). Median OSI immediately pre‐iEpo initiation was 22.9 (IQR 16.1–27.3), at 6 h was 16.8 (IQR 12.6–27.5, p = 0.57 vs. pre‐initiation) and at 12 h was 15.1 (IQR 10.7–27.5, p = 0.48 vs. pre‐initiation). Discontinuity regression demonstrated a change in the slope (rate of change) of OSI from increasing slope of +0.60/hr to decreasing slope of −1.38/hour in the 12 h pre‐ versus post‐ iEpo initiation ( p < 0.001). At 6 h after iEpo initiation, most patients (12/18, 67%) had a decrease in OSI and 5/18 (28%) were responders with a decrease of ≥ 20%. Responders did not differ significantly by presence of pulmonary hypertension, severity of pARDS, or age. The majority of responders (4/5, 80%) had improvement in OSI by 1 h after initiation of iEpo and all (5/5, 100%) had improvement by 4 h after iEpo initiation. Conclusion Rate of change of OSI improved significantly after initiation of iEpo in a cohort children with pARDS, with heterogeneity of response that was not associated with pHTN or other clinical factors evaluated. Improvement in OSI was seen by 4 h in all responders.

OBJECTIVES:In the PICU, predicting death within 1 hour after terminal extubation (TE) is valuable in augmenting family counseling and in identifying suitable candidates for organ donation after circulatory determination of death (DCDD). The objective of this study was to train and validate a machine learning model to predict death within 1 hour after TE. DESIGN:The Death One Hour After Terminal Extubation (DONATE) database was generated using multicenter retrospective data from 2009 to 2021. Data covering demographics, clinical features, vital signs, laboratory values, ventilator settings, medications, and procedures were collected. Machine learning models were trained to predict whether a pediatric patient would die within 1 hour after TE and evaluated on a holdout set. SETTING:Ten U.S. PICUs. PATIENTS:Children and adolescents, 0-21 years old, who died after TE ( n = 957). INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The final model was a parsimonious extra-trees model with 21 input features. It was trained on the 2009-2018 data from eight sites ( n = 634) and evaluated on a holdout set comprised of the 2019-2021 data of all ten sites ( n = 323), representing temporal and external validation. The area under the receiver operating characteristic curve and 95% CI was 0.84 (95% CI, 0.81-0.87). At a sensitivity of 90%, the positive predictive value (PPV) was 88%, the negative predictive value (NPV) was 70%, and the number needed to alert (NNA) was 1.14. Among potential organ donors, at the same sensitivity level, the PPV was 86%, the NPV was 74%, and the NNA was 1.17. CONCLUSIONS:Our model, trained and validated on multisite data, predicted whether a child will die within 1 hour of TE with high discrimination and a low false alarm rate. This finding has important applications to end-of-life counseling and institutional resource utilization when families wish to attempt DCDD.

BACKGROUND:Social drivers of health affect severity of asthma in children, but any association with outcomes in children with critical asthma is unknown. METHODS:Retrospective cohort study of children 2-17 years old admitted to 15 United States PICUs for asthma from 2019 to 2020. Child Opportunity Index (COI) was assigned by census tract. Primary outcome was use of positive pressure ventilation (PPV), including invasive mechanical ventilation or non-invasive continuous or bilevel support. RESULTS:A total of 2093 admissions in 1926 patients were included; median age was 6.9 years (IQR 4.3-10.8). Patients were often from very low COI neighborhoods (46.7%), a higher percentage than in children admitted to participating PICUs concurrently for other respiratory (28.2% very low COI) or non-respiratory causes (24.8%) (p < 0.0001 for each comparison). PICU mortality was low (0.57%), with no difference by COI category. Median PICU length of stay was within 8.5 h across COI categories (1.0-1.4 days). PPV was used in 39% of admissions. Multivariable analysis revealed no association of COI category with use of PPV; older age, commercial insurance, and origin of admission were associated with PPV use. PICU readmission for asthma during a subsequent hospitalization occurred in 7.1% patients during the study period, with a stepwise decrease as COI category increased [very low 8.9%; low 7.4%; moderate 5.0%; high 4.4%; very high 3.8%, p = 0.02]. CONCLUSIONS:Children admitted to 15 PICUs for asthma were disproportionately from very low COI neighborhoods. Mortality and use of PPV were not significantly associated with COI; however, PICU readmission was significantly associated with lower COI.

OBJECTIVE:Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care.DESIGN:Scoping review and expert opinion.SETTING:We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness. Articles were excluded if the majority of patients were adults or neonates, if unsupervised machine learning was the primary methodology, or if information related to the development, validation, and/or implementation of the model was not reported. Article selection and data extraction were performed using dual review in the Covidence tool, with discrepancies resolved by consensus.SUBJECTS:Articles reporting on the development, validation, or implementation of supervised machine learning models in the field of pediatric critical care medicine.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:Of 5075 identified studies, 141 articles were included. Studies were primarily (57%) performed at a single site. The majority took place in the United States (70%). Most were retrospective observational cohort studies. More than three-quarters of the articles were published between 2018 and 2022. The most common algorithms included logistic regression and random forest. Predicted events were most commonly death, transfer to ICU, and sepsis. Only 14% of articles reported external validation, and only a single model was implemented at publication. Reporting of validation methods, performance assessments, and implementation varied widely. Follow-up with authors suggests that implementation remains uncommon after model publication.CONCLUSIONS:Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.

Scalone, Eleanor; Woodruff, Alan; Wright, John; Bass, Andora; Saha, Amit; Dixon, Kristopher; Walsh, Michael; McCrory, Michael Author Information

OBJECTIVES: To evaluate for associations between a child's neighborhood, as categorized by Child Opportunity Index (COI 2.0), and 1) PICU mortality, 2) severity of illness at PICU admission, and 3) PICU length of stay (LOS). DESIGN: Retrospective cohort study. SETTING: Fifteen PICUs in the United States. PATIENTS: Children younger than 18 years admitted from 2019 to 2020, excluding those after cardiac procedures. Nationally-normed COI category (very low, low, moderate, high, very high) was determined for each admission by census tract, and clinical features were obtained from the Virtual Pediatric Systems LLC (Los Angeles, CA) data from each site. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 33,901 index PICU admissions during the time period, median patient age was 4.9 years and PICU mortality was 2.1%. There was a higher percentage of admissions from the very low COI category (27.3%) than other COI categories (17.2-19.5%, p < 0.0001). Patient admissions from the high and very high COI categories had a lower median Pediatric Index of Mortality 3 risk of mortality (0.70) than those from the very low, low, and moderate COI groups (0.71) (p < 0.001). PICU mortality was lowest in the very high (1.7%) and high (1.9%) COI groups and highest in the moderate group (2.5%), followed by very low (2.3%) and low (2.2%) (p = 0.001 across categories). Median PICU LOS was between 1.37 and 1.50 days in all COI categories. Multivariable regression revealed adjusted odds of PICU mortality of 1.30 (95% CI, 0.94-1.79; p = 0.11) for children from a very low versus very high COI neighborhood, with an odds ratio [OR] of 0.996 (95% CI, 0.993-1.00; p = 0.05) for mortality for COI as an ordinal value from 0 to 100. Children without insurance coverage had an OR for mortality of 3.58 (95% CI, 2.46-5.20; p < 0.0001) as compared with those with commercial insurance. CONCLUSIONS: Children admitted to a cohort of U.S. PICUs were often from very low COI neighborhoods. Children from very high COI neighborhoods had the lowest risk of mortality and observed mortality; however, odds of mortality were not statistically different by COI category in a multivariable model. Children without insurance coverage had significantly higher odds of PICU mortality regardless of neighborhood.

McCrory, Michael; Slain, Katherine; Grunwell, Jocelyn; Rogerson, Colin; Zurca, Adrian; Winter, Meredith; Kennedy, Curtis; Woodruff, Alan; Wakeham, Martin; Dziorny, Adam; Xin Huang, Jia; Garg, Anjali; Pinto, Neethi; Maddux, Aline; Saha, Amit; Sharma, Meesha; Stottlemyre, Morgan; Barnack, Kyle; Akande, Manzilat Author Information

Introduction: The doctrine of double effect provides an ethical framework for providers to titrate medications to patient comfort at the end-of-life even if doing so hastens death, but moral distress may result from perceived under- or over- treatment. Objective of this study was to describe the doses of opioids and benzodiazepines (BZD) administered to children around the time of Terminal Extubation (TE) and to identify their association with the time to death (TTD). Methods: Secondary analysis of data collected for the Death One Hour After Terminal Extubation (DONATE) study, which included retrospective data from 9 U.S. hospitals. Medications included total doses of opioids and BZD 24 hours before and 1 hour after TE. Correlations between drug doses and TTD in minutes were calculated, and multivariable linear regression was performed to determine their association with TTD after adjusting for age, sex, last Saturation/FiO2 (SF) ratio, inotrope requirement in last 24 hours, and last recorded Glasgow Coma Scale (GCS) score. Results: Analysis cohort included 680 patients between 0-21 years who died within 1 hour in ICU after TE (2010-2021). Median age of the study population was 2.1 (IQR 0.4, 11) years. The median TTD was 15 (IQR 8, 23) minutes. 40% (278/680) of patients received either opioids or BZD within one hour after TE, with the largest proportion receiving opioids only (23%, 159/680). Among patients who received medications, the median IV morphine equivalent (eq) within 1 hour after TE was 0.75 (IQR 0 .3, 1.8) mg/kg/hr (n=263), and median lorazepam eq was 0.22 (IQR 0.11, 0.44) mg/kg/hr (n=118). The median morphine eq and lorazepam eq rates after TE were 7.5-fold and 22-fold greater than the median pre-extubation rates, respectively. No significant direct correlation was observed between either opioid or BZD doses before or after TE and TTD. After adjusting for confounding variables regression analysis also failed to show any association between drug dose and TTD. Conclusions: Children after TE are often prescribed opioids and BZD. Time to death after TE is not associated with the dose of medication administered as part of comfort care. Providers should titrate analgesic and sedative/anxiolytic medications to patient comfort after terminal extubation.

Objectives:To describe the doses of opioids and benzodiazepines administered around the time of terminal extubation (TE) to children who died within 1 hour of TE and to identify their association with the time to death (TTD). Design:Secondary analysis of data collected for the Death One Hour After Terminal Extubation study. Setting:Nine U.S. hospitals. Patients:Six hundred eighty patients between 0 and 21 years who died within 1 hour after TE (2010-2021). Measurements and Main Results:Medications included total doses of opioids and benzodiazepines 24 hours before and 1 hour after TE. Correlations between drug doses and TTD in minutes were calculated, and multivariable linear regression performed to determine their association with TTD after adjusting for age, sex, last recorded oxygen saturation/Fio(2) ratio and Glasgow Coma Scale score, inotrope requirement in the last 24 hours, and use of muscle relaxants within 1 hour of TE. Median age of the study population was 2.1 years (interquartile range [IQR], 0.4-11.0 yr). The median TTD was 15 minutes (IQR, 8-23 min). Forty percent patients (278/680) received either opioids or benzodiazepines within 1 hour after TE, with the largest proportion receiving opioids only (23%, 159/680). Among patients who received medications, the median IV morphine equivalent within 1 hour after TE was 0.75 mg/kg/hr (IQR, 0.3-1.8 mg/kg/hr) (n = 263), and median lorazepam equivalent was 0.22 mg/kg/hr (IQR, 0.11-0.44 mg/kg/hr) (n = 118). The median morphine equivalent and lorazepam equivalent rates after TE were 7.5-fold and 22-fold greater than the median pre-extubation rates, respectively. No significant direct correlation was observed between either opioid or benzodiazepine doses before or after TE and TTD. After adjusting for confounding variables, regression analysis also failed to show any association between drug dose and TTD. Conclusions:Children after TE are often prescribed opioids and benzodiazepines. For patients dying within 1 hour of TE, TTD is not associated with the dose of medication administered as part of comfort care.

Background: Timely trial start-up is a key determinant of trial success; however, delays during start-up are common and costly. Moreover, data on start-up metrics in pediatric clinical trials are sparse. To expedite trial start-up, the Trial Innovation Network piloted three novel mechanisms in the trial titled Dexmedetomidine Opioid Sparing Effect in Mechanically Ventilated Children (DOSE), a multi-site, randomized, double-blind, placebo-controlled trial in the pediatric intensive care setting.Methods: The three novel start-up mechanisms included: 1) competitive activation; 2) use of trial start-up experts, called site navigators; and 3) supplemental funds earned for achieving pre-determined milestones. After sites were activated, they received a web-based survey to report perceptions of the DOSE start-up process. In addition to perceptions, metrics analyzed included milestones met, time to start-up, and subsequent enrollment of subjects.Results: Twenty sites were selected for participation, with 19 sites being fully activated. Across activated sites, the median (quartile 1, quartile 3) time from receipt of regulatory documents to site activation was 82 days (68, 113). Sites reported that of the three novel mechanisms, the most motivating factor for expeditious activation was additional funding available for achieving start-up milestones, followed by site navigator assistance and then competitive site activation.Conclusion: Study start-up is a critical time for the success of clinical trials, and innovative methods to minimize delays during start-up are needed. Milestone-based funds and site navigators were preferred mechanisms by sites participating in the DOSE study and may have contributed to the expeditious start-up timeline achieved. ClinicalTrials.gov #: NCT03938857

OBJECTIVE:Terminal extubation (TE) and terminal weaning (TW) during withdrawal of life-sustaining therapies (WLSTs) have been described and defined in adults. The recent Death One Hour After Terminal Extubation study aimed to validate a model developed to predict whether a child would die within 1 hour after discontinuation of mechanical ventilation for WLST. Although TW has not been described in children, pre-extubation weaning has been known to occur before WLST, though to what extent is unknown. In this preplanned secondary analysis, we aim to describe/define TE and pre-extubation weaning (PW) in children and compare characteristics of patients who had ventilatory support decreased before WLST with those who did not.DESIGN:Secondary analysis of multicenter retrospective cohort study.SETTING:Ten PICUs in the United States between 2009 and 2021.PATIENTS:Nine hundred thirteen patients 0-21 years old who died after WLST.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:71.4% ( n = 652) had TE without decrease in ventilatory support in the 6 hours prior. TE without decrease in ventilatory support in the 6 hours prior = 71.4% ( n = 652) of our sample. Clinically relevant decrease in ventilatory support before WLST = 11% ( n = 100), and 17.6% ( n = 161) had likely incidental decrease in ventilatory support before WLST. Relevant ventilator parameters decreased were F io2 and/or ventilator set rates. There were no significant differences in any of the other evaluated patient characteristics between groups (weight, body mass index, unit type, primary diagnostic category, presence of coma, time to death after WLST, analgosedative requirements, postextubation respiratory support modality).CONCLUSIONS:Decreasing ventilatory support before WLST with extubation in children does occur. This practice was not associated with significant differences in palliative analgosedation doses or time to death after extubation.