Factors associated with family decision-making after pediatric out-of-hospital cardiac arrest.

AIM: This study aims to identify demographic factors, area-based social determinants of health (SDOH), and clinical features associated with medical decision-making after pediatric out-of-hospital cardiac arrest (OHCA). METHODS: This is a retrospective, exploratory, descriptive analysis of patients < 18 years old admitted to the pediatric intensive care unit (ICU) after OHCA from 2011 to 2022 (n = 217) at an urban tertiary care, free-standing children's hospital. Outcomes of interest included: (1) whether a new advance care plan (ACP) (defined as a written advance directive including do not resuscitate and/or do not intubate) was ordered during hospitalization, and (2) whether the patient was discharged with new medical technology (defined as tracheostomy and/or feeding tube). Logistic regression models identified features associated with these outcomes. RESULTS: Of the 217 patients, 78 patients (36%) had a new ACP placed during their admission. Of the survivors, 26% (27/102) were discharged home with new medical technology. Factors associated with ACP were greater change in Pediatric Cerebral Performance Category (PCPC) score (aOR = 1.49, 95% CI [1.28-1.73], p-value < 0.001) and palliative care consultation (aOR = 2.39, 95% CI [1.16-4.89], p-value 0.018). Factors associated with new medical technology were lower change in PCPC score (aOR = 0.76, 95% C.I. [0.61-0.95], p-value = 0.015) and palliative care consultation (aOR = 7.07, 95% CI [3.01-16.60], p-value < 0.001). There were no associations between area-based SDOH and outcomes. CONCLUSIONS: Understanding factors associated with decision-making related to ACP after OHCA is critical to optimize counseling for families. Multi-institutional studies are warranted to identify whether these findings are generalizable.

Child Opportunity Index and Pediatric Intensive Care Outcomes: A Multicenter Retrospective Study in the United States.

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.

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.

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.

Ventilator Weaning and Terminal Extubation: Withdrawal of Life-Sustaining Therapy in Children. Secondary Analysis of the Death One Hour After Terminal Extubation Study.

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.

Analgesia and Sedation at Terminal Extubation: A Secondary Analysis From Death One Hour After Terminal Extubation Study Data.

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/F io2 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.

Multicentric validation of a prognostic tool for predicting brain death following out-of-hospital cardiac arrest in children.

AIM: Out-of-hospital cardiac arrest (OHCA) in pediatric patients is associated with high rates of mortality and neurologic injury, with no definitive evidence-based method to predict outcomes available. A prognostic scoring tool for adults, The Brain Death After Cardiac Arrest (BDCA) score, was recently developed and validated. We aimed to validate this score in pediatric patients. METHODS: Retrospective cohort study of pediatric patients admitted to 5 PICUs after OHCA between 2011 and 2021. We extracted BDCA score elements for those who survived at least 24 hours but died as a result of their OHCA. We assessed score discrimination for the definitive outcome of brain death. Subgroup analysis was performed for infants < 12mo versus children ≥ 12mo, those who likely had brain death but had withdrawal of life sustaining therapy (WLST) prior to declaration, and by etiology and duration of arrest. RESULTS: 389 subjects were identified across 5 institutions, with 282 meeting inclusion criteria. 169 (59.9%) were formally declared brain dead; 58 (20.6%) had findings consistent with brain death but had withdrawal of life sustaining therapies prior to completion of formal declaration. Area under the receiver operating characteristic curve for the age ≥ 12mo cohort was 0.82 [95% CI 0.75, 0.90], which mirrored the adult subject AUCs of 0.82 [0.77, 0.86] and 0.81 [0.76, 0.86] in the development and validation cohorts. Scores demonstrated worse discrimination in the infant cohort (AUC = 0.61). CONCLUSIONS: The BDCA score shows promise in children ≥ 12mo following OHCA and may be considered in conjunction with existing multimodal prognostication approaches.

Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in Children.

Accurately predicting time to death after withdrawal of life-sustaining treatment is valuable for family counseling and for identifying candidates for organ donation after cardiac death. This topic has been well studied in adults, but literature is scant in pediatrics. The purpose of this report is to assess the performance and clinical utility of the available tools for predicting time to death after treatment withdrawal in children. DATA SOURCES: Terms related to predicting time to death after treatment withdrawal were searched in PubMed and Embase from 1993 to November 2021. STUDY SELECTION: Studies endeavoring to predict time to death or describe factors related to time to death were included. Articles focusing on perceptions or practices of treatment withdrawal were excluded. DATA EXTRACTION: Titles, abstracts, and full text of articles were screened to determine eligibility. Data extraction was performed manually. Two-by-two tables were reconstructed with available data from each article to compare performance metrics head to head. DATA SYNTHESIS: Three hundred eighteen citations were identified from the initial search, resulting in 22 studies that were retained for full-text review. Among the pediatric studies, predictive models were developed using multiple logistic regression, Cox proportional hazards, and an advanced machine learning algorithm. In each of the original model derivation studies, the models demonstrated a classification accuracy ranging from 75% to 91% and positive predictive value ranging from 0.76 to 0.93. CONCLUSIONS: There are few tools to predict time to death after withdrawal of life-sustaining treatment in children. They are limited by small numbers and incomplete validation. Future work includes utilization of advanced machine learning models.

A New Trick for an Old Dog: L-Epinephrine Delivered Continuously in the Vapor Phase.

Inhaled L-epinephrine is a known treatment of severe croup and postextubation upper airway obstruction. L-epinephrine can be delivered continuously in the vapor phase, but the indications, safety, and efficacy of this novel practice have yet to be evaluated. Theoretical risks are tachycardia, hypertension, and dysrhythmias. The study objective was to describe patient characteristics and vital sign changes related to continuous vaporized L-epinephrine use in critically ill children with the hypothesis that it can be practically and safely administered to children with subglottic edema and lower airway obstruction. DESIGN: Retrospective cohort study. SETTING: PICU and cardiothoracic ICU in a tertiary academic children's hospital. PATIENTS: Patients age 0-21 years treated with continuous vaporized L-epinephrine from 2013 to 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Continuous vaporized L-epinephrine was administered 140 times to 129 subjects via a high-flow nasal oxygen device. The median age was 10.6 months (1.3; interquartile range, 4.8-17.1 mo). The most common indications were lower respiratory tract obstruction (45%), postextubation subglottic edema (31%), and croup (16%). Eighty-eight percent had no escalation of respiratory support within 24 hours of initiation of continuous vaporized L-epinephrine, 5% progressed to require endotracheal intubation, and 3% were reintubated within 24 hours of initiation of continuous vaporized L-epinephrine following an extubation attempt. After starting continuous vaporized L-epinephrine, 85% of subjects had a decrease in heart rate and 80% had a decrease in respiratory rate. Six subjects had an increase in heart rate, and eight had an increase in blood pressure of more than 20% from baseline. These subjects did not receive interventions specific to these vital sign changes, including discontinuation of continuous vaporized L-epinephrine. CONCLUSIONS: Continuous vaporized L-epinephrine was safely administered to critically ill children with most subjects demonstrating a decrease in heart rate, blood pressure, and respiratory rate.

Machine Learning to Predict Cardiac Death Within 1 Hour After Terminal Extubation.

OBJECTIVES: Accurate prediction of time to death after withdrawal of life-sustaining therapies may improve counseling for families and help identify candidates for organ donation after cardiac death. The study objectives were to: 1) train a long short-term memory model to predict cardiac death within 1 hour after terminal extubation, 2) calculate the positive predictive value of the model and the number needed to alert among potential organ donors, and 3) examine associations between time to cardiac death and the patient's characteristics and physiologic variables using Cox regression. DESIGN: Retrospective cohort study. SETTING: PICU and cardiothoracic ICU in a tertiary-care academic children's hospital. PATIENTS: Patients 0-21 years old who died after terminal extubation from 2011 to 2018 (n = 237). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The median time to death for the cohort was 0.3 hours after terminal extubation (interquartile range, 0.16-1.6 hr); 70% of patients died within 1 hour. The long short-term memory model had an area under the receiver operating characteristic curve of 0.85 and a positive predictive value of 0.81 at a sensitivity of 94% when predicting death within 1 hour of terminal extubation. About 39% of patients who died within 1 hour met organ procurement and transplantation network criteria for liver and kidney donors. The long short-term memory identified 93% of potential organ donors with a number needed to alert of 1.08, meaning that 13 of 14 prepared operating rooms would have yielded a viable organ. A Cox proportional hazard model identified independent predictors of shorter time to death including low Glasgow Coma Score, high Pao2-to-Fio2 ratio, low-pulse oximetry, and low serum bicarbonate. CONCLUSIONS: Our long short-term memory model accurately predicted whether a child will die within 1 hour of terminal extubation and may improve counseling for families. Our model can identify potential candidates for donation after cardiac death while minimizing unnecessarily prepared operating rooms.

Beyond Reporting Early Warning Score Sensitivity: The Temporal Relationship and Clinical Relevance of "True Positive" Alerts that Precede Critical Deterioration.

BACKGROUND: Clinical deterioration is difficult to detect in hospitalized children. The pediatric Rothman Index (pRI) is an early warning score that incorporates vital signs, laboratory studies, and nursing assessments to generate deterioration alerts. OBJECTIVES: (1) Evaluate the timing of pRI alerts and clinicians recognizing deterioration or escalating care prior to critical deterioration events (CDEs) and (2) determine whether the parameters triggering alerts were clinically related to deterioration. DESIGN: CDEs are unplanned transfers to the intensive care unit with noninvasive ventilation, tracheal intubation, and/or vasopressor infusion in the 12 hours after transfer. Using one year of data from a large freestanding children's hospital without the pRI, we analyzed CDEs that would have been preceded by pRI alerts. We (1) compared the timing of pRI alerts to time-stamped notes describing changes in patient status and orders reflecting escalations of care and (2) identified score component(s) that caused alerts to trigger and determined whether these were clinically related to CDE etiology. RESULTS: Fifty CDEs would have triggered pRI alertsif the pRI had been in use (sensitivity 68%). In 90% of CDEs, the first clinician note reflecting change in patient status and/or the first order reflecting escalation of care preceded the first pRI alert. All of the vital sign and laboratory components of the pRI and 51% of the nursing components were clinically related to the etiology of the CDE. CONCLUSIONS: Evidence that clinicians were awareof deterioration preceded pRI alerts in most CDEs that generated alerts in the preceding 24 hours.

Content review of pediatric ethics consultations at a cancer center.

BACKGROUND/OBJECTIVES: Ethical challenges in pediatric oncology arise at every stage of illness. However, there are sparse data on the content of and reason for ethics consultations in the field. We sought to evaluate the content and characteristics of ethics consultations in pediatric patients at a cancer center. DESIGN/METHODS: We retrospectively identified ethics consultations performed for patients diagnosed with cancer at ≤21 years of age who were treated in the Department of Pediatrics from 2007 to 2017. Using an established coding schema, two independent reviewers analyzed the content of ethics consultation notes and identified core ethical issues and relevant contextual issues. Demographic, clinical, and consultation-specific data were also collected. RESULTS: Thirty-five consultations were performed for 32 unique patients. The most commonly identified ethical issues were obligation to provide nonbeneficial treatment (29%) and resuscitation preferences (26%). Communication conflicts were the most commonly identified contextual issue (40%). There were two themes that emerged repeatedly but were not a part of the original coding schema-four consultations (11%) that involved physicians questioning their obligation to provide potentially toxic treatment in the setting of poor patient/parent compliance, and two consultations (6%) related to complex risk-benefit analysis in the setting of an invasive procedure with uncertain benefit. CONCLUSIONS: Pediatric ethics consultations are infrequent at this specialty cancer hospital. Ethical issues focused on treatment and end-of-life care and included a diversity of communication conflicts.

Evaluation of an HIV adherence counseling program in La Romana, Dominican Republic.

Research has demonstrated that adherence to antiretroviral therapy (ART) results in lower rates of morbidity and mortality associated with HIV infection, yet adherence remains a challenge in resource-limited settings like the Dominican Republic. Clinica de Familia La Romana addressed this problem with an education-based adherence program for adult patients new to ART, and this retrospective cohort study aimed to evaluate the impact of this intervention. Appointment adherence and biological markers were assessed in cases and controls through 12 months. A total of 101 participants were included, with 61 controls and 40 cases. The baseline CD4 count was 162 and 157 cells/mm3 in controls and cases, respectively. Cases showed a 15-fold increase in CD4 count compared with a 2.5-fold increase in controls. Cases were more likelyto adhere to appointments with adherence rates of 86% versus 76% in controls. There was no difference between the rates of treatment abandonment, transfer of care, or death.