Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome.

BACKGROUNDThe molecular signature of pediatric acute respiratory distress syndrome (ARDS) is poorly described, and the degree to which hyperinflammation or specific tissue injury contributes to outcomes is unknown. Therefore, we profiled inflammation and tissue injury dynamics over the first 7 days of ARDS, and associated specific biomarkers with mortality, persistent ARDS, and persistent multiple organ dysfunction syndrome (MODS).METHODSIn a single-center prospective cohort of intubated pediatric patients with ARDS, we collected plasma on days 0, 3, and 7. Nineteen biomarkers reflecting inflammation, tissue injury, and damage-associated molecular patterns (DAMPs) were measured. We assessed the relationship between biomarkers and trajectories with mortality, persistent ARDS, or persistent MODS using multivariable mixed effect models.RESULTSIn 279 patients (64 [23%] nonsurvivors), hyperinflammatory cytokines, tissue injury markers, and DAMPs were higher in nonsurvivors. Survivors and nonsurvivors showed different biomarker trajectories. IL-1α, soluble tumor necrosis factor receptor 1, angiopoietin 2 (ANG2), and surfactant protein D increased in nonsurvivors, while DAMPs remained persistently elevated. ANG2 and procollagen type III N-terminal peptide were associated with persistent ARDS, whereas multiple cytokines, tissue injury markers, and DAMPs were associated with persistent MODS. Corticosteroid use did not impact the association of biomarker levels or trajectory with mortality.CONCLUSIONSPediatric ARDS survivors and nonsurvivors had distinct biomarker trajectories, with cytokines, endothelial and alveolar epithelial injury, and DAMPs elevated in nonsurvivors. Mortality markers overlapped with markers associated with persistent MODS, rather than persistent ARDS.FUNDINGNIH (K23HL-136688, R01-HL148054).

Mechanical Power Is Associated With Mortality in Pediatric Acute Respiratory Distress Syndrome.

OBJECTIVES: Mechanical power (MP) transferred from the ventilator to the lungs has been proposed as a summary variable that may impact mortality in children with acute respiratory distress syndrome (ARDS). To date, no study has shown an association between higher MP and mortality in children with ARDS. DESIGN: Secondary analysis of a prospective observational study. SETTING: Single-center, tertiary, academic PICU. PATIENTS: Five hundred forty-six intubated children with ARDS enrolled between January 2013 and December 2019 receiving pressure-controlled ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Higher MP was associated with increased mortality (adjusted hazard ratio [HR] 1.34 per 1 sd increase, 95% CI 1.08-1.65; p = 0.007). When assessing the contribution of individual components of MP, only positive end-expiratory pressure (PEEP) was associated with mortality (HR 1.32; p = 0.007), whereas tidal volume, respiratory rate, and driving pressure (ΔP = [peak inspiratory pressure (PIP)-PEEP]) were not. Finally, we tested whether there remained an association when specific terms were removed from the MP equation by calculating MP from static strain (remove ΔP), MP from dynamic strain (remove PEEP), and mechanical energy (remove respiratory rate). MP from static strain (HR 1.44; p < 0.001), MP from dynamic strain (HR 1.25; p = 0.042), and mechanical energy (HR 1.29; p = 0.009) were all associated with mortality. MP was associated with ventilator-free days only when using MP normalized to predicted body weight, but not when using measured weight. CONCLUSIONS: Higher MP was associated with mortality in pediatric ARDS, and PEEP appears to be the component most consistently driving this association. As higher PEEP is used in sicker patients, the association between MP and mortality may reflect a marker of illness severity rather than MP itself being causal for mortality. However, our results support future trials testing different levels of PEEP in children with ARDS as a potential means to improve outcome.

Measuring Training Disruptions Using an Informatics Based Tool.

OBJECTIVE: Training disruptions, such as planned curricular adjustments or unplanned global pandemics, impact residency training in ways that are difficult to quantify. Informatics-based medical education tools can help measure these impacts. We tested the ability of a software platform driven by electronic health record data to quantify anticipated changes in trainee clinical experiences during the COVID-19 pandemic. METHODS: We previously developed and validated the Trainee Individualized Learning System (TRAILS) to identify pediatric resident clinical experiences (i.e. shifts, resident provider-patient interactions (rPPIs), and diagnoses). We used TRAILS to perform a year-over-year analysis comparing pediatrics residents at a large academic children's hospital during March 15-June 15 in 2018 (Control #1), 2019 (Control #2), and 2020 (Exposure). RESULTS: Residents in the exposure cohort had fewer shifts than those in both control cohorts (P < .05). rPPIs decreased an average of 43% across all PGY levels, with interns experiencing a 78% decrease in Continuity Clinic. Patient continuity decreased from 23% to 11%. rPPIs with common clinic and emergency department diagnoses decreased substantially during the exposure period. CONCLUSIONS: Informatics tools like TRAILS may help program directors understand the impact of training disruptions on resident clinical experiences and target interventions to learners' needs and development.

Characteristics of Emergency Room and Hospital Encounters Resulting From Consumer Home Monitors.

BACKGROUND AND OBJECTIVES: Consumer home monitors (CHM), which measure vital signs, are popular products marketed to detect airway obstruction and arrhythmia. Yet, they lack evidence of infant death prevention, demonstrate suboptimal accuracy, and may result in false alarms that prompt unnecessary acute care visits. To better understand the hospital utilization and costs of CHM, we characterized emergency department (ED) and hospital encounters associated with CHM use at a children's hospital. METHODS: We used structured query language to search the free text of all ED and admission notes between January 2013 and December 2019 to identify clinical documentation discussing CHM use. Two physicians independently reviewed the presence of CHM use and categorized encounter characteristics. RESULTS: Evidence of CHM use contributed to the presentation of 36 encounters in a sample of over 300 000 encounters, with nearly half occurring in 2019. The leading discharge diagnoses were viral infection (13, 36%), gastroesophageal reflux (8, 22%) and false positive alarm (6, 17%). Median encounter duration was 20 hours (interquartile range: 3 hours to 2 days; max 10.5 days) and median cost of encounters was $2188 (interquartile range: $255 to $7632; max $84 928). CONCLUSIONS: Although the annual rate of CHM-related encounters was low and did not indicate a major public health burden, for individual families who present to the ED or hospital for concerns related to CHMs, there may be important adverse financial and emotional consequences.

Plasma Nucleosomes Are Associated With Mortality in Pediatric Acute Respiratory Distress Syndrome.

OBJECTIVES: Circulating nucleosomes and their component histones have been implicated as pathogenic in sepsis and acute respiratory distress syndrome in adults. However, their role in pediatric acute respiratory distress syndrome is unknown. DESIGN: We performed a prospective cohort study in children with acute respiratory distress syndrome, with plasma collection within 24 hours of acute respiratory distress syndrome onset. We associated nucleosome levels with severity of acute respiratory distress syndrome and with nonpulmonary organ failures and tested for association of nucleosomes with PICU mortality and ventilator-free days at 28 days in univariate and multivariable analyses. We also performed proteomics of DNA-bound plasma proteins in a matched case-control study of septic children with and without acute respiratory distress syndrome in order to identify specific histone proteins elevated in acute respiratory distress syndrome. SETTING: Large academic tertiary-care PICU. PATIENTS: Intubated children meeting Berlin criteria for acute respiratory distress syndrome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We enrolled 333 children with acute respiratory distress syndrome, with 69 nonsurvivors (21%). Plasma nucleosomes were correlated with acute respiratory distress syndrome severity and with the number of nonpulmonary organ failures at acute respiratory distress syndrome onset. Nucleosomes were higher (p < 0.001) in nonsurvivors (0.40 [interquartile range, 0.20-0.71] arbitrary units) relative to survivors (0.10 [interquartile range, 0.04-0.25] arbitrary units). Nucleosomes were associated with PICU mortality in multivariable analysis (adjusted odds ratio 1.84 per 1 sd increase; 95% CI, 1.38-2.45; p < 0.001). Nucleosomes were also associated with a lower probability of being extubated alive by day 28 after multivariable adjustment (adjusted subdistribution hazard ratio, 0.74; 95% CI, 0.63-0.88; p = 0.001). Proteomic analysis demonstrated higher levels of the core nucleosome histones H2A, H2B, H3, and H4 in septic children with acute respiratory distress syndrome, relative to septic children without acute respiratory distress syndrome. CONCLUSIONS: Plasma nucleosomes are associated with acute respiratory distress syndrome severity, nonpulmonary organ failures, and worse outcomes in pediatric acute respiratory distress syndrome.

Attributing Patients to Pediatric Residents Using Electronic Health Record Features Augmented with Audit Logs.

OBJECTIVE: Patient attribution, or the process of attributing patient-level metrics to specific providers, attempts to capture real-life provider-patient interactions (PPI). Attribution holds wide-ranging importance, particularly for outcomes in graduate medical education, but remains a challenge. We developed and validated an algorithm using EHR data to identify pediatric resident PPIs (rPPIs). METHODS: We prospectively surveyed residents in three care settings to collect self-reported rPPIs. Participants were surveyed at the end of primary care clinic, emergency department (ED), and inpatient shifts, shown a patient census list, asked to mark the patients with whom they interacted, and encouraged to provide a short rationale behind the marked interaction. We extracted routine EHR data elements, including audit logs, note contribution, order placement, care team assignment, and chart closure, and applied a logistic regression classifier to the data to predict rPPIs in each care setting. We also performed a comment analysis of the resident-reported rationales in the inpatient care setting to explore perceived patient interactions in a complicated workflow. RESULTS: We surveyed 81 residents over 111 shifts and identified 579 patient interactions. Among EHR extracted data, time-in-chart was the best predictor in all three care settings (primary care clinic: odds ratio [OR] = 19.36, 95% confidence interval [CI]: 4.19-278.56; ED: OR = 19.06, 95% CI: 9.53-41.65' inpatient: OR = 2.95, 95% CI: 2.23-3.97). Primary care clinic and ED specific models had c-statistic values > 0.98, while the inpatient-specific model had greater variability (c-statistic = 0.89). Of 366 inpatient rPPIs, residents provided rationales for 90.1%, which were focused on direct involvement in a patient's admission or transfer, or care as the front-line ordering clinician (55.6%). CONCLUSION: Classification models based on routinely collected EHR data predict resident-defined rPPIs across care settings. While specific to pediatric residents in this study, the approach may be generalizable to other provider populations and scenarios in which accurate patient attribution is desirable.

Influence of simulation on electronic health record use patterns among pediatric residents.

Objective: Electronic health record (EHR) simulation with realistic test patients has improved recognition of safety concerns in test environments. We assessed if simulation affects EHR use patterns in real clinical settings. Materials and Methods: We created a 1-hour educational intervention of a simulated admission for pediatric interns. Data visualization and information retrieval tools were introduced to facilitate recognition of the patient's clinical status. Using EHR audit logs, we assessed the frequency with which these tools were accessed by residents prior to simulation exposure (intervention group, pre-simulation), after simulation exposure (intervention group, post-simulation), and among residents who never participated in simulation (control group). Results: From July 2015 to February 2017, 57 pediatric residents participated in a simulation and 82 did not. Residents were more likely to use the data visualization tool after simulation (73% in post-simulation weeks vs 47% of combined pre-simulation and control weeks, P <. 0001) as well as the information retrieval tool (85% vs 36%, P < .0001). After adjusting for residents' experiences measured in previously completed inpatient weeks of service, simulation remained a significant predictor of using the data visualization (OR 2.8, CI: 2.1-3.9) and information retrieval tools (OR 3.0, CI: 2.0-4.5). Tool use did not decrease in interrupted time-series analysis over a median of 19 (IQR: 8-32) weeks of post-simulation follow-up. Discussion: Simulation was associated with persistent changes to EHR use patterns among pediatric residents. Conclusion: EHR simulation is an effective educational method that can change participants' use patterns in real clinical settings.

A Model for Clinical Informatics Education for Residents: Addressing an Unmet Need.

Opportunities for education in clinical informatics exist throughout the spectrum of formal education extending from high school to postgraduate training. However, physicians in residency represent an underdeveloped source of potential informaticians. Despite the rapid growth of accredited fellowship programs since clinical informatics became a board-eligible subspecialty in 2011, few resident physicians are aware of their role at the intersection of clinical medicine and health information technology or associated opportunities. In an effort to educate and engage residents in clinical informatics, Children's Hospital of Philadelphia has developed a three-pronged model: (1) an elective rotation with hands-on project experience; (2) a longitudinal experience that offers increased exposure and mentorship; and (3) a resident founded and led working group in clinical informatics. We describe resident participation in these initiatives and lessons learned, as well as resident perceptions of how these components have positively influenced informatics knowledge and career choices. Since inception of this model, five residents have pursued the clinical informatics fellowship. This educational model supports resident involvement in hospital-wide informatics efforts with tangible projects and promotes wider engagement through educational opportunities commensurate with the resident's level of interest.

Controlling testing volume for respiratory viruses using machine learning and text mining.

Viral testing for pediatric inpatients with respiratory symptoms is common, with considerable associated charges. In an attempt to reduce testing volumes, we studied whether data available at the time of admission could aid in identifying children with low likelihood of having a particular viral origin of their symptoms, and thus safely forgo broad viral testing. We collected clinical data for 1,685 pediatric inpatients receiving respiratory virus testing from 2010-2012. Machine-learning on the data allowed us to construct pre-test models predicting whether a patient would test positive for a particular virus. Text mining improved the predictions for one viral test. Cost-sensitive models optimized for test sensitivity showed reasonable test specificities and an ability to reduce test volume by up to 46% for single viral tests. We conclude that diverse forms of data in the electronic medical record can be used productively to build models that help physicians reduce testing volumes.

Lhx2 selector activity specifies cortical identity and suppresses hippocampal organizer fate.

The earliest step in creating the cerebral cortex is the specification of neuroepithelium to a cortical fate. Using mouse genetic mosaics and timed inactivations, we demonstrated that Lhx2 acts as a classic selector gene and essential intrinsic determinant of cortical identity. Lhx2 selector activity is restricted to an early critical period when stem cells comprise the cortical neuroepithelium, where it acts cell-autonomously to specify cortical identity and suppress alternative fates in a spatially dependent manner. Laterally, Lhx2 null cells adopt antihem identity, whereas medially they become cortical hem cells, which can induce and organize ectopic hippocampal fields. In addition to providing functional evidence for Lhx2 selector activity, these findings show that the cortical hem is a hippocampal organizer.