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.

International Consensus Criteria for Pediatric Sepsis and Septic Shock.

Importance: Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children. Objective: To update and evaluate criteria for sepsis and septic shock in children. Evidence Review: The Society of Critical Care Medicine (SCCM) convened a task force of 35 pediatric experts in critical care, emergency medicine, infectious diseases, general pediatrics, nursing, public health, and neonatology from 6 continents. Using evidence from an international survey, systematic review and meta-analysis, and a new organ dysfunction score developed based on more than 3 million electronic health record encounters from 10 sites on 4 continents, a modified Delphi consensus process was employed to develop criteria. Findings: Based on survey data, most pediatric clinicians used sepsis to refer to infection with life-threatening organ dysfunction, which differed from prior pediatric sepsis criteria that used systemic inflammatory response syndrome (SIRS) criteria, which have poor predictive properties, and included the redundant term, severe sepsis. The SCCM task force recommends that sepsis in children be identified by a Phoenix Sepsis Score of at least 2 points in children with suspected infection, which indicates potentially life-threatening dysfunction of the respiratory, cardiovascular, coagulation, and/or neurological systems. Children with a Phoenix Sepsis Score of at least 2 points had in-hospital mortality of 7.1% in higher-resource settings and 28.5% in lower-resource settings, more than 8 times that of children with suspected infection not meeting these criteria. Mortality was higher in children who had organ dysfunction in at least 1 of 4-respiratory, cardiovascular, coagulation, and/or neurological-organ systems that was not the primary site of infection. Septic shock was defined as children with sepsis who had cardiovascular dysfunction, indicated by at least 1 cardiovascular point in the Phoenix Sepsis Score, which included severe hypotension for age, blood lactate exceeding 5 mmol/L, or need for vasoactive medication. Children with septic shock had an in-hospital mortality rate of 10.8% and 33.5% in higher- and lower-resource settings, respectively. Conclusions and Relevance: The Phoenix sepsis criteria for sepsis and septic shock in children were derived and validated by the international SCCM Pediatric Sepsis Definition Task Force using a large international database and survey, systematic review and meta-analysis, and modified Delphi consensus approach. A Phoenix Sepsis Score of at least 2 identified potentially life-threatening organ dysfunction in children younger than 18 years with infection, and its use has the potential to improve clinical care, epidemiological assessment, and research in pediatric sepsis and septic shock around the world.

Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock.

Importance: The Society of Critical Care Medicine Pediatric Sepsis Definition Task Force sought to develop and validate new clinical criteria for pediatric sepsis and septic shock using measures of organ dysfunction through a data-driven approach. Objective: To derive and validate novel criteria for pediatric sepsis and septic shock across differently resourced settings. Design, Setting, and Participants: Multicenter, international, retrospective cohort study in 10 health systems in the US, Colombia, Bangladesh, China, and Kenya, 3 of which were used as external validation sites. Data were collected from emergency and inpatient encounters for children (aged <18 years) from 2010 to 2019: 3 049 699 in the development (including derivation and internal validation) set and 581 317 in the external validation set. Exposure: Stacked regression models to predict mortality in children with suspected infection were derived and validated using the best-performing organ dysfunction subscores from 8 existing scores. The final model was then translated into an integer-based score used to establish binary criteria for sepsis and septic shock. Main Outcomes and Measures: The primary outcome for all analyses was in-hospital mortality. Model- and integer-based score performance measures included the area under the precision recall curve (AUPRC; primary) and area under the receiver operating characteristic curve (AUROC; secondary). For binary criteria, primary performance measures were positive predictive value and sensitivity. Results: Among the 172 984 children with suspected infection in the first 24 hours (development set; 1.2% mortality), a 4-organ-system model performed best. The integer version of that model, the Phoenix Sepsis Score, had AUPRCs of 0.23 to 0.38 (95% CI range, 0.20-0.39) and AUROCs of 0.71 to 0.92 (95% CI range, 0.70-0.92) to predict mortality in the validation sets. Using a Phoenix Sepsis Score of 2 points or higher in children with suspected infection as criteria for sepsis and sepsis plus 1 or more cardiovascular point as criteria for septic shock resulted in a higher positive predictive value and higher or similar sensitivity compared with the 2005 International Pediatric Sepsis Consensus Conference (IPSCC) criteria across differently resourced settings. Conclusions and Relevance: The novel Phoenix sepsis criteria, which were derived and validated using data from higher- and lower-resource settings, had improved performance for the diagnosis of pediatric sepsis and septic shock compared with the existing IPSCC criteria.

Obstacle course activity in soldiers impedes recall but not learning of a read text.

Research suggests that preceding physical activity benefits learning in the general population, however the impact of physical activity before testing has not been systematically explored. We examined how an acute, complex anaerobic activity impacted learning and retention of text. Soldiers read Special Operations or Pension texts and were tested on recall and comprehension at 1 and 48 hours after reading. Participants also performed a challenging physical course before learning, before testing, or outside of these two periods. Results were compared using a mixed Analysis of Covariance with a "fitness-effort" covariate factor. Testing complied with Human Research Ethics Committee guidelines. Participants performing physical activity before testing had lower mean first test scores than participants performing the activity outside of the learning or testing window. After 48 hours, there was no difference among groups. Equally, while participants who read the Special Operations materials performed better than those who read the Pension materials, there was no effect related to activity timing. Acute obstacle course activity impeded recall but not learning of a read text. Additional study is needed to determine whether metabolic or motoric demands of the physical activity caused the deficit.

Computed Tomography Perfusion Data for Acute Ischemic Stroke Evaluation Using Rapid Software: Pitfalls of Automated Postprocessing.

Computed tomography perfusion (CTP) is increasingly used to determine treatment eligibility for acute ischemic stroke patients. Automated postprocessing of raw CTP data is routinely used, but it can fail. In reviewing 176 consecutive acute ischemic stroke patients, failures occurred in 20 patients (11%) during automated postprocessing by the RAPID software. Failures were caused by motion (n = 11, 73%), streak artifacts (n = 2, 13%), and poor contrast bolus arrival (n = 2, 13%). Stroke physicians should review CTP results with care before they are being integrated in their decision-making process.

Collateral Status in Ischemic Stroke: A Comparison of Computed Tomography Angiography, Computed Tomography Perfusion, and Digital Subtraction Angiography.

OBJECTIVE: To compare assessment of collaterals by single-phase computed tomography (CT) angiography (CTA) and CT perfusion-derived 3-phase CTA, multiphase CTA and temporal maximum-intensity projection (tMIP) images to digital subtraction angiography (DSA), and relate collateral assessments to clinical outcome in patients with acute ischemic stroke. METHODS: Consecutive acute ischemic stroke patients who underwent CT perfusion, CTA, and DSA before thrombectomy with occlusion of the internal carotid artery, the M1 or the M2 segments were included. Two observers assessed all CT images and one separate observer assessed DSA (reference standard) with static and dynamic (modified American Society of Interventional and Therapeutic Neuroradiology) collateral grading methods. Interobserver agreement and concordance were quantified with Cohen-weighted κ and concordance correlation coefficient, respectively. Imaging assessments were related to clinical outcome (modified Rankin Scale, ≤ 2). RESULTS: Interobserver agreement (n = 101) was 0.46 (tMIP), 0.58 (3-phase CTA), 0.67 (multiphase CTA), and 0.69 (single-phase CTA) for static assessments and 0.52 (3-phase CTA) and 0.54 (multiphase CTA) for dynamic assessments. Concordance correlation coefficient (n = 80) was 0.08 (3-phase CTA), 0.09 (single-phase CTA), and 0.23 (multiphase CTA) for static assessments and 0.10 (3-phase CTA) and 0.27 (multiphase CTA) for dynamic assessments. Higher static collateral scores on multiphase CTA (odds ratio [OR], 1.7; 95% confidence interval [CI], 1.1-2.7) and tMIP images (OR, 2.0; 95% CI, 1.1-3.4) were associated with modified Rankin Scale of 2 or less as were higher modified American Society of Interventional and Therapeutic Neuroradiology scores on 3-phase CTA (OR, 1.5; 95% CI, 1.1-2.2) and multiphase CTA (OR, 1.7; 95% CI, 1.1-2.6). CONCLUSIONS: Concordance between assessments on CT and DSA was poor. Collateral status evaluated on 3-phase CTA and multiphase CTA, but not on DSA, was associated with clinical outcome.

Hypoperfusion Intensity Ratio Is Correlated With Patient Eligibility for Thrombectomy.

Background and Purpose- Hypoperfusion intensity ratio (HIR) is associated with collateral status in acute ischemic stroke patients with anterior circulation large vessel occlusion. We assessed whether HIR was correlated to patient eligibility for mechanical thrombectomy (MT). Methods- We performed a retrospective cohort study of consecutive acute ischemic stroke patients with a proximal middle cerebral artery or internal carotid artery occlusion who underwent MT triage with computed tomography or magnetic resonance perfusion imaging. Clinical data, ischemic core (mL), HIR (defined as time-to-maximum [TMax] >10 seconds/TMax >6 seconds), mismatch volume between core and penumbra, and MT details were assessed. Primary outcome was favorable HIR collateral score (HIR <0.4) between patients who underwent MT (MT+) and those who did not (MT-) according to American Heart Association guidelines both in the <6 hours and 6 to 24 hours windows. Secondary outcomes were favorable HIR score in MT- subgroups (National Institutes of Health Stroke Scale <6 versus core >70 mL) and core-penumbra mismatch volumes. Patients who did not meet guidelines were not included. Results- We included 197 patients (145 MT+ and 52 MT-). MT+ patients had a significantly lower median HIR compared with MT- patients (0.4 [interquartile range, 0.2-0.5] versus 0.6 [interquartile range, 0.5-0.8]; P<0.001) and a higher mismatch volume (96 versus 27 mL, P<0.001). Among MT- patients, 43 had a core >70 mL, and 9 had a National Institutes of Health Stroke Scale <6. MT- patients with National Institutes of Health Stroke Scale <6 had a lower HIR than MT- patients with core >70 mL (0.2 [interquartile range, 0.2-0.3] versus 0.7 [interquartile range, 0.6-0.8], P<0.001) but their HIR was not significantly different that MT+ patients. Conclusions- Patients who meet American Heart Association guidelines for thrombectomy are more likely to have favorable collaterals (low HIR). HIR may be used as a marker of eligibility for MT triage.

Reduced Intravoxel Incoherent Motion Microvascular Perfusion Predicts Delayed Cerebral Ischemia and Vasospasm After Aneurysm Rupture.

BACKGROUND AND PURPOSE: Proximal artery vasospasm and delayed cerebral ischemia (DCI) after cerebral aneurysm rupture result in reduced cerebral perfusion and microperfusion and significant morbidity and mortality. Intravoxel incoherent motion (IVIM) magnetic resonance imaging extracts microvascular perfusion information from a multi-b value diffusion-weighted sequence. We determined whether decreased IVIM perfusion may identify patients with proximal artery vasospasm and DCI. METHODS: We performed a pilot retrospective cohort study of patients with ruptured cerebral aneurysms. Consecutive patients who underwent a brain magnetic resonance imaging with IVIM after ruptured aneurysm treatment were included. Patient demographic, treatment, imaging, and outcome data were determined by electronic medical record review. Primary outcome was DCI development with proximal artery vasospasm that required endovascular treatment. Secondary outcomes included mortality and clinical outcomes at 6 months. RESULTS: Sixteen patients (11 females, 69%; P=0.9) were included. There were no differences in age, neurological status, or comorbidities between patients who subsequently underwent endovascular treatment of DCI (10 patients; DCI+ group) and those who did not (6 patients; DCI- group). Compared with DCI- patients, DCI+ patients had decreased IVIM perfusion fraction f (0.09±0.03 versus 0.13±0.01; P=0.03), reduced diffusion coefficient D (0.82±0.05 versus 0.92±0.07×10-3 mm2/s; P=0.003), and reduced blood flow-related parameter fD* (1.18±0.40 versus 1.83±0.40×10-3 mm2/s; P=0.009). IVIM pseudodiffusion coefficient D* did not differ between DCI- (0.011±0.002) and DCI+ (0.013±0.005 mm2/s; P=0.4) patients. No differences in mortality or clinical outcome were identified. CONCLUSIONS: Decreased IVIM perfusion fraction f and blood flow-related parameter fD* correlate with DCI and proximal artery vasospasm development after cerebral aneurysm rupture.

Conditioning Methodologies for DanceSport: Lessons from Gymnastics, Figure Skating, and Concert Dance Research.

OBJECTIVES: Dancesport, the competitive branch of ballroom dancing, places high physiological and psychological demands on its practitioners, but pedagogical resources in these areas for this dance form are limited. Dancesport competitors could benefit from strategies used in other aesthetic sports. In this review, we identify conditioning methodologies from gymnastics, figure skating, and contemporary, modern, and ballet dance forms that could have relevance and suitability for dancesport training, and propose several strategies for inclusion in the current dancesport curriculum. METHODS: We reviewed articles derived from Google Scholar, PubMed, ScienceDirect, Taylor & Francis Online, and Web of Science search engines and databases, with publication dates from 1979 to 2013. The keywords included MeSH terms: dancing, gymnastics, physiology, energy metabolism, physical endurance, and range of motion. Out of 47 papers examined, 41 papers met the inclusion criteria (validity of scientific methods, topic relevance, transferability to dancesport, publication date). Quality and validity of the data were assessed by examining the methodologies in each study and comparing studies on similar populations as well as across time using the PRISMA 2009 checklist and flowchart. RESULTS: The relevant research suggests that macro-cycle periodization planning, aerobic and anaerobic conditioning, range of motion and muscular endurance training, and performance psychology methods have potential for adaptation for dancesport training. CONCLUSIONS: Dancesport coaches may help their students fulfill their ambitions as competitive athletes and dance artists by adapting the relevant performance enhancement strategies from gymnastics, figure skating, and concert dance forms presented in this paper.

Bias and sensitivity of proprioception of a passively felt hand path with and without a secondary task.

Previously, we observed changes in the scale, rotation, and location of drawn shapes when subjects simultaneously performed a secondary task, but not in the shape or proportion of the drawing. We suggested the secondary task impacted motor planning and execution or proprioception of the primary task. To isolate for proprioceptive effects, here we used the same secondary task during passive shape perception. A robotic manipulandum moved the subject's hand around the perimeter of a template shape and then a test shape differing in size, proportion, or location. Subjects also performed the same primary task while simultaneously performing a secondary task of reporting the orientation of right or left tilted arrows. We compared the performance between single and dual task, and different workspaces. In single-task conditions, subjects perceived scale, location, and proportion very close to the actual (all biases under 1 cm). A secondary task only increased the uncertainty range for judgment of scale, with no other effect. Subjects judged shapes in the centered workspace to be smaller and closer relative to the template compared with those in the peripheral workspace, although in that workspace, it was more difficult to discern changes in the proportion of the shape. The result for scale in the current passive paradigm is not different from our active study in which efference copy was available. This suggests that the scale parameters of the shape, whether actively or passively encountered, are disrupted by task interference at the level of proprioception or sensory integration rather than motor planning and execution.

A case report of an 18-year-old receiving nebulized lidocaine for treatment of COVID-19 cough.

An 18-year-old girl presenting with respiratory and gastrointestinal symptoms was found to have COVID-19 pneumonia and severe acute respiratory distress syndrome (ARDS). She was transferred to our pediatric intensive care unit (PICU) for ongoing mechanical ventilation and initiation of venovenous extracorporeal membrane oxygenation (VV-ECMO) for management of progressive hypoxic respiratory failure. She developed a worsening cough with associated life-threatening desaturation events that impaired ECMO flow and required deep sedation. Despite multiple sedative agents, our patient continued to have frequent coughing episodes with associated tachycardia, hypertension, and hypoxemia. The PICU team started nebulized lidocaine 1% 4 mL (40 mg) every 6 hours with albuterol pretreatment, gabapentin, and scheduled ipratropium. Lidocaine levels were <1 mcg/mL throughout the treatment duration. Nebulized lidocaine was stopped after 18 days given improvement in coughing episode severity. Our patient is one of the first reports of an adolescent patient receiving nebulized lidocaine for COVID-19 associated cough. Administration of nebulized lidocaine was well tolerated in this patient without adverse effects and was associated with decreased sedation needs. Given the widespread impact of the COVID-19 pandemic and its sequelae in pediatric, adolescent, and adult patients, additional research is warranted to explore options for management of COVID-19 associated cough.

Bridging Bone Health: Osteoporosis Disparities in the Rio Grande Valley.

INTRODUCTION: Osteoporosis is characterized by decreased bone mass and decreased bone quality, leading to increased bone fragility and risk of fractures. The number of fractures due to osteoporosis is projected to increase to over three million by the year 2025 and cost $25.3 billion annually. It ranks highly among diseases that cause patients to become bedridden with serious complications and reduced quality of life. Additionally, osteoporosis disproportionately affects Hispanics, which comprise most of the Rio Grande Valley (RGV) population. Therefore, our primary objective was to determine the prevalence of osteoporosis within the RGV. Additionally, we had secondary objectives to determine the screening rates of osteoporosis in the RGV and identify other potential risk factors associated with osteoporosis. We hypothesize that individuals residing in the RGV have higher rates of osteoporosis and lower rates of osteoporosis screening than the national average. METHODS: This retrospective observational cross-sectional study utilized Medicare beneficiary data via the "Mapping Medicare Disparities by Population" interactive tool. Osteoporosis data were compared within the RGV (comprising Starr, Hidalgo, Cameron, and Willacy counties) and compared with national averages between the years 2016 and 2021. Statistical analysis included prevalence ratios with 95% confidence intervals and chi-square values when applicable. RESULTS: Among Medicare beneficiaries residing in the RGV, there are higher rates of osteoporosis compared to the national average (11.5% vs. 7.20%; p < .00001). Screening for osteoporosis within the RGV is above the national average (9.29% vs. 6.67%, p < .00001). Hispanics residing in the RGV have higher overall rates of osteoporosis than Caucasians residing in the RGV (12.3% vs. 8.60%, p < .00001). Females residing in the RGV have nearly twice the rate of osteoporosis compared to the national average (19.1% vs. 11.8%, p < .00001) and 6.58 times the rate of males residing in the RGV (19.1% vs. 2.9%, p < .00001). CONCLUSION: Individuals residing in the RGV are disproportionately affected by osteoporosis. Despite increased screening rates seen among Medicare beneficiaries, we also suspect many individuals, uninsured or undocumented, have not received any appropriate osteoporosis screening. Risk factors in the RGV associated with higher rates of osteoporosis could include low education levels, socioeconomic status, physical activity, and mineral intake. These results demonstrate a need to address osteoporosis health literacy, promote earlier interventions to treat osteoporosis and increase healthcare accessibility in the RGV.

Improving Pediatric Intensive Care Unit Discharge Timeliness of Infants with Bronchiolitis Using Clinical Decision Support.

BACKGROUND: Identifying children ready for transfer out of the pediatric intensive care unit (PICU) is an area that may benefit from clinical decision support (CDS). We previously implemented a quality improvement (QI) initiative to accelerate the transfer evaluation of non-medically complex PICU patients with viral bronchiolitis receiving floor-appropriate respiratory support. OBJECTIVES: Design a CDS tool adaptation of this QI initiative to further accelerate transfer evaluation of appropriate patients. METHODS: The original initiative focused on identifying for transfer evaluation otherwise healthy children admitted to the PICU with bronchiolitis who had been receiving floor-appropriate levels of respiratory support for at least 6 hours. However, this initiative required that clinicians manually track the respiratory support of qualifying patients. We designed an electronic health record (EHR)-based CDS tool to automate identification of transfer-ready candidates. The tool parses EHR data to identify children meeting prior QI initiative criteria and alerts clinicians to assess transfer readiness once a child has been receiving floor-appropriate respiratory support for 6 hours. We compared time from reaching floor-appropriate support to placement of the transfer order ("time-to-transfer"), PICU length of stay (LOS), and hospital LOS between patients admitted prior to our QI initiative (December 1, 2018-October 19, 2019, "pre-QI phase"), during the initiative but before CDS tool implementation (October 20, 2019-February 7, 2022, "QI phase"), and after CDS implementation (February 8-November 11, 2022, "CDS phase"). RESULTS: CDS-phase patients (n = 131) had a shorter median time-to-transfer of 5.23 (interquartile range [IQR], 3.38-10.0) hours compared with QI-phase patients (n = 304) at 5.93 (IQR, 4.23-12.2) hours (p = 0.04). PICU and hospital LOS values decreased from the pre-QI (n = 150) to QI phase. Though LOS reductions were sustained during the CDS phase, further reductions from QI to CDS phase were not statistically significant. CONCLUSION: An EHR-based CDS adaptation of a prior QI initiative facilitated timely identification of PICU patients with bronchiolitis ready for transfer evaluation. Such tools might allow PICU clinicians to focus on other high-acuity tasks while accelerating transfer evaluation of appropriate patients.

Ontologizing health systems data at scale: making translational discovery a reality.

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Machine Learning Approach to Predicting Absence of Serious Bacterial Infection at PICU Admission.

BACKGROUND AND OBJECTIVES: Serious bacterial infection (SBI) is common in the PICU. Antibiotics can mitigate associated morbidity and mortality but have associated adverse effects. Our objective is to develop machine learning models able to identify SBI-negative children and reduce unnecessary antibiotics. METHODS: We developed models to predict SBI-negative status at PICU admission using vital sign, laboratory, and demographic variables. Children 3-months to 18-years-old admitted to our PICU, between 2011 and 2020, were included if evaluated for infection within 24-hours, stratified by documented antibiotic exposure in the 48-hours prior. Area under the receiver operating characteristic curve (AUROC) was the primary model accuracy measure; secondarily, we calculated the number of SBI-negative children subsequently provided antibiotics in the PICU identified as low-risk by each model. RESULTS: A total of 15 074 children met inclusion criteria; 4788 (32%) received antibiotics before PICU admission. Of these antibiotic-exposed patients, 2325 of 4788 (49%) had an SBI. Of the 10 286 antibiotic-unexposed patients, 2356 of 10 286 (23%) had an SBI. In antibiotic-exposed children, a radial support vector machine model had the highest AUROC (0.80) for evaluating SBI, identifying 48 of 442 (11%) SBI-negative children provided antibiotics in the PICU who could have been spared a median 3.7 (interquartile range 0.9-9.0) antibiotic-days per patient. In antibiotic-unexposed children, a random forest model performed best, but was less accurate overall (AUROC 0.76), identifying 33 of 469 (7%) SBI-negative children provided antibiotics in the PICU who could have been spared 1.1 (interquartile range 0.9-3.7) antibiotic-days per patient. CONCLUSIONS: Among children who received antibiotics before PICU admission, machine learning models can identify children at low risk of SBI and potentially reduce antibiotic exposure.

Reducing PICU-to-Floor Time-to-Transfer Decision in Critically Ill Bronchiolitis Patients using Quality Improvement Methodology.

INTRODUCTION: Specific criteria for de-escalation from the PICU are often not included in viral bronchiolitis institutional pathways. Variability of transfer preferences can prolong PICU length of stay. We aimed to decrease the time from reaching floor-appropriate heated high flow nasal cannula (HHF) settings to the transfer decision by 20% through standardizing PICU-to-floor transfer assessment in a PICU bronchiolitis cohort. METHODS: We included PICU bronchiolitis admissions from October 2019 to April 2020, who were 6-months to 2-years-old with no comorbidities nor intubation during their encounter. Our intervention bundle included introduction of transfer criteria and standardization of transfer-readiness assessment. The primary outcome was time from reaching floor-appropriate HHF settings [8 L per minutes (Lpm)] to placement of the transfer order ("time-to-transfer decision"). The secondary outcome was PICU length of stay. The main process measure was the proportion of patients transferred on ≥6 Lpm HHF. Balancing measures included Rapid Response Team activation and unplanned PICU readmission. We assessed admissions meeting inclusion criteria from December, 2018-March, 2019 for the preintervention baseline. RESULTS: Special cause variation indicated improvement in our primary outcome and process measures. Comparison of baseline to postintervention revealed a reduction in median time-to-transfer decision (14.4-7.8 hours; P < 0.001) and increase in children transferred on ≥6 Lpm (51%-72%; P < 0.001). We observed no change in PICU length of stay or balancing measures. CONCLUSION: Standardizing de-escalation criteria and transfer-readiness assessment reduced the time-to-transfer decision out of the PICU and increased the proportion transferred on ≥6 Lpm HHF for children with viral bronchiolitis without increasing PICU readmissions.

Characteristics, Outcomes, and Severity Risk Factors Associated With SARS-CoV-2 Infection Among Children in the US National COVID Cohort Collaborative.

Importance: Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data. Objective: To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C). Design, Setting, and Participants: A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US. Participants included children younger than 19 years at initial SARS-CoV-2 testing. Main Outcomes and Measures: Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C), and Delta vs pre-Delta variant differences for children with SARS-CoV-2. Results: A total of 1 068 410 children were tested for SARS-CoV-2 and 167 262 test results (15.6%) were positive (82 882 [49.6%] girls; median age, 11.9 [IQR, 6.0-16.1] years). Among the 10 245 children (6.1%) who were hospitalized, 1423 (13.9%) met the criteria for severe disease: mechanical ventilation (796 [7.8%]), vasopressor-inotropic support (868 [8.5%]), extracorporeal membrane oxygenation (42 [0.4%]), or death (131 [1.3%]). Male sex (odds ratio [OR], 1.37; 95% CI, 1.21-1.56), Black/African American race (OR, 1.25; 95% CI, 1.06-1.47), obesity (OR, 1.19; 95% CI, 1.01-1.41), and several pediatric complex chronic condition (PCCC) subcategories were associated with higher severity disease. Vital signs and many laboratory test values from the day of admission were predictive of peak disease severity. Variables associated with increased odds for MIS-C vs acute COVID-19 included male sex (OR, 1.59; 95% CI, 1.33-1.90), Black/African American race (OR, 1.44; 95% CI, 1.17-1.77), younger than 12 years (OR, 1.81; 95% CI, 1.51-2.18), obesity (OR, 1.76; 95% CI, 1.40-2.22), and not having a pediatric complex chronic condition (OR, 0.72; 95% CI, 0.65-0.80). The children with MIS-C had a more inflammatory laboratory profile and severe clinical phenotype, with higher rates of invasive ventilation (117 of 707 [16.5%] vs 514 of 8241 [6.2%]; P < .001) and need for vasoactive-inotropic support (191 of 707 [27.0%] vs 426 of 8241 [5.2%]; P < .001) compared with those who had acute COVID-19. Comparing children during the Delta vs pre-Delta eras, there was no significant change in hospitalization rate (1738 [6.0%] vs 8507 [6.2%]; P = .18) and lower odds for severe disease (179 [10.3%] vs 1242 [14.6%]) (decreased by a factor of 0.67; 95% CI, 0.57-0.79; P < .001). Conclusions and Relevance: In this cohort study of US children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.

Impact of Clot Shape on Successful M1 Endovascular Reperfusion.

Objectives: The susceptibility-vessel-sign (SVS) allows thrombus visualization, length estimation and composition, and it may impact reperfusion during mechanical thrombectomy (MT). SVS can also describe thrombus shape in the occluded artery: in the straight M1-segment (S-shaped), or in an angulated/traversing a bifurcation segment (A-shaped). We determined whether SVS clot shape influenced reperfusion and outcomes after MT for proximal middle-cerebral-artery (M1) occlusions. Methods: Between May 2015 and March 2018, consecutive patients who underwent MT at one comprehensive stroke center and who had a baseline MRI with a T2* sequence were included. Clinical, procedural and radiographic data, including clot shape on SVS [angulated/bifurcation (A-SVS) vs. straight (S-SVS)] and length were assessed. Primary outcome was successful reperfusion (TICI 2b-3). Secondary outcome were MT complication rates, MT reperfusion time, and clinical outcome at 90-days. Predictors of outcome were assessed with univariate and multivariate analyses. Results: A total of 62 patients were included. 56% (35/62) had an A-SVS. Clots were significantly longer in the A-SVS group (19 mm vs. 8 mm p = 0.0002). Groups were otherwise well-matched with regard to baseline characteristics. There was a significantly lower rate of successful reperfusion in the A-SVS cohort (83%) compared to the S-SVS cohort (96%) in multivariable analysis [OR 0.04 (95% CI, 0.002-0.58), p = 0.02]. There was no significant difference in long term clinical outcome between groups. Conclusion: Clot shape as determined on T2* imaging, in patients presenting with M1 occlusion appears to be a predictor of successful reperfusion after MT. Angulated and bifurcating clots are associated with poorer rates of successful reperfusion.

Children with SARS-CoV-2 in the National COVID Cohort Collaborative (N3C).

IMPORTANCE: SARS-CoV-2. OBJECTIVE: To determine the characteristics, changes over time, outcomes, and severity risk factors of SARS-CoV-2 affected children within the National COVID Cohort Collaborative (N3C). DESIGN: Prospective cohort study of patient encounters with end dates before May 27th, 2021. SETTING: 45 N3C institutions. PARTICIPANTS: Children <19-years-old at initial SARS-CoV-2 testing. MAIN OUTCOMES AND MEASURES: Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs MIS-C contrasts for children infected with SARS-CoV-2. RESULTS: 728,047 children in the N3C were tested for SARS-CoV-2; of these, 91,865 (12.6%) were positive. Among the 5,213 (6%) hospitalized children, 685 (13%) met criteria for severe disease: mechanical ventilation (7%), vasopressor/inotropic support (7%), ECMO (0.6%), or death/discharge to hospice (1.1%). Male gender, African American race, older age, and several pediatric complex chronic condition (PCCC) subcategories were associated with higher clinical severity (p ≤ 0.05). Vital signs (all p≤0.002) and many laboratory tests from the first day of hospitalization were predictive of peak disease severity. Children with severe (vs moderate) disease were more likely to receive antimicrobials (71% vs 32%, p<0.001) and immunomodulatory medications (53% vs 16%, p<0.001). Compared to those with acute COVID-19, children with MIS-C were more likely to be male, Black/African American, 1-to-12-years-old, and less likely to have asthma, diabetes, or a PCCC (p < 0.04). MIS-C cases demonstrated a more inflammatory laboratory profile and more severe clinical phenotype with higher rates of invasive ventilation (12% vs 6%) and need for vasoactive-inotropic support (31% vs 6%) compared to acute COVID-19 cases, respectively (p<0.03). CONCLUSIONS: In the largest U.S. SARS-CoV-2-positive pediatric cohort to date, we observed differences in demographics, pre-existing comorbidities, and initial vital sign and laboratory test values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.