Faculty Bibliography

BACKGROUND:Metabolites represent a read-out of cellular processes underlying states of health and disease. METHODS:We evaluated cross-sectional and longitudinal associations between 1255 serum and 1398 urine known and unknown (denoted with "X" in name) metabolites (Metabolon HD4, 721 detected in both biofluids) and kidney function in 1612 participants of the Atherosclerosis Risk in Communities (ARIC) Study. All analyses were adjusted for clinical and demographic covariates, including for baseline eGFR and UACR in longitudinal analyses. RESULTS:At visit 5 of the ARIC study, the mean age of participants was 76 years (SD 6), 56% were women, mean eGFR was 62 ml/min/1.73m2 (SD 20), and median urine albumin-to-creatinine level (UACR) was 13 mg/g (IQR 25). In cross-sectional analysis, 675 serum and 542 urine metabolites were associated with eGFR (Bonferroni-corrected p < 4.0E-5 for serum analyses and p < 3.6E-5 for urine analyses), including 248 metabolites shared across biofluids. Fewer metabolites (75 serum and 91 urine metabolites, including 7 shared across biofluids) were cross-sectionally associated with albuminuria. Guanidinosuccinate, N2,N2-dimethylguanosine, hydroxy-N6,N6,N6-trimethyllysine, X-13844, and X-25422 were significantly associated with both eGFR and albuminuria. Over a mean follow-up of 6.6 years, serum mannose (HR 2.3 [1.6,3.2], p = 2.7E-5) and urine X-12117 (HR 1.7 [1.3,2.2], p = 1.9E-5) were risk factors for UACR doubling, whereas urine sebacate (HR 0.86 [0.80,0.92], p = 1.9E-5) was inversely associated. Compared to clinical characteristics alone, including the top 5 endogenous metabolites in serum and urine associated with longitudinal outcomes improved the outcome prediction (AUCs for eGFR decline: clinical model = 0.79, clinical + metabolites model = 0.87, p = 8.1E-6; for UACR doubling: clinical model = 0.66, clinical + metabolites model = 0.73, p = 2.9E-5). CONCLUSIONS:Metabolomic profiling in different biofluids provided distinct and potentially complementary insights into the biology and prognosis of kidney diseases.

BACKGROUND:Current methods to predict height potential are inaccurate. Predicting height by using MRI of the physeal cartilage has shown promise but the applicability of this technique in different imaging setups has not been well-evaluated. PURPOSE:To assess variability in diffusion tensor imaging of the physis and metaphysis (DTI-P/M) of the distal femur between different scanners, imaging parameters, tractography software, and resolution. STUDY TYPE:Prospective. POPULATION/SUBJECTS:Eleven healthy subjects (five males and six females ages 10-16.94). FIELD STRENGTH/SEQUENCE:3 T; DTI single shot echo planar sequences. ASSESSMENT:Physeal DTI tract measurements of the distal femur were compared between different scanners, imaging parameters, tractography settings, interpolation correction, and tractography software. STATISTICAL TESTS:Bland-Altman, Spearman correlation, linear regression, and Shapiro-Wilk tests. Threshold for statistical significance was set at P = 0.05. RESULTS:) did not significantly affect DTI values (bias = 1.4 [LOA -5.7 to 8.4], P = 0.35) but maintained a strong correlation (ρ = 0.82). Gap size (0 mm vs. 0.6 mm) significantly affects tract volume (bias = 1.8 [LOA -5.4 to 1.8]) but maintains a strong correlation (ρ = 0.93). Comparison of tractography algorithms generated significant differences in tract number, length, and volume while maintaining correlation (ρ = 0.86, 0.99, 0.93, respectively). Comparison of interobserver variability between different tractography software also revealed significant differences while maintaining high correlation (ρ = 0.85-0.98). DATA CONCLUSION:DTI of the pediatric physis cartilage shows high reproducibility between different imaging and analytic parameters. EVIDENCE LEVEL:2 TECHNICAL EFFICACY: Stage 1.

OBJECTIVES/OBJECTIVE:Cardiac surgery-associated acute kidney injury (CS-AKI) is associated with adverse outcomes. Single-center studies suggest that the prevalence of CS-AKI is high after the Norwood procedure, or stage 1 palliation (S1P), but multicenter data are lacking. DESIGN/METHODS:A secondary analysis of the Neonatal and Pediatric Heart and Renal Outcomes Network (NEPHRON) multicenter cohort who underwent S1P. Using neonatal modification of Kidney Disease Improving Global Outcomes (KDIGO) criteria, perioperative associations between CS-AKI with morbidity and mortality were examined. Sensitivity analysis, with the exclusion of prophylactic peritoneal dialysis (PD) patients, was performed. SETTING/METHODS:Twenty-two hospitals participating in the Pediatric Cardiac Critical Care Consortium (PC 4 ) and contributing to NEPHRON. PATIENTS/METHODS:Three hundred forty-seven neonates (< 30 d old) with S1P managed between September 2015 and January 2018. INTERVENTIONS/METHODS:None. MEASUREMENTS AND MAIN RESULTS/RESULTS:Of 347 patients, CS-AKI occurred in 231 (67%). The maximum stages were as follows: stage 1, in 141 of 347 (41%); stage 2, in 51 of 347 (15%); and stage 3, in 39 of 347 (11%). Severe CS-AKI (stages 2 and 3) peaked on the first postoperative day. In multivariable analysis, preoperative feeding was associated with lower odds of CS-AKI (odds ratio [OR] 0.48; 95% CI, 0.27-0.86), whereas prophylactic PD was associated with greater odds of severe CS-AKI (OR 3.67 [95% CI, 1.88-7.19]). We failed to identify an association between prophylactic PD and increased creatinine (OR 1.85 [95% CI, 0.82-4.14]) but cannot exclude the possibility of a four-fold increase in odds. Hospital mortality was 5.5% ( n = 19). After adjusting for risk covariates and center effect, severe CS-AKI was associated with greater odds of hospital mortality (OR 3.67 [95% CI, 1.11-12.16]). We failed to find associations between severe CS-AKI and respiratory support or length of stay. The sensitivity analysis using PD failed to show associations between severe CS-AKI and outcome. CONCLUSIONS:KDIGO-defined CS-AKI occurred frequently and early postoperatively in this 2015-2018 multicenter PC 4 /NEPHRON cohort of neonates after S1P. We failed to identify associations between resource utilization and CS-AKI, but there was an association between severe CS-AKI and greater odds of mortality in this high-risk cohort. Improving the precision for defining clinically relevant neonatal CS-AKI remains a priority.

Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation of updated growth standards. Purpose To train an AI model using standing slot-scanning radiographs in a racially diverse data set of pediatric patients to measure lower extremity length and to compare expected growth curves derived using AI measurements to those of the conventional Anderson-Green method. Materials and Methods This retrospective study included pediatric patients aged 0-21 years who underwent at least two slot-scanning radiographs in routine clinical care between August 2015 and February 2022. A Mask Region-based Convolutional Neural Network was trained to segment the femur and tibia on radiographs and measure total leg, femoral, and tibial length; accuracy was assessed with mean absolute error. AI measurements were used to create quantile polynomial regression femoral and tibial growth curves, which were compared with the growth curves of the Anderson-Green method for coverage based on the central 90% of the estimated growth distribution. Results In total, 1874 examinations in 523 patients (mean age, 12.7 years ± 2.8 [SD]; 349 female patients) were included; 40% of patients self-identified as White and not Hispanic or Latino, and the remaining 60% self-identified as belonging to a different racial or ethnic group. The AI measurement training, validation, and internal test sets included 114, 25, and 64 examinations, respectively. The mean absolute errors of AI measurements of the femur, tibia, and lower extremity in the test data set were 0.25, 0.27, and 0.33 cm, respectively. All 1874 examinations were used to generate growth curves. AI growth curves more accurately represented lower extremity growth in an external test set (n = 154 examinations) than the Anderson-Green method (90% coverage probability: 86.7% [95% CI: 82.9, 90.5] for AI model vs 73.4% [95% CI: 68.4, 78.3] for Anderson-Green method; χ² test, P < .001). Conclusion Lower extremity growth curves derived from AI measurements on standing slot-scanning radiographs from a diverse pediatric data set enabled more accurate prediction of pediatric growth. © RSNA, 2024 Supplemental material is available for this article.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Patient and Family Centered I-PASS (PFC I-PASS) emphasizes family and nurse engagement, health literacy, and structured communication on family-centered rounds organized around the I-PASS framework (Illness severity-Patient summary-Action items-Situational awareness-Synthesis by receiver). We assessed adherence, safety, and experience after implementing PFC I-PASS using a novel "Mentor-Trio" implementation approach with multidisciplinary parent-nurse-physician teams coaching sites. METHODS:Hybrid Type II effectiveness-implementation study from 2/29/19-3/13/22 with ≥3 months of baseline and 12 months of postimplementation data collection/site across 21 US community and tertiary pediatric teaching hospitals. We conducted rounds observations and surveyed nurses, physicians, and Arabic/Chinese/English/Spanish-speaking patients/parents. RESULTS:We conducted 4557 rounds observations and received 2285 patient/family, 1240 resident, 819 nurse, and 378 attending surveys. Adherence to all I-PASS components, bedside rounding, written rounds summaries, family and nurse engagement, and plain language improved post-implementation (13.0%-60.8% absolute increase by item), all P < .05. Except for written summary, improvements sustained 12 months post-implementation. Resident-reported harms/1000-resident-days were unchanged overall but decreased in larger hospitals (116.9 to 86.3 to 72.3 pre versus early- versus late-implementation, P = .006), hospitals with greater nurse engagement on rounds (110.6 to 73.3 to 65.3, P < .001), and greater adherence to I-PASS structure (95.3 to 73.6 to 72.3, P < .05). Twelve of 12 measures of staff safety climate improved (eg, "excellent"/"very good" safety grade improved from 80.4% to 86.3% to 88.0%), all P < .05. Patient/family experience and teaching were unchanged. CONCLUSIONS:Hospitals successfully used Mentor-Trios to implement PFC I-PASS. Family/nurse engagement, safety climate, and harms improved in larger hospitals and hospitals with better nurse engagement and intervention adherence. Patient/family experience and teaching were not affected.

IMPORTANCE:Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections (LRTIs) and infant hospitalization worldwide. OBJECTIVE:To evaluate the characteristics and outcomes of RSV-related critical illness in US infants during peak 2022 RSV transmission. DESIGN, SETTING, AND PARTICIPANTS:This cross-sectional study used a public health prospective surveillance registry in 39 pediatric hospitals across 27 US states. Participants were infants admitted for 24 or more hours between October 17 and December 16, 2022, to a unit providing intensive care due to laboratory-confirmed RSV infection. EXPOSURE:Respiratory syncytial virus. MAIN OUTCOMES AND MEASURES:Data were captured on demographics, clinical characteristics, signs and symptoms, laboratory values, severity measures, and clinical outcomes, including receipt of noninvasive respiratory support, invasive mechanical ventilation, vasopressors or extracorporeal membrane oxygenation, and death. Mixed-effects multivariable log-binomial regression models were used to assess associations between intubation status and demographic factors, gestational age, and underlying conditions, including hospital as a random effect to account for between-site heterogeneity. RESULTS:The first 15 to 20 consecutive eligible infants from each site were included for a target sample size of 600. Among the 600 infants, the median (IQR) age was 2.6 (1.4-6.0) months; 361 (60.2%) were male, 169 (28.9%) were born prematurely, and 487 (81.2%) had no underlying medical conditions. Primary reasons for admission included LRTI (594 infants [99.0%]) and apnea or bradycardia (77 infants [12.8%]). Overall, 143 infants (23.8%) received invasive mechanical ventilation (median [IQR], 6.0 [4.0-10.0] days). The highest level of respiratory support for nonintubated infants was high-flow nasal cannula (243 infants [40.5%]), followed by bilevel positive airway pressure (150 infants [25.0%]) and continuous positive airway pressure (52 infants [8.7%]). Infants younger than 3 months, those born prematurely (gestational age <37 weeks), or those publicly insured were at higher risk for intubation. Four infants (0.7%) received extracorporeal membrane oxygenation, and 2 died. The median (IQR) length of hospitalization for survivors was 5 (4-10) days. CONCLUSIONS AND RELEVANCE:In this cross-sectional study, most US infants who required intensive care for RSV LRTIs were young, healthy, and born at term. These findings highlight the need for RSV preventive interventions targeting all infants to reduce the burden of severe RSV illness.

OBJECTIVES/OBJECTIVE:We aimed to critically evaluate the effectiveness of a designated ECMO team in our ECMO selection process and patient outcomes in the first 3 years of our low-volume pediatric ECMO program. METHODS:We conducted a retrospective chart review of patients who received an ECMO consultation between the start of our program in March 2015 and May 2018. We gathered clinical and demographic information on patients who did and did not receive ECMO, and described our selection process. We reflected on the processes used to initiate our program and our outcomes in the first 3 years. RESULTS:, lactate, and pH between the patients who went on ECMO and who did not. We improved our outcomes from 0% survival to discharge in 2015, to 60% in 2018, with an average of 63% survival to discharge over the first 3 years of our program. CONCLUSIONS:In a low-volume pediatric ECMO center, having a designated team to assist in the patient selection process and management can help provide safe and efficient care to these patients, and improve patient outcomes. Having a strict management protocol and simulation sessions involving all members of the medical team yields comfort for the providers and optimal care for patients. This study describes our novel structure, processes, and outcomes, which we hope will be helpful to others seeking to develop a new pediatric ECMO program.

OBJECTIVES:Extracorporeal membrane oxygenation (ECMO) has been used successfully to support adults with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related cardiac or respiratory failure refractory to conventional therapies. Comprehensive reports of children and adolescents with SARS-CoV-2-related ECMO support for conditions, including multisystem inflammatory syndrome in children (MIS-C) and acute COVID-19, are needed. DESIGN:Case series of patients from the Overcoming COVID-19 public health surveillance registry. SETTING:Sixty-three hospitals in 32 U.S. states reporting to the registry between March 15, 2020, and December 31, 2021. PATIENTS:Patients less than 21 years admitted to the ICU meeting Centers for Disease Control criteria for MIS-C or acute COVID-19. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The final cohort included 2,733 patients with MIS-C ( n = 1,530; 37 [2.4%] requiring ECMO) or acute COVID-19 ( n = 1,203; 71 [5.9%] requiring ECMO). ECMO patients in both groups were older than those without ECMO support (MIS-C median 15.4 vs 9.9 yr; acute COVID-19 median 15.3 vs 13.6 yr). The body mass index percentile was similar in the MIS-C ECMO versus no ECMO groups (89.9 vs 85.8; p = 0.22) but higher in the COVID-19 ECMO versus no ECMO groups (98.3 vs 96.5; p = 0.03). Patients on ECMO with MIS-C versus COVID-19 were supported more often with venoarterial ECMO (92% vs 41%) for primary cardiac indications (87% vs 23%), had ECMO initiated earlier (median 1 vs 5 d from hospitalization), shorter ECMO courses (median 3.9 vs 14 d), shorter hospital length of stay (median 20 vs 52 d), lower in-hospital mortality (27% vs 37%), and less major morbidity at discharge in survivors (new tracheostomy, oxygen or mechanical ventilation need or neurologic deficit; 0% vs 11%, 0% vs 20%, and 8% vs 15%, respectively). Most patients with MIS-C requiring ECMO support (87%) were admitted during the pre-Delta (variant B.1.617.2) period, while most patients with acute COVID-19 requiring ECMO support (70%) were admitted during the Delta variant period. CONCLUSIONS:ECMO support for SARS-CoV-2-related critical illness was uncommon, but type, initiation, and duration of ECMO use in MIS-C and acute COVID-19 were markedly different. Like pre-pandemic pediatric ECMO cohorts, most patients survived to hospital discharge.

INTRODUCTION/BACKGROUND:Communication, failures during patient handoffs are a significant cause of medical error. There is a paucity of data on standardized handoff tools for intershift transitions of care in pediatric emergency medicine (PEM). The purpose of this quality improvement (QI) initiative was to improve handoffs between PEM attending physicians (i.e., supervising physicians ultimately responsible for patient care) through the implementation of a modified I-PASS tool (ED I-PASS). Our aims were to: (1) increase the proportion of physicians using ED I-PASS by two-thirds and (2) decrease the proportion reporting information loss during shift change by one-third, over a 6-month period. METHODS:After literature and stakeholder review, Expected Disposition, Illness Severity, Patient Summary, Action List, Situational Awareness, Synthesis by Receiver (ED I-PASS) was implemented using iterative Plan-Do-Study-Act cycles, incorporating: trained "super-users"; print and electronic cognitive support tools; direct observation; and general and targeted feedback. Implementation occurred from September to April of 2021, during the height of the COVID-19 pandemic, when patient volumes were significantly lower than prepandemic levels. Data from observed handoffs were collected for process outcomes. Surveys regarding handoff practices were distributed before and after ED I-PASS implementation. RESULTS:82.8% of participants completed follow-up surveys, and 69.6% of PEM physicians were observed performing a handoff. Use of ED I-PASS increased from 7.1% to 87.5% ( p < .001) and the reported perceived loss of important patient information during transitions of care decreased 50%, from 75.0% to 37.5% ( p = .02). Most (76.0%) participants reported satisfaction with ED I-PASS, despite half citing a perceived increase in handoff length. 54.2% reported a concurrent increase in written handoff documentation during the intervention. CONCLUSION/CONCLUSIONS:ED I-PASS can be successfully implemented among attending physicians in the pediatric emergency department setting. Its use resulted in significant decreases in reported perceived loss of patient information during intershift handoffs.