Connecticut Children's Medical Center is a nationally ranked, independent, non-profit, pediatric acute care hospital located in Hartford, Connecticut. The hospital has 185 beds and is the primary pediatric teaching affiliate of the University of Connecticut School of Medicine and the Frank H. Netter MD School of Medicine at Quinnipiac University. The hospital provides comprehensive pediatric specialties and subspecialties to pediatric patients aged 0–21 throughout Connecticut and the New England region, but also treats some adults that would be better treated under pediatricians. Connecticut Children's Medical Center also features the only ACS verified level 1 pediatric trauma center in the region, and 1 of 2 in the state. The hospital is also 1 of 2 children's hospital in the state of Connecticut.
Recent technologic advances in neonatal dialysis have changed current dialysis practices. The goal of this study was to define demographics, diagnoses, initial dialysis modality, modality changes, and outcomes of neonates receiving dialysis. Retrospective, multicenter cohort of neonates (≤ 30 days of age) from 26 U.S. centers, who received dialysis between 6/2017 and 5/2022. Measures of central tendency were calculated to describe the cohort stratified by the primary dialysis-related diagnosis including acute kidney injury requiring dialysis (AKI-D), stage 5 chronic kidney disease (CKD 5), hyperammonemia, and other causes. The primary outcome was death during the initial hospitalization. For the 405 neonates in this cohort, AKI-D (57
Malignancy-associated hemophagocytic lymphohistiocytosis (mHLH), a hyperinflammatory syndrome, has poor prognosis and no standard therapy. Emapalumab, a fully human monoclonal antibody that neutralizes the proinflammatory cytokine interferon-gamma, is approved for treating primary hemophagocytic lymphohistiocytosis (pHLH). REAL-HLH, a retrospective chart review conducted across 33 US hospitals, evaluated real-world treatment patterns and outcomes in patients treated with at least 1 dose of emapalumab between November 20, 2018, and October 31, 2021. Data are presented for the subset of patients with mHLH. Overall, 51/105 (48.6%) patients did not meet the pHLH classification criteria and were categorized as presenting with secondary HLH; 17/51 patients had underlying malignancy (mHLH). At HLH diagnosis, median age (range) was 15.0 (3.0-27.0) years, 6/14 (42.9%) patients with available data had a positive Optimized HLH Inflammatory index indicating pathologic inflammation; 9/17 (52.9%) had infections, and 10/17 (58.8%) received emapalumab in an intensive care unit. Emapalumab was primarily initiated for treating refractory (10/17; 58.8%) or progressive (3/17, 17.7%) disease. Most patients received HLH-related therapies before (16/17; 94.1%) and/or concurrent with (15/17; 88.2%) emapalumab. Most key laboratory parameters improved, and some (fibrinogen [11/13; 84.6%], absolute neutrophil count [6/10; 60%], and CXCL9 [7/8; 87.5%]), normalized or stabilized per physician assessment, following treatment with emapalumab-containing regimens. Overall survival at the end of follow-up and 12-month survival probability from emapalumab initiation were 23.5% and 22.1%, respectively. In conclusion, emapalumab-containing regimens improved or normalized most laboratory parameters in patients with mHLH. Future studies are warranted to establish appropriate emapalumab dosing and utility in this high-risk population.
This study aimed to summarize contemporary evidence on the definition, epidemiology, risk factors, and prevention of acute kidney injury (AKI) in critically ill and preterm infants in the neonatal intensive care unit (NICU), and to highlight prevention-focused strategies to improve outcomes. Narrative review of current literature evaluating AKI burden, diagnostic criteria, modifiable and nonmodifiable risk factors, and preventive interventions in neonatal intensive care settings. AKI is common in critically ill and preterm infants and is associated with increased mortality, prolonged hospitalization, neurodevelopmental impairment, and progression to chronic kidney disease. Modified Kidney Disease: Improving Global Outcomes criteria have improved diagnostic consistency and revealed particularly high AKI prevalence in extremely low birth weight infants. Key modifiable risk factors include hemodynamic instability, patent ductus arteriosus, nephrotoxic drug exposure, fluid overload, and sepsis, while preventive strategies span optimized antenatal management, therapeutic hypothermia for hypoxic ischemic encephalopathy, careful postnatal hemodynamic and fluid management, nephrotoxic drug stewardship, early infection control, individualized ductus arteriosus therapy, and potential use of caffeine, alongside emerging urinary biomarkers for earlier detection. Given limited therapeutic options once AKI occurs, prevention through structured surveillance, timely identification of high-risk states, and rigorous implementation of kidney protective practices is essential. Integrating quality improvement, protocolized care pathways, and educational outreach within NICUs offers the greatest promise for improving short and long-term outcomes in infants with AKI.
Objective: Smartwatches with photoplethysmographic (PPG) sensors are ideal for early atrial fibrillation (AF) detection through continuous monitoring. However, prior deep learning was limited either to controlled environments, to minimize motion artifacts, or to short duration data collection. Additionally, premature atrial/ventricular contractions (PAC/PVC), which often confound AF detection algorithms, remains understudied due to limited datasets. Current state-of-the-art methods achieve only 75% sensitivity for PAC/PVC class on minimally motion artifact corrupted PPG data, despite showing 97% AF detection accuracy. Methods: We addressed the above limitations using data from the recently completed NIH-funded Pulsewatch clinical trial which collected over two weeks of smartwatch PPG data from 106 subjects. Our computationally efficient 1D bi-directional Gated Recurrent Unit deep learning model incorporated multi-modal inputs (1D PPG, accelerometer, and heart rate data) to classify normal sinus rhythm, AF, and PAC/PVC. Results: Our model achieved an unprecedented 83% sensitivity for PAC/PVC detection while maintaining a high accuracy of 97.31% for AF detection, outperforming the best retrained state-of-the-art model by 20.81% and 2.55%, respectively. It was also 14 times more computationally efficient and 2.7 times faster. Testing on two external PPG datasets collected with a different smartwatch and a fingertip PPG sensor, our model demonstrated better generalizability with macro-averaged AUROC values of 96.22% and 94.17%, respectively. Conclusion: A light-weight multimodal input deep learning model can accurately distinguish PAC/PVC from AF, reducing false positive detection of AF. Significance: Accurate AF and PAC/PVC detection with minimal false positive detection can enhance clinical and public acceptance of smartwatch-based AF monitoring.
Prevailing evidence underscores the critical influence of infant gut microbiota on systemic immune responses and intestinal health. The role of functional programming of effector immune cells at extra-intestinal mucosal sites is increasing in interest. Common connections between development of gut and lung microbiomes and reciprocal signaling between the two organ systems has reinforced the concept of a "gut-lung axis." Narrative review of existing literature evaluating mechanistic evidence linking microbial dysbiosis and necrotizing enterocolitis (NEC) to development of preterm acute lung injury and subsequent progression to chronic lung disease or bronchopulmonary dysplasia (BPD). Evidence across animal and human studies indicates that gut-derived microbial ligands and metabolites are foundational in programming respiratory immunity. Conversely, primary pulmonary insults appear to trigger reciprocal shifts in gut microbiome function. This bidirectional signaling likely drives the clinical association between NEC-associated systemic inflammation and the subsequent increased risk of BPD. By focusing on mediators involved in this gut-lung crosstalk, we seek to highlight avenues such as microbiome modulation or targeted anti-inflammatory signaling to prevent or reduce the severity of two of the major morbidities of prematurity. · Gut dysbiosis drives systemic inflammation and mediates pro-inflammatory responses in the lungs.. · The communication between gut and lungs is mediated by microbiome, metabolites and immune cells.. · Modulating the gut microbiome presents a promising strategy for prevention of BPD in preterm infants.
