Pediatric Research

Background: Infants with critical congenital heart disease (CHD) are at high risk for abnormal brain development and later neurodevelopmental impairment. We hypothesized that the trajectory of perioperative whole-brain network development would predict neurodevelopmental outcomes in early childhood. Methods: This prospective longitudinal cohort of neonates with critical CHD (n = 97) underwent preoperative and/or postoperative brain MRI with diffusion imaging. Whole-brain network measures were derived from structural connectomes. Neurodevelopment was assessed between 1 and 4 years using the Bayley Scales of Infant and Toddler Development. Results: White matter injury was associated with slower perioperative growth in global efficiency (p = 0.013), a measure of network integration, whereas cardiac physiology was not associated with network development. Infants with greater perioperative increases in global efficiency had higher cognitive (p = 0.001), language (p < 0.001), and motor (p = 0.008) scores. For each 1-standard deviation increase in the trajectory of global efficiency, cognitive scores increased by 8.2 points (95% CI, 3.64-12.78), independent of brain injury and socioeconomic factors. Conclusion: In infants with critical CHD, longitudinal whole-brain network development was associated with neurodevelopment across multiple domains. Early network development may represent a candidate biomarker of neurodevelopmental risk and resilience in this population.

Background: 48,XXYY syndrome is a rare sex chromosome aneuploidy (SCA) characterized by neurodevelopmental deficits and medical comorbidities. The limited information available in the literature is almost exclusively limited to postnatally diagnosed cases. This study aims to describe the early medical and developmental features of prenatally identified 48,XXYY infants, with comparisons to 47,XYY, 47,XXY cohorts, and typical populations, as well as previously reported postnatally diagnosed 48,XXYY cases. Methods: The eXtraordinarY Babies Study prospectively follows children prenatally identified to be at high risk for SCA with annual medical and neurodevelopmental evaluations. Data presented herein include the prevalence of medical conditions, developmental milestones, developmental and adaptive functioning assessment scores, and therapy utilization in participants confirmed to have 48,XXYY. Comparisons were made between this cohort and the typical population, infants with 47,XYY and 47,XXY also enrolled in the eXtraordinarY Babies Study, and a 2008 cohort of individuals postnatally identified 48,XXYY. Results: Infants with 48,XXYY exhibited a range of early medical features, including high rates of feeding and GI disorders (breastfeeding difficulties, gastroesophageal reflux, and eosinophilic esophagitis), allergic disorders (food allergies and environmental allergies), and hypotonia. Developmental and adaptive functioning scores indicated delays in motor, communication, and social domains, with nearly all infants receiving speech therapy, physical and/or occupational therapy. Comparisons with the 47,XYY and 47,XXY cohorts revealed more medical and developmental challenges in the 48,XXYY group, however there was variability and some overlap with both the general population and sex chromosome trisomy conditions. Additionally, comparison to the 2008 postnatally identified 48,XXYY cohort indicated that while prenatal diagnosis allowed for earlier intervention, developmental outcomes in the first years of life were similar between the two groups. Conclusions: 48,XXYY diagnosed prenatally facilitates early monitoring, anticipatory guidance, and proactive referrals for medical evaluations and intervention, given developmental delays and medical challenges are more common in infancy and early childhood compared to the general population and trisomy SCAs. These findings provide valuable insights for genetic counselors and healthcare providers, emphasizing the spectrum of medical and developmental findings and importance of early and proactive care to support individual outcomes. Prospective study of this prenatally identified cohort will provide important natural history and phenotypic variability in XXYY, as well as identification of predictors of health and developmental outcomes.

Background Sierra Leones neonatal mortality rate is among the highest in the world. Koidu Government Hospital opened a Special Care Baby Unit (SCBU) in 2020. To increase knowledge of the SCBU health care providers (HCPs), a neonatal curriculum was implemented to facilitate HCP education on management of neonatal conditions. The aim of this study was to understand the effect of the curriculum on knowledge acquisition and the perception of the teaching methodologies among participating HCPs. Methods US-based mentors facilitated a two-phase, flipped classroom, virtual neonatal medicine curriculum between October 2024 and April 2025, followed by one-week in-person education sessions with SCBU HCPs. With each phase, participants completed pre- and post-test educational assessments. At the end of the curriculum, they completed a subjective assessment to capture perceptions related to the quality of teaching methodologies integrated within the curriculum. Wilcoxon signed rank test was used to assess pre- versus post-test change. Descriptive statistics were used to analyse the subjective assessment. Results Thirty-eight participants completed the educational assessments, 30 (79%) took all four pre- and post-tests; 25/38 (65.8%) were female, 27 (71.1%) were nurses. Median correct answers for both phases increased from the pre- to post-test for individual learners [Phase 1, pre-test 14/27 (51.9%), post-test 23/27 (85.2%), p<0.001], [Phase 2, pre-test 14/25 (56.0%), post-test 23/25 (92.0%), p <0.001]. Thirty-one participants completed the subjective assessment, of whom 96.8% (30/31) rated the curriculum to be "very effective." All 31 participants indicated that the in-person instruction was "very helpful." Through open text responses, they offered valuable insight into challenges, strengths, and next steps. Conclusion This neonatal curriculum resulted in significantly increased knowledge and was well regarded. Adapting this curriculum or similar curricula show promise to improve the quality of care for small and/or sick neonates in low resource settings.

Background. Capillary refill time is a resuscitation target in septic shock,1-4 but bedside measurement is examiner-dependent. An ICU monitor co-records a photoplethysmogram on the pulse oximeter and intermittent noninvasive blood pressure cuff cycles; if the probe and the cuff share a limb, each cycle is an unplanned vascular occlusion test on the distal microvascular bed. Standard practice places the two on opposite limbs. Objective. To measure how often, in MIMIC-IV-WDB v0.1.0, charted cuff cycles show the photoplethysmographic morphology expected of a same-limb cuff and probe, and to characterize the candidate capillary refill-like signal when that morphology is present. Methods. MIMIC-IV-WDB v0.1.05 was linked to the MIMIC-IV clinical database.6 A pre-registered rule-based detector identified candidate occlusion-reperfusion signatures on the 1-Hz perfusion-index envelope around each charted cuff timestamp. The primary endpoint was the proportion of cuff cycles suitable for analysis that were detector-positive at a 15-second reperfusion threshold, with 95% confidence intervals estimated by resampling patients at a fixed seed. A secondary analysis used a locally hosted multimodal language model (a Gemma-3 derivative on a non-device server) to adjudicate the same signature on perfusion-index plots; no MIMIC-IV-WDB content left the workstation. Results. Of 9,224 charted cuff cycles, 8,909 had a usable pulse-oximeter waveform, and 268 cycles in 15 patients (4.30% of the 6,236 cuff cycles suitable for analysis, 95% CI 2.60 to 6.03) met the primary 15-second threshold. The language model adjudicated the same cycles and called 1,367 of the 8,909 cycles with a usable waveform (15.34%) signature-present, roughly five times the detectors count. Because no laterality ground truth exists, agreement with a single blinded reader served as the comparator rather than accuracy. The two methods were about equally concordant with the reader: precision was 0.25 (95% CI 0.14 to 0.39) for the detector and 0.24 (95% CI 0.10 to 0.35) for the language model, although reweighting to the full population of cycles with a usable waveform lowered the language model to 0.030 (95% CI 0.009 to 0.053). These estimates are reference-limited: a blinded re-read of a 150-card subsample showed only moderate intra-rater reliability (Cohen {kappa} 0.46 to 0.59) with systematic undercalling on the first pass, and rescoring against the corrected re-read roughly doubled precision for both methods. Conclusions. Opportunistic extraction of capillary refill-like signals from archived ICU pulse oximetry is limited in two distinct ways. First, sensor geometry limits how often the signal is recordable: cuff cycles rarely show the morphology expected of a same-limb cuff and probe pair, consistent with opposite-limb placement, so the bottleneck is geometry rather than signal processing. Second, the modest reliability of morphology adjudication limits how well any single flagged cycle can be confirmed: against a blinded reader the detector is a usable screen but a noisy confirmer, the reference is itself only moderately reliable, and the language model is no more concordant despite flagging many more cycles. The minority of cycles in which the morphology appears contain a candidate signal that may merit prospective study under controlled placement with laterality recorded.

Background. Tethered cord syndrome (TCS) is classically associated with a low-lying conus medullaris, yet many surgically treated children have a normally positioned conus (occult TCS). Large-scale normative data on conus position in children, and the diagnostic value of quantitative conus assessment, are limited. Purpose. To establish a large-cohort reference distribution for conus medullaris termination level in children, to quantify conus position in children surgically treated for presumed (occult) TCS, and to test whether automated conus segmentation and radiomics can distinguish TCS from normal. Materials and Methods. In this retrospective single-center study, conus termination level was extracted from structured radiology reports of consecutive pediatric lumbosacral MRI examinations and encoded numerically (L1 = 1, L2 = 2, etc.). Children surgically treated for tethered cord were identified by linkage to an operative registry (name and date of birth) and restricted to preoperative examinations. A deep-learning model (nnU-Net) was trained for conus segmentation on axial T2-weighted images. IBSI-compliant radiomic features were extracted; reproducibility was assessed by intra- and inter-observer intraclass correlation (ICC). A case-control radiomics analysis used batch-only ComBat harmonization and cross-validated L1-penalized logistic regression; discrimination was compared with conus level by paired bootstrap. Results. Among 9,808 examinations with a parseable conus level (98.5% of reports; parser validated against dual blinded annotation, 99.4% agreement, weighted kappa 0.946), the conus terminated in the L1 region in 85.7% and the L2 region in 14.3% of the reference cohort (postoperative examinations excluded, n = 9,655); a low-lying conus (>=L3) occurred in only 0.05% (5/9,655), and remained rare (0.14%, 14/9,808) including operated examinations (median L1; mean 1.13 +/- 0.33). A slightly more cephalad position was seen with increasing age (negligible correlation). Among 475 preoperative children surgically treated for tethered cord, 99.6% had a normally positioned conus (<=L2) and only 0.4% were low-lying. Automated conus segmentation achieved a held-out Dice of 0.85. Conus radiomics likewise did not distinguish TCS from controls (equivalence-tested null; full segmentation/radiomics pipeline reported in the companion methodological paper). Conclusion. In children, the conus medullaris terminates at L1-L2 in more than 99% of cases and is normally positioned in virtually all children surgically treated for TCS. Within the conus, neither position nor texture (radiomics) identifies tethered cord; whether the filum terminale carries a diagnostic signal was not tested here.

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.

Background Children in low- and middle-income countries (LMICs) face an elevated risk of developmental delay, yet scalable neuroimaging tools to study early brain development in these contexts remain limited. Children who are HIV-exposed but uninfected (CHEU) represent a growing population with evidence of language and motor delays and altered brain development compared with children who are HIV-unexposed (CHU). Ultra-low-field (ULF) MRI offers a more affordable alternative to conventional high-field (HF) MRI, but its application in early childhood remains underexplored. Methods We compared brain volumes derived from ULF (64mT) and HF (3T) MRI in South African CHEU and CHU as part of the DolPHIN-2 PLUS study. Volumetric segmentation was performed using FreeSurfer v7.4.1 and SynthSeg on the Flywheel platform. Agreement between modalities was assessed using Pearsons and Lins concordance correlation coefficients across global and subcortical regions. Associations between ULF-derived brain volumes and developmental outcomes, measured by the Bayley Scales of Infant Development, Third Edition, were evaluated using partial correlations adjusted for sex and age. Results Forty-five children (9 CHEU, 36 CHU; mean age 45.6 months) had paired ULF and HF scans of usable quality. Strong correlations were observed between ULF and HF volumes for global white and grey matter regions (r > 0.92) and larger subcortical grey matter structures such as the thalamus, caudate, and putamen (r = 0.86-0.89). Moderate-to-weak correlations were evident in smaller structures (hippocampus, pallidum, amygdala). ULF underestimated most grey matter volumes, and overestimated total white matter volume relative to HF. ULF-derived global and subcortical volumes were associated with receptive and expressive communication (r = 0.34-0.59, all p < 0.05). Conclusions ULF MRI produces brain volume estimates comparable to HF MRI and captures meaningful associations with early language development. These findings support ULF MRI as a feasible and scalable tool for studying neurodevelopment in vulnerable paediatric populations in LMICs.

Background: Epic Cosmos is a relatively new centralized electronic health record dataset with high potential utility in perinatal epidemiologic research. Objectives: The study objectives were to develop replicable steps to create longitudinal, linked maternal-infant cohorts in Cosmos, assess completeness of key variables, evaluate potential selection bias with restrictions for longitudinal healthcare encounters, and provide an example epidemiologic analysis. Methods: We created maternal-infant cohorts by starting with live births during 2023-2024 recorded in the BirthFact data table and joining with additional data tables as needed. We selected and created variables for perinatal characteristics, common comorbidities, and routinely measured vital signs and laboratory values, and assessed variable completeness. We sequentially restricted the birth cohort for maternal-infant linkage and longitudinal healthcare from first-trimester prenatal care encounter through infant follow-up care within 12 weeks post-discharge from birth hospitalization. Finally, we conducted an example analysis of the association between high systolic blood pressure in the first trimester ([&ge;]140 mm Hg) and later onset of preeclampsia among those with chronic hypertension. Results: The total linked birth cohort included 2,624,186 pregnancies. Completeness was >90% for most variables assessed but was 77% for racial and ethnic group and 76% for body mass index at delivery. Characteristics of the cohort were similar to those reported for the entire United States birth population based on birth certificate data, including similar regional and racial-ethnic composition. Longitudinal cohort restriction requiring linked records from first trimester prenatal care through infant follow-up care reduced the cohort size to 509,148 pregnancies. However, restriction had minimal effects on cohort characteristics. In the example analysis, high systolic blood pressure was associated with increased risk of preeclampsia among those with chronic hypertension (aRR: 1.26; 95% CI: 1.22, 1.30). Conclusions: This study provides a rigorous and reproducible approach to creating longitudinal, linked maternal-infant cohorts in Epic Cosmos and the analytical findings suggest high data quality and representativeness.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

Background Pediatric immunizations for Respiratory Syncytial Virus (RSV), including monoclonal antibodies for infants and vaccines for pregnant people, have become broadly available and can prevent severe RSV outcomes in infants. However, quantifying the impact of RSV immunization in prevention of severe pediatric illness at the population-level is limited by lack of RSV case surveillance data. The Massachusetts Department of Public Health (DPH) conducted a modeling analysis using routine public health surveillance data to estimate the state-level impact of new RSV immunization products on Emergency Department (ED) visits and hospitalizations in Massachusetts for highest risk pediatric groups. Methods A scenario projection tool, called R.Scenario.Vax, was utilized to simulate RSV-associated ED hospital encounters by age group in the context of newly available immunizations. ED visit and hospitalization data from the National Syndromic Surveillance Program (NSSP) during the time period 10/08/2017--10/19/2024 were analyzed, scaled to account for changes in RSV testing practices over time and missing encounter volume in historic data, and utilized to inform model fit of a "typical" RSV season. RSV immunization data from the Massachusetts Immunization Information System (MIIS) for the 2023--2024 and 2024--2025 RSV seasons informed high and moderate pediatric RSV immunization coverage scenarios and their impact was compared to a counterfactual reference scenario of no new immunizations. Median projections were quantitatively and qualitatively compared to observed 2024--2025 season data. Percent reduction in hospital encounters and encounters averted per 10,000 population were calculated for each scenario as compared to the reference. Results Projections for the youngest at-risk age groups showed significantly lower RSV-associated ED visits and hospitalizations during the 2024--2025 season for both high and moderate immunization coverage scenarios. Median projections for infants under 6 months old in the highest coverage scenario, wherein nearly all infants were immunized, showed 72.6% lower ED visits and 73.4% lower hospitalizations when compared to the reference scenario, equating to 262 ED visits and 85 hospitalizations averted per 10,000 population. Conclusions Our results support the use of modeling methods for public health insights and suggest that RSV immunizations for infant populations result in significantly lower RSV-related ED encounters in Massachusetts.

While microbiome is increasingly recognized as crucial for human health, translating this knowledge into effective healthcare and preventive strategies remains challenging. Many studies focus on identifying changes in microbiome composition associated with disease and evaluating the potential of such disease-associated microbial profiles as biomarkers for disease diagnosis. Under the hypothesis that microbiome dysbiosis may reflect physiological alterations present long before disease onset, in this work, we analyse the potential of disease-specific microbial signatures not as a diagnostic tool when the disease is already present, but as a means of health assessment in the general population. Moreover, instead of trying to define a single health measure, we believe it is necessary to consider several ways in which the microbiome departs from health, according to different disease-related physiological changes. To evaluate our assumptions, we designed a two-stage study: the identification of disease-specific microbial signatures (discovery stage) and, subsequently, the study of their distribution in the general population to assess associations with general health (external validation stage). Specifically, in the discovery phase we characterized 16 disease-specific bacterial signatures from large public microbiome data using a compositional data analysis methodology. In the second phase, we quantified these microbial signatures in the Lifelines-DMP cohort, a large population-based cohort, and evaluated their association with self-reported health status. Results indicate that most disease-specific microbial signatures associate with health status, supporting our assumption that microbial composition can capture physiological alterations before disease onset, and highlighting the importance of considering multiple ways in which microbiome departs from a healthy state. These findings reaffirm the potential of microbial information as an additional tool in preventive medicine.

Background. Tobacco smoke exposure, quantified by serum cotinine, is associated with cardiovascular, metabolic, and sleep-related health risks. The relationship between biomarker-verified tobacco smoke exposure and objectively measured, free-living wrist-worn ambient light patterns has not been examined in a nationally representative U.S. adult sample. Methods. We analyzed NHANES 2011-2014 cross-sectional data from 6,937 adults aged >20 years with valid serum cotinine and wrist-worn Physical Activity Monitor (PAM) ambient light data. Seven light outcomes were modeled using survey-weighted linear regression with log2(cotinine+1) as the continuous exposure across four covariate adjustment levels. Benjamini-Hochberg false discovery rate (FDR) correction was applied across the 7 outcomes within each model. Results. In Model 2 (adjusted for age, sex, race/ethnicity, education, poverty-income ratio, BMI, and survey cycle; N = 6,350), higher serum cotinine was associated with significantly higher nighttime light (beta = +0.024, 95% CI: 0.010, 0.038; p-FDR = 0.014) and lower evening light (beta = -0.031, 95% CI: -0.055, -0.008; p-FDR = 0.042). In exploratory behavioral models without alcohol (Model 3a; N = 5,766), both nighttime and evening associations remained FDR-significant. After additional adjustment for alcohol, which substantially reduced the sample due to 37.6% missingness (Model 3b; N = 3,866), the nighttime association attenuated below the FDR threshold, while the evening association remained FDR-significant. Categorical analyses showed progressively higher nighttime light across cotinine groups, and a hypothesis-generating sex interaction was identified (p-interaction = 0.001). Conclusions. Higher serum cotinine concentrations were associated with higher nighttime and lower evening ambient light after sociodemographic adjustment. Attenuation after behavioral adjustment and the cross-sectional design preclude causal inference. Longitudinal studies with formal mediation analyses are needed to clarify the temporal ordering and mechanisms linking tobacco smoke exposure, smoking-related behaviors, and personal light-dark cycle patterns.

Background: Pregnancy loss has important implications for womens health. Although maternal age is a well-established risk factor, the contribution of routinely measured cardiometabolic and behavioral markers at population-scale remains incompletely characterized. Objective: To examine associations between cardiometabolic, nutritional, and behavioral risk markers and pregnancy loss among U.S. women of reproductive age. Methods: We conducted a cross-sectional analysis of 4,842 U.S. women aged 20-44 years with [&ge;]1 pregnancy using the National Health and Nutrition Examination Survey data (2013-2023). Pregnancy loss was defined as [&ge;]1 prior miscarriages. Exposures included body mass index, smoking exposure (cotinine), lipid biomarkers, vitamin D and folate, and a composite cardiometabolic-nutritional risk score. Survey-weighted logistic regression estimated adjusted odds ratios (aORs) and 95% confidence intervals, with bootstrap resampling for predictor robustness. Results: The weighted prevalence of pregnancy loss was 23%. Higher odds of pregnancy loss were associated with increasing age (aOR per year=1.02; 95% CI: 1.00-1.04), Non-Hispanic Black race (aOR=1.32; 95% CI: 1.00-1.74), overweight (aOR=1.56; 95% CI: 1.16-2.11), obesity (aOR=2.06; 95% CI: 1.39-3.05), and smoking (aOR=1.58; 95% CI: 1.19-2.10). Adverse lipid profiles, particularly elevated triglycerides (aOR=1.83; 95% CI: 1.16-2.90) and high low-density lipoprotein (aOR=2.97; 95% CI: 1.45-6.61), were independently associated with pregnancy loss. Vitamin D/folate were not stable predictors. Higher composite cardiometabolic-nutritional risk scores were observed among women with pregnancy loss (P=0.026). Conclusion: Pregnancy loss clustered with adverse cardiometabolic and behavioral risk markers in a nationally representative population. These findings highlight pregnancy loss as a marker of broader metabolic vulnerability supporting the need for longitudinal studies and cardiometabolic profiling to inform preconception care and risk stratification.

High-frequency physiological monitoring in ICUs can identify impending deterioration hours before clinical recognition yet extracting reliable early-warning signals from noisy vital-sign streams remains challenging. We present SIgnose, an interpretable prediction framework for early detection of abnormal shock index (SI), built from routinely monitored vital signs using physiologic variability and nonlinear time-series features. SIgnose was developed on the eICU Collaborative Research Database and externally validated on the MIMIC-III adult database and a pediatric SafeICU cohort (AIIMS New Delhi), with additional prospective validation in the pediatric ICU. We benchmarked three representation strategies: (i) engineered physiologic variability and nonlinear time-series features, (ii) deep learning, and (iii) Llama-3.1-8B embeddings with low-rank adaptation. Physiologic variability features consistently demonstrated superior cross-cohort generalization. The final model used 3,970 features from five vital signs to predict abnormal SI up to 8 hours ahead, achieving AUROC 0.861 (95% CI 0.859-0.863) and AUPRC 0.927 (95% CI 0.925-0.929) on eICU. External validation yielded AUROC 0.870 (95% CI 0.863-0.876) and AUPRC 0.935 (95% CI 0.930-0.940) on MIMIC-III, and AUROC 0.875 (95% CI 0.863-0.888) and AUPRC 0.915 (95% CI 0.898-0.930) on SafeICU; prospective pediatric validation (n = 88) achieved AUROC 0.885 (95% CI 0.868-0.902) and AUPRC 0.911 (95% CI 0.882-0.936). SHAP interpretability analysis identified heart rate variability, respiratory trend dynamics, and multi-scale blood pressure variability as key early-warning signatures. These findings establish SIgnose as a reproducible, low-compute, early-warning framework and demonstrate that physiologic variability features provide robust, generalizable representations for early deterioration detection across adult and pediatric critical care.

Introduction: To investigate the epidemiological characteristics of chronic kidney diseases (CKD) in China in 2021 and its trends between 1990 and 2021, in the context of significant population growth and lifestyle changes over the past 30 years that have likely influenced the CKD spectrum. Methods: Data on CKD prevalence, mortality, disability-adjusted life-years (DALY), and risk factors were obtained from the Global Burden of Disease Study 2021. The estimated decadal percentage changes were calculated to evaluate changes in trends in prevalence, mortality and disease burden. Results: In 2021, an estimated 118.4 (95% UI 109.4 to 127.5) million people in China were affected by CKD, contributing to 204 230 (95% UI 164 736 to 246 372) deaths and 6.13 (95% UI 5.18 to 7.21) million DALY. Although CKD due to diabetes mellitus and hypertension accounted for less than a quarter of all cases, they were responsible for over 90% of CKD-related deaths. Over the past three decades, CKD mortality and DALY rates have steadily increased, although the prevalence has stabilized in the last decade. Diabetes mellitus type 2 and hypertension have emerged as key drivers of CKD burden in China. Conclusions: The CKD burden in China shows a dual pattern of rising incidence and high mortality from diabetes and hypertension-related chronic kidney disease, alongside persistently high years lived with disability from glomerulonephritis and other causes.

The human small intestine (SI) plays a central role in nutrient processing, host-microbe interactions, and immune regulation, yet remains poorly characterized due to the lack of minimally disruptive sampling methods. Here, we present a protocol for deploying, recovering, and analyzing samples collected using an ingestible device that enables multi-region, lumen-targeted SI sampling during normal digestion. The device incorporates a ~30-cm collapsible tube wound into pH- or time-responsive layers that sequentially unfurl in situ, typically capturing three spatially ordered samples with high yield and reliable retrieval. This protocol outlines study design, participant handling, device recovery, contamination control, and standardized workflows for analyses, including cell quantification, culturomics, sequencing, and metabolomics. We further describe benchmarking approaches for evaluating spatial resolution and strategies for assay prioritization when sample volume is limiting. By reducing participant burden and facilitating integration with stool, saliva, and clinical metadata, this approach enables longitudinal and large-cohort studies linking SI microbial ecology and host physiology to human health.

To understand the utility of healthcare facility-level wastewater surveillance (WWS) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to correlate wastewater SARS-CoV-2 RNA detection with the number of clinical infections. WWS for SARS-CoV-2 was performed at three skilled nursing facilities (SNFs) over 25 weeks. Electronegative membrane filtration (enMF) and Nanotrap(R) Magnetic Virus Particles (NP) virus concentration methods were compared. Extracts were tested by droplet digital polymerase chain reaction. Spearman's correlations ({rho}) between wastewater virus RNA concentrations and infection counts were calculated. From split wastewater samples, enMF recovered higher SARS-CoV-2 RNA concentrations than NP. Combining data from all facilities, the median concentrations were 53.0 versus 38.6 gc/100 mL for enMF and NP, respectively (p=0.001). Using enMF, correlations were moderate to strong at SNF A ({rho} ranged 0.67 to 0.86, all p-values <0.001). Weak to moderate correlations can be explained by the sampled manhole not representing the entire facility (SNF B, {rho} ranged 0.47 to 0.72, p-values ranged <0.001 to 0.12) and longitudinal data gaps from summer heat and equipment maintenance (SNF C, {rho} ranged 0.14 to 0.59, p-values ranged 0.52 to <0.01). WWS can be a valuable tool for tracking dynamics of SARS-CoV-2 infections in healthcare facilities.

Objective To verify the reliability of a self developed bowel sound monitoring device under real biological tissue acoustic propagation conditions using a controllable sound source, and to establish quantitative evidence for its translational applicability. Methods Freshly euthanized six month old Bama miniature pigs were used as an experimental model. A high fidelity Bluetooth audio playback device was implanted into the abdominal cavity to deliver manually annotated bowel sound recordings as controllable acoustic stimuli. A self developed bowel sound monitoring device was fixed on the abdominal surface for continuous signal acquisition. Playback timestamps were defined as the ground truth, and event level matching was performed within a predefined temporal tolerance window. Four performance indicators were evaluated: (1) bowel sound acquisition and energy amplification, (2) event matching accuracy, (3) acoustic feature consistency, and (4) subjective agreement assessed by blinded auscultation from gastroenterologists with different levels of clinical experience. Results The monitoring device exhibited stable detection capability and effectively covered the full spectral range of the original signals. It significantly enhanced bowel sound energy while preserving temporal and spectral characteristics, demonstrating high consistency in time and frequency domain features. Blinded clinician assessments showed a subjective agreement rate of 88.9% between original and surface recorded bowel sound events. Conclusions Under real tissue acoustic propagation conditions, the self-developed bowel sound monitoring device reliably captures bowel sound events with high temporal accuracy, acoustic fidelity, and clinical perceptual consistency. This controllable sound source based validation provides robust technical evidence for subsequent in vivo studies and clinical translation, supporting the development of objective and continuous gastrointestinal function monitoring.

Childhood diarrheal disease remains a leading cause of morbidity and mortality among children under five years in sub-Saharan Africa, particularly in settings affected by inadequate sanitation, climate variability, malnutrition, and limited healthcare access. Conventional forecasting approaches are often constrained by sparse surveillance data, weak spatial representation, and limited incorporation of mechanistic disease dynamics. This study presents a Physics-Informed Multimodal Artificial Intelligence Digital Twin framework that integrates Physics-Informed Neural Networks, Graph Neural Networks, diffusion-reaction epidemiological modeling, multimodal fusion learning, and Digital Twin simulation to estimate and predict childhood diarrheal disease burden in Kenya, Somaliland, and Zimbabwe. Using public epidemiological, environmental, climate, sanitation, and synthetic proof-of-concept datasets, the framework modeled temporal disease dynamics, spatial transmission, pathogen-attributed burden, and outbreak trajectories while enforcing epidemiological consistency through physics-informed optimization. Results demonstrated robust forecasting performance, enhanced spatial transmission modeling, uncertainty-aware predictions, and realistic outbreak simulations across the three countries. Rotavirus, Shigella, and Cryptosporidium were identified as major contributors to modeled mortality burden, while unsafe water exposure, poor sanitation, malnutrition, and climate-sensitive transmission substantially increased disease risk. Compared with a Bayesian baseline model, the multimodal framework achieved superior nonlinear risk characterization, geospatial learning, and temporal prediction. These findings highlight the potential of scientific machine learning and digital twin systems for infectious disease surveillance, outbreak forecasting, climate-health analytics, and evidence-based public health decision-making in low-resource African settings. Keywords: Physics-Informed Neural Networks, Graph Neural Networks, Digital Twin, Childhood Diarrheal Disease, Epidemiology, Kenya, Somaliland, Zimbabwe, Scientific Machine Learning, Spatial Epidemiology, Multimodal Fusion

Introduction: Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality, and low-dose aspirin (LDA) prophylaxis is the cornerstone of evidence-based prevention. Despite guideline recommendations, LDA adherence remains poor, with 10-25% of moderate-risk patients taking aspirin. Objective personalized risk stratification using biomarkers has been shown to motivate behavior change in other disease contexts. Survey data suggest that patients are more motivated to take aspirin if informed by an objective predictive test. Here, we report real-world LDA adherence among patients who received a high-risk result from a cell-free RNA (cfRNA) PE risk prediction test. Methods: This retrospective, observational survey study included asymptomatic patients of advanced maternal age (AMA; [&ge;] 35 years at delivery) with singleton pregnancies without USPSTF-defined preexisting high-risk conditions for PE who received the cfRNA PE risk prediction test. Patients who opted in to receive text message surveys were asked about LDA use following receipt of test results. High adherence was defined as reporting LDA use on at least 6 of 7 days per week at least 85% of the time surveyed. The primary analysis included patients with a high-risk test result and at least one LDA frequency survey response following receipt of test result. The observed proportion of adherent patients was compared to a baseline estimate of 25% using an exact binomial test. Results: Of 166 patients who received a cfRNA PE risk prediction test result, 48 (28.9%) received a high-risk result. Of these, 29 (60%) opted in and responded to at least one survey, constituting the primary analysis population. Twenty-seven of the 29 (93.1%; 95% CI: 78.0-98.1%) were classified as highly adherent, significantly higher than the 25% baseline adherence estimate for moderate-risk patients (p < 0.0001). Conclusion: Among surveyed patients who received a high-risk cfRNA PE test result, the proportion classified as highly adherent to LDA (93%) substantially exceeded published estimates of adherence in a similar patient population and met the clinically meaningful threshold of [&ge;] 80% associated with reduced risk of preterm preeclampsia. These findings indicate that objective and personalized biomarker risk testing may be a powerful driver of behavior change that current guidelines have failed to produce.