The postpartum period includes the care of the baby. An overprotective approach to the baby in this process can lead to the emergence of obsessive behaviors. This study aimed to examine the relationship between vulnerable baby perception and postpartum obsessive-compulsive behaviors in mothers. This descriptive cross-sectional study was conducted with 334 mothers who were 2-8 weeks postpartum. The study data were collected using the Introductory Information Form, the Vulnerable Baby Scale, and the Obsessive and Compulsive Behaviors of Mothers Related to Baby Care in the Postpartum Period Scale. It was completed with 334 mothers who were 2-8 weeks postpartum. The SPSS 27 program was used to analyze the research data. The mean Vulnerable Baby Scale score was 35.81 ± 6.13, while the mean postpartum obsessive-compulsive behavior score was 26.27 ± 8.42. Women with a history of risky pregnancy had significantly higher vulnerable baby perception scores. A significant positive association was found between vulnerable baby perception and postpartum obsessive-compulsive behaviors. Hierarchical regression analysis showed that vulnerable baby perception remained a significant independent predictor of postpartum obsessive-compulsive behavior scores after adjustment for sociodemographic and obstetric variables (β = 0.142, p = 0.007). The final model explained 15.1% of the variance in postpartum obsessive-compulsive behavior scores. Mothers' perceptions of vulnerable babies were positively associated with postpartum obsessive-compulsive behaviors, and vulnerable baby perception remained a significant independent predictor after adjustment for sociodemographic and obstetric variables.
South Africa (SA) faces a silent crisis of infant abandonment, often in unsafe environments, driven by poverty, stigma and limited access to abortion. Baby Saver Boxes - secure, monitored drop-off points - offer a humane alternative aligned with constitutional imperatives of life, dignity, healthcare and the best interests of the child. However, proposed amendments to the Children's Act risk criminalising compassion, reframing safe relinquishment as abandonment and undermining harm-reduction strategies. This punitive approach causes increased cases of neonaticide and maternal desperation, deters healthcare engagement, and places healthcare professionals in ethically fraught positions. Evidence from global best practice - including Germany's Babyklappe and US safe haven laws - demonstrates that legal recognition of safe relinquishment reduces mortality and promotes maternal health. A rights-based approach, informed by trauma-sensitive policy and intersectoral collaboration, is essential to protect vulnerable mothers and infants. SA must choose compassion over control, integrating Baby Saver Boxes into public health systems to uphold human rights and prevent avoidable deaths.
Spontaneous limb movements provide the foundation for motor development, yet knowledge of their normative characteristics has been limited by small homogenous samples and short observation windows. Leveraging the HEALthy Brain and Child Development (HBCD) study, we present descriptive characteristics of the first large-scale dataset of leg movements from 421 infants aged 0-2 months, captured with wearable sensors worn continuously for 72 h in naturalistic settings across multiple research sites in the United States. Our analysis focused on three domains: movement characteristics, variability of movement acceleration time-series, and physical activity intensity. Movement characteristics included leg movements per hour awake, peak acceleration per movement, average acceleration per movement, and movement duration. These characteristics aligned with earlier smaller-scale studies and showed highly consistent patterns between right and left legs. Sample entropy analysis revealed left-skewed distributions with median values near 1.3. Physical activity intensity estimations showed that infants spent the majority of time in sedentary activity, followed by light activity, with only brief periods of moderate-to-vigorous activity. Together, these findings provide initial characterization of multiple dimensions of infant leg movements, hence significantly contributing to derive reference distributions in early life. By establishing scalable, ecologically valid, and computationally tractable measures of infant motor behavior, this study lays the groundwork for integrating wearable sensing with longitudinal developmental science and for identifying early indicators of atypical trajectories. Ultimately, these findings contribute to the broader goals of the HBCD study: to understand how the brain develops and is shaped by environmental, social, and biological factors during pregnancy and after birth.
Pain is a challenging, multifaceted symptom reported by most pediatric patients. This systematic review aims to explore the progress and effectiveness of applying artificial intelligence (AI) technology in pediatric pain management. A comprehensive search of PubMed, Embase, Web of Science, Cochrane, Scopus, IEEE Xplore, ACM Library, and ClinicalTrials.gov was conducted. The search combined pain-related terms ("Pain management", "Pain assessment", "Pain measurement", "Pain relief", "Pain control", "Analgesics", "Pediatric pain"), age-related terms ("Children", "pediatrics", "Neonate", "Infant"), and AI core sub-domain terms ("Artificial intelligence", "Machine learning", "Deep learning", "Convolutional neural network", "Support vector machine", "Random forest", "Long short-term memory") using strict Boolean operators (AND/OR/NOT) published up to March 20, 2026. AI models, their validation, and performance were summarized. The analysis of 71 studies revealed distinct AI application patterns in pediatric pain management. Fifty-nine studies focused on pain assessment using deep learning (post-2020: 86.7%) and classical machine learning (pre-2015: 83.3%) through facial expression analysis (40.8%), multimodal fusion (25.4%), or physiological signals (9.9%). Most employed observational designs (57.7%) with small (<50 participants, 42.2%) to medium (50-200, 33.8%) samples, reflecting clinical data challenges. Multimodal approaches significantly outperformed unimodal methods (AUC difference: +0.13, p<0.01). The remaining 12 studies (16.9%) explored pain management, primarily using robot-assisted interventions with cognitive-behavioral strategies like guided breathing and gamification during procedural pain. However, a substantial proportion of the included studies (47.5% of assessment studies and 11 of 12 intervention studies) showed high risk of bias. This review offers substantiation that AI technology has been employed to enhance the efficiency of pain detection and assessment, thereby assisting healthcare professionals and patients in more adeptly managing acute pain. Future progress in precise pain assessment and management will depend on integrating deep learning with multimodal data and large clinical databases, alongside efforts to establish standardized datasets and validate models in real-world settings.
While high-intensity interval training (HIIT) has shown effectiveness in improving cardiorespiratory fitness (CRF) across various chronic respiratory diseases, its impacts on individuals with post-infectious bronchiolitis obliterans (PIBO) remain unexplored. To assess the effects of a home-based remotely-supervised HIIT programme on CRF, clinical and functional variables in patients with PIBO. Participants of this assessor-blinded, multicentre, randomized controlled trial were individuals with PIBO aged 6 to 20 years. An exercise group (EXE) underwent two 40-min sessions of HIIT remotely supervised in real time per week. Sessions were continued for 16 weeks. The control group (CON) adhered to general physical activity recommendations. The primary outcome was peak oxygen consumption (VO2peak), time to ventilatory threshold (VT1), percentage of VO2 at VT1, and ventilatory equivalent for carbon dioxide, determined via cardiopulmonary exercise testing on a treadmill. Secondary outcomes were lung function (spirometry), muscle strength (dynamometry), functional capacity (30-second Sit-To-Stand test), body mass index, and Saint George Respiratory Questionnaire. Fifty-one PIBO patients were enrolled (EXE=25; CON=26) (mean age 13.3±4.2 years; females 49%; FEV1 -3.56±1.28 (z-score); VO2peak 36.8±8.6 mL.kg-1.min-1). The HIIT intervention resulted in improvements in VO2peak (Δ=3.39; p=0.04), time (min) to VT1 (Δ=1.05; p=0.04), and in the number of repetitions in the 30s-STS (Δ=2.21; p=0.04). No differences were found in the other variables. Our real-time, remotely-supervised HIIT intervention was effective at significantly increasing CRF and functional capacity in children and adolescents with PIBO.
Chronotype is commonly assessed using the mid-sleep point as an indicator of circadian phase. In infants, however, this assessment typically relies on actigraphy, and most available sleep-scoring algorithms have been developed and validated for adolescents and adults, limiting their applicability in early childhood. The aim of this study was to examine the relationship between the mid-sleep point and L5 onset, a nonparametric measure derived from rest-activity rhythms that reflects the start of the least active 5-h period. A total of 502 nights from 81 six-month-old infants were analyzed. Sleep onset and offset were determined by visual inspection of actograms, and the mid-sleep point was subsequently calculated. A positive correlation was observed between mid-sleep point and L5 onset (r = 0.22, p < 0.001). Linear mixed-effects models indicated significant associations both between infants (β = 0.63, p < 0.001) and within infants (β = 0.10, p < 0.001). These findings suggest that L5 onset may serve as a practical proxy for circadian phase in 6-month-old infants, offering an alternative to sleep parameters derived from algorithms not specifically validated for this age group.
The first year after childbirth is a critical yet insufficiently monitored period for parental health. Postpartum mental and physical morbidity can affect both mothers and co-parents, but national longitudinal data remain scarce. The Stress Of Co-parents Related to A Traumatic Experience of birth across Switzerland (SOCRATES) cohort study aims to describe maternal and co-parental health and well-being trajectories during the first year after childbirth. SOCRATES is a prospective, population-based cohort study conducted in all linguistic regions of Switzerland. Eligible participants include women aged 14 and above who gave birth to a live or stillborn infant (≥22+0 weeks' gestation and ≥500 g) and their cohabiting co-parents, provided they speak German, French, Italian or English. Recruitment was conducted in 81 of the 112 Swiss maternity units, birth centres and organisations of midwives over 6 weeks in spring 2025. Clinical data on pregnancy, childbirth and the early postpartum period are extracted from medical records. Postpartum hospitalisation data are obtained through linkage with national medico-administrative databases. Participants complete online questionnaires shortly after birth and at 2, 6 and 12 months post partum, including sociodemographic characteristics and patient-reported outcomes. The primary outcome is the prevalence of childbirth-related post-traumatic stress disorder at 2 months, assessed using the City Birth Trauma Scale. Secondary outcomes include depression, physical recovery, sexual health, quality of life, healthcare use, perceived care quality and overall well-being. A weighting procedure will be used to ensure representativeness and to account for attrition. Ethical approval was granted by all seven Swiss ethics committees (number 2024-02262). All participants provided informed consent. Findings will be disseminated through national and international conferences, peer-reviewed publications, policy briefs, social media and stakeholder engagement activities. NCT06886841.
Further studies are needed to better characterize the association between craniofacial growth and feeding methods in infants aged 0-6 months. To evaluate the longitudinal association between feeding modality (exclusive breastfeeding versus mixed feeding) and craniofacial growth in infants aged 0-6 months. Observational, analytical, longitudinal cohort study. A total of 120 infants were evaluated four times. Nine craniofacial variables were assessed: four width, two height, and three depth measurements. Growth increments were estimated by feeding type, and linear mixed models were used to assess associations with craniofacial development. Exclusively breastfed infants showed greater increases in anthropometric and craniofacial measures compared with mixed feeding. Significant differences were observed in total craniofacial height (3.50 ± 0.08 vs. 3.25 ± 0.01 cm; p = 0.046), anterior facial height (2.08 ± 0.40 vs. 1.76 ± 0.07 cm; p = 0.016), maxillary depth (2.33 ± 0.04 vs. 2.21 ± 0.11 cm; p = 0.007), and mandibular depth (2.55 ± 0.02 vs. 2.41 ± 0.12 cm; p = 0.040). Exclusive breastfeeding was associated with greater craniofacial growth from 0 to 6 months compared with mixed feeding, supporting its role in early craniofacial development.
Brain age estimation provides a noninvasive MRI biomarker of neurodevelopment. In infancy, rapid regionally ordered myelination reflects brain maturation, yet early-life brain age estimation remains underexplored, particularly with myelination-sensitive MRI and biologically informed modeling. To develop and evaluate a biologically informed deep learning framework for infant brain age estimation using T1w/T2w ratio MRI. Retrospective. Internal cohort: 629 infants aged 0-24 months (626 with age-appropriate myelination, train/validation/test = 376/125/125), 3 with myelin-related developmental abnormalities for qualitative review. External cohort: 10 healthy infants aged 0-15 months (5 females, 5 males). Internal: 3T; 3D gradient-echo or 2D spin-echo T1w, and 2D turbo spin-echo T2w. External: 3T; 3D gradient-echo T1w and 2D turbo spin-echo T2w. 3D convolutional neural networks were trained with T1w, T2w, and T1w/T2w ratio inputs using manually defined biological age labels from visual myelination assessment. The model incorporated multi-task learning for age regression, white matter segmentation, and image reconstruction. Performance was evaluated using five-fold cross-validation with repeated random splits. Metrics included mean absolute error, root mean squared error, R 2 $$ {R}^2 $$ , and Pearson and Spearman correlations. Modality differences were tested using one-way ANOVA, t $$ t $$ -tests, and Mann-Whitney U $$ U $$ , with Cohen's d $$ d $$ and 95% confidence intervals. In the external cohort, absolute prediction errors were compared using the Wilcoxon signed-rank test. Statistical significance was defined as p < 0.05 $$ p<0.05 $$ . T1w/T2w ratio models achieved the best overall performance (MAE: 1.489  ± $$ \pm $$ 0.302 months; r $$ r $$  = 0.966  ± $$ \pm $$  0.012), compared with T1w (2.055  ± $$ \pm $$  0.944; 0.933  ± $$ \pm $$  0.061), T2w (1.794  ± $$ \pm $$  0.434; 0.947  ± $$ \pm $$  0.023), T1w+T2w (1.546  ± $$ \pm $$  0.291; 0.960  ± $$ \pm $$  0.013), and T1w+T2w+RI (1.498  ± $$ \pm $$  0.313; 0.963 ± $$ \pm $$ 0.012). Modality effects were significant for MAE, RMSE, R 2 $$ {R}^2 $$ , r $$ r $$ , but not for ρ $$ \rho $$ ( p = 0.250 $$ p=0.250 $$ ). Auxiliary-task and multi-scale modeling numerically improved performance (MAE, 1.203 months; r $$ r $$  = 0.979). External validation showed the lowest error for the RI-based model (MAE, 1.16 months), and Grad-CAM highlighted myelination-relevant white matter. T1w/T2w ratio MRI combined with biologically informed deep learning enabled accurate and interpretable infant brain age estimation. This framework showed promising cross-scanner performance and may support MRI-based assessment of early brain maturation. 3. 2. Assessing brain development in infants is critical for early detection of developmental delays. This study developed a deep learning model that estimates infant brain age from MRI by combining two standard scan types into a ratio image highlighting myelin, the insulating coating around nerve fibers that increases as the brain matures. Trained on 629 infants aged 0–24 months, the model predicted developmental age with a mean error of approximately 1.5 months. Attention maps confirmed the model focused on regions known to undergo early myelination. This approach showed consistent performance across two different scanners and may support objective monitoring of infant brain maturation.
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This study explores the use of response time (RT) data in type-2 receiver operating characteristic (ROC) analysis, a method traditionally used to examine the relationship between confidence and response correctness. Analyses of 16 perceptual decision-making datasets revealed that: (1) RT data contains roughly two-thirds as much information about response correctness as confidence; (2) RT carries unique predictive power for response correctness, independent of confidence; (3) RT and confidence interact synergistically, with confidence becoming a stronger predictor of response correctness when RT is short; (4) Despite these unique properties of RT, type-2 sensitivity (meta-d') derived from RT and confidence showed a reasonably high correlation across subjects. These findings carry two key implications. First, in the absence of confidence data, RT can serve as a viable proxy, incurring minimal cognitive and logistical costs. This makes type-2 analysis feasible across various settings, potentially including infant and animal studies. Second, when both RT and confidence data are available, their combined use in type-2 analysis offers complementary insights into the processes underlying subjects' behavior. To illustrate this, we present a simulation showing how the observed behavioral patterns align with the two-stage dynamic signal detection model. We propose that RT-based type-2 analysis is a valuable tool for researchers, helping to uncover previously underexplored aspects of decision-making behavior.
To estimate cause specific mortality among neonates and children under 5 for 195 countries from 2000 to 2024. Secondary data analysis using a Bayesian multinomial logistic regression model to estimate cause specific mortality fractions. PubMed, Embase, Web of Science, SCOPUS, Cochrane, Global Health Index Medicus, PAHO, Global Health OVID, Africa-Wide Information, IndMed, WHO Mortality Database, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and Health and Demographic and Surveillance Systems (HDSS). Studies in the general population reporting empirical cause specific mortality for at least two causes in the age groups of interest, with a specified method for cause ascertainment. For studies identifying causes of mortality with verbal autopsy, ≥25 deaths reported with ≤25% of these deaths with unknown cause. For vital registration, ≥80% population completeness and ≤10% deaths assigned to ill defined causes determined by the international classification of diseases, 10th revision. Cause specific mortality for countries with adequate quality vital registration was estimated with their own data with minor adjustments. For countries with low mortality without adequate quality vital registration, cause specific mortality was modeled by age group and based on vital registration. For high mortality areas, cause specific mortality was modeled primarily on the basis of verbal autopsy data identified in a systematic review. Estimated cause distributions were applied to all cause mortality rates and death counts estimated by the United Nations Inter-agency Group for Child Mortality Estimation. Among 4.9 million estimated global deaths in under 5s in 2024, the most important cause of death was preterm birth complications, with 0.82 (90% uncertainty interval 0.76 to 0.88) million deaths and 6.17 (5.93 to 6.42) deaths for every 1000 live births. This was followed closely by lower respiratory infections at 0.66 (0.60 to 0.71) million deaths, intrapartum related events (0.48 (0.43 to 0.52) million), and malaria (0.45 (0.39 to 0.51) million). Analysis for trends over time showed that the decline in most causes has slowed since 2016. With the recent slowed pace of decline in under 5 mortality for most primary causes of death, many high mortality countries are at risk of missing the sustainable development goal targets of ≤12 neonatal deaths and ≤25 under 5 deaths per 1000 live births without acceleration. Estimates presented here can help countries to determine the most appropriate course of action to reduce under 5 mortality and achieve these targets.
Fetomaternal hemorrhage (FMH) is a pathological process that can cause severe perinatal complications. Its clinical manifestations are often insidious, which makes it prone to missed diagnosis. It can occur in low-risk pregnancies without identifiable risk factors, posing significant challenges to obstetric and neonatal clinicians. This case report aims to highlight the prenatal warning signs, diagnostic workflow, and management pitfalls of acute massive FMH, providing actionable insights for clinical practice. A neonate born at 34+1 weeks exhibited severe anemia, metabolic acidosis, and shock. Despite immediate resuscitation efforts and comprehensive multi-organ support, the infant deteriorated into fatal multi-organ failure within 25 h. A maternal Kleihauer-Betke test confirmed the diagnosis, estimating a fetal blood loss of 175 mL (approximately 85.8 mL/kg). Placental pathology revealed only focal villous edema. FMH is an insidious perinatal emergency that demands heightened vigilance even in low-risk pregnancies. Reduced fetal movements, when combined with abnormal middle cerebral artery peak systolic velocity and cardiotocography findings, should prompt immediate obstetric evaluation. Timely multidisciplinary intervention (obstetric emergency delivery and neonatal resuscitation) and adherence to standardized diagnostic-therapeutic pathways are essential to mitigate adverse outcomes. This case provides valuable clinical insights for the early identification and management of massive FMH, particularly in pregnancies without preexisting risk factors.
Poor nutrition during early childhood affects growth/development and increases the risk of morbidity and mortality. This study assessed child feeding practices and the nutritional status of children from selected Nigerian tertiary health institutions. This study employed a descriptive cross-sectional design to digitally elicit responses from 1,295 mothers and child pairs accessing welfare services at four tertiary health institutions in Nigeria. Harmonized indicators such as Infant and Young Child Feeding Index (ICFI), WHO/UNICEF Infant and Young Child Feeding (IYCF) Practices Indicators, and WHO growth standards were used to evaluate the children's feeding practices and anthropometric status. All descriptive and bivariate analysis (Fisher-Exact test) were done using IBM SPSS for Windows 25. The study revealed that while 80.7% and 86.9% of the children met the minimum meal frequency and age-appropriate complementary feeding introduction criteria, breastfeeding initiation (48.5%), exclusive breastfeeding (EBF) rates (68.4%) and diversified food intake were suboptimal. However, 44.1% of children with stunting and 44.1% of children with overweight/obesity were identified. Exclusive breastfeeding was positively associated with BMI-for-age (OR = 1.51; 95% CI: 1.06-2.16; p = 0.02). Current breastfeeding status was also significantly associated with height-for-age (OR = 0.54; 95% CI: 0.37-0.78; p < 0.001) and BMI-for-age (OR = 1.78; 95% CI: 1.23-2.58; p = 0.002). Several aspects of the children's feeding practices were sub-optimal, nutritional status was polarized, with many children affected by stunting and overweight/obesity. Interventions tailored towards strengthening breastfeeding and complementary feeding practices are critical for improving nutrition outcomes.
Infants in resource-limited areas frequently receive early-life antibiotic treatment for respiratory and diarrheal illness, but the influence of antibiotics on parenteral vaccine immunogenicity in these settings remains underexplored. Therefore, we conducted a retrospective cohort study within a randomized, controlled, oral rotavirus and poliovirus vaccine trial performed in Dhaka, Bangladesh. Among 582 evaluable infants at 53 weeks of age, plasma antibody concentrations against measles, pertussis, diphtheria, tetanus, and Haemophilus influenzae type b (Hib) were evaluated for associations with prior antibiotic exposure. Most antibiotic prescriptions were broad-spectrum, with a mean of 85.5 days of antibiotics in the first year. Most children demonstrated protective antibody levels against measles (96%), tetanus (88%), and Hib (91%) at 53 weeks of age; fewer maintained protective levels against pertussis antigens (25-42%) and diphtheria (28%). Antibiotic exposure through 14 weeks of age, before completion of the primary vaccination series, did not significantly affect antibody concentrations at 53 weeks of age against diphtheria, tetanus, pertussis, and Hib antigens. Antibiotic exposure through 14 weeks of age was positively associated with measles antibodies at 53 weeks of age (change in concentration per antibiotic course was 9.09%; 95% CI: 5.13 to 12.75; q-value = 0.0003), but despite this association, nearly all children had protective antibody levels, limiting clinical significance. Although antibody levels varied by antigen, infant antibiotic exposure did not appear to clinically impact parenteral vaccine-induced antibody concentrations in this population. These findings support the robustness of parenteral vaccine responses in resource-limited settings despite high antibiotic use.
Lutein is a diet-derived carotenoid present in human milk through maternal intake and has been associated with visual and neurodevelopmental processes in infancy. Lutein-containing infant formulas have therefore been developed to increase lutein exposure, although no evidence shows that formula fortification fully reproduces the biological effects associated with human milk. This review provides a comprehensive synthesis of clinical evidence on lutein supplementation in infants, patented formulations, and delivery technologies that influence lutein stability, bioavailability, and safety. The first section of the review evaluates lutein fortified infant formulas, including their health effects, regulatory standards, patent claims, and commercialization in the U.S. market. Although patents frequently include lutein as an optional ingredient, relatively few emphasize its developmental relevance or address the specific formulation challenges. The systematic review evaluates human and animal studies on clinical outcomes of lutein-fortified infant formulas, including lutein bioavailability, distribution in circulation and key tissues (brain and retina), safety, and tolerance. Across studies, lutein-fortified formulas consistently increase circulating lutein concentrations relative to unfortified formulas, yet bioavailability remains lower than that of breast milk. By combining both the patent and clinical literature, this review identifies critical scientific, technological, and regulatory gaps and highlights opportunities for future innovation in newborn nutrition.
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Chronic diseases have become a major public health burden globally, and online health information seeking behavior (OHISB) has emerged as a potential tool for improving health literacy and protecting individuals from chronic diseases. Nevertheless, previous studies have shown that OHISB may exacerbate health disparities, and its specific association with chronic disease prevalence remains unclear. This study aims to investigate the relationships between OHISB, chronic disease literacy, and chronic disease prevalence, with a focus on sociodemographic heterogeneity. A cross-sectional questionnaire survey was conducted in China, from June to September 2024. Partial correlation analysis and restricted cubic spline (RCS) regression were used to analyze the specific relationships among OHISB engagement, chronic disease literacy and prevalence. Stratified interaction analyses were performed to explore the heterogeneous effects of OHISB across distinct sociodemographic subgroups. OHISB was positively associated with chronic disease literacy (r = 0.218, P < 0.001), The RCS model revealed a significant nonlinear relationship between OHISB and chronic disease literacy (P nonlinear < 0.001), characterized by an initial significant increase followed by a plateau. Significant interaction effects of OHISB and sociodemographic factors were observed (P interaction < 0.001), OHISB conferred more benefits on vulnerable subgroups, including those aged ≥45, suburban residents, non-college graduates, and low-consumption individuals (≤¥3,000/month). Conversely, while the RCS plot revealed a descriptive risk convergence trend, no significant association was found between OHISB and chronic disease prevalence (r = -0.005, P = 0.855). OHISB was positively associated with chronic disease literacy, although its benefits were limited by a ceiling effect. Moreover, it was also associated with the narrowing of sociodemographic gaps in chronic disease literacy. However, we did not observe a significant link between OHISB and chronic disease prevalence. Therefore, targeted digital interventions are essential to bridge the knowledge-behavior gap and promote chronic disease prevention among vulnerable populations.
We present 2 cases of spinal astrocytoma in infants mistaken for brachial plexus birth injuries (BPBI). (1) A 5-month-old infant had upper-extremity weakness resembling a global plexus injury. An magnetic resonance imaging (MRI) and biopsy revealed a low-grade cervical astrocytoma. The patient underwent chemotherapy with partial recovery of upper extremity motor function. (2) A 5-month-old infant had upper-extremity weakness resembling upper trunk BPBI. MRI and biopsy revealed pilocystic astrocytoma. The patient underwent spinal decompression and proton therapy but did not regain function. A high degree of suspicion for neoplasia in the setting of presumed brachial plexus birth injury can prevent incorrect diagnosis allow timely treatment.
Caffeine is the standard therapy for apnea of prematurity and used near-universally in preterm infants. Interindividual variability in clearance, exposure, and clinical responses persists in neonates. CYP1A2 is the primary enzyme responsible for caffeine metabolism in adults, but the enzyme activity in neonates has historically been considered negligible. Scavenged plasma samples from neonates receiving caffeine therapy in a neonatal intensive care unit were analyzed to quantify caffeine and paraxanthine concentrations. The caffeine metabolic ratio (CMR) was used as a functional biomarker of in vivo CYP1A2 activity. Associations between CMR, postmenstrual age, and clinical covariates were evaluated using univariate analyses, linear mixed-effects modeling, and longitudinal analyses. To compare our data to model predictions, caffeine concentrations were simulated in preterm infants using two previously published physiologically based pharmacokinetic (PBPK) models: the default Simcyp preterm infant model and a 2025 modified model. Thirty-one neonates (186 plasma samples) were recruited for this study. Paraxanthine was detectable in all samples, demonstrating measurable CYP1A2 activity. CMR increased with postmenstrual age even after adjusting for clinical covariates (β = 0.05, p = 0.01). Interindividual variability was observed and longitudinal analyses showed heterogeneous CMR trajectories, indicating modulation by clinical factors beyond age alone. Both PBPK models tested demonstrated systematic overprediction of caffeine exposure, consistent with underestimation of clearance, although the modified model showed better concordance with observed data. These findings provide the first in vivo evidence of quantifiable CYP1A2 activity in neonates and demonstrate the feasibility of using caffeine as a probe drug to study enzyme ontogeny. Current published PBPK models do not accurately capture caffeine concentrations in our cohort, likely reflecting differences between our population and the preterm models. Integrating empirically derived neonatal pharmacokinetic data into PBPK models that more accurately reflect a preterm NICU population may better inform individualized dosing based on developmental age and clinical illness severity. By anchoring neonatal drug dosing in empirically derived physiology rather than adult extrapolation, these models have the potential to transform dosing practice and advance pharmacoequity for one of the most vulnerable and historically understudied populations.