Pediatric Infectious Disease Journal

Abstract Background: Pediatric respiratory infections are a leading cause of morbidity and mortality globally, representing a major health challenge in children. Research Gap: Despite extensive studies on epidemiology, clinical management, and specific pathogens, no bibliometric analysis has systematically evaluated the most influential research in this field. Objectives: This study aimed to evaluate the characteristics of the top 50 most-cited articles on pediatric respiratory infections and to identify emerging research trends. Methods: The Web of Science database was searched without publication year restrictions. Independent reviewers screened studies based on predefined inclusion and exclusion criteria. Data were extracted using a standardized form, including study details. Results: The 50 most-cited articles ranged from 34 to 384 citations and showed a right-skewed distribution with a sharp drop after the top ten. Publication years ranged from 1978 to 2021, with over half published in the 2010s. Articles appeared in 31 journals, with Pediatrics contributing five. Leading countries were the United States (18%), China (12%), and Canada (10%), with research largely concentrated in high-income regions and limited multicenter collaboration. Cohort studies dominated (66%), while randomized trials (12%) and reviews/meta-analyses (16%) were less common. Research clustered around three themes: clinical outcomes (e.g., pneumonia, bronchiolitis); viral etiology/diagnostics (e.g., RSV, SARS-CoV-2); and antimicrobial stewardship. Conclusion: Over the past decades, pediatric respiratory infection research has developed but remains unbalanced, relying heavily on observational evidence from high-income countries, with limited randomized trials, systematic reviews, multicenter collaborations, and LMIC-led studies. These findings provide insights that may direct researchers to identify potential focal points and guide future research in the field.

Objective: Lyme disease diagnosis in children is challenging due to atypical presentations and testing limitations. We sought to evaluate the association between Lyme disease and socio-geographic risk factors in children. Materials and methods: We enrolled children undergoing evaluation for acute Lyme disease at one of eight Pedi Lyme Net pediatric emergency departments located in high Lyme disease incidence states over a ten-year period (2015-2024). We defined a case of Lyme disease with an erythema migrans (EM) lesion or a positive two-tier serology result in a child with signs and/or symptoms of acute disease. We linked each childs primary residential county to the following factors: urban-rural residence, socioeconomic status, population-level disease incidence, wildland-urban interface, and "Lyme disease" Google searches. We performed a multi-level logistic regression analysis to evaluate associations between Lyme disease and county factors after adjusting for individual demographics. Results: Among 5,529 children enrolled, 1,396 (25.2%) had Lyme disease: 101 (7.2%) with early-localized disease, 584 (41.8%) with early-disseminated disease, and 711 (50.9%) with late-disseminated disease. Rural residence (aOR 1.9, 95% CI 1.3-2.9), higher socioeconomic advantage (aOR 1.3, 95% CI 1.1-1.4), more "Lyme disease" Google searches (aOR 1.1, 95% CI 1.0-1.2), and higher wildland urban interface (aOR 1.2, 95% CI: 1.0-1.4) were independently associated with Lyme disease. Conclusion: Incorporating socio-geographic factors alongside clinical data may augment diagnostic risk assessment in children with suspected Lyme disease. However, these factors should be incorporated carefully to ensure clinical assessments are not based on a childs geographic location alone.

Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious condition associated with pediatric SARS-CoV-2 infection. While COVID-19 vaccines prevent infection and reduce severity, less conclusive evidence exists regarding their role in preventing MIS-C during breakthrough infections. This systematic review assessed the impact of SARS-CoV-2 vaccination on MIS-C risk during breakthrough infection. Cross-sectional studies, surveillance studies, and cohort studies were included. Of the 944 studies identified, 6 were included. A significant protective effect was seen in patients who received two doses of SARS-CoV-2 vaccination after exclusion of a biased sample (d= 0.71 [95% CI 0.07 to 1.35; p=0.03]). A trend towards a protective effect was seen after one dose of vaccination, but this effect was not statistically significant. Current literature supports a protective effect of two doses of SARS-CoV-2 vaccination against development of MIS-C in breakthrough COVID-19. The evidence supports clinician advocacy for continued vaccination of children against SARS-CoV-2.

Background: Diarrheal illness in children leads to 3.5 million care visits and 200,000 hospitalizations annually in the US. Viruses are responsible for most pediatric diarrheal cases, yet limited guidance on distinguishing viral from bacterial etiologies complicates clinical decision-making, especially regarding empiric antibiotic use. Methods: We used clinical and qualitative molecular etiologic data from the Implementation of Molecular Diagnostics for Pediatric Acute Gastroenteritis (IMPACT) study to develop prediction models for viral etiology of diarrhea. We used conditional random forests to identify informative clinical and environmental predictors and evaluated model performance using logistic regression and random forests within a 5-fold cross-validation framework. We conducted external validation using the Alberta Provincial Pediatric Enteric Infection Team (APPETITE) dataset. Results: Variables predictive of viral etiology included younger age, non-bloody diarrhea, winter season, and presence of vomiting. External validation showed that an AUC of 0.82 can be achieved with a parsimonious 5-variable model, yielding a sensitivity of 0.92 and specificity of 0.55 Conclusion: Our results suggest that in North American healthcare settings, clinical prediction models can inform decision-making by identifying children with a high probability of viral diarrhea, improving diagnostic clarity, and reducing unnecessary testing and treatment.

Background Diarrhea remains a leading cause of child morbidity and mortality worldwide. Improved and ongoing estimates of the etiologies of severe diarrhea, particularly in low- and middle-income countries (LMICs), are crucial to inform the use of current vaccines and other interventions and to help prioritize the development of new vaccines. Producing rigorous longitudinal data on the global burden and etiology of pediatric diarrhea requires a geographically broad surveillance network with standardized epidemiologic, laboratory, and analytic protocols. Methods We describe the rationale and methods of the Global Pediatric Diarrhea Surveillance (GPDS) network, a World Health Organization (WHO)-coordinated public health surveillance network investigating the etiology of hospitalized diarrhea among children aged <5 years in LMICs. The GPDS network enrolls children hospitalized with diarrhea at 38 sentinel surveillance sites in 31 LMICs across all 6 WHO Regions. Randomly selected stool specimens were tested by TaqMan Array Card quantitative polymerase chain reaction for 16 enteric pathogens previously associated with pediatric diarrhea. GPDS produces estimates of pathogen-specific attributable fractions and incidence of diarrheal hospitalizations at the global, regional, and country levels. Conclusions As a WHO-coordinated global surveillance network, GPDS evaluates pathogens associated with hospitalized pediatric diarrhea. The network monitors the changing burden of pathogens over time, monitors circulating strains, and generates data to inform decision-making around public health interventions. GPDS also improves global, regional, and country diarrheal disease burden estimates, informs new enteric vaccine development, and potentially provides a platform for future enteric vaccine evaluation.

Nasopharyngeal (NP) swabs remain the dominant gold standard for respiratory infection diagnostics. While there has been increased use of alternative sample types since the COVID-19 pandemic, guidance on their use for detecting respiratory viruses is not yet definitive, especially for children. In this systematic review and meta-analysis, we aimed to compare the diagnostic accuracy and tolerability of multiple respiratory specimen types for detecting respiratory viruses in pediatric populations. Searches were conducted on July 17, 2025 in MEDLINE, Embase, Web of Science, and Scopus, with screening and data extraction performed in Covidence. English-language primary research articles published since 2000 comparing respiratory virus detection rates in children, using nucleic acid amplification tests between paired respiratory specimens, were included. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies criteria. We calculated pooled sensitivities and specificities of index specimens: nasopharyngeal aspirates (NPA), mid-turbinate swabs (MT), anterior nasal swabs (ANS), oropharyngeal swabs (OP), and bronchoalveolar lavage fluid (BAL), as compared to the reference, NP swabs, using random-effects modeling, firstly without discrimination by virus. Index specimens were then grouped by sample collection site as nasal, oral, and lower respiratory tract (LRT) specimens for virus-specific analyses. Overall performance and statistical validity were evaluated by hierarchical summary receiver operating characteristic (HSROC) analysis. Data regarding sampling tolerability was also assessed. We screened 2,448 studies and identified 36 publications (total N participants = 10,687) that reported diagnostic test accuracy using paired index-reference data in children. Of these, 18 (total N participants = 4,310) used NP specimens as the reference and were included in the diagnostic test accuracy analysis. Virus-agnostic pooled sensitivity estimates indicated that MT (0.92%) performed most similarly to NP, though sensitivities of ANS (0.79%) and OP (0.70%) were also moderately high for detection of any respiratory virus. BAL sensitivity was the lowest (0.37%). All sample types demonstrated high specificity (0.98%-0.99%). Group estimates and HSROC statistics found that nasal specimens, when grouped, had the highest sensitivity and accuracy for all examined viruses, including for influenza (92%) and RSV (90%). By comparison, oral and LRT specimens performed less well, with more variability, though both showed moderately high sensitivities for RSV (78%, 76%, respectively) and influenza (82%, 80%, respectively), and LRT samples showed high sensitivity for HMPV (82%). Analysis of sample tolerability found that NP swabs consistently ranked as the least comfortable and least preferred, while nasal swabs and saliva both performed well. Datasets for LRT and oral specimens were sparser than for nasal, and this contributed to greater variability, underscoring the need for further diagnostic accuracy studies on alternatives to NP sampling. These data support the viability of nasal and oral alternatives to NP swabs and affirm their application in pediatric care, particularly in outpatient settings. Such alternatives could greatly improve sampling tolerability and increase global access, including in resource-limited settings, to accurate diagnostic methods for respiratory infections.

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.

Shigella is a major cause of childhood diarrhea in sub-Saharan Africa. Current World Health Organization (WHO) guidelines recommend empiric antibiotics only for dysentery, yet non-dysenteric presentations account for 40-89% of Shigellainfections. We quantified the performance of existing guidelines to identify Shigella infection and evaluated enhanced syndromic criteria for improved management of Shigella cases. We leveraged data from the Enteric for Global Health (EFGH) Kenyan site, which enrolled children aged 6-35 months with medically attended diarrhea, collected rectal swabs at enrolment, and tested these for Shigella using both the culture and TaqMan-array cards (TAC). Shigella positivity was defined as either a culture-confirmed Shigella or a TAC-attributable result (CT <29.5). We compared categorical variables using the {chi}{superscript 2} test or Fishers exact as appropriate while continuous variables were compared between groups using the Wilcoxon rank-sum test. A logistic regression model was fitted to identify a parsimonious set of predictors. Out of the enrolled 1400 MAD cases, of whom 175 (12.5%) were Shigella positive, of which 134 (76.5%) being non-dysenteric. Among all enrolled children, 148 (10.6%) were dysenteric and 1,252 (89.4%) were non-dysenteric. Of the non-dysenteric cases, 57/1,252 (4.6%) and 129/1,251 (10.3%) of children were Shigella attributable by culture and TAC, respectively. Compared to Shigella negative cases, positive cases were older (Median age in months [Q1-Q3]: 20 [14-24] vs 13 [8-19], p<0.001), had higher stool frequency (5 [3-6] vs 4 [3-5], p<0.049) and were more likely to be dysenteric (42 [24%] vs 106 [8.7%], p<0.001). Contrarily, Shigella positive cases were less likely to present with vomiting (66 [37.7%] vs 587 [47.9%], p=0.014) and difficulty in breathing (0 (0%) vs 27 [2.2%], p<0.040). Dysentery alone had minimal predictive power to identify Shigella (area under the ROC curve (AUC) [95% CI]: 0.58 [0.54-0.61]), while Dysentery and Age binary (<17 months) (0.70 [0.66-0.74]), and Dysentery, Vomiting, Difficult breathing, and Age binary (0.72 [0.68-0.76]) had acceptable predictive performance. Our data shows that current guidelines miss up to 76.5% of Shigella-positive cases which are non-dysenteric. This suggests that dysentery alone has limited predictive power, but incorporating additional symptoms increases discriminatory ability by up to 14%, with age alone improving it by 12%. These findings support the need to re-evaluate the current syndromic based guidelines to better detect Shigellosis and strengthen antibiotic stewardship.

Kawasaki disease (KD) is an acute pediatric vasculitis characterized by dysregulated host immune responses and risk of coronary artery injury. Although a two-transcript IFI27-MCEMP1 axis has been clinically validated to distinguish KD from other febrile illnesses, the long noncoding RNA (lncRNA) context of this interferon-myeloid imbalance remains incompletely understood. We evaluated whether peripheral blood mononuclear cell (PBMC)-derived lncRNAs are altered in KD and associated with the interferon and myeloid components of the IFI27-MCEMP1 transcriptomic axis. Children younger than 8 years with suspected KD were prospectively enrolled at the Children's Hospital of Fudan University from 2024 to 2025. The newly enrolled cohort included 55 children with KD and 48 febrile controls. For integrated immune-transcript association analyses, these data were combined with two previously characterized same-site cohorts, yielding 188 children with KD and 175 febrile controls. Expression of IFI27, MCEMP1, CHROMR, MALAT1, and NEAT1 was measured by reverse transcription quantitative PCR and normalized to GAPDH using {Delta}Ct values. In the newly enrolled cohort, the IFI27-MCEMP1 axis reproduced discrimination between KD and febrile controls, with an area under the receiver operating characteristic curve of 0.88; performance was similar in the integrated cohort, with an area under the curve of 0.89. In PBMC lncRNA analyses, CHROMR and MALAT1 {Delta}Ct values were significantly higher in KD than in febrile controls, indicating lower relative expression, whereas NEAT1 did not show a significant KD-specific differential-expression signal. CHROMR showed the strongest association with the IFI27 interferon-associated component, while MALAT1 showed weaker but directionally informative associations with both IFI27 and MCEMP1, including an inverse association with MCEMP1. These findings support an lncRNA-associated interferon-myeloid immune architecture in KD, marked by coordinated attenuation of IFI27, CHROMR, and MALAT1 together with increased MCEMP1. This PBMC RNA pattern provides a biologically interpretable framework for KD immune dysregulation and generates testable hypotheses regarding RNA-regulatory programs in KD vasculitis.

Purpose: To assess maternal knowledge of preterm infant care in Gaza and identify clinically actionable education priorities in a resource-constrained neonatal setting. Methods: A cross-sectional survey was conducted among 170 mothers of premature infants admitted to neonatal departments in four government hospitals. A 30-item interviewer-administered questionnaire assessed knowledge across thermoregulation, feeding, phototherapy, and infection and skin care. Bivariate analyses, ordinal logistic regression, adjusted predicted probabilities, and exploratory clinical-priority gap analyses were conducted. Results: Overall knowledge was moderate, with a mean score of 64.1% (SD 22.3). Knowledge was classified as poor in 53 mothers (31.2%), good in 41 (24.1%), and excellent in 76 (44.7%). Knowledge differed across domains (p<0.001), with feeding weakest (53.6%) and infection and skin care strongest (73.8%). Not receiving specialist premature-care antenatal follow-up was independently associated with lower odds of higher knowledge (adjusted OR 0.34, 95% CI 0.15-0.80, p=0.013). Mothers without specialist follow-up also had a higher adjusted probability of poor knowledge than those who received it (37.4% vs 18.1%) and more clinical-priority gaps (IRR 1.28, 95% CI 1.04-1.57, p=0.019). Among the 10 lowest-scoring items, 110 mothers (64.7%) had five or more gaps. Conclusion: Maternal knowledge was uneven, with clinically important gaps in practical care domains. Domain-specific education checklists may strengthen antenatal counselling, bedside teaching, and discharge preparation in similar constrained neonatal settings.

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.

Introduction: Newborn babies frequently encounter acute respiratory failure requiring assisted ventilation. Acute respiratory failure in infants commonly present in a form of respiratory distress syndrome. There are several studies that documented factors associated with CPAP failure rates among preterm newborns worldwide. However, they were either statistically underpowered or defined by overt design errors. The proposed study will estimate incidence rate and predictors of Continuous Positive Airway Pressure (CPAP) failure among preterm newborns delivered at representative hospitals in a typical urban area of Africa. Methods and analysis: a prospective longitudinal cohort observational, analytical study will be conducted at neonatal and emergency units of all Dar es Salaam public regional referral hospitals from March to (and including) August 2026. Newborns with CPAP failure will be the target population. Newborns without CPAP failure will be the control group. Follow up for each child will commence from the moment the child is subjected to CPAP until CPAP failure is clinically evident or day seven of life, whichever comes first. Interval assessment of the SAS scores (for CPAP potency) will be done using Silverman-Anderson score sheet in 4-6 hours intervals (unless otherwise dictated by the child clinical situation). The main outcome/dependent variable will be proportion of new CPAP failure per newborn-time of follow up. A multivariable linear model will be used to account for independent predictors of CPAP failure. Unless otherwise stated, an alpha-level of 5% will be used as a limit of type 1 error in findings. Ethics and Dissemination process: The study has received an IRB certificate (IRB reference: KU/IREC/27/10/639) from the Institutional Research Ethics Committee of KU. Permission to recruit the affected children has been sought from Municipals based hospitals directors of Amana, Mwananyamala and Temeke regional referral hospitals respectively. Written informed consent will be sought from mothers of all recruited newborn babies.

Background: Apnoea of prematurity is common and may cause desaturation and/or bradycardia. There is marked variability in infants cardiorespiratory responses to apnoea, despite standardised clinical thresholds. Factors influencing apnoea-related cardiorespiratory instability and whether instability can be predicted warrant investigation. Methods: 181,511 apnoeas >5 seconds were identified from continuous physiological recordings from 146 preterm infants <37 weeks postmenstrual age. Cardiorespiratory instability was defined as bradycardia (>30% heart rate reduction) and/or oxygen desaturation (<85%). Mixed-effects models assessed clinical, demographic and dynamic modulators of the relationship between apnoea duration and cardiorespiratory instability. Machine learning (XGBoost) was used to train models to predict apnoea-related cardiorespiratory instability. Results: Longer duration apnoeas were associated with increased instability, although variability was substantial and 3.6% of apnoeas <10 seconds were associated with cardiorespiratory instability, while 61.2% of apnoeas [&ge;]20 seconds were not. Multiple clinical/demographic (postmenstrual and gestational age, sex, weight z-score, and ventilation mode) and dynamic (baseline heart rate, oxygen saturation, and recent apnoea clustering) factors were associated with increased instability risk. Apnoea-related cardiorespiratory instability could be predicted with a balanced test accuracy of 75.8% when incorporating all features, while a model using only clinical/demographic features achieved 66.0%. Conclusions: Multiple factors influence cardiorespiratory responses to apnoea. Predictive modelling may enable personalised apnoea definitions, improving individualised care.

Background and Objectives: SARS-CoV-2 (COVID-19) continues to mutate, circulate, and adversely impact health and quality of life. While COVID-19 vaccines remain safe and effective, uptake remains low, especially among children, the youngest of whom were not vaccine-eligible until after Omicron and are underrepresented in published research. This study estimated vaccine effectiveness (VE) among under-5-year-olds. Methods: We used Virginia Department of Health surveillance data from June 2022 through October 2022 to conduct a test negative case-control study. We estimated VE derived from odds ratios (ORs) of reported infections using logistic regression among children aged 6-months to 5-years. Results: Using the earliest positive (cases) or negative (controls) post-vaccine-eligible test results, the VE associated with two doses of a COVID-19 vaccine was 78% (95% CI=45%, 93%; p=0.004) in unadjusted analyses and 70% (95% CI=25%, 91%, p=0.023) when adjusting for age, sex, prior testing behavior, and prior reported infections. The adjusted VE was 74% (95% CI=28%, 94%; p=0.025) among those with no prior positives reported and 45% (95% CI=-302%, 97%; p=0.569) among those with a prior positive reported. Conclusions: These results show that even though the vaccine was not closely matched to the dominant variants circulating during the time period analyzed, it was effective at reducing the risk of reported infections. This study adds to the body of knowledge on pediatric COVID-19 VE in an underrepresented age-group and in a rural region, illustrates the utility of surveillance data for evaluation, and can inform vaccine decisions to improve vaccine uptake for young children.

Background Large-for-gestational-age (LGA) and macrosomic newborns are at increased risk of adverse perinatal outcomes, including death, yet the burden of neonatal mortality associated with these conditions in low- and middle-income countries (LMICs), where ongoing nutritional and epidemiological transitions suggest their prevalence will rise, remains poorly quantified. In this study, we quantify the neonatal mortality risk associated with LGA and macrosomia from 16 subnational birth cohorts in low- and middle-income countries between 2000 and 2017. Methods and findings This is an individual-participant meta-analysis to estimate neonatal mortality rates (NMRs) and relative risks among LGA infants (>90th and >97th percentile birth weight-for-gestational-age using INTERGROWTH-21st) versus appropriate-for-gestational-age (AGA, 10th-90th percentile) infants. Macrosomic ([&ge;]4000 g and [&ge;]4500 g) neonates were compared with those weighing 2500 g-3999g. Missing birth weights were imputed using recalibration and multiple imputation methods. We used random effects meta-analysis to pool relative risks. Median prevalences of LGA >90th and >97th percentile were 5.3% (interquartile range 3.6-8.2) and 2.6% (IQR 1.3-4.5), respectively; macrosomia ([&ge;]4000 g and [&ge;]4500 g) prevalences were 1.0% (IQR 0.3-3.1) and 0.06% (IQR 0.0, 0.30), respectively. Mortality was highest among preterm plus LGA infants (61.3 per 1000). LGA infants in the >90th percentile had over twofold increased mortality compared with appropriate-for-gestational-age infants (RR: 2.46; 95% CI: 1.86-3.25), while >97th percentile infants had a higher risk (RR: 3.77; 95% CI: 2.50-5.69). Term LGA >97th percentile infants also showed elevated mortality (RR: 3.14; 95% CI: 1.58-6.22). For LGA >97th percentile, the risk was higher in the early neonatal period (RR: 2.71; 95% CI: 1.92-3.82) than late (RR: 1.69; 95% CI: 1.22-2.34). There was no overall association between macrosomia ([&ge;]4000 g) and neonatal mortality. Population attributable fractions were 7.2% for LGA >90th percentile and 0.4% for macrosomia ([&ge;]4000 g). Conclusions Neonatal mortality risks were elevated among LGA infants in low- and middle-income countries, particularly at extreme values (>97th percentile) and during the early neonatal period. Macrosomia showed weaker, less robust associations. Although LGA prevalence is currently low ([~]5%) and contributes less to neonatal mortality than small newborns, ongoing nutritional and epidemiological transitions suggest increasing prevalence. This highlights the need for strengthened surveillance, monitoring, and improved delivery planning to ensure that no population is left behind.

Background Microbiological confirmation of paediatric pulmonary tuberculosis is frequently unattainable, rendering chest radiography a critical yet underutilised diagnostic tool. Methods We conducted a retrospective diagnostic accuracy study of the qXR version 4.2.1 (Qure.ai), a paediatric optimized computer-aided detection (CAD) algorithm, for pulmonary tuberculosis. Diagnostic performance was assessed against microbiological (MRS) and clinical reference standards (ClRS). Bayesian latent class analysis (LCA) was applied to address the imperfection of both reference standards in children. Performance was quantified using area under the receiver operating characteristic curve (AUROC) and estimates of sensitivity and specificity. Results We included digital chest radiographs of 932 Gambian children (< 15 years) comprising 80 (9%) children with confirmed tuberculosis, 163 (17%) with unconfirmed tuberculosis, and 689 (74%) classified as unlikely tuberculosis. Against MRS, qXR demonstrated AUROC, sensitivity and specificity of 0.68 (95% CI, 0.61 to 0.75), 54% (95% CI, 43 to 64%), and 82% (95% CI, 79 to 84%), respectively. Against ClRS, the AUROC, sensitivity and specificity were 0.73 (95% CI, 0.69 to 0.77), 41% (95% CI, 34 to 49%), and 87% (95% CI, 84 to 89%), respectively. Bayesian LCA, assuming conditional independence, estimated sensitivity of 79% (95% CrI, 65 to 89%) and specificity of 82% (95% CrI, 79 to 84%). Assuming conditional dependence between qXR and expert radiologist, and between culture and Xpert, estimated sensitivity increased to 89% (95% CrI, 71 to 98%), with specificity remaining at 82% (95% CrI, 79 to 84%). Conclusions Paediatric optimized qXR algorithm provides a valuable complementary tool for diagnosis of paediatric pulmonary tuberculosis. Conventional reference standards likely underestimate the true diagnostic performance of CAD systems in children.

Background: Shigella is a leading cause of childhood diarrhea in low- and middle-income countries and is increasingly resistant to first-line antibiotics. We conducted a surveillance study to determine the incidence, genomic characteristics, and AMR profiles of Shigella infections in children under five with moderate to severe diarrhea (MSD) in Lusaka, Zambia. Methods: Between 15 September 2020 and 30 November 2021, a prospective cohort study of 1,400 children under five was enrolled during a community census in a peri-urban setting and passively followed for 9.5 months for MSD. During enrollment, socio-demographic data were collected using electronic questionnaires, while clinical data were collected through the DHIS platform. The main outcome, Shigella in diarrheal stool in under 5 children, was detected using culture and Loop-mediated Isothermal Amplification (LAMP) targeting the ipaH gene. Cox proportional hazards models were used to assess the incidence and risk factors of Shigella (ipaH) infections. Whole-genome sequencing (WGS) was used to characterize the genomic diversity and antimicrobial resistance genes, complemented by phenotypic antibiotic susceptibility testing. Results: There were 230 first episodes of Shigella over a follow-up time of 9,581.7 child-months, yielding an incidence of 24.0 (95% CI 21.1-27.3) cases per 1,000 child-months, with the highest incidence among 2 to 3-year-olds. The key risk factors identified were the water source (p=0.025) and age group (p=0.014). Genotypic characterization revealed 10 S. flexneri, 9 S. sonnei, and 3 S. boydii. The S. sonnei isolates formed two clusters, differing in virulence factors and plasmid profiles, indicating two possible circulating strains. Shigella isolates exhibited phenotypic and genotypic multidrug resistance, including against trimethoprim, aminoglycosides, and beta-lactams. Plasmid-mediated quinolone resistance (qnrS1) was identified in four S. flexneri isolates, with these genes located on the IncFIB(K) plasmid, highlighting the potential for horizontal transmission and spread of quinolone resistance in this region. No phenotypic and genotypic resistance to macrolides, the first-line treatment for Shigella in Zambia, was observed. Interpretation: We report a high burden of Shigella with multidrug resistance, including resistance to fluoroquinolones. These findings highlight the increasing resistance of Shigella to first-line antibiotics and underscore the importance of developing safe and effective vaccines, improving WASH conditions, and ongoing AMR surveillance. Funding: The EDCTP2 program, supported by the European Union, the Faculty for the Future Foundation (FFTF), the Netherlands Organization for Health Research and Development (ZonMw), and Health-Holland AMR-Global, Gloria, and Track-AMR.

Background: Platinum-based chemotherapy is known to cause severe and debilitating hearing loss, but unlike cisplatin, the true incidence of carboplatin-induced hearing loss remains unclear. We evaluated functional hearing outcomes in children receiving carboplatin to determine the incidence and severity of ototoxicity. Procedure: We identified a large cohort of children with cancer treated with carboplatin and graded their audiograms using the SIOP ototoxicity scale. Patients with inadequate audiological follow-up, prior hearing loss, or exposure to cisplatin were excluded. Fishers exact test, logistic regression, and ROC analyses were performed to investigate associations of demographic, treatment, and exposure-related risk factors with incidence of hearing loss. Results: 200 patients were included, all of whom had been treated with carboplatin. Only nine (4.5%) patients developed clinically significant hearing loss (SIOP grade [&ge;]2). Younger age at first exposure to carboplatin was the only significant predictor of hearing loss (OR = 0.7888, p=0.0241). Age [&le;]28 months was significantly associated with hearing loss (OR 12.37, p=0.0042). No other risk factors or exposures were statistically significant. Conclusions: Clinically significant carboplatin-associated hearing loss was uncommon (incidence 4.5%). We show that young age is the single-most important risk factor for hearing loss; of nine children who developed hearing loss, eight were aged [&le;]28 months. Children below this age have twelve-fold higher odds of developing hearing loss compared to those above this age (OR 12.37). These findings will allow physicians to provide more appropriate counselling to families regarding ototoxic risk and support intensified hearing surveillance in young children.

Objective: Readmissions to the PICU are associated with increased morbidity and mortality. A prediction model that can identify children at risk of readmission at the time of transfer can allow providers to intervene and potentially improve patient outcomes. The objective of this study was to derive and validate machine learning models to predict PICU readmission at the time of transfer. Design: Retrospective observational cohort study Setting: Three quaternary care PICUs in the city of Chicago Patients: All children admitted to the PICU between 2012 and 2019. Measurements: The primary outcome was unplanned readmission to the PICU within 48 hours of transfer to the inpatient ward. Predictor variables included vital signs, patient characteristics, and laboratory results. We developed and externally validated four models to predict PICU readmission: logistic regression, elastic net, random forest, and XGBoost. Main Results: This study included 35,601 patients, with readmission rates ranging from 2.2-3.7% by site. The performance of models during internal validation was consistent at the three sites, with the area under the receiver operating characteristic (AUC) values between 0.70 and 0.73 and no difference across the four models. Model performance decreased significantly during external validation (AUCs of 0.60-0.69). The variables most important to the prediction differed at each site. Conclusion: Machine learning models for predicting readmissions to the PICU have limited generalizability. Locally derived models demonstrated modest performance in our study and could potentially inform provider decision-making if prospectively validated. Externally developed models are unlikely to perform well at predicting PICU readmissions.

Introduction: Respiratory infections are a leading cause of morbidity. Newly available vaccines to prevent respiratory syncytial virus (RSV) disease and encouraging clinical progress on vaccines for human metapneumovirus (hMPV) and parainfluenza (PIV) could reduce the disease burden beyond existing influenza and SARS-CoV-2 immunisation programs. However, evidence on the contribution of these viruses to respiratory disease burden across the lifespan remains limited. Methods: We reviewed studies from 01/2002-11/2025 reporting age-stratified, medically attended cases of influenza, and at least one of RSV, hMPV, or PIV, in high-income countries, excluding periods substantially overlapping with the COVID-19 pandemic. Using only studies that tested for all four viruses, we estimated the age-specific proportion of cases that were non-influenza (total across RSV, hMPV and PIV) compared to influenza using a mixed-effects logistic regression model. Results: Following exclusions and screening, 61 studies were included in the primary analysis comprising >500,000 detections of the four viruses. We found that a substantial proportion of medically attended respiratory illness in infants and young children was due to PIV, hMPV and RSV, rather than influenza, with a non-influenza virus proportion of 90.2% (95% CI 85.9-93.2%) in young infants aged 0-6 months. The converse was true for school-aged children, with a non-influenza virus proportion of 34.8% (95% CI 26.5-44.2%) in children aged 5-18 years. In adults aged 65+ years, non-influenza causes of medically attended disease were common at 60.2% (95% CI 50.0-69.5%). Restricting to studies reporting hospitalised cases (n=19) produced broadly similar age-specific trends in relative virus burden contributions. Discussion: We highlight the significant burden of medically attended illness due to PIV, hMPV and RSV across ages, particularly in infant and preschool-aged children and older adults, supporting the need for effective vaccines targeting this burden.