To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification and early intervention. Using the Pediatric Intensive Care (PIC) database, we analyzed data from 3,624 children with AKI admitted between 2010 and 2018. Nine machine learning algorithms, including CatBoost, were trained to predict mortality, with feature importance assessed via SHapley Additive exPlanations (SHAP). Time-to-event analyses, including Kaplan-Meier and restricted cubic spline methods, examined the temporal impact of predictors on 28-day mortality, stratified by age and AKI stage. CatBoost achieved the highest area under the curve (AUC) values: 0.871 (95% CI: 0.824–0.918) for 7-day, 0.871 (95% CI: 0.829–0.913) for 14-day, and 0.867 (95% CI: 0.829–0.905) for 28-day mortality. Lactate was the top predictor across all models. Time-to-event analyses revealed a linear association between elevated lactate (cut-off: 1.5 mmol/L) and 28-day mortality (p-overall < 0.001), with stronger effects in infants (0–3 years) and AKI stage 1 patients (HR > 1). Machine learning, particularly CatBoost, combined with survival analysis, accurately predicts AKI-related mortality in critically ill children, with lactate as a pivotal marker. These findings support precision risk stratification and early lactate-targeted interventions, though multicenter validation is needed for clinical adoption.

Lyme disease, caused by Borrelia burgdorferi and transmitted by blacklegged ticks (Ixodes species), is the most common vector-borne disease in the United States. Its spatiotemporal dynamics are influenced by environmental and socioeconomic factors, yet the impacts of the COVID-19 pandemic on Lyme disease remain unclear. We analyzed county-level Lyme disease surveillance data (2001−2022) alongside environmental, socioeconomic, and tick vector data. Using machine learning models (Random Forest, Boosted Regression Trees, and XGBoost) and Shapley Additive Explanations (SHAP), we evaluated the influence of key predictors on Lyme disease risk. Predicted cases for 2020–2022 were compared with actual reports to assess the pandemic's effects. Lyme disease cases rose from 16,862 in 2001 to 61,802 in 2022, with geographic expansion into southeastern regions. Population density, ecological niche of I. scapularis, and maximum temperature were presented as the key predictors of disease risk. The COVID-19 pandemic severely disrupted reporting dynamics, with 2020 and 2021 cases falling 43.9 % (95 % CI: 41.2–46.7 %) and 22.0 % (95 % CI: 19.5–24.5 %) below predictions, respectively—a decline most pronounced in the Northeast and linked to reduced healthcare access and outdoor activity during lockdowns. Our findings highlight the complex interactions of environmental, socioeconomic, and behavioral factors in Lyme disease dynamics, including the significant impact of the COVID-19 pandemic on disease reporting. These insights underscore the need for integrated, data-driven public health strategies to mitigate Lyme disease risk in the United States.

The coronavirus disease 2019 (COVID-19) pandemic profoundly disrupted the global epidemiology of respiratory syncytial virus (RSV), leading to atypical off-season surges and altering infection dynamics across different climatic zones. This review synthesizes evidence on the landscape of pediatric RSV co-infections in this transformed post-pandemic context. RSV co-infection is frequent, with human rhinovirus (HRV) being the most common viral co-pathogen and Streptococcus pneumoniae (Spn) and Haemophilus influenzae (Hi) predominating as bacterial co-infections. Critically, these co-infections are significantly associated with heightened disease severity, including more intense clinical presentations, prolonged hospitalizations, increased intensive care unit (ICU) admission rates, and greater therapeutic complexity. The relaxation of non-pharmaceutical interventions has been linked to a rebound in co-infection rates. While advances in molecular diagnostics have improved detection, and new prophylactics like nirsevimab offer promise, significant challenges remain. These include gaps in understanding pathogenic synergies, inequities in access to novel interventions, and the need for strategies to manage the ongoing evolution of RSV epidemiology. This underscores the necessity for enhanced surveillance, equitable prevention, and targeted research to mitigate the substantial burden of pediatric RSV co-infections.

Serratia marcescens (S. marcescens) is a gram-negative opportunistic pathogen causing healthcare-associated infections in neonatal intensive care

Background: Non-communicable diseases (NCDs) have surpassed infectious diseases as the leading cause of disability and mortality globally. However, the burden of NCDs among children and adolescents in the Asia-Pacific region remains underexplored. This study evaluates changes in NCD burden among individuals aged 0–19 years in the Asia-Pacific region from 1990 to 2021. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2021 study, we estimated deaths, disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) with 95% uncertainty intervals (UIs). We analyzed changes in disease burden by age, sex, location, and socio-demographic index (SDI) between 1990 and 2021. Results: In 2021, NCDs accounted for a YLD rate of 56488.99 (95% UI: 40849.26–75780.79) and a death rate of 356.45 (95% UI: 280.27–433.27) per 100,000 population among children and adolescents aged 0–19 years. Other NCDs were the leading cause of death (167.08 [95% UI: 116.63–216.90]), YLLs (14584.60 [95% UI: 10126.88–18,962.14]), and DALYs (20327.20 [95% UI: 14815.25–26238.15]) per 100,000, while mental disorders led in YLDs. Death rates were higher in males, but DALYs were higher in females. From 1990 to 2021, NCD death rates decreased by 44.63% (from 643.71 [95% UI: 508.48–758.86] to 356.45 [95% UI: 280.27–433.27]) and YLLs by 45.49%. However, mental disorder-related deaths, YLLs, and DALYs increased by 29.26%, 29.16%, and 10.07%, respectively. Lower SDI countries reported higher NCD burdens, particularly for other NCDs. Conclusions: While the NCD burden among children and adolescents in the Asia-Pacific region decreased significantly from 1990 to 2021, the rising burden of mental disorders is a critical public health concern.

Background/Objectives: Acute respiratory failure (ARF) is associated with a high mortality. This study aimed to explore the association of arterial partial pressure of carbon dioxide (PaCO₂) in relation to survival outcomes in mechanically ventilated patients with ARF. Methods: This multicenter retrospective cohort study integrated the data from the eICU Collaborative Research Database (eICU-CRD; n = 10,946), the Medical Information Mart for Intensive Care IV (MIMIC-IV; n = 6683), and clinical records from two university-affiliated intensive care units in China (n = 410). The patients were categorized into low, normal, and high PaCO₂ groups using a restricted cubic spline model to explore the relationship between PaCO₂ and mortality. The 28-day survival distributions among the three groups were compared using Kaplan–Meier curves, with statistical significance assessed via the log-rank test. A multivariable Cox proportional hazards model was constructed to evaluate the independent prognostic value of PaCO₂ for multiple complications. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for the low and high PaCO₂ groups relative to the normal PaCO₂ group. Results: A U-shaped relationship was observed between PaCO₂ and mortality, with both low PaCO₂ (57.9 mmHg) associated with an increased mortality risk. Kaplan–Meier survival analysis demonstrated that patients in the intermediate PaCO₂ range (36.4–57.9 mmHg) exhibited the highest survival rate (65.2%), whereas those in the low and high PaCO₂ groups had significantly lower survival rates (60.0% and 63.2%) (log-rank test, p < 0.001). Adjusted survival analyses further revealed that complications such as sepsis and chronic kidney disease significantly influenced the mortality across PaCO₂ strata. Compared with the intermediate PaCO₂ group, the hazard of death increased by 25.5% in the low PaCO₂ group and by 18.9% in the high PaCO₂ group. Conclusions: This retrospective analysis indicates that arterial PaCO₂ levels within the optimal range are associated with improved survival in patients with acute respiratory failure (ARF) on mechanical ventilation, but prospective studies are needed to establish causality and consider potential confounding factors.