Background: Although heart failure is a well‐known major global public health concern, the general understanding of the clinical status of pediatric heart failure (PHF) is inadequate. Therefore, this study aims to enhance the general understanding of clinical characteristics across different PHF age groups and provide references for improving PHF treatment strategies. Methods: This multicenter retrospective cohort study involved patients from 20 Chinese provinces, primarily including hospitalized patients (aged ≤18 years) diagnosed with heart failure between January 2013 and December 2022. The study subjects were categorized into 4 groups: neonatal, infant and toddler, young children, and adolescent. Results: Herein, 2903 hospitalized patients with PHF were included. Significant differences were observed across age groups in clinical characteristics, auxiliary examination results, comorbid diagnoses, and hospitalization outcomes. After adjusting for covariates, the odds of in‐hospital death were significantly lower in the infant and toddler (odds ratio [OR], 0.46 [95% CI, 0.25–0.85]), young children (OR, 0.39 [95% CI, 0.18–0.85]), and adolescent (OR, 0.34 [95% CI, 0.13–0.87]) groups compared with the neonatal group. Furthermore, the odds of cardiovascular adverse events were significantly higher in the young children (OR, 1.91 [95% CI, 1.62–2.88]) and adolescent (OR, 2.16 [95% CI, 1.15–4.06]) groups compared with the neonatal group. Additionally, regarding the odds of a bad Ross class, the adolescent group had 1.85 times higher odds (95% CI, 1.11–3.09) compared with the neonatal group, 2.36 times (95% CI, 1.67–3.35) higher odds compared with the infant and toddler group, and 1.45 times (95% CI, 1.05–2.02) higher odds compared with the young children group ( P <0.05). Conclusions: This study emphasizes the importance of age‐specific stratification in PHF management, revealing distinct clinical and prognostic differences across various developmental stages. Registration: URL: https://www.chictr.org.cn . Unique identifier: ChiCTR2300078262.

Cardiovascular disease (CVD) is the leading global cause of death and health loss. The epidemiology and factors influencing CVD in children are unique, making it essential to first evaluate current and future trends to guide interventions and reduce the disease burden. To analyze the incidence, mortality, and disability-adjusted life years (DALY) of CVD in children aged 0–14 from 1990 to 2021, and explore global disease burden, risk factors, and trends over the next 30 years. The study focuses on China, Japan, South Korea, India, and Singapore to aid in developing targeted prevention and treatment strategies. Using data from the Global Burden of Disease Study (GBD) 1990–2021, we assessed age- and sex-specific morbidity, mortality, and DALY of CVD in Asian children aged 0–14 and computed the EAPC. We analyzed risk factors, specific causes, and projected prevalence trends through 2050 using the Bayesian Age-Period-Cohort (BAPC) model. From 1990 to 2021, CVD incidence among Asian children aged 0–14 decreased by 8.03 % (95 % UI:13.63 to -4.02). Mortality saw a significant drop of 67.98 % (95 % UI:73.73 to -62.23), with the greatest decline in children aged 2–4, and the highest death rate in those under 1 year. Disability and mortality patterns were similar across gender, age, etiology, and overall trends. In 2021, South Asia had the highest rates of morbidity, mortality, and disability. Rates varied significantly, with Mongolia exhibiting the highest rate and Cyprus the lowest, showing a sixfold difference. Rheumatic heart disease (RHD) and intracerebral hemorrhage were the most critical diseases needed attention. Abnormal temperatures were identified as a risk factor associated with CVD outcomes in children. The burden of CVD is projected to increase in various regions and countries across Asia. The burden of CVD continues to challenge children aged 0–14 in Asia. Enhancing our understanding of pediatric CVD epidemiology, addressing risk factors, and reinforcing prevention and control measures are essential for reducing this burden.

Background: Pediatric heart failure (PHF) remains a major contributor to morbidity and mortality, yet standardized diagnostic and prognostic frameworks–particularly those leveraging left ventricular ejection fraction (LVEF)–are not well-established. This study evaluates clinical profiles, therapeutic interventions, and mortality outcomes across LVEF thresholds while identifying an optimal cutoff to refine risk stratification in PHF. Methods: This multicenter retrospective cohort study analyzed 1449 PHF patients (aged 1–18 years) across 30 tertiary centers (2013–2022). LVEF stratification employed conventional thresholds (50%, 55%) and an ROC-optimized cutoff (53%, derived via Youden index maximization). The primary outcome was in-hospital all-cause mortality. Multivariable logistic regression models, adjusted for clinical covariates, evaluated mortality predictors. The discriminative performance of LVEF thresholds was compared using area under the curve (AUC) analysis. Results: Distinct clinical profiles, etiologies, and treatments were observed across LVEF strata (50% vs. 55%; p < 0.05). A data-driven optimized LVEF threshold of 53% was identified for mortality prediction, demonstrating superior diagnostic accuracy with enhanced sensitivity and specificity across age groups. Multivariate analysis revealed LVEF ≥ 55% as protective (OR = 0.81, 95% CI: 0.68–0.96, p = 0.003), while ≥50% was non-significant (OR = 0.91, 95% CI: 0.74–1.12, p = 0.06). Elevated BNP (OR = 2.78, p < 0.001) and NT-proBNP (OR = 2.34, p < 0.001) strongly correlated with mortality risk. Age and sex showed no significant association with outcomes. Conclusion: In conclusion, an LVEF of 53% emerged as the optimal pediatric threshold for mortality prediction, outperforming conventional cutoffs of 50% and 55%. The integration of LVEF with biomarkers (BNP/NT-proBNP) provides a robust prognostic framework, underscoring the necessity for pediatric-specific LVEF criteria and multidimensional risk assessment in PHF management.

Background: Pediatric heart failure (PHF) is a lethal syndrome with a distinct pathophysiology from adult heart failure, posing a significant public health challenge in China. However, the impact of the nation’s profound geospatial healthcare disparities on this vulnerable population remains unquantified. This national multicenter cohort study aimed to systematically examine the association between geographic location and PHF patient profiles, management, and survival outcomes. Methods: We conducted a retrospective analysis of 2,903 pediatric inpatients (≤18 years) with a primary HF diagnosis from 30 centers (2013–2022). Patients with >20% missing data were excluded. Geospatial analysis stratified cohorts into Eastern, Western, and Central China. The primary outcome was in-hospital mortality, analyzed using multivariable logistic regression adjusted for key clinical confounders including age, etiology, and disease severity. Length of stay (LOS) was analyzed using a Gamma generalized linear model. All analyses were performed using Python (version 3.12). Results: Profound geospatial disparities were identified. Western patients presented significantly younger (median 6.93 months) with a higher prevalence of complex congenital heart disease (39.2%) and more severe clinical status (85.9% ROSS Class III-IV). In contrast, cardiomyopathy was the dominant etiology in the East (42.2%). Utilization of guideline-directed medical therapy (GDMT) was lowest in non-Eastern regions. Critically, geographic region was independently associated with mortality. Compared to the East, the adjusted odds of death were 2.58-fold higher in the West (95% CI: 1.5–4.45) and 3.54-fold higher in the Central region (95% CI: 2.11–5.94). Conclusion: This study provides robust, national-level evidence that geographic location in China is a potent independent predictor of survival for children with heart failure, revealing a tiered healthcare landscape. These findings underscore an urgent public health imperative for targeted interventions to mitigate these disparities and establish equitable care systems through regional capacity building and standardized referral pathways.

Background: Pediatric heart failure (PHF) is a heterogeneous syndrome with high morbidity, but existing classification systems inadequately capture its developmental and pathophysiological complexity due to reliance on adult-centric parameters. Using machine learning, we aimed to identify clinically distinct PHF phenotypes with unique outcomes and therapeutic implications. Methods: In this multicenter retrospective study, we analyzed 2903 consecutive PHF patients (≤18 years) from 30 Chinese tertiary centers from 20 provinces (2013–2022). Unsupervised machine learning (k-means clustering with PCA) evaluated 99 clinical, biomarker, and echocardiographic variables to derive phenotypes, which were compared for mortality, hospitalization, and treatment responses. Results: Three phenotypically distinct clusters emerged. Cluster 1 (Chronic Hypertensive and Cardiorenal Profile, 30.1%) predominantly affected older children (78%) with hypertension (54.4%), renal dysfunction (creatinine 45.8 μmol/L), and ventricular tachycardia (53.8%). This cluster showed the lowest in-hospital mortality (2.5%) but frequent 7–14 day hospitalizations (35.8%) and the highest beta-blocker use (54.5%). Cluster 2 (Preterm and CHD-Associated HF, 43.4%) comprised preterm infants (71.4%) with congenital heart disease (72.2%) and preserved LVEF (67%), demonstrating the highest mortality (5.1%) and prolonged stays (>30 days: 10.6%) with predominant diuretic (40.6%) and antibiotic use (54.3%). Cluster 3 (Fulminant Myocarditis Profile, 26.5%) exhibited cardiogenic shock with severely reduced LVEF (33%) and elevated BNP (3234 pg/mL), showing bimodal outcomes (4.8% LOS < 3 days vs. 32.2% LOS 15–30 days) and the highest IVIG utilization (46.5%) with intermediate mortality (3.8%). The majority of between-group differences were statistically significant (p < 0.001). Conclusions: Machine learning identified three PHF phenotypes with distinct in-hospital risk profiles and therapeutic implications, challenging current classification systems. These findings highlight the potential for phenotype-specific management strategies and provide a rationale for future research into arrhythmia prevention in hypertensive profiles and early immunomodulation in fulminant myocarditis, while highlighting the need for specialized care pathways for preterm/CHD patients. Prospective validation is warranted to translate this framework into clinical practice.