Yuxing Yuan

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.

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.

Progressive aging is known to negatively affect cardiopulmonary function, which increases the risk of developing cardiac/respiratory diseases. However, the relationship between the decline in pulmonary function and aortic arch stiffness in aging is not well understood. This study investigated the correlation between lung function impairment and aortic arch stiffness in male and female C57BL/6 mice from 2 to 52 weeks of age. Lung function was assessed using forced oscillation ventilation and aortic arch stiffness was measured through echocardiography. Our results show a progressive decline in lung function markers such as respiratory system resistance (Rrs) and tissue elastance (H) with age, alongside an increase in inspiratory capacity (IC) and compliance of the respiratory system (Crs). Aortic arch stiffness significantly increased with age, particularly during early adulthood, and was found to be a strong predictor of lung function impairment in both sexes. While linear regression models indicated that body weight was a more accurate predictor of lung function variability, aortic arch stiffness emerged as a reliable marker for the decline in pulmonary function. These findings suggest that aortic arch stiffness can serve as an early indicator of declining lung function and therefore provide a noninvasive method to assess cardiopulmonary health in aging populations. Future studies should explore the molecular mechanisms underlying these changes and extend the investigation to older mice to fully understand the long‐term impacts of aging on cardiopulmonary function.

Background: Pediatric cardiomyopathies are rare but life-threatening conditions with high mortality. Limited data exists on their clinical features and risk factors, especially in Asian populations, highlighting the need for further research in this area.Methods: This retrospective cohort study analyzed data from 212 pediatric patients diagnosed with hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RCM), or restrictive phenotype hypertrophic cardiomyopathy (RP-HCM) at a single center in China from October 2012 to October 2023, with follow-up until October 31, 2024. Demographic, clinical, and diagnostic data, as well as follow-up outcomes, were reviewed. Logistic and Cox regression models identified risk factors for in-hospital and long-term mortality.Results: Among the 212 patients, 79.72% (169/212) had HCM, 16.98% (36/212) had RCM, and 3.30% (7/212) had RP-HCM. Infection (75.47%, 160/212) and heart failure (51.42%, 109/212) were common comorbidities. In-hospital mortality was 5.19% (11/212), with follow-up mortality of 20.28% (43/212). The independent risk factors for mortality included left ventricular ejection fraction (LVEF), pulmonary hypertension, and low-density lipoprotein (LDL) levels (P < 0.05). Patients with RP-HCM showed the poorest outcomes, with a follow-up mortality rate of 42.86%. Only 10.4% (22/212) of patients underwent genetic testing, yet the positive detection rate was 63.7% (14/22).Conclusions: This study underscores the importance of early diagnosis, genetic testing, and integrated management in pediatric cardiomyopathies. LVEF, pulmonary hypertension, and LDL levels are critical prognostic factors, offering insights for risk assessment and management in affected children.

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.