We conducted a single-center retrospective analysis of children hospitalized for DCM at our institution between January 2012 and January 2023. Eligibility criteria included left ventricular dilation [left ventricular end-diastolic dimension (LVEDD) Z-score >2] and left ventricular systolic dysfunction (LVEF <55%) (5). Due to varying effects of SUA levels across different types of HF, we excluded patients with mixed DCM, such as hypertrophic, restrictive, or noncompaction cardiomyopathy. Our focus was on children with primary DCM (5); thus, we excluded those with congenital left-to-right shunt heart disease, myocarditis, coronary artery disease, or metabolic diseases. Infants younger than 1 month were excluded to eliminate the influence of maternal factors. Additionally, patients with severe kidney disease and those missing SUA levels were not included. The final cohort consisted of 145 pediatric patients hospitalized for DCM who met the inclusion criteria. The study was approved by the research ethics committee of the First Affiliated Hospital of Guangxi Medical University (approval number: 2023-E478-01). Informed consent was obtained from the parents or guardians of all participants.

Baseline data were collected from initial hospitalization records, encompassing (1) demographics such as sex, age, and prior HF diagnosis; (2) physical examination findings at admission, including New York Heart Association (NYHA)/Ross classification and body mass index (BMI); (3) laboratory indicators and echocardiographic findings (Table 1); and (4) discharge medications, including renin-angiotensin-aldosterone system inhibitors, digoxin, diuretics, and β-blockers. For patients with multiple admissions, only data from the first admission were used to avoid confounding factors. Laboratory data were collected within 24 h, and echocardiography and electrocardiography data were gathered within 48 h of admission. The LVEDD was normalized using age- and body surface area-specific Z-scores. The LVEF was calculated from the parasternal long-axis view using the Teichholz method.

The primary outcome was all-cause mortality or heart transplantation, assessed at 1 year and during long-term follow-up (maximum duration: 108.4 months). Follow-ups included telephone interviews and regular outpatient clinic visits. Information on deaths was also obtained from provincial registries for children lost to follow-up.

Participants were categorized into tertiles based on their SUA levels. Baseline characteristics were detailed according to these tertiles. Group differences were evaluated using statistical tests appropriate for the data type. Specifically, categorical variables were assessed with the chi-squared test, normally distributed variables with one-way analysis of variance, and skewed variables with Kruskal–Wallis tests. Characteristics are presented as mean ± standard deviation, median with interquartile range (IQR), or number (n) with percentage (%), as suitable. Kaplan–Meier cumulative incidence curves were created for SUA level tertiles and compared using the log-rank test.

To examine the association between SUA levels and all-cause mortality at 1 year and maximum follow-up, as well as the dose-response relationship, we used multivariate Cox regression models and restricted cubic spline (RCS) models. Covariates for the regression model were chosen based on their clinical relevance and univariate analysis results (Supplementary Tables S1, S2). Before multivariate analysis, significant univariate variables were checked for collinearity using a tolerance cutoff of <0.02 and a variance inflation factor cutoff of >5 (Supplementary Tables S3). Non-collinear variables were included in the multiple regression model and reported as hazard ratios (HRs) with 95% confidence intervals (CIs) and corresponding p-values.

Three multivariate Cox regression models were adjusted for different covariates: Model 1 was unadjusted; Model 2 was adjusted for age and sex; and Model 3 was adjusted for Model 2 plus BMI, serum creatinine (SCr), blood urea nitrogen (BUN) levels, and LVEF. SUA levels were analyzed as continuous or categorical variables in tertiles. When treated as a continuous variable, SUA levels were log-transformed (base 2) to minimize the influence of outliers, and the data were presented as per log2 unit increase. Multivariate Cox regression models were constructed using the baseline SUA tertiles, with the lowest SUA tertile as the reference group. Variables with more than 10% missing values were excluded, while those with less than 10% missing values were imputed using the mean.

Subgroup analyses were stratified by relevant covariates, including sex, age, NYHA/Ross score, LVEF, and estimated glomerular filtration rate (eGFR). A cutoff age of 10 years was used for stratification as it represents the onset of adolescence. Interactions among subgroups were assessed using likelihood ratio (LR) tests.

All statistical analyses were conducted using SPSS (version 27.0; IBM Inc., New York, NY, USA) and R Statistical Software version 4.2.0 (http://www.R-project.org; R Foundation).

We analyzed data from 145 patients with a median age of 5.7 years [interquartile range (IQR): 1.0–11.6]. Among these patients, 89 (61.4%) were male, and 56 (38.6%) were female. Forty-nine patients (33.8%) exhibited NYHA class III or IV symptoms, and 25 (15.9%) had a history of HF. Patients in the highest SUA tertile were generally younger and had worse SCr, BUN levels, and LVEF at admission (P < 0.05). The types of medications prescribed at discharge were similar across the tertiles, with digoxin, diuretics, and RAASi being more commonly used, while β-blockers were mostly prescribed post-discharge. Table 1 outlines the participants' baseline characteristics and their associations with SUA tertiles.

As shown in Table 1, the SUA tertiles were categorized as follows: lowest (1st tertile) 70–266 µmol/L, median (2nd tertile) 266–415 µmol/L, and highest (3rd tertile) 415–1,015 µmol/L. Figure 1 illustrates that SUA levels varied by age and sex. In children under 10 years, the mean SUA levels increased almost linearly with no significant differences between sexes. However, in males aged 10 years and older, SUA levels rose rapidly with considerable fluctuations, while in females, the mean SUA levels plateaued around age 13 and then declined.

In this cohort of 145 patients, the median follow-up period was 4.0 months (IQR: 6.2–108.4 months). The all-cause mortality rate was 31% (45 patients) at 1 year and 44.8% (65 patients) at the maximum follow-up. None of the patients underwent heart transplantation. Kaplan–Meier estimates for 1-year and maximum follow-up periods revealed significant differences in the incidence of all-cause mortality among the SUA tertiles during the follow-up period (P < 0.01) (Figures 2A,B).

To identify independent predictors of mortality risk and analyze the dose-response relationship, multivariate Cox regression analyses were conducted (Table 2). After adjusting for age, sex, BMI, SCr and BUN levels, and LVEF, SUA levels were found to be independently associated with mortality at 1 year (HR = 2.66 per log2 unit increase) and during the maximum follow-up period (HR = 1.97 per log2 unit increase). Compared to the lowest SUA tertile, the highest SUA tertile was linked to a higher incidence of all-cause mortality at 1 year (HR = 4.26, 95% CI: 1.5–12.06) and during the maximum follow-up (HR = 2.56, 95% CI: 1.06–6.16), after adjusting for age, sex, BMI, SCr, BUN, and LVEF (Table 1). A dose-response relationship was evident in each model (P for trend < 0.05). No significant differences in all-cause mortality were found between the lowest and median SUA tertiles.

Figure 3A illustrates the RCS models, which revealed an inverted L-shaped association between baseline SUA levels and all-cause mortality risk. Further age-stratified analysis in 10-year intervals showed notable differences in the curve trajectories (Figures 3B,C). For individuals under 10 years old, a clear linear relationship was observed, with SUA levels up to 278.5 μmol/L correlating with a higher risk of mortality. In contrast, for individuals aged 10 years and older, the relationship between SUA and mortality approximated a U-shaped curve, with the lowest risk of all-cause mortality occurring at an SUA of 466 μmol/L.

In the subgroup analysis stratified by sex, age, NYHA/Ross score, LVEF, and eGFR, each log2 unit increase in SUA concentration showed a significant age-related modification effect (P < 0.05) (Figures 4A,B). Interactions across the subgroups were tested using the likelihood ratio test. Among participants younger than 10 years, each log2 unit increase in SUA concentration significantly increased the risk of mortality. However, for participants older than 10 years, an increase in SUA concentrations did not significantly reflect this risk.