Risk factors for hyperuricemia in congenital heart disease patients and its relation to cardiovascular death

Clinical impact of circulating biomarkers in prediction of adverse cardiac events in patients with congenital heart disease. A systematic review

INTRODUCTION

Patients with congenital heart disease (ConHD) are at increased risk for adverse cardiac events. Predicting long-term outcomes and guidance of patient management might benefit from a range of (new) biomarkers. This is a rapidly evolving field with potentially large consequences for clinical decision making. With a systematic review of available biomarkers in ConHD we identified the clinical role of these markers, knowledge gaps and future research directions.

METHODS

We systematically reviewed the literature on associations between blood biomarkers and outcome measures (mortality or composite adverse outcomes in patients with ConHD.

RESULTS

The inclusion criteria were met by 102 articles. Biomarkers assessed in more than 3 studies are discussed in the main text, those studied in 3 or less studies are summarized in the supplement. Thus, we discuss 15 biomarkers from 92 studies. These biomarkers were studied in 32,399 / 10,735 patients for the association with mortality and composite adverse outcomes, respectively. Biomarkers that were studied most and had statistically significant associations with mortality or composite adverse outcomes were (NT-pro)BNP, MELD-XI score, Hs-CRP, creatinine, albumin and sodium. Most of these biomarkers are involved in intracardiac processes associated with inflammation or are markers of renal function.

CONCLUSION

For (NT-pro)BNP, clinical value for prediction of mortality and composite adverse outcomes in adult and paediatric ConHD has been shown. For MELD-XI, hs-CRP, albumin, creatinine, sodium, RDW, and GDF-15, correlations with mortality and composite adverse outcomes have been demonstrated in patient groups with mixed types of ConHD, but clinical utility needs additional exploration.

Analysis and Validation of Tyrosine Metabolism-related Prognostic Features for Liver Hepatocellular Carcinoma Therapy

AIMS

To explore tyrosine metabolism-related characteristics in liver hepatocellular carcinoma (LIHC) and to establish a risk signature for the prognostic prediction of LIHC. Novel prognostic signatures contribute to the mining of novel biomarkers, which are essential for the construction of a precision medicine system for LIHC and the improvement of survival.

BACKGROUND

Tyrosine metabolism plays a critical role in the initiation and development of LIHC. Based on the tyrosine metabolism-related characteristics in LIHC, this study developed a risk signature to improve the prognostic prediction of patients with LIHC.

OBJECTIVE

To investigate the correlation between tyrosine metabolism and progression of LIHC and to develop a tyrosine metabolism-related prognostic model.

METHODS

Gene expression and clinicopathological information of LIHC were obtained from The Cancer Genome Atlas (TCGA) database. Distinct subtypes of LIHC were classified by performing consensus cluster analysis on the tyrosine metabolism-related genes. Univariate and Lasso Cox regression were used to develop a RiskScore prognosis model. Kaplan-Meier (KM) survival analysis with log-rank test and area under the curve (AUC) of receiver operating characteristic (ROC) were employed in the prognostic evaluation and prediction validation. Immune infiltration, tyrosine metabolism score, and pathway enrichment were evaluated using single-sample gene set enrichment analysis (ssGSEA). Finally, a nomogram model was developed with the RiskScore and other clinicopathological features.

RESULTS

Based on the tyrosine metabolism genes in the TCGA cohort, we identified 3 tyrosine metabolism-related subtypes showing significant prognostic differences. Four candidate genes selected from the common differentially expressed genes (DEGs) between the 3 subtypes were used to develop a RiskScore model, which could effectively divide LIHC patients into high- and lowrisk groups. In both the training and validation sets, high-risk patients tended to have worse overall survival, less active immunotherapy response, higher immune infiltration and clinical grade, and higher oxidative, fatty, and xenobiotic metabolism pathways. Multivariate analysis confirmed that the RiskScore was an independent indicator for the prognosis of LIHC. The results from pan-- cancer analysis also supported that the RiskScore had a strong prognostic performance in other cancers. The nomogram demonstrated that the RiskScore contributed the most to the prediction of LIHC prognosis.

CONCLUSION

Our study developed a tyrosine metabolism-related risk model that performed well in survival prediction, showing the potential to serve as an independent prognostic predictor for LIHC treatment.

Using Innovative Machine Learning Methods to Screen and Identify Predictors of Congenital Heart Diseases

Objective: Congenital heart diseases (CHDs) are associated with an extremely heavy global disease burden as the most common category of birth defects. Genetic and environmental factors have been identified as risk factors of CHDs previously. However, high volume clinical indicators have never been considered when predicting CHDs. This study aimed to predict the occurrence of CHDs by considering thousands of variables from self-reported questionnaires and routinely collected clinical laboratory data using machine learning algorithms.

Methods: We conducted a birth cohort study at one of the largest cardiac centers in China from 2011 to 2017. All fetuses were screened for CHDs using ultrasound and cases were confirmed by at least two pediatric cardiologists using echocardiogram. A total of 1,127 potential predictors were included to predict CHDs. We used the Explainable Boosting Machine (EBM) for prediction and evaluated the model performance using area under the Receive Operating Characteristics (ROC) curves (AUC). The top predictors were selected according to their contributions and predictive values. Thresholds were calculated for the most significant predictors.

Results: Overall, 5,390 mother-child pairs were recruited. Our prediction model achieved an AUC of 76% (69-83%) from out-of-sample predictions. Among the top 35 predictors of CHDs we identified, 34 were from clinical laboratory tests and only one was from the questionnaire (abortion history). Total accuracy, sensitivity, and specificity were 0.65, 0.74, and 0.65, respectively. Maternal serum uric acid (UA), glucose, and coagulation levels were the most consistent and significant predictors of CHDs. According to the thresholds of the predictors identified in our study, which did not reach the current clinical diagnosis criteria, elevated UA (>4.38 mg/dl), shortened activated partial thromboplastin time (<33.33 s), and elevated glucose levels were the most important predictors and were associated with ranges of 1.17-1.54 relative risks of CHDs. We have developed an online predictive tool for CHDs based on our findings that may help screening and prevention of CHDs.

Conclusions: Maternal UA, glucose, and coagulation levels were the most consistent and significant predictors of CHDs. Thresholds below the current clinical definition of “abnormal” for these predictors could be used to help develop CHD screening and prevention strategies.

Relationship of uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide with acute cerebral infarction

OBJECTIVE

The objective was to study the relationship of serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels with acute cerebral infarction.

METHODS

A total of 96 acute cerebral infarction patients were divided into small, middle, and large infarct size groups based on the size of infarct focus and mild, moderate, and severe infarction groups based on the evaluation criteria of nerve defect degree. In addition, 75 healthy people were selected as the control group. The serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels of all subjects were detected.

RESULTS

The serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels in the acute cerebral infarction group were significantly higher than the control group (p<0.05). Compared with the small infarct size group, each index in middle and large infarct size groups was significantly increased (p<0.05). Compared with the middle infarct size group, each index in the large infarct size group was significantly increased (p<0.05). The serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels in moderate and severe infarction groups were significantly higher than the mild infarction group (p<0.05). Compared with the moderate infarction group, each index in the severe infarction group was significantly increased (p<0.05). The serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels were positively correlated with the infarct size and nerve defect degree (p<0.05).

CONCLUSIONS

The serum uric acid, C-reactive protein, and N-terminal pro-B-type natriuretic peptide levels are closely correlated with the occurrence and development of acute cerebral infarction. The detection of these indexes has significance for understanding the severity of acute cerebral infarction, guiding the individual treatment scheme, and evaluating the prognosis.

Rasburicase versus intravenous allopurinol for non-malignancy-associated acute hyperuricemia in paediatric cardiology patients

OBJECTIVES

Limited data exist for management of hyperuricemia in non-oncologic patients, particularly in paediatric cardiac patients. Hyperuricemia is a risk factor for acute kidney injury and may prompt treatment in critically ill patients. The primary objective was to determine if rasburicase use was associated with greater probability normalisation of serum uric acid compared to allopurinol. Secondary outcomes included percent reduction in uric acid, changes in serum creatinine, and cost of therapy.

DESIGN

A single-centre retrospective chart review.

SETTING

A 20-bed quaternary cardiovascular ICU in a university-based paediatric hospital in California.

PATIENTS

Patients admitted to cardiovascular ICU who received rasburicase or intravenous allopurinol between 2015 and 2016.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Data from a cohort of 14 patients receiving rasburicase were compared to 7 patients receiving IV allopurinol. Patients who were administered rasburicase for hyperuricemia were more likely to have a post-treatment uric acid level less than 8 mg/dl as compared to IV allopurinol (100 versus 43%; p = 0.0058). Patients who received rasburicase had a greater absolute reduction in post-treatment day 1 uric acid (-9 mg/dl versus -1.9 mg/dl; p = 0.002). There were no differences in post-treatment day 3 or day 7 serum creatinine or time to normalisation of serum creatinine. The cost of therapy normalised to a 20 kg patient was greater in the allopurinol group ($18,720 versus $1928; p = 0.001).

CONCLUSION

In a limited paediatric cardiac cohort, the use of rasburicase was associated with a greater reduction in uric acid levels and associated with a lower cost compared to IV allopurinol.

Hyperuricemia in Children and Adolescents: Present Knowledge and Future Directions

Recent evidence suggests that hyperuricemia is an important condition in children and adolescents, particularly in association with noncommunicable diseases. This review aims to summarize our current understanding of this condition in pediatric patients. An analysis of serum uric acid reference values in a healthy population indicates that they increase gradually with age until adolescence, with differences between the sexes arising at about 12 years of age. This information should be taken into consideration when defining hyperuricemia in studies. Gout is extremely rare in children and adolescents, and most patients with gout have an underlying disease. The major causes of hyperuricemia are chronic conditions, including Down syndrome, metabolic or genetic disease, and congenital heart disease, and acute conditions, including gastroenteritis, bronchial asthma (hypoxia), malignant disorders, and drug side effects. The mechanisms underlying the associations between these diseases and hyperuricemia are discussed, together with recent genetic information. Obesity is a major cause of hyperuricemia in otherwise healthy children and adolescents. Obesity is often accompanied by metabolic syndrome; hyperuricemia in obese children and adolescents is associated with the components of metabolic syndrome and noncommunicable diseases, including hypertension, insulin resistance, dyslipidemia, and chronic kidney disease. Finally, strategies for the treatment of hyperuricemia, including lifestyle intervention and drug administration, are presented.