Novel Biomarkers Improve Prediction of 365-Day Readmission After Pediatric Congenital Heart Surgery

Neonatal multimorbidity and the phenotype of premature aging in preterm infants

Multimorbidity is the co-occurrence of multiple chronic health problems, associated with aging, frailty, and poor functioning. Children born preterm experience more multimorbid conditions in early life compared to term-born peers. Though neonatal multimorbidity is linked to poor health-related quality of life, functional outcomes, and peer group participation, gaps in our theoretical understanding and conceptualization remain. Drawing from life course epidemiology and the Developmental Origins of Heath and Disease models, we offer a framework that neonatal multimorbidity reflects maturational vulnerability posed by preterm birth. The impact of such vulnerability on health and development may be further amplified by adverse exposures and interventions within the environment of the neonatal intensive care unit. This can be exacerbated by disadvantaged home or community contexts after discharge. Uncovering the physiologic and social antecedents of multiple morbid conditions in the neonatal period and their biological underpinnings will allow for more accurate risk-prediction, counseling, and care planning for preterm infants and their families. According to this framework, the maturational vulnerability to multimorbidity imparted by preterm birth and its negative effects on health and development are not predetermined or static. Elucidating pathways of early biologic and physical aging will lead to improvements in care and outcomes. IMPACT: Multimorbidity is associated with significant frailty and dysfunction among older adults and is indicative of early physiologic aging. Preterm infants commonly experience multimorbidities in the newborn period, an underrecognized threat to long-term health and development. We offer a novel framework incorporating multimorbidity, early cellular aging, and life course health development to innovate risk-prediction, care-planning, and therapeutics.

The Role of Galectin-3 in Predicting Congenital Heart Disease Outcome: A Review of the Literature

Galectin-3 (Gal-3) is a novel pro-fibrotic biomarker that can predict both right and left cardiac dysfunction caused by various cardiovascular conditions. Its expression seems to be progressively altered with evolving cardiac remodeling processes, even before the onset of heart failure. Hence, Gal-3 has been found to be an individual predictor of acute and chronic heart failure or to serve as part of an integrated biomarker panel that can foresee adverse cardiac outcomes. In congenital heart disease (CHD), Gal-3 correlates with cardiac mortality and complications in both children and adults and is proposed as a therapeutic target in order to reverse the activation of pro-fibrosis pathways that lead to heart failure. Positive associations between serum Gal-3 levels, post-operatory hospitalization rates, complications and ventricular dysfunction have also been reported within studies conducted on patients with CHD who underwent corrective surgery. Thus, this review tried to address the potential utility of Gal-3 in patients with CHD and particularly in those who undergo corrective surgery. The heterogeneity of the literature data and the lack of validation of the results obtained by the current studies on larger cohorts cannot be neglected, though. Further longitudinal research is required to establish how Gal-3 can relate to long-term outcomes in pediatric CHD.

Insights and perspectives into clinical biomarker discovery in pediatric heart failure and congenital heart disease-a narrative review

Background and Objective

Heart failure (HF) in the pediatric population is a multi-factorial process with a wide spectrum of etiologies and clinical manifestations, that are distinct from the adult HF population, with congenital heart disease (CHD) as the most common cause. CHD has high morbidity/mortality with nearly 60% developing HF during the first 12 months of life. Hence, early discovery and diagnosis of CHD in neonates is pivotal. Plasma B-type natriuretic peptide (BNP) is an increasingly popular clinical marker in pediatric HF, however, in contrast to adult HF, it is not yet included in pediatric HF guidelines and there is no standardized reference cut-off value. We explore the current trends and prospects of biomarkers in pediatric HF, including CHD that can aid in diagnosis and management.

Methods

As a narrative review, we will analyze biomarkers with respect to diagnosis and monitoring in specific anatomical types of CHD in the pediatric population considering all English PubMed publications till June 2022.

Key Content and Findings

We present a concise description of our own experience in applying plasma BNP as a clinical biomarker in pediatric HF and CHD (tetralogy of fallot vs. ventricular septal defect) in the context of surgical correction, as well as untargeted metabolomics analyses. In the current age of Information Technology and large data sets we also explored new biomarker discovery using Text Mining of 33M manuscripts currently on PubMed.

Conclusions

(Multi) Omics studies from patient samples as well as Data Mining can be considered for the discovery of potential pediatric HF biomarkers useful in clinical care. Future research should focus on validation and defining evidence-based value limits and reference ranges for specific indications using the most up-to-date assays in parallel to commonly used studies.

Circulating biomarkers for management of cancer therapeutics related cardiac dysfunction

Cancer therapeutics related cardiac dysfunction (CTRCD) has emerged as a major cause of morbidity and mortality in cancer survivors. Effective clinical management of CTRCD is impeded by a lack of sensitive diagnostic and prognostic strategies. Circulating molecular markers could potentially address this need as they are often indicative of cardiac stress before cardiac damage can be detected clinically. A growing understanding of the underlying physiological mechanisms for CTRCD has inspired research efforts to identify novel pathophysiologically-relevant biomarkers that may also guide development of cardio-protective therapeutic approaches. The purpose of this review is to evaluate current circulating biomarkers of cardiac stress and their potential role in diagnosis and management of CTRCD. We also discuss some emerging avenues for CTRCD-focused biomarker investigations.

A Scoping Review of Galectin-3 as a Biomarker of Cardiovascular Diseases in Pediatric Populations

Galectin-3 as a cardiac biomarker has proven to be a significant prognostic tool in adults. However, it has not yet been established in the pediatric population as a biomarker in daily clinical practice. The aim of the study was to summarize the current knowledge on galectin-3 as a biomarker in children with cardiac conditions by reviewing the literature. Bibliographic databases such as PubMed, Web of Science and Embase were searched, and consequently twelve articles met the inclusion criteria. Supplemental handsearching of references delivered one additional source. These prospective studies concerning galectin-3 as a cardiac biomarker present analyses performed in cohorts composed of healthy children and children with cardiovascular diseases. The results, despite being based on small cohort studies, inform that galectin-3 could serve as a potential biomarker in cardiovascular risk stratification in children with heart failure, arrhythmia, Kawasaki disease or in patients undergoing cardiac surgery. The evidence for the usefulness of galectin-3 in the assessment of such pathologies as idiopathic dilated cardiomyopathy, coarctation of the aorta, functionally univentricular heart or tetralogy of Fallot were not completely confirmed. Galectin-3 seems to be a promising biomarker; however, there is a need for further research to establish its use in daily clinical practice.

The Society of Thoracic Surgeons Congenital Heart Surgery Database: 2021 Update on Outcomes and Research

The Society of Thoracic Surgeons Congenital Heart Surgery Database is a comprehensive clinical outcomes registry that captures almost all pediatric cardiac surgical operations in the United States. It is the platform for all activities of The Society of Thoracic Surgeons related to the analysis of outcomes and improvement of quality in this subspecialty. This report summarizes current aggregate national outcomes in congenital and pediatric cardiac surgery performed between July 1, 2016, and June 30, 2020. The reported data on aggregate national outcomes are exemplified by an analysis of 10 prespecified benchmark operation groups performed. This report further reviews related activities in the areas of data collection and analysis, quality measurement, performance improvement, and research.

A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image

PURPOSE

In this study, we try to consider the most common type of total anomalous pulmonary venous connection and established a machine learning-based prediction model for postoperative pulmonary venous obstruction by using clinical data and CT images jointly.

METHOD

Patients diagnosed with supracardiac TPAVC from January 1, 2009, to December 31, 2018, in Guangdong Province People's Hospital were enrolled. Logistic regression were applied for clinical data features selection, while a convolutional neural network was used to extract CT images features. The prediction model was established by integrating the above two kinds of features for PVO prediction. And the proposed methods were evaluated using fourfold cross-validation.

RESULT

Finally, 131 patients were enrolled in our study. Results show that compared with traditional approaches, the machine learning-based joint method using clinical data and CT image achieved the highest average AUC score of 0.943. In addition, the joint method also achieved a higher sensitivity of 0.828 and a higher positive prediction value of 0.864.

CONCLUSION

Using clinical data and CT images jointly can improve the performance significantly compared with other methods that using only clinical data or CT images. The proposed machine learning-based joint method demonstrates the practicability of fully using multi-modality clinical data.

Predicting 30-day readmission after congenital heart surgery across the lifespan

INTRODUCTION

Hospital readmission is an important driver of costs among patients with CHD. We assessed predictors of 30-day rehospitalisation following cardiac surgery in CHD patients across the lifespan.

METHODS

This was a retrospective analysis of 981 patients with CHD who had cardiac surgery between January 2011 and December 2012. A multivariate logistic regression model was used to identify demographic, clinical, and surgical predictors of 30-day readmission. Receiver operating curves derived from multivariate logistic modelling were utilised to discriminate between patients who were readmitted and not-readmitted at 30 days. Model goodness of fit was assessed using the Hosmer-Lemeshow test statistic.

RESULTS

Readmission in the 30 days following congenital heart surgery is common (14.0%). Among 981 patients risk factors associated with increased odds of 30-day readmission after congenital heart surgery through multivariate analysis included a history of previous cardiac surgery (p < 0.001), longer post-operative length of stay (p < 0.001), as well as nutritional (p < 0.001), haematologic (p < 0.02), and endocrine (p = 0.04) co-morbidities. Patients who underwent septal defect repair had reduced odds of readmission (p < 0.001), as did children (p = 0.04) and adult (p = 0.005) patients relative to neonates.

CONCLUSION

Risk factors for readmission include a history of cardiac surgery, longer length of stay, and co-morbid conditions. This information may serve to guide efforts to prevent readmission and inform resource allocation in the transition of care to the outpatient setting. This study also demonstrated the feasibility of linking a national subspecialty registry to a clinical and administrative data repository to follow longitudinal outcomes of interest.

Cardiac Biomarkers Associated With Hospital Length of Stay After Pediatric Congenital Heart Surgery

BACKGROUND

Prolonged hospital length of stay after congenital heart surgery is a significant cost burden and is associated with postoperative morbidity. Our goal was to evaluate the association between pre- and postoperative biomarker levels and in-hospital length of stay for children after congenital heart surgery.

METHODS

We enrolled patients <18 years of age who underwent at least 1 congenital heart operation at Johns Hopkins Hospital from 2010 to 2014. Blood samples were collected before the index operation and at the end of the bypass. ST2 and N-terminal pro-brain natriuretic peptide (NT-proBNP) measurements were evaluated as log-transformed, median, and tercile cut-points. We evaluated the association between pre- and postoperative NT-proBNP and ST2 measurements with in-hospital postoperative length of stay using multivariate logistic regression. We adjusted for covariates used in The Society of Thoracic Surgeons Congenital Heart Surgery Mortality Risk Model.

RESULTS

In our cohort 45% of our patients had an in-hospital postoperative length of stay longer than the median. Before adjustment preoperative NT-proBNP above the population median and the highest tercile exhibited a significantly longer in-hospital length of stay. After adjustment for covariates in the risk model, pre- and postoperative ST2 and NT-proBNP demonstrated a significantly longer length of stay.

CONCLUSIONS

Perioperative ST2 and NT-proBNP had a significant association with increased postoperative in-hospital length of stay before and after adjustment. ST2 in particular could be used to guide an earlier assessment of patient risk for complications that may lead to adverse outcomes.

ST2 Predicts Risk of Unplanned Readmission Within 1 Year After Pediatric Congenital Heart Surgery

BACKGROUND

Approximately 10% to 20% of children are readmitted after congenital heart surgery. Very little is known about biomarkers as predictors of risk of unplanned readmission after pediatric congenital heart surgery. Novel cardiac biomarker ST2 may be associated with risk of unplanned readmission. ST2 concentrations are believed to reflect cardiovascular stress and fibrosis. Our objective was to explore the relationship between pre- and postoperative ST2 biomarker levels and risk of readmission within 1 year after congenital heart surgery.

METHODS

We prospectively enrolled pediatric patients aged < 18 years who underwent at least 1 congenital heart operation at Johns Hopkins Hospital from 2010 to 2014. Plasma samples were collected immediately before surgery and at the end of bypass. We used Kaplan-Meier survival analysis and multivariable Cox regression models to adjust for variables used in The Society of Thoracic Surgeons Congenital Heart Surgery Database mortality risk model.

RESULTS

Of our cohort of 145 patients, we found 39 children with readmissions within 365 days. The median time to unplanned readmission was 54 days (interquartile range, 10-153). Kaplan-Meier analysis demonstrated a significant difference across terciles of pre- and postoperative ST2 biomarker levels. After adjustment, elevated serum levels of ST2 measured preoperatively and postoperatively were associated with increased risk of readmission (hazard ratio, 2.5-3.7; all P < .05).

CONCLUSIONS

Elevated levels of ST2 are significantly associated with increased risk of unplanned readmission within 1 year after pediatric congenital heart surgery. Novel serum biomarker ST2 can be used for risk stratification or estimating postsurgical prognosis.

Prognostic value of perioperative NT-proBNP after corrective surgery for pediatric congenital heart defects

Background

It is critically important to assess the prognostic value of NT-proBNP in the form of repeated measures among children undergoing surgery for congenital heart defects (CHD). The aim of the present study is to assess the value of repeated perioperative NT-proBNP in evaluating the time dependent and temporal trajectory in prognostics diagnosis during the perioperative period in a large series of children with CHD.

Methods

Repeated measures of NT-proBNP from 329 consecutive children with CHD were obtained before and 1, 12, and 36 h after surgery, respectively. For fully utilizing longitudinal characteristics, we employed parallel cross-sectional logistic regression, a two stage mixed effect model and trajectories over time analysis to mine the predictive value of perioperative NT-proBNP on the binary outcome of prolonged intensive care unit (ICU) stay.

Results

The two stage mixed effects model confirmed that both the mean NT-proBNP level (aOR = 1.46, P = 0.001) and the time trends had prognostic value on the prediction of prolonged ICU stay. In the fully adjusted logistic regression analyses based on gaussian distributions, “rapidly rising NT-proBNP” put the subjects at 5.4-times higher risk of prolonged ICU stay compared with “slowly rising” group (aOR = 5.40, P = 0.003).

Conclusions

Comprehensive assessment of the time dependent and temporal trajectory in perioperative NT-proBNP, indicated by repeated measurements, can provide more accurate identification of children with higher risk of prolonged ICU stay after CHD surgery.

Preoperative miRNA-208a as a Predictor of Postoperative Complications in Children with Congenital Heart Disease Undergoing Heart Surgery

Major perioperative cardiovascular events are important causes of morbidity in pediatric patients with congenital heart disease who undergo reparative surgery. Current preoperative clinical risk assessment strategies have poor accuracy for identifying patients who will sustain adverse events following heart surgery. There is an ongoing need to integrate clinical variables with novel technology and biomarkers to accurately predict outcome following pediatric heart surgery. We tested whether preoperative levels of miRNAs-208a can serve as such a biomarker. Serum samples were obtained from pediatric patients immediately before heart surgery. MiRNA-208a was quantified by RQ-PCR. Correlations between the patient's clinical variables and miRNA levels were tested. Lower levels of preoperative miRNA-208a correlated with and could predict the appearance of postoperative cardiac and inflammatory complications. MiRNA-208a may serve as a biomarker for the prediction of patients who are at risk to develop complications following surgery for the repair of congenital heart defects.

Biomarkers improve prediction of 30-day unplanned readmission or mortality after paediatric congenital heart surgery

OBJECTIVE

To evaluate the association between novel pre- and post-operative biomarker levels and 30-day unplanned readmission or mortality after paediatric congenital heart surgery.

METHODS

Children aged 18 years or younger undergoing congenital heart surgery (n = 162) at Johns Hopkins Hospital from 2010 to 2014 were enrolled in the prospective cohort. Collected novel pre- and post-operative biomarkers include soluble suppression of tumorgenicity 2, galectin-3, N-terminal prohormone of brain natriuretic peptide, and glial fibrillary acidic protein. A model based on clinical variables from the Society of Thoracic Surgery database was developed and evaluated against two augmented models.

RESULTS

Unplanned readmission or mortality within 30 days of cardiac surgery occurred among 21 (13%) children. The clinical model augmented with pre-operative biomarkers demonstrated a statistically significant improvement over the clinical model alone with a receiver-operating characteristics curve of 0.754 (95% confidence interval: 0.65-0.86) compared to 0.617 (95% confidence interval: 0.47-0.76; p-value: 0.012). The clinical model augmented with pre- and post-operative biomarkers demonstrated a significant improvement over the clinical model alone, with a receiver-operating characteristics curve of 0.802 (95% confidence interval: 0.72-0.89; p-value: 0.003).

CONCLUSIONS

Novel biomarkers add significant predictive value when assessing the likelihood of unplanned readmission or mortality after paediatric congenital heart surgery. Further exploration of the utility of these novel biomarkers during the pre- or post-operative period to identify early risk of mortality or readmission will aid in determining the clinical utility and application of these biomarkers into routine risk assessment.