A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study.

Background: Although evidence-based medicine proposes personalized care that considers the best evidence, it still fails to address personal treatment in many real clinical scenarios where the complexity of the situation makes none of the available evidence applicable. "Medicine-based evidence" (MBE), in which big data and machine learning techniques are embraced to derive treatment responses from appropriately matched patients in real-world clinical practice, was proposed. However, many challenges remain in translating this conceptual framework into practice. Objective: This study aimed to technically translate the MBE conceptual framework into practice and evaluate its performance in providing general decision support services for outcomes after congenital heart disease (CHD) surgery. Methods: Data from 4774 CHD surgeries were collected. A total of 66 indicators and all diagnoses were extracted from each echocardiographic report using natural language processing technology. Combined with some basic clinical and surgical information, the distances between each patient were measured by a series of calculation formulas. Inspired by structure-mapping theory, the fusion of distances between different dimensions can be modulated by clinical experts. In addition to supporting direct analogical reasoning, a machine learning model can be constructed based on similar patients to provide personalized prediction. A user-operable patient similarity network (PSN) of CHD called CHDmap was proposed and developed to provide general decision support services based on the MBE approach. Results: Using 256 CHD cases, CHDmap was evaluated on 2 different types of postoperative prognostic prediction tasks: a binary classification task to predict postoperative complications and a multiple classification task to predict mechanical ventilation duration. A simple poll of the k-most similar patients provided by the PSN can achieve better prediction results than the average performance of 3 clinicians. Constructing logistic regression models for prediction using similar patients obtained from the PSN can further improve the performance of the 2 tasks (best area under the receiver operating characteristic curve=0.810 and 0.926, respectively). With the support of CHDmap, clinicians substantially improved their predictive capabilities. Conclusions: Without individual optimization, CHDmap demonstrates competitive performance compared to clinical experts. In addition, CHDmap has the advantage of enabling clinicians to use their superior cognitive abilities in conjunction with it to make decisions that are sometimes even superior to those made using artificial intelligence models. The MBE approach can be embraced in clinical practice, and its full potential can be realized.

Corrigendum: Analysis of signature genes and association with immune cells infiltration in pediatric septic shock.

[This corrects the article DOI: 10.3389/fimmu.2022.1056750.].

Risk factors of postoperative neurodevelopmental abnormalities in neonates with critical congenital heart disease. / å±é‡å ˆå¤©æ€§å¿ƒè„ç— æ–°ç”Ÿå„¿æœ¯åŽæ–°å‘ç¥žç»å‘è‚²å¼‚å¸¸çš„å±é™©å› ç´ .

OBJECTIVES: To investigate the risk factors of postoperative neuro-developmental abnormalities in neonates with critical congenital heart disease (CCHD). METHODS: Clinical data of 50 neonates with CCHD admitted in the Cardiac Intensive Care Unit, The Children's Hospital, Zhejiang University School of Medicine from November 2020 to December 2021 were retrospectively analyzed. Neurological assessment was performed with cranial ultrasonography, CT/MRI, video electroencephalogram and clinical symptoms before and after surgical treatment for all patients, and neurodevelopmental abnormalities were documented. Binary logistic stepwise regression was used to analyze risk factors of postoperative new-onset neurodysplasia in children with CCHD, and the predictive value of the risk factors on postoperative neurodevelopmental abnormalities were evaluated using the receiver operating characteristic (ROC) curve. RESULTS: Neurodevelopmental abnormalities were detected in 22 cases (44.0%) and not detected in 28 cases (56.0%) before surgery. There were no significant differences in gender, birth weight, age at admission, gestational age, preoperative SpO2 level, prematurity, cyanotic congenital heart disease, and ventilator support between the two groups (all P>0.05). After surgery, there were 22 cases (44.0%) with new-onset neurological abnormalities and 28 cases (56.0%) without new-onset abnormalities. Multivariate logistic regression analysis showed that postoperative 24 h peak lactic acid (OR=1.537, 95%CI: 1.170-2.018, P<0.01) and postoperative length of ICU stay (OR=1.172, 95%CI:1.031-1.333, P<0.05) were independent risk factors for postoperative new-onset neurodevelopmental abnormalities. The area under ROC curve (AUC) of the postoperative 24 h peak lactic acid for predicting the new-onset neurological abnormalities after operation was 0.829, with cut-off value of 4.95 mmol/L. The diagnostic sensitivity and specificity were 90.0% and 64.3%, respectively. The AUC of postoperative length of ICU stay for predicting the new-onset neurological abnormalities after operation was 0.712, with cut-off value of 18.0 d. The diagnostic sensitivity and specificity were 50.0% and 96.4%, respectively. The AUC of the combination of the two indicators was 0.917, the diagnostic sensitivity and specificity were 95.5% and 64.3%, respectively. CONCLUSIONS: The incidence of neurodysplasia in neonatal CCHD is high, and new neurological abnormalities may occur after surgery. The postoperative 24 h peak lactic acid and postoperative length of ICU stay are risk factors for new-onset neurodysplasia after surgery. The combination of the two indicators has good predictive value for neurodevelopmental outcomes after surgery in CCHD infants.

Analysis of signature genes and association with immune cells infiltration in pediatric septic shock.

Background: Early diagnosis of septic shock in children is critical for prognosis. This study committed to investigate the signature genes and their connection with immune cells in pediatric septic shock. Methods: We screened a dataset of children with septic shock from the GEO database and analyzed differentially expressed genes (DEGs). Functional enrichment analysis was performed for these DEGs. Weighted gene co-expression network analysis (WCGNA) was used to screen the key modules. Least absolute shrinkage and selection operator (LASSO) and random forest analysis were finally applied to identify the signature genes. Then gene set enrichment analysis (GSEA) was exerted to explore the signaling pathways related to the hub genes. And the immune cells infiltration was subsequently classified via using CIBERSORT. Results: A total of 534 DEGs were screened from GSE26440. The data then was clustered into 17 modules via WGCNA, which MEgrey module was significantly related to pediatric septic shock (cor=-0.62, p<0.0001). LASSO and random forest algorithms were applied to select the signature genes, containing UPP1, S100A9, KIF1B, S100A12, SLC26A8. The receiver operating characteristic curve (ROC) of these signature genes was 0.965, 0.977, 0.984, 0.991 and 0.989, respectively, which were verified in the external dataset from GSE13904. GSEA analysis showed these signature genes involve in positively correlated fructose and mannose metabolism and starch and sucrose metabolism signaling pathway. CIBERSORT suggested these signature genes may participate in immune cells infiltration. Conclusion: UPP1, S100A9, KIF1B, S100A12, SLC26A8 emerge remarkable diagnostic performance in pediatric septic shock and involved in immune cells infiltration.

Maternal air pollution exposure and neonatal congenital heart disease: A multi-city cross-sectional study in eastern China.

OBJECTIVE: To examine the association between air pollution and neonatal congenital heart disease (CHD), and evaluate the cumulative burden of CHD attributed to above certain level for ambient air pollution exposure. METHODS: We identified newborns who were diagnosed as CHD by echocardiography in Network Platform for Congenital Heart Disease (NPCHD) from January 2019 to December 2020 in 11 cities eastern China. The exposure lag response relationship between air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) concentration and CHDs was calculated by the distributed lag nonlinear model (DLNM). We further calculated the cumulative risk ratios (CRRs) of each air pollutant above reference concentrations on CHDs. RESULTS: A total of 5904 CHDs from 983, 523 newborns were enrolled in this study. A 10 µg/m3 increase in PM2.5, PM10, SO2, NO2, CO and O3 exposure was associated with an increased risk of higher CHD incident RR = 1.025, 95% CI: 1.016-1.038 for PM2.5 in the third trimester, RR = 1.001, 95% CI: 1.000-1.002 for PM10 in the third trimester, 1.020, 95%CI: 1.004-1.036 for NO2 in the third trimester, RR = 1.001, 95%CI: 1.000-1.002 for O3 in the first trimester, all P value < 0.05). Cumulative effect curves of PM2.5, PM10, SO2, NO2, CO, and O3 were observed as sub-linear with a maximum of 1.876 (95%CI:1.220-2.886), 1.973 (95%CI:1.477,2.637), 2.169 (95%CI:1.347-3.493), 2.902 (95%CI:1.859-4.530), 1.398 (95%CI:1.080-1.809), 2.691 (95%CI:1.705-4.248), respectively. Significant associations were observed for air pollutants and CHDs in cities with higher average education years and babies concepted in cold season. CONCLUSIONS: Our findings could provide growing evidence regarding the adverse health effects of air pollution on CHD, thereby strengthening the hypothesis that air pollutants have harmful impacts on cardiac development. Further studies are needed to verify the associations.

NOD-like receptor protein 3 and high mobility group box-1 are associated with prognosis of patients with congenital heart disease.

OBJECTIVE: To investigate the association between plasma levels of nucleotide-binding oligomerization domain-like (NOD)-like receptor protein 3 (NLRP3) and high mobility group box-1 (HMGB1) and their prognostic significance in neonatal patients with congenital heart disease (CHD). METHODS: This study enrolled neonatal patients with CHD and collected their demographic and clinical data. Plasma concentrations of NLRP3 and HMGB1 were measured using enzyme-linked immunosorbent assays. Spearman's analysis was used to determine the correlation between NLRP3 and HMGB1 levels. The association between NLRP3 and HMGB1 levels and 2-year survival and mortality were evaluated using Kaplan-Meier curve and logistic regression analyses. RESULTS: A total of 84 neonatal patients with CHD were included in the study. Plasma NLRP3 and HMGB1 levels were significantly higher in deceased patients compared with those that survived. There was a positive correlation between NLRP3 and HMGB1 levels in neonatal patients with CHD. Patients with elevated levels of NLRP3 and HMGB1 showed significantly lower 2-year survival and higher mortality rates compared with those with lower NLRP3 and HMGB1 levels. CONCLUSION: Neonatal patients with CHD and a poor prognosis had higher NLRP3 and HMGB1 levels, which suggests that these might be potential biomarkers of CHD prognosis.

MicroRNA-486-5p down-regulation protects cardiomyocytes against hypoxia-induced cell injury by targeting IGF-1.

BACKGROUND: MicroRNA has been reported to play an important role in congenital heart disease (CHD) in children. Recently, microRNA-486-5p (miR-486-5p) has been found increased in patients with cyanotic heart disease compared with those without heart disease. The present study aimed to investigate the effect of miR-486-5p on hypoxia-induced cardiomyocyte injury to reveal the role of miR-486-5p in cyanotic congenital heart disease (CCHD). METHODS: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to determine the expression of miR-486-5p in hypoxia-induced H9C2 cells. Dual luciferase reporter gene assay was used to confirm IGF-1 was a direct target of miR-486-5p. miR-486-5p inhibitor and IGF-1-siRNA were transfected into H9C2 cells. The cell viability was detected by MTT. Cell apoptosis was detected using flow cytometry. The expression of IGF-1, Bcl-2, caspase-3, caspase-9, and Bax mRNA and protein were detected by RT-qPCR and western blotting, respectively. RESULTS: miR-486-5p expression gradually increased with prolonged hypoxia time in H9C2 cells. Dual luciferase reporter gene results confirmed IGF-1 was a direct target of miR-486-5p. In addition, inhibition of miR-486-5p significantly increased the hypoxia-induced decrease in cell survival and attenuated hypoxia-induced apoptosis. Furthermore, inhibition of miR-486-5p significantly attenuated the hypoxia-induced decrease in the level of IGF-1 and Bcl-2 and the increase in pro-apoptotic proteins such as caspase-3, caspase-9 and Bax. These effects could be reversed by IGF-1-siRNA. CONCLUSION: The data demonstrated that inhibition of miR-486-5p increased cardiomyocyte growth and reduced cell apoptosis under hypoxic conditions by targeting IGF-1, indicating that miR-486-5p may be an effective target for the treatment of CCHD.