Screening For Heart Disease Research Articles

Retracted: Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

Retracted: Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

The Impact of a Handheld Ultrasound Device in a Rheumatic Heart Disease Screening Program in Ethiopia

Background: Rheumatic heart disease affects 33 million people in low and middle income countries and is the leading cause of cardiovascular death among children and young adults. Penicillin prophylaxis prevents progression in asymptomatic disease. Efforts to expand echocardiographic screening are focusing on simplified protocols, non-physician ultrasonographers, and portable ultrasound devices, including handheld ultrasound. Recent advances support the use of single-view screening protocols. With the increasing availability and low cost of handheld devices, studies are needed to evaluate their performance in these settings.
 Methods: We conducted a retrospective study comparing the rate of screen positive ultrasounds before and after the use of a handheld ultrasound in an RHD screening program in Ethiopia. We also performed a cross-sectional device comparison in 19 at-risk school-children participating in the rheumatic heart disease screening program.
 Results: Between March of 2019 and Jan of 2022, 6631 children were screened for rheumatic heart disease of whom 4029 were screened after the introduction of a handheld device. Before the use of the handheld ultrasound device 291 (11.2%) children had a screen positive ultrasounds compared with 167 (4.1%) afterwards (p < 0.001). We also compared non-expert to expert interpretation by device and found a significant difference in interpretation for the Lumify (p=0.025). There was a trend towards shorter jet length by color Doppler in the handheld ultrasound device for both expert and non-expert review. 
 Conclusions: Our study highlights that the screen-positive rate in a RHD screening program is influenced by the device being used in the screening process.

Leveraging School Health Programs in Africa: Integrated Screening for Rheumatic Heart Disease and Dental Caries.

Rheumatic heart disease (RHD) and dental caries (DC) disproportionately affect children and young adults in sub-Saharan countries, with major impact on schoolchildren's health and education. DC in children with RHD constitutes an important risk for fatal complications. Our study aimed at assessing the feasibility of simultaneous RHD and DC screening in school environment. March 20-24, 2022, we performed an observational descriptive study of schoolchildren in a public school in Maputo City, Mozambique. RHD screening involved two stages: first, a physical examination (including cardiac auscultation and direct observation of the oral cavity), and second, an abbreviated echocardiography performed by a cardiologist. Rapid testing for group A Streptococcus (GAS) was done to every eighth child in the classroom and for those with signs suggesting recent infection, in accordance with the study protocol developed for screening. A multidisciplinary team collected the data. Data were analyzed using descriptive statistics. A total of 954 students (median age 9; range 6-15) were screened. One hundred and twenty-five participants were eligible for a rapid antigen test, of which 6 (4.8%) tested positive. On clinical evaluation 52 children (5.3%) presented a heart murmur. Echocardiography on 362 children showed borderline RHD in 35 children and definite RHD in 2 (0.6%); 1 child had a ventricular septal defect. Dental cavities were present in 444 (48.4%), despite 904 out of 917 students reporting brushing of their teeth once to three times daily (98.6%). School-based integrated oral and cardiovascular screenings and use of rapid tests for GAS carriage provide crucial information to create customized preventive strategies for rheumatic fever (RF) and RHD in low- and middle-income countries (LMICs), in addition to detecting children at very high risk of bacterial endocarditis. The sustainability of such interventions and acceptability by health providers needs to be assessed.

Identification of abnormal ventricular asymmetry in 2nd trimester fetal ultrasound using artificial intelligence

Abstract Introduction Prenatal ultrasound screening for congenital heart disease (CHD) suffers from poor detection yield (10%-56%)[1, 2], with a strong impact on neonatal morbidity and mortality. The need for expertise in fetal cardiology and the high volume of screening cases limit the current detection rates. Computer-assisted prenatal screening could support clinicians in improving diagnostic yield, including for abnormal ventricular asymmetry, which is often hard to discriminate from physiological asymmetry. Here we aim at evaluating a deep neural network (DNN) for detection of abnormal ventricular asymmetry, which can be linked to multiple types of CHD, including coarctation of the aorta, pulmonary or aortic valve stenosis, ventricular hypoplasia or univentricular heart. Purpose To determine if a novel DNN can identify cases of abnormal ventricular asymmetry in 2nd trimester fetal ultrasound videos. Methods We used as an endpoint the presence of any abnormality causing a significantly abnormal asymmetry of the ventricles as seen in the fetal ultrasound. Consecutive patients who had an echocardiography performed at one center were included retrospectively starting from 2022, January 1st. Inclusion criteria were single pregnancy between 18 and 25 weeks of gestation. To have a high number of positive patients, patients were included separately if they were expected to be positive (n=35) or negative (n=75) to the endpoint, based on their medical record. Each case was reviewed by one of two physicians expert in fetal echocardiography interpretation to confirm the presence or absence of the endpoint. For each patient, a single video showing an interpretable four chamber view was selected. Patients with no such video were excluded. The DNN takes as input fetal ultrasound videos, and predicts the absence or presence of the endpoint for each video. If its confidence is low, the DNN predicts an "inconclusive" output instead. The DNN has a ResNet-50 architecture[3] adapted to videos and was trained on data from patients not included in the evaluation. The detection performance of the DNN and the proportion of conclusive outputs were assessed. Results Overall, 37 positive and 66 negative ultrasound videos were included. The DNN achieved an AUC of 75.5%, a sensitivity of 71.4% (54.9-83.7, 95%CI) and a specificity of 64.4% (51.7-75.4, 95%CI) in identifying cases of abnormal ventricular asymmetry, after excluding inconclusive diagnosis. The DNN predicted a conclusive diagnosis in 91.3% of cases. Conclusion A DNN could accurately identify cases of abnormal ventricular asymmetry in fetal heart ultrasound videos. Importantly, this evaluation was performed in a population of patients who had an echocardiogram, and which therefore contains more abnormal cases compared to patients undergoing standard screening. This work lays the ground for diagnostic support to enable a more efficient, accurate, and scalable analysis of fetal heart ultrasounds.

Determinants of childbearing intentions among pregnant women with a suspected fetal congenital heart disease

BackgroundThe Saudi population is characterized by a high fertility rate, a conservative sociocultural context, and an ongoing societal and lifestyle transition. Yet, data regarding childbearing intentions and the associated factors is scarce. Furthermore, childbearing intention may be impacted by abnormal pregnancy events, such as the clinical suspicion or diagnosis of a fetal congenital disease and the negative experience that may result from it. ObjectivesThe present study explored childbearing intention and determined the sociodemographic and health-related factors discouraging from future pregnancies among women visiting the cardiology clinic for antenatal screening of congenital heart diseases (CHD). MethodsA one-year cross-sectional study involved 150 consecutive pregnant women aged between 18 and 47 years old, who presented for antenatal screening of CHD at the fetal echocardiography clinic for, of a teaching hospital in Jeddah, Saudi Arabia. An interview-based questionnaire was administered before the clinic visit and collected sociodemographic data, obstetrical history, risk factors of congenital diseases, mothers’ knowledge about fetal echocardiography and CHDs, and childbearing intention (the primary outcome). ResultsFetal echocardiography and CHD were correctly described by 60 % and 31.3 % of the participants respectively, while 40.7 % and 12 % recognized the association of congenital diseases with consanguinity and advanced maternal age respectively. Childbearing intentions showed 68.0 % of the participants declared desiring a future baby while the remaining 32.0 % declared having no further pregnancy expectations. Attitudes towards a hypothetical baby with CHD were positive in 97.3 % of the participants, and only 30 % declared that the fetal echocardiography results will impact their future childbearing decision. However, childbearing intention showed no significant association with knowledge or attitudes towards CHD. On the other hand, childbearing intention was independently associated with the number of children (OR=0.34; p<0.001), consanguinity with husband (OR=3.64; p = 0.010), and history of gestational diabetes (OR=0.28; p = 0.040). ConclusionFertility expectations among Saudi mothers are more likely to be impacted by the personal experience and judgment of own pregnancy fitness, while no significant impact of fetal risks and events. This demonstrates a certain level of autonomy balanced with deeply rooted religious ethics yet combined with a lack of awareness about fetal and maternal risks associated with advanced maternal age and consanguinity. We emphasize the unmet need of education and family planning.

Abstract 17098: Detection of Multiple Structural Heart Diseases Using a Novel Artificial Intelligence-Driven Algorithm for Noisy Real-World Single-Lead ECGs

Background: Wearable devices capable of ECG acquisition can help scale screening of structural heart disease (SHD) if diagnoses can be made with a single lead ECG. Algorithms for portable and wearable ECG require resilience to noisy acquisition but can enable detecting SHD in a community setting before symptom onset, ideal for public health management. Methods: Using Yale EHR data (2015-2021), we developed an artificial intelligence model to detect the presence of left ventricular systolic dysfunction, severe left-sided valvular disease, or hypertrophic cardiomyopathy using lead I of an ECG, which is commonly captured by wearable devices. We used 563,668 ECGs paired with echocardiograms obtained within 30 days of each other from 131,804 patients to develop the model. The dataset was split into training, validation, and test sets (85:5:10). For individual disease labels, we trained 6 convolutional neural network models using ECG signals augmented with random Gaussian real-world noise within 4 distinct frequency ranges and at 4 signal-to-noise ratios. Then, we included their prediction probabilities and age and sex as inputs to an XGBoost model to predict the composite SHD (Fig). Results: In the development set, the prevalence of composite SHD was 13%, encompassing left ventricular systolic dysfunction (9%), severe valvular disease (4%), and hypertrophic cardiomyopathy (1%). In the held-out test set of 13,181 patients (65±17 years, 49% women, 14% Black), AUROC and AUPRC of the ensemble model for prediction of SHD were 0.92 (0.90-0.93) and 0.61 (0.54-0.68), respectively (Fig). With optimized Youden's index, the model has a sensitivity of 0.83, specificity of 0.87, PPV of 0.41, and NPV of 0.98 to detect SHD. Conclusion: A novel wearable-adapted model demonstrated promising performance for detecting multiple SHD using single-lead ECG. This can enable community screening for SHD and improve patient outcomes through early initiation of guideline-directed therapies.

Abstract 16681: Echocardiogram-Based Screening and Prevalence of Rheumatic Heart Disease in Children and Adolescents From Endemic Areas: A Systematic Review and Updated Meta-Analysis

Background: Rheumatic heart disease (RHD) is the leading cause of cardiac death in children, posing a significant burden to health systems, particularly in developing countries. Echocardiogram is a sensitive tool to identify early RHD patients, who may benefit from secondary prevention. Therefore, we performed an updated meta-analysis to determine the prevalence of latent RHD using echocardiogram-based screening performed in endemic regions across the globe. Methods: PubMed, Embase, Cochrane, and Lilacs databases were searched for cross-sectional studies reporting the prevalence of RHD in individuals aged 5-20 years, through echocardiogram-based screening programs in endemic areas. Studies with screening based on auscultation were excluded. Echocardiography-detected RHD was considered as borderline or definite by World Heart Federation (WHF) criteria and possible, probable or definite by World Heart Organization (WHO) criteria. We used random-effects models to assess the prevalence of RHD according to the geographic distribution. Results: A total of 57 studies were included, with a total of 224,100 screened subjects. WHF criteria for RHD echocardiographic diagnosis were used in 46 studies, WHO criteria in 6, and others in 3. The overall prevalence of echocardiography detected RHD was 23 per 1,000 individuals (95% CI 18 to 29 per 1,000), with a pooled prevalence of definitive RHD of 9 per 1,000 individuals (95% CI 7 to 12 per 1,000). Analysis of the prevalence of echocardiography detected RHD in different continents yielded an overall prevalence of 21 per 1,000 (95% CI 14 to 31 per 1,000) in Africa, 28 per 1,000 (95% CI 18 to 42 per 1,000) in Oceania, 21 per 1,000 (95% CI 15 to 30 per 1,000) in Asia, and 22 per 1,000 (95% CI 6 to 76 per 1,000) in Latin America. Conclusion: Screening programs incorporating echocardiography found a significant prevalence of RHD, in the range of 20 to 30 per 1,000 children and adolescents screened in endemic areas across different continents.

Abstract 14599: A Pilot Rheumatic Heart Disease Screening Program Using Portable, Handheld Echocardiography in Rivas, Nicaragua

Introduction: Portable, handheld echocardiography offers several advantages for rheumatic heart disease (RHD) screening in low-resource settings. Analyses of focused protocols using handheld echocardiography have yielded acceptable sensitivity and specificity for diagnosis of RHD, including in those performed by non-expert sonographers. Previous studies estimate high burden of RHD in Nicaragua. We conducted a pilot community-based RHD screening program using handheld echocardiography in Rivas, Nicaragua using contemporary RHD diagnostic criteria. Methods: Non-expert sonographers were trained using the GE Vscan Extend TM device and a simplified version of the 2012 World Heart Federation criteria for diagnosis of RHD. Referral criteria for complete echocardiogram included the presence of a mitral regurgitant jet of &gt; 2.0 cm, aortic regurgitant jet &gt; 1.0 cm, or any morphologic abnormality of the mitral or aortic valve, as well as left ventricular dysfunction or significant congenital heart disease. Participants were recruited by convenience-based sampling in communities throughout Rivas, Nicaragua. Participants were notified at the point-of-care of need for complete echocardiogram. All studies were overread asynchronously by expert readers for diagnostic accuracy. Results: Between March 2022 and April 2023, 494 screening echocardiographic studies were performed and evaluated for diagnostic accuracy. The median age was 36.3 years (IQR 19.2, 56.2), 22% of participants were &lt;18 years of age, and 60% of participants were female. There were 17.6% of participants referred for complete echocardiogram at the point-of-care compared with 13.0% meeting referral criteria on expert review. Negative and positive predictive values for non-expert vs. expert assessment were 92.4% and 62.1%, respectively. Cohen’s kappa for inter-rater reliability was 0.338, suggesting fair agreement. Conclusions: This pilot program demonstrated the feasibility of a screening program for RHD in rural Nicaragua with non-expert sonographers. Lessons from this program are intended to inform future epidemiological studies to determine the population prevalence and longitudinal outcomes of RHD in this region.

Abstract 14701: Agreement Between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren From High-Prevalence Settings

Background: Handheld echocardiography (echo) is the tool of choice for Rheumatic Heart Disease (RHD) screening, based on the 2012 World Heart Federation (WHF) Criteria. We aimed to assess the agreement between screening and standard echo for diagnosis of latent RHD in schoolchildren from an endemic setting. Methods: Over 14 months, 3 non-physicians used handheld machines (GE, VSCAN) and the 2012 WHF Criteria to determine RHD prevalence in low-income public schools in Minas Gerais, Southeast Brazil. Consented children were eligible for participation. Studies were interpreted remotely using a telemedicine cloud-server by 2 experts in Brazil and the US. RHD-positive children (borderline and definite) and those with congenital heart disease (CHD) were referred for standard echo with portable devices (GE, Vivid IQ), with acquisition and interpretation by an expert cardiologist. Agreement between screening and standard echo, by category and according to the WHD criteria, was assessed, and the kappa statistic was applied. Results: A total of 1,390 students were screened in 6 schools and, among these, 110 (7.9%, 95% CI 6.5 - 9.5) were screen-positive and referred for standard echo, with mean age of 14±2 years, 80 (72%) women. Among the 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline and 1 to normal. Among the 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) to definite RHD and 2 had mild CHD. Among 11 children with CHD in screening, 4 were confirmed, 5 were reclassified to normal and 2 to RHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criteria was B (isolated mitral regurgitation): 64%, followed by A (2 morphological features of the mitral valve): 31%. In the only patient with definite RHD reclassified to normal, WHF criteria was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3 - 4.2). Conclusions: Although practical, RHD screening with handheld devices tend to overestimate prevalence. Even in endemic settings, continuous education for detection, and application of risk stratification for management are crucial.

Abstract 13368: Availability of PGE1 in Northern California Hospitals: Before and After Routine CCHD Screening

Introduction: Fetal echocardiogram and critical congenital heart disease (CCHD) screening has improved early detection of CCHD. CCHD screening has been recommended for all infants since 2011 and mandated in California since July 2013. In patients with suspected ductal dependent congenital heart disease, early intervention with prostaglandin E1 (PGE1) is the standard of care to reduce morbidity and mortality. Hypothesis: In 2004, we assessed the availability of PGE1 in Northern California hospitals that care for newborn infants and found that 32% of hospitals with obstetric services did not have the ability to institute PGE1 infusion. As California has adopted CCHD screening for all newborn infants prior to hospital discharge, our aim was to assess the percentage of hospitals that perform CCHD screening as well as reassess PGE1 availability. Our hypothesis was that CCHD screening would increase the availability of PGE1 at hospitals providing obstetric services. Methods: The initial study contacted 117 Northern California hospitals to determine PGE1 availability. We contacted the same hospitals, ending up with 106 hospitals due to closures and mergers. The newborn nursery and/or NICU for each of these hospitals was contacted to determine CCHD screening practices and availability of PGE1. Mileage to the nearest level IV NICU was used as a gross estimate of distance to a tertiary care center. Results: In 2004, 92 of 117 hospitals had obstetric service, and 30 (32.6%) of those did not have PGE1. In this study, 74 of the 106 provided obstetric services. All performed CCHD screening, but 15 (20.3%) did not have ability to provide PGE1 infusion. 8 of the 15 hospitals were more than 30 miles (range 1.5 - 192 miles) from the closest level IV NICU. Conclusions: All hospitals in Northern California providing obstetric service are performing CCHD screening. However, 20.3% of these hospitals still do not have the ability to administer PGE1 infusion. Of these, 53% were in suburban and rural areas of Northern California, with significant transportation distance to a tertiary care center. Delay in initiating PGE1 infusion in patients with ductal dependent CCHD may lead to morbidity or mortality, and increasing PGE1 availability is an opportunity to improve access to care.

An edge-device-compatible algorithm for valvular heart diseases screening using phonocardiogram signals with a lightweight convolutional neural network and self-supervised learning

Background and objectivesDetection and classification of heart murmur using mobile-phone-collected sound is an emerging approach to the scale-up screening of valvular heart disease at a population level. Nonetheless, the widespread adoption of artificial intelligence (AI) methods for this type of mobile health (mHealth) application requires highly accurate and lightweight AI models that can be deployed in consumer-grade mobile devices. This study presents a lightweight deep learning model and a self-supervised learning (SSL) method to utilise unlabelled data to improve the accuracy of valvular heart disease classification using phonocardiogram data. MethodsThis study proposes a lightweight convolutional neural network (CNN) that consists of ten times fewer parameters than other deep learning models to classify phonocardiogram data. SSL is applied to harness a large collection of unlabelled data as pre-training to enhance the accuracy and robustness of the model and reduce the number of epochs required to converge. A mobile application prototype that encapsulates the model is developed to perform in-device inference and fine-turning. ResultsThe proposed lightweight model achieves an average accuracy of 98.65% in 10-fold cross-validation. When coupled with SSL using unlabelled data, the pre-trained model can reach an average accuracy higher than 99.4% in 10-fold cross-validation. Furthermore, SSL-trained models have a 4–20% improvement in classification accuracy over non-SSL-trained models when tested with perturbed or noisy data, suggesting that SSL improves robustness of the model. When deployed on common smartphones, in-device fine-tuning and inference of the model can be completed within 0.03–0.37 s, which is considerably faster than 0.22–5.7 s by a standard CNN model that have ten times the number of parameters. Our lightweight model also consumes only a third of the power compared to the larger standard model. ConclusionThis work presents a lightweight and accurate phonocardiogram classifier that supports near real-time performance on standard mobile devices.

Contemporary review: recognition, management, and screening for radiation-induced heart disease

Radiation is a primary therapy in the treatment of thoracic malignancies with clear survival benefits. Consequently, patients with cancer are living longer but may be subject to a wide array of cardiotoxic effects from collateral radiation damage. Ensuing fibrosis can affect any portion of the cardiac parenchyma, increasing the risk for accelerated coronary artery disease, pericardial sequelae such as constrictive pericarditis, valvulopathy, restrictive cardiomyopathy, and a myriad of conduction system abnormalities. Unfortunately, the effects of cardiotoxicity can be subclinical or delayed and there remains an unmet need to standardize management strategies for these patients. Based on current data, it is prudent to consider percutaneous approaches first for coronary and valvular disease and traditional, supportive measures for the remaining sequelae. Every attempt should be made to undergo a complete operative haul due to the increased risks of re-operation if surgery is to be performed. Surrounding the patient with a multidisciplinary heart team is critical.

Custom machine learning algorithm for large-scale disease screening - taking heart disease data as an example

Heart disease accounts for millions of deaths worldwide annually, representing a major public health concern. Large-scale heart disease screening can yield significant benefits both in terms of lives saved and economic costs. In this study, we introduce a novel algorithm that trains a patient-specific machine learning model, aligning with the real-world demands of extensive disease screening. Customization is achieved by concentrating on three key aspects: data processing, neural network architecture, and loss function formulation. Our approach integrates individual patient data to bolster model accuracy, ensuring dependable disease detection.We assessed our models using two prominent heart disease datasets: the Cleveland dataset and the UC Irvine (UCI) combination dataset. Our models showcased notable results, achieving accuracy and recall rates beyond 95 % for the Cleveland dataset and surpassing 97 % accuracy for the UCI dataset. Moreover, in terms of medical ethics and operability, our approach outperformed traditional, general-purpose machine learning algorithms. Our algorithm provides a powerful tool for large-scale disease screening and has the potential to save lives and reduce the economic burden of heart disease.

OC19.04: A deep learning model for prenatal congenital heart disease screening generalises to a community setting and outperforms clinical detection

OC19.04: A deep learning model for prenatal congenital heart disease screening generalises to a community setting and outperforms clinical detection

Arterial oxygen saturation in healthy Mexican full-term newborns at different altitudes above sea level.

Arterial oxygen saturation (SaO2) values are used to make clinical decisions that might change a patient's prognosis, and it has been proposed as the fifth vital sign. This study aimed to determine the variation of SaO2 at different altitudes above sea level (ASL) in healthy Mexican full-term newborns. From July 2018 to June 2019, a cross-over study was conducted in six hospitals at different altitudes ASL in Mexico. SaO2 was measured in 4015 newborns after the first 24 h of birth and before leaving the hospital using pulse oximetry. We analyzed three groups: < 250 m ASL (group 1), 1500 m ASL (group 2), and 2250 m ASL (group 3). The mean SaO2 was 97.6 ± 1.8%. For group 1, mean oxygen saturation was 98.2 ± 1.9%; for group 2, 96.7 ± 1.9%, and for group 3, 96.0 ± 2.1%. A statistically significant difference was observed among the groups (p < 0.001), and this difference was higher between groups 1 and 2 (1.5%, p < 0.001). Linear regression analysis showed a decrease in oxygen saturation of 1.01% for every 1000 m ASL. We demonstrated a statistically significant reduction in SaO2 levels at higher altitudes. This observation can be relevant for clinical decision-making based on pulse oximetry such as critical congenital heart disease screening in Mexico, where more than half of the population lives above 1500 m ASL.

Prenatal screening for congenital heart disease: Status report in a level 3 maternity hospital

Prenatal screening for congenital heart disease: Status report in a level 3 maternity hospital

The role of N-terminal pro-brain natriuretic peptide, chromogranin A, and 5-hydroxyindoleacetic acid in screening for carcinoid heart disease.

Carcinoid heart disease (CHD) is a serious complication for patients with neuroendocrine tumors (NETs), and early detection is crucial. We aimed to investigate N-terminal pro-brain natriuretic peptide (NT-proBNP), chromogranin A (CgA), and plasma 5-hydroxyindoleacetic acid (P-5-HIAA) as a screening tool for detection of CHD. We prospectively included patients with disseminated small intestinal NETs (SI-NETs) and performed transthoracic echocardiography (TTE), questionnaires, and biochemical assessment of NT-proBNP, CgA, and P-5-HIAA. The presence and severity of CHD was assessed using a scoring system based on echocardiographic characteristics. A total of 93 patients were included in the final analysis. Fifteen (16%) were diagnosed with CHD. The median NT-proBNP (219 ng/L vs. 124 ng/L, p = .05), CgA (3930 pmol/L vs. 256 pmoL/L, p < .0001), and P-5-HIAA (1160 nmol/L vs. 210 nmoL/L, p < .0001) were significantly higher in patients with CHD compared to non-CHD patients. For NT-proBNP, the area under the receiver operating characteristic (AUROC) curve for detection of CHD was 0.67 (95% CI: 0.50-0.84), and at a 260 ng/L cutoff level, the sensitivity and specificity were 46% and 79%. For CgA, the AUROC was 0.91 (95% CI: 0.84-0.97), and at a cutoff level of 598 pmol/L, the sensitivity and specificity were 100% and 69%. For P-5-HIAA, the AUROC was 0.89 (95% CI: 0.80-0.98), and at a cutoff level of 752 nmol/L, the sensitivity and specificity were 92% and 85%. In conclusion, CgA and P-5-HIAA proved excellent markers of CHD while NT-proBNP lacked the required diagnostic accuracy to be used as a screening tool.

Analysis of the current protocol for screening and early diagnosis of acyanogenic congenital heart disease in pediatrics

Analysis of the current protocol for screening and early diagnosis of acyanogenic congenital heart disease in pediatrics

Current status and challenges in prenatal and neonatal screening, diagnosis, and management of congenital heart disease in China.

Congenital heart disease (CHD), a wide spectrum of diseases with varied outcomes, is the most common congenital malformation worldwide. In this Series of three papers, we describe the burden of CHD in China; the development of screening, diagnosis, treatment, and follow-up strategies; and challenges associated with the disease. We also propose solutions and recommendations for policies and actions to improve the outcomes of CHD. In the first paper in this Series, we focus on prenatal and neonatal screening, diagnosis, and management of CHD. Based on advanced international knowledge, the Chinese Government has developed a network system comprising prenatal screening, diagnosis of CHD subtypes, specialist consultation appointments, and treatment centres for CHD. A new professional discipline, fetal cardiology, has been formed and rapidly developed. Consequently, the overall coverage of prenatal and neonatal screening and the accuracy of CHD diagnoses have gradually improved, and the neonatal CHD mortality rate has decreased substantially. However, China still faces several challenges in the prevention and treatment of CHD, such as insufficient diagnostic capabilities and unqualified consultation services in some regions and rural areas. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Abbreviated Echocardiographic Screening for Rheumatic Heart Disease by Non-Experts: A Diagnostic Accuracy Study of Two Approaches

Abbreviated Echocardiographic Screening for Rheumatic Heart Disease by Non-Experts: A Diagnostic Accuracy Study of Two Approaches