Identification Of Congenital Heart Defects Research Articles

Positive Predictive Value of International Classification of Diseases, Ninth Revision, Clinical Modification, and International Classification of Diseases, Tenth Revision, Clinical Modification, Codes for Identification of Congenital Heart Defects.

Background Administrative data permit analysis of large cohorts but rely on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes that may not reflect true congenital heart defects (CHDs). Methods and Results CHDs in 1497 cases with at least 1 encounter between January 1, 2010 and December 31, 2019 in 2 health care systems, identified by at least 1 of 87 ICD-9-CM/ICD-10-CM CHD codes were validated through medical record review for the presence of CHD and CHD native anatomy. Interobserver and intraobserver reliability averaged >95%. Positive predictive value (PPV) of ICD-9-CM/ICD-10-CM codes for CHD was 68.1% (1020/1497) overall, 94.6% (123/130) for cases identified in both health care systems, 95.8% (249/260) for severe codes, 52.6% (370/703) for shunt codes, 75.9% (243/320) for valve codes, 73.5% (119/162) for shunt and valve codes, and 75.0% (39/52) for "other CHD" (7 ICD-9-CM/ICD-10-CM codes). PPV for cases with >1 unique CHD code was 85.4% (503/589) versus 56.3% (498/884) for 1 CHD code. Of cases with secundum atrial septal defect ICD-9-CM/ICD-10-CM codes 745.5/Q21.1 in isolation, PPV was 30.9% (123/398). Patent foramen ovale was present in 66.2% (316/477) of false positives. True positives had younger mean age at first encounter with a CHD code than false positives (22.4 versus 26.3 years; P=0.0017). Conclusions CHD ICD-9-CM/ICD-10-CM codes have modest PPV and may not represent true CHD cases. PPV was improved by selecting certain features, but most true cases did not have these characteristics. The development of algorithms to improve accuracy may improve accuracy of electronic health records for CHD surveillance.

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) - a study protocol for developing an automated intelligent decision support system for early fetal echocardiography

BackgroundCongenital Heart Disease represents the most frequent fetal malformation. The lack of prenatal identification of congenital heart defects can have adverse consequences for the neonate, while a correct prenatal diagnosis of specific cardiac anomalies improves neonatal care neurologic and surgery outcomes. Sonographers perform prenatal diagnosis manually during the first or second-trimester scan, but the reported detection rates are low. This project’s primary objective is to develop an Intelligent Decision Support System that uses two-dimensional video files of cardiac sweeps obtained during the standard first-trimester fetal echocardiography (FE) to signal the presence/absence of previously learned key features.MethodsThe cross-sectional study will be divided into a training part of the machine learning approaches and the testing phase on previously unseen frames and eventually on actual video scans.Pregnant women in their 12–13 + 6 weeks of gestation admitted for routine first-trimester anomaly scan will be consecutively included in a two-year study, depending on the availability of the experienced sonographers in early fetal cardiac imaging involved in this research.The Data Science / IT department (DSIT) will process the key planes identified by the sonographers in the two- dimensional heart cine loop sweeps: four-chamber view, left and right ventricular outflow tracts, three vessels, and trachea view. The frames will be grouped into the classes representing the plane views, and then different state-of-the- art deep-learning (DL) pre-trained algorithms will be tested on the data set. The sonographers will validate all the intermediary findings at the frame level and the meaningfulness of the video labeling.DiscussionFE is feasible and efficient during the first trimester. Still, the continuous training process is impaired by the lack of specialists or their limited availability. Therefore, in our study design, the sonographer benefits from a second opinion provided by the developed software, which may be very helpful, especially if a more experienced colleague is unavailable. In addition, the software may be implemented on the ultrasound device so that the process could take place during the live examination.Trial registrationThe study is registered under the name „Learning deep architectures for the Interpretation of Fetal Echocardiography (LIFE)”, project number 408PED/2020, project code PN-III-P2–2.1-PED-2019. Trial registration: ClinicalTrials.gov, unique identifying number NCT05090306, date of registration 30.10.2020.

Clinical score to detect congenital heart defects: Concept of second screening.

Introduction:Neonatal screening for congenital heart defects at birth can miss some heart defects, sometimes few critical ones, and the scenario is even worse in those neonates who had never undergone a neonatal checkup (home deliveries). Immunization clinic can serve as a unique opportunity as the second checkpoint for the screening of the children. A history- and examination-based test can serve as an effective tool to screen out children with heart defects.Aims and Objectives:The aim of this study was to establish the sensitivity and specificity of a clinical screening tool for the identification of congenital heart defects at the first visit of an infant after birth for immunization.Materials and Methods:This is a cross-sectional observational study which the consecutive children presenting at 6 weeks of age for immunization or any child presenting for the first time (outborn delivery) till 6 months of age in the immunization clinic were subjected to detailed history and examination and findings were recorded on a predesigned pro forma and a clinical score was calculated. All these children were then subjected to echocardiography for confirmation of the diagnosis of congenital heart disease (CHD), and the sensitivity and specificity of the test were recordedObservations and Results:A total of 970 babies were screened, out of them 31 were diagnosed with CHD and 18 had undergone neonatal screening at birth. A clinical score of 3 or more had more chances of detecting CHD. The sensitivity of the cutoff score as 3 was 96.77% and specificity was 98.72, with a positive predictive value of 71.43%, a negative predictive value of 99.89%, and an accuracy of 98.66%.Conclusions:The history- and examination-based tool is an effective method for early identification of CHD and can easily be used by peripheral workers working in remote places with poor resources enabling prompt referral.

986: The utility of Fetal Intelligent Navigation Echocardiography in obtaining fetal echocardiography views

Prenatal identification of congenital heart defects can be difficult due to the complex anatomy, size and motion of the fetal heart. Newer evidence suggests that 3D and 4D sonographic imaging using a dynamic volume dataset may improve identification of fetal heart anomalies. We aimed to evaluate the performance of Fetal Intelligent Navigation Echocardiography (FINE) when applied to volume datasets of the normal fetal heart. Prospective cohort study from a single academic institution of low risk women presenting for fetal anatomic evaluation between 18 and 23 weeks gestation. During sonographic evaluation, one or more dynamic volume acquisitions were obtained by a qualified, trained sonographer of the apical 4 chamber view of the heart. Each dynamic volume dataset was assessed for quality of anatomical views and the presence of motion or shadow artifact by a trained sonographer and physician prior to application of FINE (5D) software. The rates (95% CI) for visualization of the various heart views using diagnostic 2D planes and the 5D heart method were calculated using the Wald method, and compared between the two groups using χ2 test. One or more dynamic volumes (160 in total) were obtained from 60 women. Non-manipulated 2D view rates of visualization for individual fetal echocardiographic views ranged from 50-95%. Applying the FINE method resulted in rates of visualization of individual fetal echocardiographic views ranging between 80-98% (Table 1). The completeness of cardiac views for basic, detailed, and fetal echocardiography surveys was improved with additional manipulations obtained through diagnostic planes or FINE-Assistance for each normal dynamic volume dataset (Table 2). The FINE (5D) method is superior to traditional 2D diagnostic plane in generating all nine standard fetal echocardiography views in cases studied. Utilization of the 5D heart (FINE) method may enhance fetal cardiac survey during second trimester anatomic ultrasounds.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Cyanotic Congenital Heart Defects – literature review

Congenital heart defects are one of the most interesting and important chapters regarding abnormal fetal growth pathology. The objective of this article is to present a literature review for the main cyanotic congenital heart defects. The ones presented in the article are: tetralogy of Fallot, transposition of the great vessels, double outlet right ventricle, truncus arteriosus, total anomalous pulmonary venous circulation and additional information regarding very rare malformations such as pentalogy of Cantrell and Uhl anomaly. An early and precise identification of congenital heart defects is an important step in an accurate follow-up of a potential problematic pregnancy. Knowing the sonographic aspect, associated pathology and the current available treatment procedures are vital for the fetal outcome and for the physician to adapt the right management in every situation that might appear during the pregnancy and in the neonatal period.

A step-wise approach for analysis of the mouse embryonic heart using 17.6 Tesla MRI

BackgroundThe mouse embryo is ideal for studying human cardiac development. However, laboratory discoveries do not easily translate into clinical findings partially because of histological diagnostic techniques that induce artifacts and lack standardization. AimTo present a step-wise approach using 17.6T MRI, for evaluation of mice embryonic heart and accurate identification of congenital heart defects. Subjects17.5-embryonic days embryos from low-risk (non-diabetic) and high-risk (diabetic) model dams. Study designEmbryos were imaged using 17.6Tesla MRI. Three-dimensional volumes were analyzed using ImageJ software. Outcome measuresEmbryonic hearts were evaluated utilizing anatomic landmarks to locate the four-chamber view, the left- and right-outflow tracts, and the arrangement of the great arteries. Inter- and intra-observer agreement were calculated using kappa scores by comparing two researchers' evaluations independently analyzing all hearts, blinded to the model, on three different, timed occasions. Each evaluated 16 imaging volumes of 16 embryos: 4 embryos from normal dams, and 12 embryos from diabetic dams. ResultsInter-observer agreement and reproducibility were 0.779 (95% CI 0.653–0.905) and 0.763 (95% CI 0.605–0.921), respectively. Embryonic hearts were structurally normal in 4/4 and 7/12 embryos from normal and diabetic dams, respectively. Five embryos from diabetic dams had defects: ventricular septal defects (n=2), transposition of great arteries (n=2) and Tetralogy of Fallot (n=1). Both researchers identified all cardiac lesions. ConclusionA step-wise approach for analysis of MRI-derived 3D imaging provides reproducible detailed cardiac evaluation of normal and abnormal mice embryonic hearts. This approach can accurately reveal cardiac structure and, thus, increases the yield of animal model in congenital heart defect research.

Modern Strategy for Identification of Congenital Heart Defects in the Neonatal Period.

Introduction:Congenital heart defects are the most common congenital anomalies and occur with an incidence from 0.8 to 1% per 1000 live births. In recent years, the pulse oximetry has become a strong candidate for detecting cyanogen congenital heart defects and in combination with routine clinical exam can improve diagnostic of congenital heart diseases.Objective:To apply the modern algorithm for early detection of congenital heart defects in order to improve the diagnosis in the neonatal period.Patients and Methods:This was a prospective study that included children born in Bihac Cantonal Hospital during 2012. The diagnostic algorithm included a clinical examination of the newborn, measuring of transcutaneous oxygen saturation with the pulse oximeter between 24 and 48 hours of life, and, in some cases, additional tests (cardiac ultrasound).Results:A total of 1,865 children were examined. The application of diagnostic protocol identified the existence of congenital heart defects in 29 children. In re-evaluating the auscultator and ultrasound findings, we identified congenital heart defects in 19 children.Conclusion:The application of the modern algorithm for early detection of congenital heart diseases in the neonatal period can significantly improve the making of diagnosis of these anomalies. The concept is simple, inexpensive and applicable in most maternity wards.

Collaborative study of 4-dimensional fetal echocardiography in the first trimester of pregnancy.

Accumulating evidence supports a role for 2-dimensional fetal echocardiography in the first trimester of pregnancy for the identification of congenital heart defects. Our objective was to investigate the role of 4-dimensional (4D) sonography in the identification of congenital heart defects between 11 and 15 weeks of pregnancy. This study included 4 centers with expertise in first-trimester 4D fetal echocardiography. Fetuses with and without confirmed heart defects were evaluated between 11 and 15 weeks and their volume data sets were uploaded onto a centralized file transfer protocol server. Forty-eight volume data sets from fetuses with normal (n = 17) and abnormal (n = 16) hearts were evaluated. Overall, the median (range) accuracy, sensitivity, and specificity, as well as the positive and negative likelihood ratios, for the identification of fetuses with congenital heart defects were 79% (77%-83%), 90% (70%-96%), 59% (58%-93%), 2.35 (2.05-9.80), and 0.18 (0.08-0.32), respectively. (1) Four-dimensional fetal echocardiography can be performed in the first and early second trimesters of pregnancy; and (2) 4D volume data sets obtained from fetuses between 11 and 15 weeks can be remotely acquired and accurately interpreted by different centers.

A new view on congenital heart disease: clinical burden prevision of changing patients

The introduction and diffusion of cross-sectional echocardiography at the end of 1970s significantly improved case ascertainment and allowed the identification of congenital heart defects with a significant increase of mild forms. However, the prevalence of severe congenital heart disease (CHD), which represented 11.7% of overall cardiovascular malformations, remained quite stable (less than 1 per 1000 live births). In past decades, a new population of adults with CHD emerged who need specialized care in centres with trained and experienced professional staff with a different level of expertise. Clinical implications of this new scenario are discussed in this article.

First‐trimester measurement of the ductus venosus pulsatility index and the prediction of congenital heart defects

This study was carried out to evaluate the additional predictive value of ductus venosus pulsatility index for veins (DV-PIV) in the identification of congenital heart defects (CHDs) in fetuses with an enlarged nuchal translucency (NT) and a normal karyotype. All chromosomally normal fetuses referred to our Fetal Medicine Unit between September 1996 and December 2008 with known NT, DV-PIV and ductus venosus (DV) a-wave measurements were included. Intrafetus variation in DV-PIV was overcome by averaging three recordings. Follow-up included special focus on CHD. The odds of CHD at any NT and DV-PIV value were evaluated using logistic regression analysis. Of 792 fetuses included, the NT was enlarged (equal to or above the 95(th) percentile (P95)) in 318 (40.2%). The DV-PIV was abnormal (≥ P95) in 41.8% of the fetuses with an enlarged NT and the a-wave was abnormal (negative or reversed) in 29.9%. CHD was diagnosed in 35 fetuses, 33 of which had an enlarged NT. Amongst the fetuses with an enlarged NT, the sensitivities for CHD of abnormal DV-PIV and DV a-wave were 73% and 55%, with specificities of 62% and 73%, respectively. Logistic regression analysis showed that in this risk group the DV-PIV multiple of the median (MoM) (as a continuous variable) was significantly associated with the risk of CHD (odds ratio = 2.4), independent of the degree of NT enlargement, whereas the DV a-wave did not significantly add to the prediction of CHD. Two-thirds of fetuses with an enlarged NT, a normal karyotype and CHD have an increased DV-PIV. DV-PIV can be used as continuous variable in combination with NT to increase specificity in the identification of CHD and to refine the individual risk assessment.