Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0018799 (heart disease)
 34,133 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

This review discusses the historical aspects, current state of the art, and potential future advances in the areas of nomenclature and databases for congenital heart disease. Five areas will be reviewed: (1) common language = nomenclature, (2) mechanism of data collection (database or registry) with an established uniform core data set, (3) mechanism of evaluating case complexity, (4) mechanism to ensure and verify data completeness and accuracy, and (5) collaboration between medical subspecialties. During the 1990s, both the Society of Thoracic Surgeons (STS) and the European Association for Cardiothoracic Surgery (EACTS) created congenital heart surgery outcomes databases. Beginning in 1998, the EACTS and STS collaborated in the work of the International Congenital Heart Surgery Nomenclature and Database Project. By 2000, a common congenital heart surgery nomenclature, along with a common core minimal data set, were adopted by the EACTS and the STS and published in the Annals of Thoracic Surgery. In 2000, the International Nomenclature Committee for Pediatric and Congenital Heart Disease was established; this committee eventually evolved into the International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD). The working component of ISNPCHD is the International Working Group for Mapping and Coding of Nomenclatures for Paediatric and Congenital Heart Disease, also known as the Nomenclature Working Group (NWG). By 2005, the NWG cross-mapped the EACTS-STS nomenclature with the European Paediatric Cardiac Code of the Association for European Paediatric Cardiology and created the International Paediatric and Congenital Cardiac Code (IPCCC) ( http://www.IPCCC.NET ). This common nomenclature (IPCCC), and the common minimum database data set created by the International Congenital Heart Surgery Nomenclature and Database Project, are now utilized by both EACTS and STS; since 1998, this nomenclature and database have been used by both the STS and EACTS to analyze outcomes of more than 75,000 patients. Two major multi-institutional efforts have attempted to measure case complexity; the Risk Adjustment in Congenital Heart Surgery-1 and the Aristotle Complexity Score. Efforts to unify these two scoring systems are in their early stages but are encouraging. Collaborative efforts involving the EACTS and STS are under way to develop mechanisms to verify data completeness and accuracy. Further collaborative efforts are also ongoing between pediatric and congenital heart surgeons and other subspecialties, including pediatric cardiac anesthesiologists (via the Congenital Cardiac Anesthesia Society), pediatric cardiac intensivists (via the Pediatric Cardiac Intensive Care Society), and pediatric cardiologists (via the Joint Council on Congenital Heart Disease). Clearly, methods of congenital heart disease outcomes analysis continue to evolve, with continued advances in five areas: nomenclature, database, complexity adjustment, data verification, and subspecialty collaboration.
 ...
PMID:Nomenclature and databases - the past, the present, and the future : a primer for the congenital heart surgeon. 1748 90

In 2000, The International Nomenclature Committee for Pediatric and Congenital Heart Disease was established. This committee eventually evolved into the International Society for Nomenclature of Paediatric and Congenital Heart Disease. The working component of this international nomenclature society has been The International Working Group for Mapping and Coding of Nomenclatures for Paediatric and Congenital Heart Disease, also known as the Nomenclature Working Group. The Nomenclature Working Group created the International Paediatric and Congenital Cardiac Code, which is available for free download from the internet at [http://www.IPCCC.NET]. In previous publications from the Nomenclature Working Group, unity has been produced by cross-mapping separate systems for coding, as for example in the treatment of the functionally univentricular heart, hypoplastic left heart syndrome, or congenitally corrected transposition. In this manuscript, we review the nomenclature, definition, and classification of heterotaxy, also known as the heterotaxy syndrome, placing special emphasis on the philosophical approach taken by both the Bostonian school of segmental notation developed from the teachings of Van Praagh, and the European school of sequential segmental analysis. The Nomenclature Working Group offers the following definition for the term "heterotaxy": "Heterotaxy is synonymous with 'visceral heterotaxy' and 'heterotaxy syndrome'. Heterotaxy is defined as an abnormality where the internal thoraco-abdominal organs demonstrate abnormal arrangement across the left-right axis of the body. By convention, heterotaxy does not include patients with either the expected usual or normal arrangement of the internal organs along the left-right axis, also known as 'situs solitus', nor patients with complete mirror-imaged arrangement of the internal organs along the left-right axis also known as 'situs inversus'." "Situs ambiguus is defined as an abnormality in which there are components of situs solitus and situs inversus in the same person. Situs ambiguus, therefore, can be considered to be present when the thoracic and abdominal organs are positioned in such a way with respect to each other as to be not clearly lateralised and thus have neither the usual, or normal, nor the mirror-imaged arrangements."The heterotaxy syndrome as thus defined is typically associated with complex cardiovascular malformations. Proper description of the heart in patients with this syndrome requires complete description of both the cardiac relations and the junctional connections of the cardiac segments, with documentation of the arrangement of the atrial appendages, the ventricular topology, the nature of the unions of the segments across the atrioventricular and the ventriculoarterial junctions, the infundibular morphologies, and the relationships of the arterial trunks in space. The position of the heart in the chest, and the orientation of the cardiac apex, must also be described separately. Particular attention is required for the venoatrial connections, since these are so often abnormal. The malformations within the heart are then analysed and described separately as for any patient with suspected congenital cardiac disease. The relationship and arrangement of the remaining thoraco-abdominal organs, including the spleen, the lungs, and the intestines, also must be described separately, because, although common patterns of association have been identified, there are frequent exceptions to these common patterns. One of the clinically important implications of heterotaxy syndrome is that splenic abnormalities are common. Investigation of any patient with the cardiac findings associated with heterotaxy, therefore, should include analysis of splenic morphology. The less than perfect association between the state of the spleen and the form of heart disease implies that splenic morphology should be investigated in all forms of heterotaxy, regardless of the type of cardiac disease. The splenic morphology should not be used to stratify the form of disease within the heart, and the form of cardiac disease should not be used to stratify the state of the spleen. Intestinal malrotation is another frequently associated lesion that must be considered. Some advocate that all patients with heterotaxy, especially those with isomerism of the right atrial appendages or asplenia syndrome, should have a barium study to evaluate for intestinal malrotation, given the associated potential morbidity. The cardiac anatomy and associated cardiac malformations, as well as the relationship and arrangement of the remaining thoraco-abdominal organs, must be described separately. It is only by utilizing this stepwise and logical progression of analysis that it becomes possible to describe correctly, and to classify properly, patients with heterotaxy.
 ...
PMID:The nomenclature, definition and classification of cardiac structures in the setting of heterotaxy. 1803 96

Electronic medical records (EMRs) for diabetic patients contain information about heart disease risk factors such as high blood pressure, cholesterol levels, and smoking status. Discovering the described risk factors and tracking their progression over time may support medical personnel in making clinical decisions, as well as facilitate data modeling and biomedical research. Such highly patient-specific knowledge is essential to driving the advancement of evidence-based practice, and can also help improve personalized medicine and care. One general approach for tracking the progression of diseases and their risk factors described in EMRs is to first recognize all temporal expressions, and then assign each of them to the nearest target medical concept. However, this method may not always provide the correct associations. In light of this, this work introduces a context-aware approach to assign the time attributes of the recognized risk factors by reconstructing contexts that contain more reliable temporal expressions. The evaluation results on the i2b2 test set demonstrate the efficacy of the proposed approach, which achieved an F-score of 0.897. To boost the approach's ability to process unstructured clinical text and to allow for the reproduction of the demonstrated results, a set of developed .NET libraries used to develop the system is available at https://sites.google.com/site/hongjiedai/projects/nttmuclinicalnet.
...
PMID:A context-aware approach for progression tracking of medical concepts in electronic medical records. 2643 55

In this paper, we present an automated procedure to determine the presence of cardiomegaly on chest X-ray image based on deep learning. The proposed algorithm CardioXNet uses deep learning methods U-NET and cardiothoracic ratio for diagnosis of cardiomegaly from chest X-rays. U-NET learns the segmentation task from the ground truth data. OpenCV is used to denoise and maintain the precision of region of interest once minor errors occur. Therefore, Cardiothoracic ratio (CTR) is calculated as a criterion to determine cardiomegaly from U-net segmentations. End-to-end Dense-Net neural network is used as baseline. This study has shown that the feasibility of combing deep learning segmentation and medical criterion to automatically recognize heart disease in medical images with high accuracy and agreement with the clinical results.
 ...
PMID:CardioXNet: Automated Detection for Cardiomegaly Based on Deep Learning. 3044 Apr 71