scholarly journals Medicine-Based Evidence in Congenital Heart Disease: How Artificial Intelligence Can Guide Treatment Decisions for Individual Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Jef Van den Eynde ◽  
Cedric Manlhiot ◽  
Alexander Van De Bruaene ◽  
Gerhard-Paul Diller ◽  
Alejandro F. Frangi ◽  
...  

Built on the foundation of the randomized controlled trial (RCT), Evidence Based Medicine (EBM) is at its best when optimizing outcomes for homogeneous cohorts of patients like those participating in an RCT. Its weakness is a failure to resolve a clinical quandary: patients appear for care individually, each may differ in important ways from an RCT cohort, and the physician will wonder each time if following EBM will provide best guidance for this unique patient. In an effort to overcome this weakness, and promote higher quality care through a more personalized approach, a new framework has been proposed: Medicine-Based Evidence (MBE). In this approach, big data and deep learning techniques are embraced to interrogate treatment responses among patients in real-world clinical practice. Such statistical models are then integrated with mechanistic disease models to construct a “digital twin,” which serves as the real-time digital counterpart of a patient. MBE is thereby capable of dynamically modeling the effects of various treatment decisions in the context of an individual's specific characteristics. In this article, we discuss how MBE could benefit patients with congenital heart disease, a field where RCTs are difficult to conduct and often fail to provide definitive solutions because of a small number of subjects, their clinical complexity, and heterogeneity. We will also highlight the challenges that must be addressed before MBE can be embraced in clinical practice and its full potential can be realized.

2021 ◽  
Vol 11 (6) ◽  
pp. 562
Author(s):  
Olga María Diz ◽  
Rocio Toro ◽  
Sergi Cesar ◽  
Olga Gomez ◽  
Georgia Sarquella-Brugada ◽  
...  

Congenital heart disease is a group of pathologies characterized by structural malformations of the heart or great vessels. These alterations occur during the embryonic period and are the most frequently observed severe congenital malformations, the main cause of neonatal mortality due to malformation, and the second most frequent congenital malformations overall after malformations of the central nervous system. The severity of different types of congenital heart disease varies depending on the combination of associated anatomical defects. The causes of these malformations are usually considered multifactorial, but genetic variants play a key role. Currently, use of high-throughput genetic technologies allows identification of pathogenic aneuploidies, deletions/duplications of large segments, as well as rare single nucleotide variants. The high incidence of congenital heart disease as well as the associated complications makes it necessary to establish a diagnosis as early as possible to adopt the most appropriate measures in a personalized approach. In this review, we provide an exhaustive update of the genetic bases of the most frequent congenital heart diseases as well as other syndromes associated with congenital heart defects, and how genetic data can be translated to clinical practice in a personalized approach.


2019 ◽  
Vol 29 (09) ◽  
pp. 1172-1182 ◽  
Author(s):  
Malindi van der Mheen ◽  
Maya G. Meentken ◽  
Ingrid M. van Beynum ◽  
Jan van der Ende ◽  
Eugène van Galen ◽  
...  

AbstractObjective:Children with congenital heart disease and their families are at risk of psychosocial problems. Emotional and behavioural problems, impaired school functioning, and reduced exercise capacity often occur. To prevent and decrease these problems, we modified and extended the previously established Congenital Heart Disease Intervention Program (CHIP)–School, thereby creating CHIP-Family. CHIP-Family is the first psychosocial intervention with a module for children with congenital heart disease. Through a randomised controlled trial, we examined the effectiveness of CHIP-Family.Methods:Ninety-three children with congenital heart disease (age M = 5.34 years, SD = 1.27) were randomised to CHIP-Family (n = 49) or care as usual (no psychosocial care; n = 44). CHIP-Family consisted of a 1-day group workshop for parents, children, and siblings and an individual follow-up session for parents. CHIP-Family was delivered by psychologists, paediatric cardiologists, and physiotherapists. At baseline and 6-month follow-up, mothers, fathers, teachers, and the child completed questionnaires to assess psychosocial problems, school functioning, and sports enjoyment. Moreover, at 6-month follow-up, parents completed program satisfaction assessments.Results:Although small improvements in child outcomes were observed in the CHIP-Family group, no statistically significant differences were found between outcomes of the CHIP-Family and care-as-usual group. Mean parent satisfaction ratings ranged from 7.4 to 8.1 (range 0–10).Conclusions:CHIP-Family yielded high program acceptability ratings. However, compared to care as usual, CHIP-Family did not find the same extent of statistically significant outcomes as CHIP-School. Replication of promising psychological interventions, and examination of when different outcomes are found, is recommended for refining interventions in the future.Trial registryDutch Trial Registry number NTR6063, https://www.trialregister.nl/trial/5780.


2020 ◽  
Author(s):  
Keila N. Lopez ◽  
Shaine A. Morris ◽  
Kristen Sexson Tejtel ◽  
Andre Espaillat ◽  
Jason L. Salemi

ABSTRACTBackgroundCongenital heart disease (CHD) accounts for approximately 40% percent of deaths in United States (US) children with birth defects. Previous US data from 1999-2006 demonstrated an overall decrease in CHD mortality. The objective of our study was to assess current trends in US mortality related to CHD from infancy to adulthood over the last 19 years and determine differences by sex and race/ethnicity.MethodsWe conducted an analysis of death certificates from 1999-2017 to calculate annual CHD mortality by age at death, race/ethnicity, and sex. Population estimates used as denominators in mortality rate calculation for infants were based on National Center for Health Statistics live birth data. Mortality rates in individuals >1 year of age utilized US Census Bureau bridged-race estimates as denominators for population estimates. We characterized temporal trends in all-cause mortality, mortality resulting directly due to and related to CHD by age, race/ethnicity, and sex using joinpoint regression.ResultsThere were 47.7 million deaths with 1 in 814 deaths due to CHD (n=58,599). While all-cause mortality decreased 16.4% across all ages, mortality resulting from CHD declined 39.4% overall. The mean annual decrease in CHD mortality was 2.6%, with the largest decrease for those age >65years. The age-adjusted mortality rate decreased from 1.37 to 0.83 per 100,000. Males had higher mortality due to CHD than females throughout the study, although both sexes declined at a similar rate (∼40% overall), with a 3-4% annual decrease between 1999 and 2009, followed by a slower annual decrease of 1.4% through 2017. Mortality resulting from CHD significantly declined among all race/ethnicities studied, although disparities in mortality persisted for non-Hispanic Blacks versus non-Hispanic Whites (mean annual decrease 2.3% versus 2.6%, respectively; age-adjusted mortality rate 1.67 to 1.05 versus 1.35 to 0.80 per 100,000, respectively).ConclusionsWhile overall US mortality due to CHD has decreased over the last 19 years, disparities in mortality persist for males compared to females and for non-Hispanic Blacks compared to non-Hispanic Whites. Determining factors that contribute to these disparities such as access to quality care, timely diagnosis, and maintenance of insurance will be important moving into the next decade.


2020 ◽  
Vol 227 ◽  
pp. 191-198.e3
Author(s):  
Johanna Calderon ◽  
David Wypij ◽  
Valerie Rofeberg ◽  
Christian Stopp ◽  
Alexandra Roseman ◽  
...  

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