Title Managing uncertainty in decision-making of common congenital cardiac defects /
Authors McMahon, Colin J ; Sendžikaitė, Skaistė ; Jegatheeswaran, Anusha ; Cheung, Yiu-Fai ; Madjalany, David S ; Hjortdal, Vibeke ; Redington, Andrew N ; Jacobs, Jeffrey P ; Asoodar, Maryam ; Sibbald, Matthew ; Geva, Tal ; van Merrienboer, Jeroen J G ; Tretter, Justin T ; van Merrienboer, Jeroen J. G
DOI 10.1017/S1047951122003316
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Is Part of Cardiology in the young.. Cambridge : Cambridge University Press. 2022, vol. 32, no. 11, art. no. PII S1047951122003316, p. 1705-1717.. ISSN 1047-9511. eISSN 1467-1107
Keywords [eng] Anomalous coronary artery ; aortic regurgitation ; decision-making ; subaortic stenosis ; uncertainty ; ventricular septal defect
Abstract [eng] Decision-making in congenital cardiac care, although sometimes appearing simple, may prove challenging due to lack of data, uncertainty about outcomes, underlying heuristics, and potential biases in how we reach decisions. We report on the decision-making complexities and uncertainty in management of five commonly encountered congenital cardiac problems: indications for and timing of treatment of subaortic stenosis, closure or observation of small ventricular septal defects, management of new-onset aortic regurgitation in ventricular septal defect, management of anomalous aortic origin of a coronary artery in an asymptomatic patient, and indications for operating on a single anomalously draining pulmonary vein. The strategy underpinning each lesion and the indications for and against intervention are outlined. Areas of uncertainty are clearly delineated. Even in the presence of "simple" congenital cardiac lesions, uncertainty exists in decision-making. Awareness and acceptance of uncertainty is first required to facilitate efforts at mitigation. Strategies to circumvent uncertainty in these scenarios include greater availability of evidence-based medicine, larger datasets, standardised clinical assessment and management protocols, and potentially the incorporation of artificial intelligence into the decision-making process.
Published Cambridge : Cambridge University Press
Type Journal article
Language English
Publication date 2022
CC license CC license description