Objective We explore shared decision making (DM) in guardians of children with heart disease by assessing the desired weight of influence on DM and factors that may alter the relative weight of parent or medical team influence. Methods Guardians of patients 1 week in the paediatric cardiac intensive care unit (PCICU) were recruited. Twelve vignettes were designed including technical (antibiotic selection, intubation, peripherally inserted central catheter placement, ventricular assist device placement, heart transplant, organ rejection, heart rhythm abnormalities and resuscitation effort) and non-technical vignettes (cessation of life-sustaining therapies, depression treatment, obesity and palliative care referral). Participants responded to questions on DM characteristics and one question querying preference for relative weight of parent or medical team influence on DM. Results Of 209 participants approached, 183 were included. Most responded with equal desire of medical team and parental influence on DM in all vignettes (range 41.0%–66.7%). Technical scenarios formed one cluster based on DM characteristics, compared with non-technical scenarios. Factors that increase the relative weight of parental influence on DM include desired input and involvement in big-picture goals (OR 0.274, CI [0.217 to 0.346]; OR 0.794, CI [0.640 to 0.986]). Factors that increase the relative weight of medical team influence on DM include perception of medical expertise needed (OR 1.949 [1.630 to 2.330]), urgency (OR 1.373 [1.138 to 1.658]), benefit (OR 1.415 [1.172 to 1.710]), number of PCICU admissions (OR 1.134 [1.024 to 1.256]) and private insurance (OR 1.921 [1.144 to 3.226]). Conclusion Although factors may alter the weight of influence on DM, most parents desire equal parental and medical team influence on DM.

BACKGROUND: With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari , to improve variant evaluation. METHODS: The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing. RESULTS: We developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P< 0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance ( P< 0.0001) and 23.4% of those reclassified as likely benign/benign ( P <0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign ( P< 0.01). CONCLUSIONS: DiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios.