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Background: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data., Methods: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups., Results: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF., Conclusions: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles., (© 2024. The Author(s).)

Congenital heart disease (CHD) has a complex and largely uncharacterised genetic etiology. Using 200,000 UK Biobank (UKB) exomes, we assess the burden of ultra-rare, potentially pathogenic variants in the largest case/control cohort of predominantly mild CHD to date. We find an association with GATA6, a member of the GATA family of transcription factors that play an important role during heart development and has been linked with several CHD phenotypes previously. Several identified GATA6 variants are previously unreported and their roles in conferring risk to CHD warrants further study. We demonstrate that despite limitations regarding detailed familial phenotype information in large-scale biobank projects, through careful consideration of case and control cohorts it is possible to derive important associations., (© 2021. The Author(s).)

Aim: We describe the characteristics and outcomes of cardiogenic shock (CS) admissions to a UK transplant unit, which is previously unreported., Patients & Methods: Fifty-nine unselected, consecutive patients over a 38-month period in CS (INTERMACS ≤2) and potentially eligible for transplant were retrospectively reviewed., Results: Patients were predominantly male (76.3%), young (mean age 42.2 years) and with severe end-organ dysfunction (acute liver/kidney injury 83%, mean lactate 3.5 mmol/l). 57.6% required mechanical support and 28.8% cardiac transplant. 30 days, discharge and 1-year survival were 78, 68 and 63%, respectively. Predictors of death included no transplant, increasing age and increasing creatinine., Conclusion: Patients with CS and potential for transplant require significant resource input but demonstrate favorable outcomes in our experience.