Royal Brompton & Harefield NHS Foundation Trust

Abstract Background Direct-to-patient platforms can remove geographic and clinic-capacity barriers to rare-disease research. Heart Hive was developed to support nationwide, genomics-enabled cardiomyopathy research and rapid patient-study matching. Methods Adults with a cardiomyopathy diagnosis or inherited risk self-enrol in the heart hive platform, complete baseline data about their condition for study matching, and are invited to provide longitudinal data including patient-reported outcomes. In a pilot Cardiomyopathy Study to validate this route of patient identification, participants provided online consent and returned saliva kits by post for central targeted sequencing (cardiomyopathy panel). Participants have consented to linkage with national death registrations (ONS) and Hospital Episode Statistics (HES). Engagement is supported by formal PPIE and patient-group partnerships. The Cardiomyopathy Study is ongoing: initially focused on HCM/DCM, it now includes ARVC and Takotsubo and is transitioning to whole-genome sequencing to characterise both rare and common variation. Results As of October 2024, 338 participants met eligibility for the validation study; 227/338 (67.5%) enrolled and completed baseline surveys; 195/227 (86%) returned saliva kits; 174 were sequenced for the study; follow-up survey completion was 83% among sequenced participants. The pilot cohort (98 DCM; 76 HCM) was 57% female, 97.7% White European ancestry, median age 57.5 years at recruitment; 78% had never previously taken part in cardiovascular research. Genetic architecture was equivalent to a clinic-recruited comparator: rare variants in DCM genes in 34.7% vs 30.6% (p=0.42) and in HCM genes in 44.7% vs 38.2% (p=0.30), with no gene-level distribution differences. Actionable variants were identified in 17% of DCM and 29% of HCM participants opting for personal results. Conclusions The pilot Cardiomyopathy Study validates that patient self-report can identify cardiomyopathy patients with the same accuracy as clinic-ascertained cohorts based on equivalent genetic architecture. We also show our approach generates strong engagement and retention. The Heart Hive platform operationalises a trial-ready, patient-centred model for cardiomyopathy: fully decentralised enrolment, sustained retention, and linkage-ready approvals for registry-verified outcomes. More broadly, the Heart Hive platform provides a national ‘front door’ for REC-approved cardiovascular research: patient–study matching (including genotype where required), study-specific e-consent, longitudinal participant-facing data capture and democratised sharing of study opportunities with research-willing participants. Optional mail-out genomic sequencing can be deployed when a project requires genotype-confirmed eligibility, enabling rapid feasibility checks, start-up, and re-contact for precision-therapy studies.

Background: Evidence of the diverse genetic architecture of dilated cardiomyopathy (DCM) continues to emerge and requires reassessment of the clinical relevance of implicated disease genes. Building on the 2019-2020 Clinical Genome Resource (ClinGen) evaluation, the DCM Gene Curation Expert Panel (GCEP) reconvened in 2024-2025 to conduct a reassessment of genes in DCM. Methods: The ClinGen semi-quantitative clinical validity classification framework was applied with specifications to DCM to classify genes into categories based upon strength of published evidence for a DCM phenotype. Previously curated genes were reassessed and newly reported gene-disease-mode of inheritance (MOI) relationships, termed ?curations,? were evaluated. Results: Sixty-eight genes were evaluated, inclusive of 72 unique gene-disease-MOI relationships across 51 previously evaluated and 17 newly assessed genes. Thirty-five curations were classified as high evidence (16 Definitive, 10 Strong, 9 Moderate), increasing by 16 from the prior assessment. Nine newly assessed genes were classified as high evidence, including BAG5, FLII, LMOD2, MYLK3, MYZAP, NRAP, PPA2, PPP1R13L, and RPL3L. Twelve genes (11 newly appraised) were rated as high evidence with an autosomal recessive (AR) MOI. Five re-evaluated genes from 2019-2020 had clinically significant changes in classification. Except for JPH2, for which curation was modified to separate autosomal dominant (-AD) and -AR MOI curations, clinically significant changes involved upgrades from low to high evidence categories (PLEKHM2, PRDM16, TBX20, TNNI3K), demonstrating the robustness of the ClinGen gene curation process over time. An additional 29 gene-disease-MOI curations were classified as Limited, including six newly evaluated genes and one new MOI for a previously evaluated gene, MYBPC3-AR; four were classified as No Known Disease Relationship, and four remained Disputed. Four previously evaluated genes were curated for both AD and AR MOIs, including JPH2 (AD-Strong, AR-Limited), LDB3 (AD-Limited, AR-Strong), MYBPC3 (AD-Limited, AR-Limited), and TNNI3 (AD- and AR- Strong). Conclusions: With substantial new evidence, the genetic architecture of DCM has rapidly expanded. This updated assessment of genes reported in DCM yielded 35 high evidence curations, an increase from 19 only five years ago. The results of this evidence-based evaluation process informs clinical interpretation of genetic information in the care of DCM patients and families.

An approach to rapid simulation of time-averaged wall shear stress (TAWSS) on 3D geometries created from 3D Quantitative Coronary Angiography (3D-QCA) methodology has been developed, which enables rapid computational fluid dynamic (CFD) shear stress simulation. We compared TAWSS estimated from 3D-QCA-CFD with optical coherence tomography (OCT)-based CFD simulations in coronary arteries. 15 normal and 5 stenotic coronary arteries in instrumented minipigs were studied. 3D arterial geometries were reconstructed from 3D-QCA and OCT using common centrelines and matched axial positions. Identical boundary conditions were used for both methods through directly measured vessel-specific inlet blood velocities. TAWSS was calculated for axially matched segments (n = 80 for normal arteries; n = 160 for stenotic arteries) and in 3mm/60° sectors. Mean TAWSS simulation times for 3D-QCA and OCT-based CFD were 17.8min and ~ 1.5h respectively. There were significant but numerically small differences in TAWSS for normal arteries (-0.21 ± 0.64Pa [95%CI -1.04,1.46], p < 0.001), and no significant difference for stenotic arteries (-0.39 ± 3.04Pa [95%CI -6.35, 5.56], p = 0.25). Axial TAWSS profiles along vessel lengths were similar between the two methods. There is a trend of underestimation by 3D-QCA at higher values of TAWSS compared with OCT, due to differences in geometry dimensions. Similar spatial distributions of TAWSS in both normal and stenotic arteries were observed from co-registered TAWSS maps. This study suggests that 3D-QCA-based TAWSS is feasible in both normal and stenotic arteries and that further clinical evaluation of rapid TAWSS from 3D-QCA is warranted, which may facilitate clinical adoption of TAWSS assessment.

Abstract Complex distal left main (LM) coronary artery disease with bifurcation involvement and chronic total occlusion (CTO) is usually treated with coronary artery bypass grafting (CABG). Patient refusal of surgery necessitates high-risk percutaneous revascularization that may require mechanical circulatory support. Here, we present a case of a 66-year-old male with Canadian Cardiovascular Society class III angina and preserved left ventricular ejection fraction (LVEF 60%) who was diagnosed with severe calcified distal LM stenosis extending into the left ostial circumflex (LCx), and a proximal left anterior descending (LAD) CTO. CABG was recommended but declined by the patient and high-risk PCI was performed with haemodynamic support using Impella CP™ with SmartAssist. Lesion preparation included rotational atherectomy followed by intravascular lithotripsy of LM, LAD, and LCx. The LAD CTO was successfully recanalized and treated with two drug-eluting stents and two drug-coated balloons. A double-kissing culotte two-stent strategy was applied for the distal LM bifurcation, guided by intravascular ultrasound. Haemodynamics remained stable, with Impella support successfully preventing instability during hypotensive phases and during extensive lesion modification of the left main using rotational atherectomy. Patient was discharged on dual antiplatelet therapy and remained free of angina with preserved LVEF and an excellent angiographic result at 6-month follow-up. This case demonstrates how Impella support enabled safe, complete revascularization of high-risk LM bifurcation CTO disease when CABG was declined. Moreover, this case illustrates that protected PCI with an Impella device can provide a safe alternative to surgery in anatomically complex LM disease, ensuring procedural stability and complete revascularization.

Background: AMR is a public health concern which leads to high global morbidity and mortality. Immunocompromised patients, who are more susceptible to contracting potentially life-threatening infections, are faced with reduced treatment options due to emerging AMR. Ceftolozane/tazobactam is a novel β-lactam/β-lactamase inhibitor which displays effectiveness against resistant Gram-negative infections. Methods: SPECTRA was a multinational, observational study conducted in seven countries including 617 patients who received ≥48 h of ceftolozane/tazobactam. Medical-record data were collected up to 6 months before treatment and 30 days after the final dose or until death. This analysis describes clinical outcomes and healthcare resource use in patients with sepsis or who were immunocompromised, specifically in patients with hematologic malignancy with and without solid tumor, febrile neutropenia, and solid organ transplant patients. Results: Clinical success ranged from 50.0% in patients with hematologic malignancy and solid tumor to 69.4% in 38 patients with febrile neutropenia. All-cause in-hospital mortality was 23.1-42.9%, with the lowest rates in patients with solid organ transplant. ICU admission was 46.4-68.2% across subpopulations (excluding febrile neutropenia) with the lowest rates in patients with hematologic malignancy. ICU length of stay was lowest within transplant patients (9 days) and highest within the hematologic malignancy and solid tumor population (32 days). Conclusions: The results from this sub analysis of SPECTRA showed that ceftolozane/tazobactam was associated with clinical success in the selected immunocompromised and sepsis patient populations and may lead to reduced morbidity, mortality, and healthcare-resource use. Further research is required to standardize treatment protocols and improve patient outcomes.

Multiple risk scores and biomarkers have been proposed for the prediction of atrial fibrillation (AF), but it is unknown how these compare with each other and whether they could be combined. This study aimed to evaluate and compare approaches for incident AF prediction. The artificial intelligence-enhanced electrocardiogram risk estimator-AF (AIRE-AF), a convolutional neural network with a discrete-time survival loss function, was developed to predict incident AF. It was trained using a dataset of 1,163,401 electrocardiograms from 189,539 patients from the Beth Israel Deaconess Medical Center and externally validated in the UK Biobank (n = 38,892). AIRE-AF was compared with other risk prediction approaches including the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF, a clinical risk score. In the Beth Israel Deaconess Medical Center cohort, AIRE-AF predicted incident AF with a C-index of 0.750 (0.743-0.758). AIRE-AF was superior to CHARGE-AF, left atrial size, and N-terminal pro-B-type natriuretic peptide. The addition of CHARGE-AF and left atrial size provided a minor improvement in performance (C-index improvement 0.017). There was no additive value of N-terminal pro-B-type natriuretic peptide in combination with AIRE-AF. The single best-performing single predictor in the volunteer population (UK Biobank) was CHARGE-AF (C-index 0.750 [0.734-0.769]). The best-performing combination of 2 predictors was AIRE-AF and CHARGE-AF (C-index 0.768 [0.743-0.792]). The addition of a polygenic risk score to AIRE-AF and CHARGE-AF provided a further significant improvement in performance (C-index 0.791 [0.766-0.816]). We present the first comprehensive evaluation of methodologies for predicting incident AF. Risk prediction with a model including AIRE-AF and CHARGE-AF resulted in similar performance to more complex models.

Routine monitoring of surgical outcomes can improve service quality. Risk-adjusted monitoring tools for adults with congenital heart disease (CHD) in England and Wales are lacking. Using national audit data of all adult CHD surgical procedures in public hospitals from 2015 to 2022, we developed logistic regression models for mortality at 30 days and 90 days and a 30-day complications outcome. Risk factors included patient demographics and categorical derived variables for case complexity and procedure risk. Model performance was assessed by area under the receiver operating characteristic curve and calibration errors for in-sample and cross-validation data sets. Average 30-day and 90-day mortality were 1.4% (49/3502) and 1.7% (58/3493). Moderate and severe CHD complexity were strong predictors of 30-day mortality (odds ratio [95% CI], 3.5 [0.8-15.8], 8.6 [2.4-30.9]), as was high-risk procedure (OR, 3.6 [2.1-6.0]). Average 30-day complication rate was 7.5% (242/3223). Procedure risk groups (OR, 2.4 [0.9-6.0] to 12.2 [4.0-36.8]) and procedure complexity (OR, 2.5 [1.5-4.3]) were the strongest predictors. In cross-validation, 30-day and 90-day mortality models had median discrimination (interquartile range in parentheses) of 0.844 (0.84-0.85) and 0.866 (0.86-0.87), calibration slopes of 1.05 (0.60-1.13) and 1.11 (0.61-1.21), and calibration-in-the-large of 0.00 (-0.12 to 0.19) and -0.07 (-0.17 to 0.30). The 30-day complications model had cross-validation discrimination of 0.760 (0.76-0.76), calibration slope of 0.93 (0.74-1.18), and calibration-in-the-large of -0.07 (-0.13 to 0.22). The adult CHD risk models perform well for short-term mortality despite a low number of events. The risk model for 30-day complications showed reduced performance, suggesting that important risk factors are not captured by routinely collected data.