Ventricular volume asymmetry as a novel imaging biomarker for disease discrimination and outcome prediction.

Aims: Disruption of the predictable symmetry of the healthy heart may be an indicator of cardiovascular risk. This study defines the population distribution of ventricular asymmetry and its relationships across a range of prevalent and incident cardiorespiratory diseases. Methods and results: The analysis includes 44 796 UK Biobank participants (average age 64.1 ± 7.7 years; 51.9% women). Cardiovascular magnetic resonance (CMR) metrics were derived using previously validated automated pipelines. Ventricular asymmetry was expressed as the ratio of left and right ventricular (LV and RV) end-diastolic volumes. Clinical outcomes were defined through linked health records. Incident events were those occurring for the first time after imaging, longitudinally tracked over an average follow-up time of 4.75 ± 1.52 years. The normal range for ventricular symmetry was defined in a healthy subset. Participants with values outside the 5th-95th percentiles of the healthy distribution were classed as either LV dominant (LV/RV > 112%) or RV dominant (LV/RV < 80%) asymmetry. Associations of LV and RV dominant asymmetry with vascular risk factors, CMR features, and prevalent and incident cardiovascular diseases (CVDs) were examined using regression models, adjusting for vascular risk factors, prevalent diseases, and conventional CMR measures. Left ventricular dominance was linked to an array of pre-existing vascular risk factors and CVDs, and a two-fold increased risk of incident heart failure, non-ischaemic cardiomyopathies, and left-sided valvular disorders. Right ventricular dominance was associated with an elevated risk of all-cause mortality. Conclusion: Ventricular asymmetry has clinical utility for cardiovascular risk assessment, providing information that is incremental to traditional risk factors and conventional CMR metrics.

Diagnostic utility of electrocardiogram for screening of cardiac injury on cardiac magnetic resonance in post-hospitalised COVID-19 patients: a prospective multicenter study.

BACKGROUND: The role of ECG in ruling out myocardial complications on cardiac magnetic resonance (CMR) is unclear. We examined the clinical utility of ECG in screening for cardiac abnormalities on CMR among post-hospitalised COVID-19 patients. METHODS: Post-hospitalised patients (n = 212) and age, sex and comorbidity-matched controls (n = 38) underwent CMR and 12­lead ECG in a prospective multicenter follow-up study. Participants were screened for routinely reported ECG abnormalities, including arrhythmia, conduction and R wave abnormalities and ST-T changes (excluding repolarisation intervals). Quantitative repolarisation analyses included corrected QT (QTc), corrected QT dispersion (QTc disp), corrected JT (JTc) and corrected T peak-end (cTPe) intervals. RESULTS: At a median of 5.6 months, patients had a higher burden of ECG abnormalities (72.2% vs controls 42.1%, p = 0.001) and lower LVEF but a comparable cumulative burden of CMR abnormalities than controls. Patients with CMR abnormalities had more ECG abnormalities and longer repolarisation intervals than those with normal CMR and controls (82% vs 69% vs 42%, p < 0.001). Routinely reported ECG abnormalities had poor discriminative ability (area-under-the-receiver-operating curve: AUROC) for abnormal CMR, AUROC 0.56 (95% CI 0.47-0.65), p = 0.185; worse among female than male patients. Adding JTc and QTc disp improved the AUROC to 0.64 (95% CI 0.55-0.74), p = 0.002, the sensitivity of the ECG increased from 81.6% to 98.0%, negative predictive value from 84.7% to 96.3%, negative likelihood ratio from 0.60 to 0.13, and reduced sex-dependence variabilities of ECG diagnostic parameters. CONCLUSION: Post-hospitalised COVID-19 patients have more ECG abnormalities than controls. Normal ECGs, including normal repolarisation intervals, reliably exclude CMR abnormalities in male and female patients.

Differentiating Left Ventricular Remodeling in Aortic Stenosis From Systemic Hypertension.

BACKGROUND: Left ventricular (LV) hypertrophy occurs in both aortic stenosis (AS) and systemic hypertension (HTN) in response to wall stress. However, differentiation of hypertrophy due to these 2 etiologies is lacking. The aim was to study the 3-dimensional geometric remodeling pattern in severe AS pre- and postsurgical aortic valve replacement and to compare with HTN and healthy controls. METHODS: Ninety-one subjects (36 severe AS, 19 HTN, and 36 healthy controls) underwent cine cardiac magnetic resonance. Cardiac magnetic resonance was repeated 8 months post-aortic valve replacement (n=18). Principal component analysis was performed on the 3-dimensional meshes reconstructed from 109 cardiac magnetic resonance scans of 91 subjects at end-diastole. Principal component analysis modes were compared across experimental groups together with conventional metrics of shape, strain, and scar. RESULTS: A unique AS signature was identified by wall thickness linked to a LV left-right axis shift and a decrease in short-axis eccentricity. HTN was uniquely linked to increased septal thickness. Combining these 3 features had good discriminative ability between AS and HTN (area under the curve, 0.792). The LV left-right axis shift was not reversible post-aortic valve replacement, did not associate with strain, age, or sex, and was predictive of postoperative LV mass regression (R2=0.339, P=0.014). CONCLUSIONS: Unique remodeling signatures might differentiate the etiology of LV hypertrophy. Preliminary findings suggest that LV axis shift is characteristic in AS, is not reversible post-aortic valve replacement, predicts mass regression, and may be interpreted to be an adaptive mechanism.

MRI-serum-based score accurately identifies liver transplant patients without rejection avoiding need for liver biopsy: A multisite European study.

BACKGROUND: Serum liver tests (serum tests) and histological assessment for T-cell mediated (TcM) rejection are essential for post-liver transplant monitoring. Liver biopsy carries risk of complications which are preferably avoided in low-risk patients. Multiparametric MRI (mpMRI) is a reliable non-invasive diagnostic method which quantifies liver disease activity and has prognostic utility. Our aim was to determine whether using mpMRI in combination with serum tests could noninvasively identify low-risk post-liver transplant patients who are eligible to avoid invasive liver biopsies. METHODS: In a multicentre prospective study (RADIcAL2), including 131 adult and paediatric (children and adolescent) patients with previous liver transplant from the Netherlands, Portugal, and UK, concomitant mpMRI and liver biopsies were performed. Biopsies were centrally read by two expert pathologists. TcM rejection was assessed using BANFF global assessment (BANFF-GA). Diagnostic accuracy to discriminate no rejection vs. indeterminate or TcM liver transplant rejection was performed using area under the receiver operating characteristic curve (AUC). RESULTS: In this study, 52% of patients received a routine (protocol) biopsy whilst 48% had a biopsy for suspicion of pathology. 38% of patients had no rejection, while 62% had either indeterminate (21%) or TcM rejection (41%). However, there was a high inter-observer variability (0

Hypertrophic cardiomyopathy detection with artificial intelligence electrocardiography in international cohorts: an external validation study.

Aims: Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results: A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm's ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910-0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case-control ratio 1:2), the AUC was 0.921 (95% CI 0.909-0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion: The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

Hyperpolarized 13C and 31P MRS detects differences in cardiac energetics, metabolism, and function in obesity, and responses following treatment.

Obesity is associated with important changes in cardiac energetics and function, and an increased risk of adverse cardiovascular outcomes. Multi-nuclear MRS and MRI techniques have the potential to provide a comprehensive non-invasive assessment of cardiac metabolic perturbation in obesity. A rat model of obesity was created by high-fat diet feeding. This model was characterized using in vivo hyperpolarized [1-13C]pyruvate and [2-13C]pyruvate MRS, echocardiography and perfused heart 31P MRS. Two groups of obese rats were subsequently treated with either caloric restriction or the glucagon-like peptide-1 analogue/agonist liraglutide, prior to reassessment. The model recapitulated cardiovascular consequences of human obesity, including mild left ventricular hypertrophy, and diastolic, but not systolic, dysfunction. Hyperpolarized 13C and 31P MRS demonstrated that obesity was associated with reduced myocardial pyruvate dehydrogenase flux, altered cardiac tricarboxylic acid (TCA) cycle metabolism, and impaired myocardial energetic status (lower phosphocreatine to adenosine triphosphate ratio and impaired cardiac ΔG~ATP). Both caloric restriction and liraglutide treatment were associated with normalization of metabolic changes, alongside improvement in cardiac diastolic function. In this model of obesity, hyperpolarized 13C and 31P MRS demonstrated abnormalities in cardiac metabolism at multiple levels, including myocardial substrate selection, TCA cycle, and high-energy phosphorus metabolism. Metabolic changes were linked with impairment of diastolic function and were reversed in concert following either caloric restriction or liraglutide treatment. With hyperpolarized 13C and 31P techniques now available for human use, the findings support a role for multi-nuclear MRS in the development of new therapies for obesity.

Liraglutide Improves Myocardial Perfusion and Energetics and Exercise Tolerance in Patients With Type 2 Diabetes.

BACKGROUND: Type 2 diabetes (T2D) is characterized by insulin resistance (IR) and dysregulated insulin secretion. Glucagon-like peptide-1 receptor agonist liraglutide promotes insulin secretion, whereas thiazolidinedione-pioglitazone decreases IR. OBJECTIVES: This study aimed to compare the efficacies of increasing insulin secretion vs decreasing IR strategies for improving myocardial perfusion, energetics, and function in T2D via an open-label randomized crossover trial. METHODS: Forty-one patients with T2D (age 63 years [95% CI: 59-68 years], 27 [66%] male, body mass index 27.8 kg/m2) [95% CI: 26.1-29.5 kg/m2)]) without cardiovascular disease were randomized to liraglutide or pioglitazone for a 16-week treatment followed by an 8-week washout and a further 16-week treatment with the second trial drug. Participants underwent rest and dobutamine stress 31phosphorus magnetic resonance spectroscopy and cardiovascular magnetic resonance for measuring the myocardial energetics index phosphocreatine to adenosine triphosphate ratio, myocardial perfusion (rest, dobutamine stress myocardial blood flow, and myocardial perfusion reserve), left ventricular (LV) volumes, systolic and diastolic function (mitral in-flow E/A ratio), before and after treatment. The 6-minute walk-test was used for functional assessments. RESULTS: Pioglitazone treatment resulted in significant increases in LV mass (96 g [95% CI: 68-105 g] to 105 g [95% CI: 74-115 g]; P = 0.003) and mitral-inflow E/A ratio (1.04 [95% CI: 0.62-1.21] to 1.34 [95% CI: 0.70-1.54]; P = 0.008), and a significant reduction in LV concentricity index (0.79 mg/mL [95% CI: 0.61-0.85 mg/mL] to 0.73 mg/mL [95% CI: 0.56-0.79 mg/mL]; P = 0.04). Liraglutide treatment increased stress myocardial blood flow (1.62 mL/g/min [95% CI: 1.19-1.75 mL/g/min] to 2.08 mL/g/min [95% CI: 1.57-2.24 mL/g/min]; P = 0.01) and myocardial perfusion reserve (2.40 [95% CI: 1.55-2.68] to 2.90 [95% CI: 1.83-3.18]; P = 0.01). Liraglutide treatment also significantly increased the rest (1.47 [95% CI: 1.17-1.58] to 1.94 [95% CI: 1.52-2.08]; P =0.00002) and stress phosphocreatine to adenosine triphosphate ratio (1.32 [95% CI: 1.05-1.42] to 1.58 [95% CI: 1.19-1.71]; P = 0.004) and 6-minute walk distance (488 m [95% CI: 458-518 m] to 521 m [95% CI: 481-561 m]; P = 0.009). CONCLUSIONS: Liraglutide treatment resulted in improved myocardial perfusion, energetics, and 6-minute walk distance in patients with T2D, whereas pioglitazone showed no effect on these parameters (Lean-DM [Targeting Beta-cell Failure in Lean Patients With Type 2 Diabetes]; NCT04657939).

Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Long COVID and cardiovascular disease: a prospective cohort study.

BACKGROUND: Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known. OBJECTIVES: To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors. METHODS: In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health. RESULTS: From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86). CONCLUSION: Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need. TRAIL REGISTRATION NUMBER: ISRCTN10980107.

Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank.

OBJECTIVES: Despite rising rates of multimorbidity, existing risk assessment tools are mostly limited to a single outcome of interest. This study tests the feasibility of producing multiple disease risk estimates with at least 70% discrimination (area under the receiver operating curve, AUROC) within the time and information constraints of the existing primary care health check framework. DESIGN: Observational prospective cohort study SETTING: UK Biobank. PARTICIPANTS: 228 240 adults from the UK population. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Myocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure. RESULTS: Using a set of predictors easily gathered at the standard primary care health check (such as the National Health Service Health Check), we demonstrate that it is feasible to simultaneously produce risk estimates for multiple disease outcomes with AUROC of 70% or greater. These predictors can be entered once into a single form and produce risk scores for stroke (AUROC 0.727, 95% CI 0.713 to 0.740), all-cause dementia (0.823, 95% CI 0.810 to 0.836), myocardial infarction (0.785, 95% CI 0.775 to 0.795), atrial fibrillation (0.777, 95% CI 0.768 to 0.785), heart failure (0.828, 95% CI 0.818 to 0.838), chronic kidney disease (0.774, 95% CI 0.765 to 0.783), fatty liver disease (0.766, 95% CI 0.753 to 0.779), alcoholic liver disease (0.864, 95% CI 0.835 to 0.894), liver cirrhosis (0.763, 95% CI 0.734 to 0.793) and liver failure (0.746, 95% CI 0.695 to 0.796). CONCLUSIONS: Easily collected diagnostics can be used to assess 10-year risk across multiple disease outcomes, without the need for specialist computing or invasive biomarkers. Such an approach could increase the utility of existing data and place multiorgan risk information at the fingertips of primary care providers, thus creating opportunities for longer-term multimorbidity prevention. Additional work is needed to validate whether these findings would hold in a larger, more representative cohort outside the UK Biobank.

Safety and Efficacy of Metabolic Modulation With Ninerafaxstat in Patients With Nonobstructive Hypertrophic Cardiomyopathy.

BACKGROUND: In nonobstructive hypertrophic cardiomyopathy (nHCM), there are no approved medical therapies. Impaired myocardial energetics is a potential cause of symptoms and exercise limitation. Ninerafaxstat, a novel cardiac mitotrope, enhances cardiac energetics. OBJECTIVES: This study sought to evaluate the safety and efficacy of ninerafaxstat in nHCM. METHODS: Patients with hypertrophic cardiomyopathy and left ventricular outflow tract gradient <30 mm Hg, ejection fraction ≥50%, and peak oxygen consumption <80% predicted were randomized to ninerafaxstat 200 mg twice daily or placebo (1:1) for 12 weeks. The primary endpoint was safety and tolerability, with efficacy outcomes also assessed as secondary endpoints. RESULTS: A total of 67 patients with nHCM were enrolled at 12 centers (57 ± 11.8 years of age; 55% women). Serious adverse events occurred in 11.8% (n = 4 of 34) in the ninerafaxstat group and 6.1% (n = 2 of 33) of patients in the placebo group. From baseline to 12 weeks, ninerafaxstat was associated with significantly better VE/Vco2 (ventilatory efficiency) slope compared with placebo with a least-squares (LS) mean difference between the groups of -2.1 (95% CI: -3.6 to -0.6; P = 0.006), with no significant difference in peak VO2 (P = 0.90). The Kansas City Cardiomyopathy Questionnaire Clinical Summary Score was directionally, though not significantly, improved with ninerafaxstat vs placebo (LS mean 3.2; 95% CI: -2.9 to 9.2; P = 0.30); however, it was statistically significant when analyzed post hoc in the 35 patients with baseline Kansas City Cardiomyopathy Questionnaire Clinical Summary Score ≤80 (LS mean 9.4; 95% CI: 0.3-18.5; P = 0.04). CONCLUSIONS: In symptomatic nHCM, novel drug therapy targeting myocardial energetics was safe and well tolerated and associated with better exercise performance and health status among those most symptomatically limited. The findings support assessing ninerafaxstat in a phase 3 study.

NHS Health Check attendance is associated with reduced multiorgan disease risk: a matched cohort study in the UK Biobank.

BACKGROUND: The NHS Health Check is a preventive programme in the UK designed to screen for cardiovascular risk and to aid in primary disease prevention. Despite its widespread implementation, the effectiveness of the NHS Health Check for longer-term disease prevention is unclear. In this study, we measured the rate of new diagnoses in UK Biobank participants who underwent the NHS Health Check compared with those who did not. METHODS: Within the UK Biobank prospective study, 48,602 NHS Health Check recipients were identified from linked primary care records. These participants were then covariate-matched on an extensive range of socio-demographic, lifestyle, and medical factors with 48,602 participants without record of the check. Follow-up diagnoses were ascertained from health records over an average of 9 years (SD 2 years) including hypertension, diabetes, hypercholesterolaemia, stroke, dementia, myocardial infarction, atrial fibrillation, heart failure, fatty liver disease, alcoholic liver disease, liver cirrhosis, liver failure, acute kidney injury, chronic kidney disease (stage 3 +), cardiovascular mortality, and all-cause mortality. Time-varying survival modelling was used to compare adjusted outcome rates between the groups. RESULTS: In the immediate 2 years after the NHS Health Check, higher diagnosis rates were observed for hypertension, high cholesterol, and chronic kidney disease among health check recipients compared to their matched counterparts. However, in the longer term, NHS Health Check recipients had significantly lower risk across all multiorgan disease outcomes and reduced rates of cardiovascular and all-cause mortality. CONCLUSIONS: The NHS Health Check is linked to reduced incidence of disease across multiple organ systems, which may be attributed to risk modification through earlier detection and treatment of key risk factors such as hypertension and high cholesterol. This work adds important evidence to the growing body of research supporting the effectiveness of preventative interventions in reducing longer-term multimorbidity.

Sex-based differences in risk factors for incident myocardial infarction and stroke in the UK Biobank.

AIM: This study examined sex-based differences in associations of vascular risk factors with incident cardiovascular events in the UK Biobank. METHODS: Baseline participant demographic, clinical, laboratory, anthropometric, and imaging characteristics were collected. Multivariable Cox regression was used to estimate independent associations of vascular risk factors with incident myocardial infarction (MI) and ischaemic stroke for men and women. Women-to-men ratios of hazard ratios (RHRs), and related 95% confidence intervals, represent the relative effect-size magnitude by sex. RESULTS: Among the 363 313 participants (53.5% women), 8470 experienced MI (29.9% women) and 7705 experienced stroke (40.1% women) over 12.66 [11.93, 13.38] years of prospective follow-up. Men had greater risk factor burden and higher arterial stiffness index at baseline. Women had greater age-related decline in aortic distensibility. Older age [RHR: 1.02 (1.01-1.03)], greater deprivation [RHR: 1.02 (1.00-1.03)], hypertension [RHR: 1.14 (1.02-1.27)], and current smoking [RHR: 1.45 (1.27-1.66)] were associated with a greater excess risk of MI in women than men. Low-density lipoprotein cholesterol was associated with excess MI risk in men [RHR: 0.90 (0.84-0.95)] and apolipoprotein A (ApoA) was less protective for MI in women [RHR: 1.65 (1.01-2.71)]. Older age was associated with excess risk of stroke [RHR: 1.01 (1.00-1.02)] and ApoA was less protective for stroke in women [RHR: 2.55 (1.58-4.14)]. CONCLUSION: Older age, hypertension, and smoking appeared stronger drivers of cardiovascular disease in women, whereas lipid metrics appeared stronger risk determinants for men. These findings highlight the importance of sex-specific preventive strategies and suggest priority targets for intervention in men and women.

Misclassification of females and males in cardiovascular magnetic resonance parametric mapping: the importance of sex-specific normal ranges for diagnosis of health vs. disease.

AIMS: Cardiovascular magnetic resonance parametric mapping enables non-invasive quantitative myocardial tissue characterization. Human myocardium has normal ranges of T1 and T2 values, deviation from which may indicate disease or change in physiology. Normal myocardial T1 and T2 values are affected by biological sex. Consequently, normal ranges created with insufficient numbers of each sex may result in sampling biases, misclassification of healthy values vs. disease, and even misdiagnoses. In this study, we investigated the impact of using male normal ranges for classifying female cases as normal or abnormal (and vice versa). METHODS AND RESULTS: One hundred and forty-two healthy volunteers (male and female) were scanned on two Siemens 3T MR systems, providing averaged global myocardial T1 and T2 values on a per-subject basis. The Monte Carlo method was used to generate simulated normal ranges from these values to estimate the statistical accuracy of classifying healthy female or male cases correctly as 'normal' when using sex-specific vs. mixed-sex normal ranges. The normal male and female T1- and T2-mapping values were significantly different by sex, after adjusting for age and heart rate. CONCLUSION: Using 15 healthy volunteers who are not sex specific to establish a normal range resulted in a typical misclassification of up to 36% of healthy females and 37% of healthy males as having abnormal T1 values and up to 16% of healthy females and 12% of healthy males as having abnormal T2 values. This paper highlights the potential adverse impact on diagnostic accuracy that can occur when local normal ranges contain insufficient numbers of both sexes. Sex-specific reference ranges should thus be routinely adopted in clinical practice.

Exercise capacity following SARS-CoV-2 infection is related to changes in cardiovascular and lung function in military personnel.

BACKGROUND: Since the COVID-19 pandemic, post-COVID syndrome (persistent symptoms/complications lasting >12 weeks) continues to pose medical and economic challenges. In military personnel, where optimal fitness is crucial, prolonged limitations affecting their ability to perform duties has occupational and psychological implications, impacting deployability and retention. Research investigating post-COVID syndrome exercise capacity and cardiopulmonary effects in military personnel is limited. METHODS: UK military personnel were recruited from the Defence Medical Services COVID-19 Recovery Service. Participants were separated into healthy controls without prior SARS-CoV-2 infection (group one), and participants with prolonged symptoms (>12 weeks) after mild-moderate (community-treated) and severe (hospitalised) COVID-19 illness (group 2 and 3, respectively). Participants underwent cardiac magnetic resonance imaging (CMR) and spectroscopy, echocardiography, pulmonary function testing and cardiopulmonary exercise testing (CPET). RESULTS: 113 participants were recruited. When compared in ordered groups (one to three), CPET showed stepwise decreases in peak work, work at VT1 and VO2 max (all p < 0.01). There were stepwise decreases in FVC (p = 0.002), FEV1 (p = 0.005), TLC (p = 0.002), VA (p < 0.001), and DLCO (p < 0.002), and a stepwise increase in A-a gradient (p < 0.001). CMR showed stepwise decreases in LV/RV volumes, stroke volumes and LV mass (LVEDVi/RVEDVi p < 0.001; LVSV p = 0.003; RVSV p = 0.001; LV mass index p = 0.049). CONCLUSION: In an active military population, post-COVID syndrome is linked to subclinical changes in maximal exercise capacity. Alongside disease specific changes, many of these findings share the phenotype of deconditioning following prolonged illness or bedrest. Partitioning of the relative contribution of pathological changes from COVID-19 and deconditioning is challenging in post-COVID syndrome recovery.

Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction.

OBJECTIVES: To use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank. METHODS: PAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods. RESULTS: We studied 1204 participants in total, 297 participants with prevalent (60 ± 7 years, 21% female) and 305 with incident (61 ± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone. Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models. CONCLUSIONS: The amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF. CLINICAL RELEVANCE STATEMENT: This study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF. KEY POINTS: •PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure. •Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups. •An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure.