Association of epicardial adipose tissue volume with heart weight in post-mortem cases.

Epicardial adipose tissue (EAT) deposition has been long associated with heart weight. However, recent research has failed to replicate this association. We aimed to determine the association of EAT volume with heart weight in post-mortem cases and identify potential confounding variables. EAT volume derived from post-mortem computed tomography (PMCT) and heart weight were measured in post-mortem cases (N = 87, age: 56 ± 16 years, 28% female). Cases with hypertrophied heart weights (N = 44) were determined from reference tables. Univariable associations were tested using Spearman correlation and simple linear regression. Independence was determined with stepwise regression. In the total cohort, EAT volume (median 66 ± 45 cm3) was positively associated with heart weight (median 435 ± 132 g) at the univariable level (r = 0.6, P < 0.0001) and after adjustment for age, female sex, and various body size metrics (R2 adjusted = 0.41-0.57). Median EAT volume was 1.9-fold greater in cases with hypertrophic hearts (P < 0.0001) but with considerably greater variability, especially in cases with extreme EAT volume or heart weight. As such, EAT volume was not associated with heart weight in hypertrophic cases, while a robust independent association was found in non-hypertrophic cases (R2 adjusted = 0.62-0.86). EAT mass estimated from EAT volume found that EAT comprised approximately 13% of overall heart mass in the total cases. This was significantly greater in cases with hypertrophy (median 15.5%; range, 3.6-36.6%) relative to non-hypertrophied cases (12.5%, 3.3-24.3%) (P = 0.04). EAT volume is independently and positively associated with heart weight in post-mortem cases. Excessive heart weight significantly confounded this association.

Association between lipoprotein(a), LPA genetic risk score, aortic valve disease, and subsequent major adverse cardiovascular events.

AIMS: Cohort studies have demonstrated associations between calcific aortic valve disease (CAVD) and Lp(a). As Lp(a) is almost entirely genetically determined, in this study, we aim to determine whether Lp(a), when predicted from genetic data, is associated with CAVD and major adverse cardiovascular events (MACEs). METHODS AND RESULTS: Patients undergoing coronary angiography between January 2012 and May 2013 were invited to participate in the study. Of 752 analysable participants, 446 had their Lp(a) measured and 703 had a calculable LPA genetic risk score (GRS). The primary outcomes were the presence of CAVD at baseline and MACE over a 7-year follow-up. The GRS explained 45% of variation in Lp(a). After adjustment for cardiac risk factors and coronary artery disease (CAD), the odds of CAVD increased with increasing Lp(a) [odds ratio (OR) 1.039 per 10-unit increase, 95% confidence interval (CI) 1.022-1.057, P < 0.001] and GRS (OR 1.054 per 10-unit increase, 95% CI 1.024-1.086; P < 0.001). Lipoprotein(a) and the GRS as continuous variables were not associated with subsequent MACEs. A dichotomized GRS (>54) was associated with MACE, but this relationship became non-significant when CAD classification was added into the model (OR 1.333, 95% CI 0.927-1.912; P = 0.12). CONCLUSION: An LPA GRS can explain 45% of variation in Lp(a) levels, and both Lp(a) and the GRS are associated with CAVD. An elevated GRS is associated with future cardiac events in a secondary risk setting, but, if the CAD status is known, it does not provide additional prognostic information.

Lipoprotein (a) [Lp(a)] is a type of cholesterol that is determined almost entirely by genetics. It is associated with heart disease and also stiffening of the heart valves. Recent advancements have made it possible to predict Lp(a) levels by analysing a person's DNA. This study examines the association between genetically predicted Lp(a) and adverse outcomes. Genetically predicted Lp(a) accounts for 45% of the variability in the actual Lp(a) level.Both actual and genetically predicted Lp(a) are associated with heart valve disease and adverse heart outcomes. If the degree of narrowing of the arteries in the heart is already known, genetically predicted Lp(a) does not help further predict risk.

Use of an ultrasound picture archiving and communication system to answer research questions: Description of data cleaning methods.

Introduction/Purpose: Ultrasound picture archiving and communication system (PACS) databases are useful for quality improvement and clinical research but frequently contain free text that is not easily readable. Here, we present a method to extract and clean a semi-structured echocardiography (cardiac ultrasound) PACS database. Methods: Echocardiography studies between 1 January 2010 and 31 December 2018 were extracted using a data mining tool. Numeric variables were recoded with extreme values excluded. Analysis of free text, including descriptions of the heart valves and right and left ventricular size and function, was performed using a rule-based system. Different levels of free text variables were initially identified using commonly used phrases and then iteratively developed. Randomly selected sets of 100 studies were compared to the electronic health record to validate the data cleaning process. Results: The data validation step was performed three times in total, with Cohen's kappa ranging between 0.88 and 1.00 for the final set of data validation across all measures. Conclusion: Free text cleaning of semi-structured PACS databases is possible using freely available open-source software. The accuracy of this method is high, and the resulting dataset can be linked to administrative data to answer research questions. We present a method that could be used to answer clinical questions or to develop quality improvement initiatives.

Outcomes of patients with early calcific aortic valve disease detected by clinically indicated echocardiography.

AIMS: Previous studies have demonstrated relatively slow rates of progression of early calcific aortic valve disease (CAVD), which encompasses aortic sclerosis (ASc) and mild aortic stenosis (AS). The potential evolution to clinically significant AS is unclear, and we therefore examined the long-term outcomes of patients with ASc and mild AS detected at the time of clinically indicated echocardiography. METHODS AND RESULTS: Data from initial clinically indicated echocardiograms performed between 2010 and 2018 in patients aged ≥18 years were extracted and linked to nationally collected outcome data. Those with impaired right or left systolic ventricular function or other significant left-sided valve disease were excluded. A time to first event analysis was performed with a composite primary outcome of cardiovascular death and aortic valve intervention (AVI). Of the 13 313 patients, 8973 had no CAVD, 3436 had ASc, and 455 had mild AS. The remainder had moderate or worse stenosis. Over a median follow-up period of 4.2 (interquartile range 1.8-6.7) years (and after adjustment for age and sex), those with ASc were at greater risk of the primary outcome [hazard ratio (HR) 2.9, 95% confidence interval (CI) 2.1-4.0] and need for AVI (HR 26.8, 95% CI 9.1-79.1) compared with those with no CAVD. Clinical event rates accelerated after ∼5 years in those with mild AS. CONCLUSION: Patients with ASc are >25 times more likely to require AVI than those with no CAVD, and follow-up echocardiography should be considered within 3-4 years in those with mild AS.

Identifying sex differences in predictors of epicardial fat cell morphology.

Predictors of overall epicardial adipose tissue deposition have been found to vary between males and females. Whether similar sex differences exist in epicardial fat cell morphology is currently unknown. This study aimed to determine whether epicardial fat cell size is associated with different clinical measurements in males and females. Fat cell sizes were measured from epicardial, paracardial, and appendix adipose tissues of post-mortem cases (N= 118 total, 37 females). Epicardial, extra-pericardial, and visceral fat volumes were measured by computed tomography from a subset of cases (N= 70, 22 females). Correlation analyses and stepwise linear regression were performed to identify predictors of fat cell size in males and females. Median fat cell sizes in all depots did not differ between males and females. Body mass index (BMI) and age were independently predictive of epicardial, paracardial, and appendix fat cell sizes in males, but not in females. Epicardial and appendix fat cell sizes were associated with epicardial and visceral fat volumes, respectively, in males only. In females, paracardial fat cell size was associated with extra-pericardial fat volume, while appendix fat cell size was associated with BMI only. No predictors were associated with epicardial fat cell size in females at the univariable or multivariable levels. To conclude, no clinical measurements were useful surrogates of epicardial fat cell size in females, while BMI, age, and epicardial fat volume were independent, albeit weak, predictors in males only.