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A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study. The process and key system components are described together with descriptive statistics to show its feasibility in general and to identify individual challenges in particular. Data of 2051 patients enrolled between 2014 and 2020 was transferred. We were able to automate the transfer of approximately 11 million individual data values, representing 95% of all entered study data. These were recorded in n = 314 variables (28% of all variables), with some variables being used multiple times for follow-up visits. Our validation approach allowed for constant good data quality over the course of the study. In conclusion, the automated transfer of multi-dimensional routine medical data from HIS to study databases using specific study data and visit structures is complex, yet viable.
Aims
It has been hypothesized that cardiac decompensation accompanying acute heart failure (AHF) episodes generates a pro-inflammatory environment boosting an adaptive immune response against myocardial antigens, thus contributing to progression of heart failure (HF) and poor prognosis. We assessed the prevalence of anti-myocardial autoantibodies (AMyA) as biomarkers reflecting adaptive immune responses in patients admitted to the hospital for AHF, followed the change in AMyA titres for 6 months after discharge, and evaluated their prognostic utility.
Methods and results
AMyA were determined in n = 47 patients, median age 71 (quartiles 60; 80) years, 23 (49%) female, and 24 (51%) with HF with preserved ejection fraction, from blood collected at baseline (time point of hospitalization) and at 6 month follow-up (visit F6). Patients were followed for 18 months (visit F18). The prevalence of AMyA increased from baseline (n = 21, 45%) to F6 (n = 36, 77%; P < 0.001). At F6, the prevalence of AMyA was higher in patients with HF with preserved ejection fraction (n = 21, 88%) compared with patients with reduced ejection fraction (n = 14, 61%; P = 0.036). During the subsequent 12 months after F6, that is up to F18, patients with newly developed AMyA at F6 had a higher risk for the combined endpoint of death or rehospitalization for HF (hazard ratio 4.79, 95% confidence interval 1.13–20.21; P = 0.033) compared with patients with persistent or without AMyA at F6.
Conclusions
Our results support the hypothesis that AHF may induce patterns of adaptive immune responses. More studies in larger populations and well-defined patient subgroups are needed to further clarify the role of the adaptive immune system in HF progression.
Functional versus morphological assessment of vascular age in patients with coronary heart disease
(2021)
Communicating cardiovascular risk based on individual vascular age (VA) is a well acknowledged concept in patient education and disease prevention. VA may be derived functionally, e.g. by measurement of pulse wave velocity (PWV), or morphologically, e.g. by assessment of carotid intima-media thickness (cIMT). The purpose of this study was to investigate whether both approaches produce similar results. Within the context of the German subset of the EUROASPIRE IV survey, 501 patients with coronary heart disease underwent (a) oscillometric PWV measurement at the aortic, carotid-femoral and brachial-ankle site (PWVao, PWVcf, PWVba) and derivation of the aortic augmentation index (AIao); (b) bilateral cIMT assessment by high-resolution ultrasound at three sites (common, bulb, internal). Respective VA was calculated using published equations. According to VA derived from PWV, most patients exhibited values below chronological age indicating a counterintuitive healthier-than-anticipated vascular status: for VA(PWVao) in 68% of patients; for VA\(_{AIao}\) in 52% of patients. By contrast, VA derived from cIMT delivered opposite results: e.g. according to VA\(_{total-cIMT}\) accelerated vascular aging in 75% of patients. To strengthen the concept of VA, further efforts are needed to better standardise the current approaches to estimate VA and, thereby, to improve comparability and clinical utility.
Prospective longitudinal follow‐up of left ventricular ejection fraction (LVEF) trajectories after acute cardiac decompensation of heart failure is lacking. We investigated changes in LVEF and covariates at 6‐months' follow‐up in patients with a predischarge LVEF ≤40%, and determined predictors and prognostic implications of LVEF changes through 18‐months' follow‐up.
Methods and Results
Interdisciplinary Network Heart Failure program participants (n=633) were categorized into subgroups based on LVEF at 6‐months' follow‐up: normalized LVEF (>50%; heart failure with normalized ejection fraction, n=147); midrange LVEF (41%–50%; heart failure with midrange ejection fraction, n=195), or persistently reduced LVEF (≤40%; heart failure with persistently reduced LVEF , n=291). All received guideline‐directed medical therapies. At 6‐months' follow‐up, compared with patients with heart failure with persistently reduced LVEF, heart failure with normalized LVEF or heart failure with midrange LVEF subgroups showed greater reductions in LV end‐diastolic/end‐systolic diameters (both P<0.001), and left atrial systolic diameter (P=0.002), more increased septal/posterior end‐diastolic wall‐thickness (both P<0.001), and significantly greater improvement in diastolic function, biomarkers, symptoms, and health status. Heart failure duration <1 year, female sex, higher predischarge blood pressure, and baseline LVEF were independent predictors of LVEF improvement. Mortality and event‐free survival rates were lower in patients with heart failure with normalized LVEF (P=0.002). Overall, LVEF increased further at 18‐months' follow‐up (P<0.001), while LV end‐diastolic diameter decreased (P=0.048). However, LVEF worsened (P=0.002) and LV end‐diastolic diameter increased (P=0.047) in patients with heart failure with normalized LVEF hospitalized between 6‐months' follow‐up and 18‐months' follow‐up.
Conclusions
Six‐month survivors of acute cardiac decompensation for systolic heart failure showed variable LVEF trajectories, with >50% showing improvements by ≥1 LVEF category. LVEF changes correlated with various parameters, suggesting multilevel reverse remodeling, were predictable from several baseline characteristics, and were associated with clinical outcomes at 18‐months' follow‐up. Repeat hospitalizations were associated with attenuation of reverse remodeling."
Introduction: Left ventricular (LV) dilatation and LV hypertrophy are acknowledged precursors of myocardial dysfunction and ultimately of heart failure, but the implications of abnormal LV geometry on myocardial function are not well-understood. Non-invasive LV myocardial work (MyW) assessment based on echocardiography-derived pressure-strain loops offers the opportunity to study detailed myocardial function in larger cohorts. We aimed to assess the relationship of LV geometry with MyW indices in general population free from heart failure.
Methods and Results: We report cross-sectional baseline data from the Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression (STAAB) cohort study investigating a representative sample of the general population of Würzburg, Germany, aged 30–79 years. MyW analysis was performed in 1,926 individuals who were in sinus rhythm and free from valvular disease (49.3% female, 54 ± 12 years). In multivariable regression, higher LV volume was associated with higher global wasted work (GWW) (+0.5 mmHg% per mL/m\(^2\), p < 0.001) and lower global work efficiency (GWE) (−0.02% per mL/m\(^2\), p < 0.01), while higher LV mass was associated with higher GWW (+0.45 mmHg% per g/m\(^2\), p < 0.001) and global constructive work (GCW) (+2.05 mmHg% per g/m\(^2\), p < 0.01) and lower GWE (−0.015% per g/m\(^2\), p < 0.001). This was dominated by the blood pressure level and also observed in participants with normal LV geometry and concomitant hypertension.
Conclusion: Abnormal LV geometric profiles were associated with a higher amount of wasted work, which translated into reduced work efficiency. The pattern of a disproportionate increase in GWW with higher LV mass might be an early sign of hypertensive heart disease.
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.