Cardiovascular risk factors, living and ageing in Halle: the CARLA study

Impact of QRS misclassifications on heart-rate-variability parameters (results from the CARLA cohort study)

BACKGROUND

Heart rate variability (HRV), an important marker of autonomic nervous system activity, is usually determined from electrocardiogram (ECG) recordings corrected for extrasystoles and artifacts. Especially in large population-based studies, computer-based algorithms are used to determine RR intervals. The Modular ECG Analysis System MEANS is a widely used tool, especially in large studies. The aim of this study was therefore to evaluate MEANS for its ability to detect non-sinus ECG beats and artifacts and to compare HRV parameters in relation to ECG processing. Additionally, we analyzed how ECG processing affects the statistical association of HRV with cardiovascular disease (CVD) risk factors.

METHODS

20-min ECGs from 1,674 subjects of the population-based CARLA study were available for HRV analysis. All ECGs were processed with the ECG computer program MEANS. A reference standard was established by experienced clinicians who visually inspected the MEANS-processed ECGs and reclassified beats if necessary. HRV parameters were calculated for 5-minute segments selected from the original 20-minute ECG. The effects of misclassified typified normal beats on i) HRV calculation and ii) the associations of CVD risk factors (sex, age, diabetes, myocardial infarction) with HRV were modeled using linear regression.

RESULTS

Compared to the reference standard, MEANS correctly classified 99% of all beats. The averaged sensitivity of MEANS across all ECGs to detect non-sinus beats was 76% [95% CI: 74.1;78.5], but for supraventricular extrasystoles detection sensitivity dropped to 38% [95% CI: 36.8;38.5]. Time-domain parameters were less affected by false sinus beats than frequency parameters. Compared to the reference standard, MEANS resulted in a higher SDNN on average (mean absolute difference 1.4ms [95% CI: 1.0;1.7], relative 4.9%). Other HRV parameters were also overestimated as well (between 6.5 and 29%). The effect estimates for the association of CVD risk factors with HRV did not differ between the editing methods.

CONCLUSION

We have shown that the use of the automated MEANS algorithm may lead to an overestimation of HRV due to the misclassification of non-sinus beats, especially in frequency domain parameters. However, in population-based studies, this has no effect on the observed associations of HRV with risk factors, and therefore an automated ECG analyzing algorithm as MEANS can be recommended here for the determination of HRV parameters.

Association of subendocardial viability ratio and mortality in the elderly population: results from the CARdiovascular disease, Living and Ageing in Halle study

OBJECTIVES

The subendocardial viability ratio (SEVR) reflects the balance of myocardial oxygen supply and demand. Low SEVR indicates a reduced subendocardial perfusion and has been shown to predict mortality in patients with kidney disease and diabetes. The aim of this study is to investigate the association of SEVR and mortality in the elderly population.

METHODS

We analysed data from the CARdiovascular disease, Living and Ageing in Halle (CARLA) study. SEVR was estimated noninvasively by radial artery tonometry and brachial blood pressure measurement. The study population was divided into a low (SEVR ≤130%) and normal (SEVR >130%) SEVR group. Cox-regression was used for survival analysis.

RESULTS

In total, 1414 participants (635 women, 779 men) aged from 50 to 87 years (mean age 67.3 years) were included in the analysis. The all-cause mortality was 22.7% during a median follow-up of 10.5 years. The unadjusted association of SEVR with all-cause mortality decreased from 3.52 (1.31-9.46) [hazard ratio (95% confidence interval) for low SEVR ≤ 130% versus normal SEVR > 130%] among those younger than 60 years to 0.86 (0.50-1.48) among those older than 80 years and from 1.81 (0.22-14.70) to 0.75 (0.30-1.91) for cardiovascular mortality. Sex-specific unadjusted analyses demonstrated an association of SEVR with all-cause and cardiovascular mortality in men [2.32 (1.61-3.34) and 2.24 (1.18-4.24)], but not in women [1.53 (0.87-2.72) and 1.14 (0.34-3.82)].

CONCLUSION

Our data suggests that SEVR is an age dependent predictor for all-cause mortality, predominantly in men younger than 60 years.

Chronic disease outcome metadata from German observational studies - public availability and FAIR principles

Metadata from epidemiological studies, including chronic disease outcome metadata (CDOM), are important to be findable to allow interpretability and reusability. We propose a comprehensive metadata schema and used it to assess public availability and findability of CDOM from German population-based observational studies participating in the consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health). Additionally, principal investigators from the included studies completed a checklist evaluating consistency with FAIR principles (Findability, Accessibility, Interoperability, Reusability) within their studies. Overall, six of sixteen studies had complete publicly available CDOM. The most frequent CDOM source was scientific publications and the most frequently missing metadata were availability of codes of the International Classification of Diseases, Tenth Revision (ICD-10). Principal investigators' main perceived barriers for consistency with FAIR principles were limited human and financial resources. Our results reveal that CDOM from German population-based studies have incomplete availability and limited findability. There is a need to make CDOM publicly available in searchable platforms or metadata catalogues to improve their FAIRness, which requires human and financial resources.

60 years of healthy aging: On definitions, biomarkers, scores and challenges

BACKGROUND AND OBJECTIVE

As the proportion of aging people in our population increases steadily, global strategies accompanied by extensive research are necessary to tackle society and health service challenges. The World Health Organization recently published an action plan: "Decade of healthy aging 2020-2030", which calls for concerted collaboration to prevent poverty of older people to provide quality education, job opportunities, and an age-inclusive infrastructure. However, scientists worldwide still struggle to find definitions and appropriate measurements of aging per se and healthy aging in particular. This literature review aims to compile concepts of healthy aging and provide a condensed overview of the challenges in defining and measuring it, along with suggestions for further research.

MATERIALS AND METHODS

We conducted three independent systematic literature searches covering the main scopes addressed in this review: (1) concepts and definitions of healthy aging, (2) outcomes and measures in (healthy) aging studies and (3) scores and indices of healthy aging. For each scope, the retrieved literature body was screened and subsequently synthesized.

RESULTS

We provide a historical overview of the concepts of healthy aging over the past 60 years. Furthermore, we identifiy current difficulties in identifying healthy agers, including dichotomous measurements, illness-centered views, study populations & designs. Secondly, markers and measures of healthy aging are discussed, including points to consider, like plausibility, consistency, and robustness. Finally, we present healthy aging scores as measurements, which combine multiple aspects to avoid a dichotomous categorization and display the bio-psycho-social concept of healthy aging.

DISCUSSION AND CONCLUSION

When deducting research, scientists need to consider the diverse challenges in defining and measuring healthy aging. Considering that, we recommend scores that combine multiple aspects of healthy aging, such as the Healthy Ageing Index or the ATHLOS score, among others. Further efforts are to be made on a harmonized definition of healthy aging and validated measuring instruments that are modular, easy to apply and provide comparable results in different studies and cohorts to enhance the generalization of results.

Physical activity trajectories at older age and all-cause mortality: A cohort study

BACKGROUND

A physically active lifestyle is recognized as a precondition of healthy aging. However, the majority of studies exploring its association with mortality in cohorts of adults used single-time physical activity (PA) estimate, which do not consider its dynamic nature with changes that occur with aging. The aim of the present study is to explore the presence of different PA trajectories in a population-based cohort and their association with mortality.

METHODS

We used data of the population-based cohort study CARLA and included 1041 older adults (45-83 years at baseline) with self-reported physical activity at baseline (2002-2006), first follow-up (2007-2010) and second follow-up (2013). Trajectories were identified using growth mixture modelling. Cox proportional hazard models were used to assess the association between trajectories of PA and all-cause mortality during ~6 years since the second follow-up after adjusting for age, sex, lifestyle factors and comorbidities and after correction for classification error. In a sensitivity analysis we weighted the models to account for selection bias during follow-up. As a further sensitivity analysis, we excluded the first year of follow-up to account for reverse causation.

RESULTS

Three PA trajectories (categorized as consistently low, consistently moderate, and high at baseline but strongly decreasing PA across time) were identified, and 121 deaths due to all causes occurred. Compared with participants who had consistently low PA-levels throughout the follow-up period, participants who maintained moderate PA-levels were at a lower risk of all-cause mortality (hazard ratio [HR], 0.49; 95%CI, 0.30-0.70). Participants with high PA-levels at baseline but strongly decreasing PA across time, had similar mortality risk compared to the participants with consistently low PA-levels (hazard ratio [HR], 0.97; 95%CI, 0.50-1.80). The effects were strengthened in the analysis weighted for selection bias.

CONCLUSIONS

Our results suggest that, compared to those who had consistently low PA levels, those who maintained a moderate level of PA showed a protective effect in terms of their mortality risk but not those who displayed a decline from high PA levels.