Metabolic cost of unloading pedalling in different groups of patients with pulmonary hypertension and volunteers.

Recently, the parameter internal work (IW) has been introduced as change in oxygen uptake (VO2) between resting and unloading workload in cardiopulmonary exercise testing (CPET). The proportional IW (PIW) was defined as IW divided by VO2 at peak exercise. A second option is to calculate the PIW based on the workload [PIW (Watt)] by considering the aerobic efficiency. The aim of our study was to investigate whether IW and PIW differ between patients with and without pulmonary hypertension and healthy controls. Our study population consisted of 580 patients and 354 healthy controls derived from the Study of Health in Pomerania. The PIW was slightly lower in patients (14.2%) than in healthy controls (14.9%; p = 0.030), but the PIW (Watt) was higher in patients (18.0%) than in the healthy controls (15.9%; p = 0.001). Such a difference was also observed, when considering only the submaximal workload up to the VAT (19.8% in patients and 15.1% in healthy controls; p < 0.001). Since the PIW (Watt) values were higher in patients with pulmonary hypertension, this marker may serve as a useful CPET parameter in clinical practice. In contrast to most of the currently used CPET parameters, the PIW does not require a maximal workload for the patient. Further studies are needed to validate the prognostic significance of the PIW.

Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.

OBJECTIVES: The biomarker N-terminal pro B-type natriuretic peptide (NT-proBNP) has predictive value for identifying individuals at risk for cardiovascular disease (CVD). However, it is not widely used for screening in the general population, potentially due to financial and operational reasons. This study aims to develop a deep-learning model as an efficient means to reliably identify individuals at risk for CVD by predicting serum levels of NT-proBNP from the ECG. METHODS: A deep convolutional neural network was developed using the population-based cohort study Hamburg City Health Study (HCHS, n=8,253, 50.9 % women). External validation was performed in two independent population-based cohorts (SHIP-START, n=3,002, 52.1 % women, and SHIP-TREND, n=3,819, 51.2 % women). Assessment of model performance was conducted using Pearson correlation (R) and area under the receiver operating characteristics curve (AUROC). RESULTS: NT-proBNP was predictable from the ECG (R, 0.566 [HCHS], 0.642 [SHIP-START-0], 0.655 [SHIP-TREND-0]). Across cohorts, predicted NT-proBNP (pNT-proBNP) showed good discriminatory ability for prevalent and incident heart failure (HF) (baseline: AUROC 0.795 [HCHS], 0.816 [SHIP-START-0], 0.783 [SHIP-TREND-0]; first follow-up: 0.669 [SHIP-START-1, 5 years], 0.689 [SHIP-TREND-1, 7.3 years]), comparable to the discriminatory value of measured NT-proBNP. pNT-proBNP also demonstrated comparable results for other incident CVD, including atrial fibrillation, stroke, myocardial infarction, and cardiovascular death. CONCLUSIONS: Deep learning ECG algorithms can predict NT-proBNP concentrations with high diagnostic and predictive value for HF and other major CVD and may be used in the community to identify individuals at risk. Long-standing experience with NT-proBNP can increase acceptance of such deep learning models in clinical practice.

Simultaneous assessment of spontaneous cage activity and voluntary wheel running in group-housed mice.

Small animal models are frequently used to improve our understanding of the molecular and biological signaling pathways underlying the beneficial effects of physical activity and exercise. Unfortunately, when running wheels are employed, mice and rats are often kept single-housed to determine the individual running distance of each animal. However, social isolation can be stressful for rodents, and may alter an individual's propensity for or response to exercise. For example, increased stress from single housing may significantly affect the results when investigating systemic metabolic responses to exercise. We have combined two already available and well-established systems, a radiotelemetry system and a running wheel, to determine spontaneous cage activity (SCA) as well as voluntary exercise (VE) levels of the individual animal in group-housed rodents. Further, we developed a simple software tool which allows monitoring and analyzing the data. Specifically, the radiotelemetry-system utilizes radio-frequency identification via a small, implanted chip to determine the location of each animal. Since, in addition to the animals' position, also the location of the running wheel in the cage is known, the conclusion of which animal is exercising can be drawn. The developed software enables a fast and reliable assignment of the VE data to the individual animal and a simple analysis of the data collected. Hence, our combined method may be used to investigate the beneficial effects of physical activity, as well as the impact of therapeutic interventions on animal behavior in group-housed rodents.

Association of sex-specific differences in lipoprotein(a) concentrations with cardiovascular mortality in individuals with type 2 diabetes mellitus.

BACKGROUND: Compared to individuals without type 2 diabetes mellitus, the relative increase in cardiovascular mortality is much higher in women than in men in individuals with type 2 diabetes mellitus. METHODS: We evaluated data from 7443 individuals (3792 women, 50.9%), aged 20 to 81 years, from two independent population-based investigations, SHIP-0 and MONICA/KORA S3. We analyzed the longitudinal sex-specific associations of lipoprotein(a) with cardiovascular mortality in individuals with and without type 2 diabetes mellitus using Cox regression. RESULTS: During a median follow-up of 20.5 years (136,802 person-years), 657 participants (404 men and 253 women) died of cardiovascular causes. Among individuals without type 2 diabetes mellitus, men had a significantly higher risk for cardiovascular mortality compared to women in unadjusted model and after adjustment. On the other hand, in participants with type 2 diabetes mellitus, the risk for cardiovascular mortality was not different between men and women in the unadjusted model and after adjustment for age, body mass index, low-density lipoprotein-cholesterol, fasting status and study sample (SHIP-0, MONICA/KORA S3). Further adjustment for lipoprotein(a) concentrations had no impact on the hazard ratio (HR) for cardiovascular mortality comparing men versus women in individuals without type 2 diabetes mellitus [HR: 1.94; 95% confidence interval (CI) 1.63 to 2.32; p < 0.001]. In individuals with type 2 diabetes mellitus, however, further adjustment for lipoprotein(a) led to an increased risk for cardiovascular mortality in men and a decreased risk in women resulting in a statistically significant difference between men and women (HR: 1.53; 95% CI 1.04 to 2.24; p = 0.029). CONCLUSIONS: Women are described to have a stronger relative increase in cardiovascular mortality than men when comparing individuals with and without type 2 diabetes mellitus. Higher lipoprotein(a) concentrations in women with type 2 diabetes mellitus than in men with type 2 diabetes mellitus might partially explain this finding.