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• W4293215840 abstract "Innovations in the development of novel heart failure therapies are essential to further increase the predictive value of early research findings. Animal models are still playing a pivotal role in 'translational research'. In recent years, the transferability from animal studies has been more and more critically discussed due to persistent high attrition rates in clinical trials. However, there is an increasing trend to implement mobile health devices in preclinical studies. These devices can increase the predictive value of animal models by providing more accurate and translatable data and protect from confounding factors. This review outlines the current prevalence and opportunities of these techniques in preclinical heart failure research studies to accelerate the integration of these important tools. A literature screening for preclinical heart failure studies in large animals implementing telemetry devices over the last decade was performed. Twelve out of 43 publications were included. A variety of different hemodynamic and cardiac parameters can be recorded in conscious state by means of telemetry devices in both, the animal model and the patient. The measurement quality is consistently rated as valid and robust. Mobile health technologies functioning as digital biomarkers represent a more predictive approach compared to the traditionally used invasive measurement techniques, due to the possibility of continuous data collection in the conscious animal. Furthermore, they help to implement the 3R concept (reduction, refinement, replacement) in animal research. Despite this, the use of these techniques in preclinical research has been restrained to date." @default.
• W4293215840 created "2022-08-27" @default.
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• W4293215840 date "2022-08-24" @default.
• W4293215840 modified "2023-09-28" @default.
• W4293215840 title "“Digital biomarkers” in preclinical heart failure models — a further step towards improved translational research" @default.
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• W4293215840 doi "https://doi.org/10.1007/s10741-022-10264-4" @default.
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• W4293215840 hasPublicationYear "2022" @default.
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