Universite de la Reunion

Transvenous cardiac pacemakers have pitfalls due to lead- and device pocket-related complications. Leadless pacemakers were developed and introduced into clinical practice to overcome the weaknesses of traditional transvenous pacemakers. The absence of atrial pacing has restricted their uses mainly for cases of paroxysmal atrioventricular block (AVB) or AVB with atrial fibrillation. The Micra AV contains an embedded accelerometer that senses the atrial contraction waveform, allowing the ventricle to be paced once the atrial contraction is complete. This atrioventricular synchronization is intended to extend the use of the device to cases of permanent complete AVB with normal sinus function. Two randomized clinicals trials have been proven it's efficacy. However, with AV-CESAR cohort, we aim to evaluate the real word effectiveness of Micra AV, in the first 1000 patients implanted by the device in France.

While the acute consequences of an ultratrail are beginning to be well documented, data on the study of recovery in the aftermath of an event are much rarer.
In order to overcome these various limitations, the main study of the ERUPTION-3 project is set up on the Grand Raid de La Réunion 2022 races.
In the context of exercise responses, the rheological properties of blood can impact the endurance performance. In contrast to short-distance events, the study of blood rheology and red blood cells integrity in long-distance events such as ultra-endurance races is poorly documented in the literature.
In the ancillary study, the work that is intended to be carried y out will complement the initial results found by a previous research on 23 runners during the Ultra Trail du Mont Blanc. This ancillary study will also be an opportunity to complete the data from the main study by studying the kinetics of biomarker recovery.

In Reunion Island, people encounter environmental and social conditions leading to premature ageing and subsequent frailty.
The study evaluates tools, supported by the latest scientific advances in "machine learning" to detect, identify and measure frailty in order to give health professionals the means to act early through preventive actions.