Clinical Research Directory

Prognosis Impact of NSVTs After an AMI (TeVeO Study).

Nowadays, Sudden Cardiac Death (SCD) due to malignant arrhythmias is an important cause of death among acute myocardial infarction (AMI) survivors. Preventive strategies with implantable cardioverter-defibrillators (ICD) are the best clinical option for patients, but associated sociosanitary impact in the National Health Systems and the fact that current implant strategy not always results in benefits for the patient requires to develop further selection criteria. The TeVeO project aims to study the events that take place early following an AMI to predict the short- and long-term risk of experiencing a potentially lethal ventricular tachycardia (VT). The project will carry out an observational and multicentric study involving 5 different hospitals to: a) qualitative and quantitative characterize non-sustained VTs (NSVT) that take place during the first 6 months after an AMI and b) characterize the evolution of the substrate (scar and surrounding tissue) in patients meeting criteria for ICD implant. Patients included in the study will be implanted with an implantable loop recorder (ILR) in order to register NSVT and cMRI images will be acquired prior to hospital discharge and at 6 months after AMI to study the substrate. Further patients' management will follow the protocols within each entity. Project results will allow us to stratify patients according to identified risks for developing malignant VT, which will improve patient selection for ICD implantation and will contribute to tailor patients' treatment and prevention, improving the cost-effectiveness of these devices and minimizing their associated problems and sociosanitary burden.

Critical Health Assessment and Outcomes Score/Study

CHAOS is based on the investigator's new and exciting results from pre-clinical and large longitudinal multi-center observational clinical studies of critically ill patients and asymptomatic community-based adults with little or no advanced disease. By integrating approaches from the physical, biological, computational, statistical and clinical sciences, this observational study will test the hypothesis that early diagnosis of subclinical signatures of critical illness encoded within physiological signals complements conventional clinical predictors by providing unique prognostic insight. The primary goal is to reduce mortality, morbidity and complications by early identification of individuals with brewing subclinical critical illness and adverse events before overt clinical presentation (e.g., cardiac arrest, arrhythmias, hemorrhage, respiratory failure, circulatory collapse). This will provide the necessary lead time for healthcare providers to deliver early, more effective and/or preventive therapies. Through innovative approaches, CHAOS also meets the challenge of medical errors to reduce missed diagnosis, misdiagnosis, preventable harm and variability in provider adherence to best practice guidelines. The goal is to validate predictive algorithms and identify subclinical signatures of illness, ranging from asymptomatic adults in the community to very sick patients in the hospital. The overall goal is to make healthcare more precise, effective, efficient, safe and timely while reducing costs, preventable harms and adverse events.