Patients with chronic heart failure (CHF) and reduced left ventricle ejection fraction benefit from cardiac resynchronization therapy (CRT) and implantable cardioverter defibrillator (ICD). However, increasing numbers of patient with CRT and ICD devices produce overload of cardiology centers where patients are admitted to ambulatory visits. This study aims to find multivariate model predicting the requirement for ambulatory follow-up of cardiac implantable electronic devices (CIEDs).The LUCY study is an observational, cohort, prospective, 2-stage trial. As equal number of patients (300) will be included in the first and the second part of the study, finally, 600 patients will be included in the study. The inclusion criteria will be: age between 18 and 90 years, CHF (New York Heart Association classes I–III) and implanted ICD or CRT at least 30 days before study inclusion. The exclusion criteria will be dementia and other conditions impeding cooperation during the study. All patients included in the study will undergo standard ambulatory visit. Primary endpoint will be defined as any ambulatory visit qualified as necessary due to patient's condition or device malfunction diagnose by the cardiologist: any change in pharmacotherapy related to patient's clinical status assessed during the visit, any change in tachyarrythmia counter or discriminator status, any change in tachyarrythmia threshold, presence of ventricular undersensing or oversensing, presence of atrial or ventricular ineffective pacing, or device's pocket infection. Secondary endpoint will be defined as any ambulatory visit qualified as necessary due to the alarm identified via Medtronic CareLink Express (MCLE): sustained or treated ventricular tachyarrythmia, any not previously diagnosed supraventricular tachyarrythmia, or elective replacement indicator.Our study is the first attempt of implementation of the machine learning and elements artificial intelligence in health care optimization of patients with CIED. The LUCY will be an open product, available for additional testing and improvement with supplementary functionalities: quality of life assessment, teleconsultation, video-streaming, automated imagine recognizing.
Nowadays, both the European System for Cardiac Operative Risk Evaluation (EuroSCORE) logistic (ESL) and EuroSCORE II (ESII) models are used worldwide in predicting in-hospital mortality after cardiac operation. However, these scales are based on different populations and represent different medical approaches. The aim of the study was to assess the effectiveness of the ESL and the ESII risk scores in predicting in-hospital death and prolonged hospitalization in intensive care unit (ICU) after coronary artery bypass grafting (CABG), aortic valve replacement (AVR), and mitral valve replacement (MVR) by comparison of an estimated risk and a real-life observation at a reference cardiac surgery unit.This retrospective study was based on medical records of patients who underwent a CABG, AVR, or MVR at a reference cardiac surgery unit in a 2-year period. Primary endpoint was defined as in-hospital death. Secondary endpoint was a prolonged hospitalization at the ICU, defined as longer than 3 days.The study encompassed 586 patients [114 (23.1%) female, mean age 65.8 ± 10.5 years], including 493 patients undergoing CABG, 66 patients undergoing AVR, and 27 patients undergoing MVR. The ESL and ESII risk scores were higher in MVR subgroup (31.7% ± 30.5% and 15.3% ± 19.4%) and AVR subgroup (9.7% ± 11.6% and 3.2% ± 4.2%) than in CABG subgroup (6.9% ± 10.4% and 2.5% ± 4.1%; P < .001). Subgroups of patients were significantly different in terms of clinical, biochemical, and echocardiography factors. Primary endpoint occurred in 36 (6.1%) patients: 21 (4.3%), 7 (10.6%), and 8 (29.7%) in CABG, AVR, and MVR subgroups, respectively. The ESII underestimated the risk of mortality. Secondary endpoint occurred in 210 (35.8%) patients: 172 (34.9%), 22 (33.4%), and 16 (59.3%) in CABG, AVR, and MVR subgroups, respectively.In the study, the perioperative risk estimated with the ESL and the ESII risk scores was compared with a real-life outcome among over 500 patients. Regardless of the type of surgery, result in the ESL was better correlated with the risk of in-hospital death.
Introduction. Electrocardiography (ECG) is one of the basic diagnostic tests used in emergency departments and by emergency medical services. Life-threatening arrhythmias can be detected using a single-lead ECG. Therefore, single-lead ECG devices can be used for arrhythmia detection, as their availability steadily increases. Kardia Mobile from Alive-Cor is an example of such a device, recording a single-lead ECG and automatically detecting atrial fibrillation (AF)-the most common complex supraventricular tachyarrhythmia. The aim of our study was to evaluate the utility of a single-lead mobile ECG device in detecting AF in medical practice of emergency services. Material and methods. Study included 118 patients (62 women and 56 men) who were hospitalized in a hospital emergency department and consented to examination with Kardia Mobile immediately after a standard 12-lead ECG. Results of both tests were subsequently compared. Ultimately, 121 different pairs of ECG recordings were analyzed (in 3 cases an additional ECG recording was performed after an electrical cardioversion). Results. Sinus rhythm was identified in 99 patients and 22 were diagnosed with AF using a 12-lead ECG (reference). Kardia Mobile correctly detected AF in 19 of 22 patients with AF (sensitivity: 86.4%) and absence of AF in 96 of 99 people without AF (specificity: 97%). Conclusions. Kardia Mobile device is effective in automated detection of AF among patients hospitalized in the emergency department.
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