A5010995930- Organ Transplantation Techniques and Outcomes
- Renal Transplantation Outcomes and Treatments
- Organ Donation and Transplantation
- Transplantation: Methods and Outcomes
- Liver Disease and Transplantation
- Machine Learning in Healthcare
- Antibiotic Use and Resistance
- Patient Safety and Medication Errors
- Medical Malpractice and Liability Issues
- Pneumonia and Respiratory Infections
- Respiratory Support and Mechanisms
- Cardiac, Anesthesia and Surgical Outcomes
- Clinical Reasoning and Diagnostic Skills
- Antibiotic Resistance in Bacteria
- Bacterial Identification and Susceptibility Testing
- Quality and Safety in Healthcare
- Sepsis Diagnosis and Treatment
- Time Series Analysis and Forecasting
- Higher Education Teaching and Evaluation
- Cardiac Arrest and Resuscitation
- Nosocomial Infections in ICU
- Clinical Nutrition and Gastroenterology
- Electronic Health Records Systems
- Cardiac pacing and defibrillation studies
- Antibiotics Pharmacokinetics and Efficacy
Hospital Universitario de Fuenlabrada
2015-2025
Universidad Autónoma de Guadalajara
2024
Emory University
2023
Universidad Rey Juan Carlos
2021
Hitachi Global Storage Technologies (United States)
2020
Instituto Tecnológico de Costa Rica
2018
Colombiana de Trasplantes
2014
Hospital Clínico San Carlos
1997-2007
Universidade da Coruña
2003
Hospital San Juan de la Cruz
2002
The aim of this study was to compare the survival and midterm function kidneys from non-heart beating donors (NHBD) with those heart (HBD). From 1989 1998, 144 were procured NHBD at Hospital Clínico San Carlos in Madrid, which 95 transplanted. kidney grafts maintained moment diagnosis cardiac arrest until time procurement by cardiopulmonary bypass. There no significant difference renal number rejection episodes between HBD transplants. showed a 5.73-fold increase incidence delayed graft...
The "Pneumonia Zero" project is a nationwide multimodal intervention based on the simultaneous implementation of comprehensive evidence-based bundle measures to prevent ventilator-associated pneumonia in critically ill patients admitted ICU.
Electronic health records provide rich, heterogeneous data about the evolution of patients' status. However, such need to be processed carefully, with aim extracting meaningful information for clinical decision support. In this paper, we leverage interpretable (deep) learning and signal processing tools deal multivariate time-series collected from Intensive Care Unit (ICU) University Hospital Fuenlabrada (Madrid, Spain). The presence antimicrobial multidrug-resistant (AMR) bacteria is one...
Background. The demand for liver transplantation has increasingly exceeded the supply of cadaver donor organs. Non-heart-beating donors (NHBDs) may be an alternative to increase pool. Methods. outcome 20 transplants from Maastricht category 2 NHBDs is compared with 40 heart-beating (HBDs). After unsuccessful cardiopulmonary resuscitation (CPR), support (CPS) simultaneous application chest and abdominal compression (n=6), bypass (CPB; n=14), which was hypothermic (n=7) or normothermic (n=7),...
The presence of bacteria with resistance to specific antibiotics is one the greatest threats global health system. According World Health Organization, antimicrobial has already reached alarming levels in many parts world, involving a social and economic burden for patient, system, society general. Because critical status patients intensive care unit (ICU), time identify their antibiotics. Since common tests require between 24 48 h after culture collected, we propose apply machine learning...
Multi-drug resistance (MDR) is one of the most current and greatest threats to global health system nowadays. This situation especially relevant in Intensive Care Units (ICUs), where critical status these patients makes them more vulnerable. Since MDR confirmation by microbiology laboratory usually takes 48 h, we propose several artificial intelligence approaches get insights risk factors during first h from ICU admission. We considered clinical demographic features, mechanical ventilation...
Bacterial resistance to antibiotics has been rapidly increasing, resulting in low antibiotic effectiveness even treating common infections. The presence of resistant pathogens environments such as a hospital Intensive Care Unit (ICU) exacerbates the critical admission-acquired This work focuses on prediction Pseudomonas aeruginosa nosocomial infections at ICU, using Long Short-Term Memory (LSTM) artificial neural networks predictive method. analyzed data were extracted from Electronic Health...
Electronic health records (EHR) is an inherently multimodal register of the patient's status characterized by static data and multivariate time series (MTS). While MTS are a valuable tool for clinical prediction, their fusion with other modalities can possibly result in more thorough insights accurate results. Deep neural networks (DNNs) have emerged as fundamental tools identifying defining underlying patterns healthcare domain. However, improvements interpretability needed DNN models to be...