Interpretable prediction of mortality in liver transplant recipients based on machine learning.

Background: Accurate prediction of the mortality of post-liver transplantation is an important but challenging task. It relates to optimizing organ allocation and estimating the risk of possible dysfunction. Existing risk scoring models, such as the Balance of Risk (BAR) score and the Survival Outcomes Following Liver Transplantation (SOFT) score, do not predict the mortality of post-liver transplantation with sufficient accuracy.

Prediabetes Is Associated with Increased Prevalence of Sleep-Disordered Breathing.

Type 2 diabetes leads to severe nocturnal hypoxemia, with an increase in apnea events and daytime sleepiness. Hence, we assessed sleep breathing parameters in the prediabetes stage. A cross-sectional study conducted on 966 middle-aged subjects without known pulmonary disease (311 patients with prediabetes and 655 controls with normal glucose metabolism) was conducted.

Weak Association between Skin Autofluorescence Levels and Prediabetes with an ILERVAS Cross-Sectional Study.

A large body of evidence demonstrates a relationship between hyperglycemia and increased concentrations of advanced glycation end-products (AGEs). However, there is little information about subcutaneous AGE accumulation in subjects with prediabetes, and whether or not this measurement could assist in the diagnosis of prediabetes is unclear. A cross-sectional study was conducted in 4181 middle-aged subjects without diabetes.

Development and Validation of a Model to Predict Severe Hospital-Acquired Acute Kidney Injury in Non-Critically Ill Patients.

Background: The current models developed to predict hospital-acquired AKI (HA-AKI) in non-critically ill fail to identify the patients at risk of severe HA-AKI stage 3.

Objective: To develop and externally validate a model to predict the individual probability of developing HA-AKI stage 3 through the integration of electronic health databases.

Methods: Study set: 165,893 non-critically ill hospitalized patients.

Idiopathic pulmonary fibrosis cluster analysis highlights diagnostic delay and cardiovascular comorbidity association with outcome.

Introduction: Idiopathic pulmonary fibrosis (IPF) prognosis is heterogeneous despite antifibrotic treatment. Cluster analysis has proven to be a useful tool in identifying interstitial lung disease phenotypes, which has yet to be performed in IPF. The aim of this study is to identify phenotypes of IPF with different prognoses and requirements.

Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data.

Background: During the last decade, the interest to apply machine learning algorithms to genomic data has increased in many bioinformatics applications. Analyzing this type of data entails difficulties for managing high-dimensional data, class imbalance for knowledge extraction, identifying important features and classifying individuals. In this study, we propose a general framework to tackle these challenges with different machine learning algorithms and techniques.

Characterization of the CPAP-treated patient population in Catalonia.

There are different phenotypes of obstructive sleep apnoea (OSA), many of which have not been characterised. Identification of these different phenotypes is important in defining prognosis and guiding the therapeutic strategy. The aim of this study was to characterise the entire population of continuous positive airway pressure (CPAP)-treated patients in Catalonia and identify specific patient profiles using cluster analysis.

Rehabilitation Profiles of Older Adult Stroke Survivors Admitted to Intermediate Care Units: A Multi-Centre Study.

Background: Stroke is a major cause of disability in older adults, but the evidence around post-acute treatment is limited and heterogeneous. We aimed to identify profiles of older adult stroke survivors admitted to intermediate care geriatric rehabilitation units.

Methods: We performed a cohort study, enrolling stroke survivors aged 65 years or older, admitted to 9 intermediate care units in Catalonia-Spain.