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.