[Health Literacy and Metabolic Control in Individuals Diagnosed with Type 2 Diabetes Mellitus: A Cluster Randomized Clinical Trial].

Unlabelled: People with type 2 diabetes mellitus (DM2) experience difficulties in self-management. One of the variables involved is the low level of health literacy (HL) which corresponds to the degree to which people access, understand, evaluate and use information to engage with health demands in different contexts, in order to promote and maintain good health.

Hypothesis: People diagnosed with diabetes mellitus who participate in an intervention to increase their level of health literacy improve their metabolic compensation measured in HBA1c.

Klebsiella pneumoniae employs a type VI secretion system to overcome microbiota-mediated colonization resistance.

Microbial species must compete for space and nutrients to persist in the gastrointestinal (GI) tract, and our understanding of the complex pathobiont-microbiota interactions is far from complete. Klebsiella pneumoniae, a problematic, often drug-resistant nosocomial pathogen, can colonize the GI tract asymptomatically, serving as an infection reservoir. To provide insight on how K.

Factors influencing salivary lactate dehydrogenase levels in oral squamous cell carcinoma and oral potentially malignant disorders.

Introduction: Salivary Lactate Dehydrogenase (sLDH) levels seem to be higher in patients with Oral Squamous Cell Carcinoma (OSCC) and Oral Potentially Malignant Disorders (OPMD) than a control group (CG).

Methods: Case-control study. Patients with OPMD [oral leukoplakia (OL) and oral lichen planus (OLP)] and OSCC who attended two services in Spain were selected.

Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.

Background: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.

Objective: To summarise the evidence on the effectiveness of NLP/ML in detecting ADEs from unstructured EHR data and ultimately improve pharmacovigilance in comparison to other data sources.

Best clinical model predicting extubation failure: a diagnostic accuracy post hoc analysis.

Purpose: Predicting extubation failure remains a clinical challenge. This study aimed to determine diagnostic accuracy of models used at the bed side.

Methods: Post hoc analysis of 2341 patients at all risk included in five multicenter randomized trials.