Predictive genetic panel for adult asthma using machine learning methods.

Background: Asthma is a chronic inflammatory disease of the airways that is heterogeneous and multifactorial, making its accurate characterization a complex process. Therefore, identifying the genetic variations associated with asthma and discovering the molecular interactions between the omics that confer risk of developing this disease will help us to unravel the biological pathways involved in its pathogenesis.

Objective: We sought to develop a predictive genetic panel for asthma using machine learning methods.

Factors associated with nosocomial pneumonia in hospitalized individuals.

Objective: To identify factors associated with nosocomial pneumonia in individuals admitted to a public hospital in Feira de Santana, Bahia.

Methods: This case control study was carried out in 211 adult individuals (46 cases and 165 controls), of a mean age of 41 years, treated at clinical wards, surgical wards or the adult intensive care unit of Cleriston Andrade General Hospital in Feira de Santana. The cases comprised individuals who developed respiratory tract infections (nosocomial pneumonia) after hospital admission.