Development of Machine Learning Algorithms for Identifying Patients With Limited Health Literacy.

Rationale: Limited health literacy (HL) leads to poor health outcomes, psychological stress, and misutilization of medical resources. Although interventions aimed at improving HL may be effective, identifying patients at risk of limited HL in the clinical workflow is challenging. With machine learning (ML) algorithms based on readily available data, healthcare professionals would be enabled to incorporate HL screening without the need for administering in-person HL screening tools.

Multicentre Study of Candida parapsilosis Blood Isolates in Türkiye Highlights an Increasing Rate of Fluconazole Resistance and Emergence of Echinocandin and Multidrug Resistance.

Objectives: Worldwide emergence of clonal outbreaks caused by fluconazole-resistant (FLCR) and the recent emergence of echinocandin- and multidrug-resistant (ECR and MDR) Candida parapsilosis isolates pose serious threats to modern clinics. Conducting large-scale epidemiological studies aimed at determining the genetic composition and antifungal resistance rates is necessary to devise antifungal stewardship and infection control strategies at international, national and local levels. Despite being severely hit by outbreaks due to FLCR C.

Clonal outbreak of Candida vulturna in a paediatric oncology ward in Maranhão, Brazil.

Objective: To describe an outbreak due to Candida vulturna, a newly emerging Candida species belonging to the Candida haemulonii species complex in the Metschnikowiaceae family.

Methods: In this retrospective cohort study we genotyped 14 C. vulturna bloodstream isolates, occurring in a 4-month-period in paediatric cancer patients in a Brazilian hospital.

Genotyping of Candida tropicalis isolates uncovers nosocomial transmission of two lineages in Italian tertiary care hospital.

Objectives: Candida tropicalis is a medically important yeast with increasing antifungal resistance, but nosocomial transmission is rarely reported. This study genotyped C. tropicalis isolates from Italian hospitals to uncover potential nosocomial transmission and assess resistance.

The Vaginal Microbiome: Patient- versus Physician-Collected Microbial Swab: A Pilot Study.

The composition of the vaginal microbiota prior to an IVF/IVF-ICSI treatment can predict the chance of achieving a pregnancy. To improve clinical applicability and be more patient-friendly, the self-collection of vaginal samples would be preferable. However, the reliability of patient-collected samples compared to physician-collected samples remains unclear.