Cautiously optimistic: paediatric critical care nurses' perspectives on data-driven algorithms in low-resource settings-a human-centred design study in Malawi.

Background: Paediatric critical care nurses face challenges in promptly detecting patient deterioration and delivering high-quality care, especially in low-resource settings (LRS). Patient monitors equipped with data-driven algorithms that monitor and integrate clinical data can optimise scarce resources (e.g.

Inhalation corticosteroids for COVID-19 - a real world data analysis on guideline adherence.

Background: The recommendation to consider prescribing inhalation corticosteroids to a subgroup of vulnerable COVID-19 patients was added to the Dutch medical guideline on November 11, 2021, and was also adopted by other countries during the pandemic.

Aim: To evaluate the adherence of general practitioners to this guideline, and whether real-world data quality is sufficient to study the effect of revised guidelines on prescribing behaviour.

Design & Setting: A retrospective cohort study using Dutch primary care data from the Extramural LUMC Academic Network database, containing patient data of 129 general practices in the Leiden - The Hague area.

Outcomes of female fertility preservation with cryopreservation of oocytes or embryos in the Netherlands: a population-based study.

Study Question: What are the reproductive outcomes of patients who cryopreserved oocytes or embryos in the context of fertility preservation in the Netherlands?

Summary Answer: This study shows that after a 10-year follow-up period, the utilization rate to attempt pregnancy using cryopreserved oocytes or embryos was 25.5% and the cumulative live birth rate after embryo transfer was 34.6% per patient.

The effect and implementation of the COVID Box, a remote patient monitoring system for patients with a COVID-19 infection in primary care: a matched cohort study.

At the onset of the COVID-19 pandemic, the pressure on hospitals increased tremendously. To alleviate this pressure, a remote patient monitoring system called the COVID Box was developed and implemented in primary care. The aim was to assess whether the COVID Box in primary care could reduce emergency department (ED) referrals due to a COVID-19 infection.

Availability of Evidence for Predictive Machine Learning Algorithms in Primary Care: A Systematic Review.

Importance: The aging and multimorbid population and health personnel shortages pose a substantial burden on primary health care. While predictive machine learning (ML) algorithms have the potential to address these challenges, concerns include transparency and insufficient reporting of model validation and effectiveness of the implementation in the clinical workflow.

Objectives: To systematically identify predictive ML algorithms implemented in primary care from peer-reviewed literature and US Food and Drug Administration (FDA) and Conformité Européene (CE) registration databases and to ascertain the public availability of evidence, including peer-reviewed literature, gray literature, and technical reports across the artificial intelligence (AI) life cycle.