Sputum metagenomics reveals a multidrug resistant Pseudomonas-dominant severe asthma phenotype in an Asian population.

Background And Objective: While the lung microbiome in severe asthma has been studied, work has employed targeted amplicon-based sequencing approaches without functional assessment with none focused on multi-ethnic Asian populations. Here we investigate the clinical relevance of microbial phenotypes of severe asthma in Asians using metagenomics.

Methods: Prospective assessment of clinical, radiological, and immunological measures were performed in a multi-ethnic Asian severe asthma cohort (N = 70) recruited across two centres in Singapore.

Unravelling ChatGPT's potential in summarising qualitative in-depth interviews.

Background/objectives: Qualitative research can be laborious and time consuming, presenting a challenge for practitioners and policymakers seeking rapid, actionable results. Data collection, transcription and analysis are the main contributors to the resource-intensive nature. OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have demonstrated potential to aid in data analysis.

Investigating Nonadherence in an Integrated Diabetic Limb Salvage Programme: Reasons, Associated Factors, and Impacts on Care Outcomes.

Adherence to treatment plans is crucial for patients with diabetic foot ulcers (DFUs) to achieve positive outcomes. With limited understanding of nonadherence and its impacts on care outcomes, this study aimed to explore the reasons and factors associated with nonadherence in an integrated diabetic limb salvage (DLS) programme and evaluate its effects on care outcomes. This study included 2798 DFU patients who were enrolled in an integrated DLS programme across multiple institutions in central and northern Singapore from 2020 to 2021.