Digital twins for chronic lung diseases.

Digital twins have recently emerged in healthcare. They combine advances in cyber-physical systems, modelling and computation techniques, and enable a bidirectional flow of information between the physical and virtual entities. In respiratory medicine, progress in connected devices and artificial intelligence make it technically possible to obtain digital twins that allow real-time visualisation of a patient's respiratory health.

The Bronchodilator and Anti-Inflammatory Effect of Long-Acting Muscarinic Antagonists in Asthma: An EAACI Position Paper.

As cholinergic innervation is a major contributor to increased vagal tone and mucus secretion, inhaled long-acting muscarinic antagonists (LAMA) are a pillar for the treatment of chronic obstructive pulmonary disease and asthma. By blocking the muscarinic receptors expressed in the lung, LAMA improve lung function and reduce exacerbations in asthma patients who remained poorly controlled despite treatment with inhaled corticosteroids and long-acting β2 agonists. Asthma guidelines recommend LAMA as a third controller to be added on before the initiation of biologicals.

"I didn't go into medicine just to be on the phone": Emotional Expression as Sacrosanct During Derious Illness Patient-Physician Advanced Cancer Care Communication During the COVID-19 Pandemic.

Guided by communication accommodation theory, we studied 27 physician reports of patient-physician advanced cancer communication during the COVID-19 pandemic. Advanced cancer communication requires recognizing patients' psychosocial states and collaboratively engaging patients empathetically to develop the shared understanding necessary to guide decision-making. However, physicians found their communication underaccommodated, stemming from personal protection equipment, social distancing, and telemedicine.

Artificial intelligence in respiratory care: perspectives on critical opportunities and challenges.

Artificial intelligence (AI) is transforming respiratory healthcare through a wide range of deep learning and generative tools, and is increasingly integrated into both patients' lives and routine respiratory care. The implications of AI in respiratory care are vast and multifaceted, presenting both promises and uncertainties from the perspectives of clinicians, patients and society. Clinicians contemplate whether AI will streamline or complicate their daily tasks, while patients weigh the potential benefits of personalised self-management support against risks such as data privacy concerns and misinformation.