Digital medicine is already well established in respiratory medicine through remote monitoring digital devices which are used in the day-to-day care of patients with asthma, COPD and sleep disorders. Image recognition software, deployed in thoracic radiology for many applications including lung cancer screening, is another application of digital medicine. Used as clinical decision support, this software will soon become part of day-to-day practice once concerns regarding generalisability have been addressed. Embodied in the electronic health record, digital medicine also plays a substantial role in the day-to-day clinical practice of respiratory medicine. Given the considerable work the electronic health record demands from clinicians, the next tangible impact of digital medicine may be artificial intelligence that aids administration, makes record keeping easier and facilitates better digital communication with patients. Future promises of digital medicine are based on their potential to analyse and characterise the large amounts of digital clinical data that are collected in routine care. Offering the potential to predict outcomes and personalise therapy, there is much to be excited by in this new epoch of innovation. However, these digital tools are by no means a silver bullet. It remains uncertain whether, let alone when, the promises of better models of personalisation and prediction will translate into clinically meaningful and cost-effective products for clinicians.

Relating Type 2 status to steroid exposure, cytokine expression and symptoms T2 low asthma remains poorly understood even though it may account for up to 50% of patients. We aimed to characterise the inflammatory signature and symptom burden in T2 low patients and relate T2 status to corticosteroid exposure. We evaluated 200 patients' T2 status from the INCA-SUN RCT over 6 visits. Four groups were identified based on frequency of T2 inflammation: Consistently T2 low (n=40), Usually T2 low (n=48), Usually T2 high (n=64) and Consistently T2 high (n=48). Inhaled (ICS) and oral corticosteroid burden (OCS) were measured by digital inhaler monitors and pharmacy records. Multiplex assays of inflammatory pathways (Th-1, T2, Th-17 and TRegs) were performed in these patients and healthy controls. Symptom burden was assessed using the Asthma Control Test (ACT). Low T2 biomarkers were independently associated with higher ICS and OCS exposure, OR 1.03 per mg fluticasone propionate (p=.011), OR 1.44 per course of OCS, p=.018. The Consistently T2 high group had higher periostin (p<.0001), IgE (p<.0001), IL-4 (p=.0061) and IL-5 (p<.0001) compared to the other cohorts. Increasing prevalence of T2 high status was associated with worse and more unstable lung function. The Consistently T2 low patients showed no evidence of alternate inflammatory pathways. Their cytokine results most closely resembled healthy controls but their symptom burden was similar to other groups. ACT scores related poorly to objective markers of asthma. Persistently low ACT scores were associated with co-morbidities such as GORD (p=.006) and anxiety/depression (p=.028) T2 low asthma may be explained by steroid exposure and co-morbid conditions.

In little over a generation, the ingenuity of scientists and clinician researchers has developed inhaled medications and pathway-specific biological agents that control the inflammation and physiology of asthma. Unfortunately, whether it is because of cost or difficulty understanding why or how to use inhaled medications, patients often do not take these medications. The consequences of poor treatment adherence, loss of control and exacerbations, are the same as if the condition remained untreated. Furthermore, poor adherence is difficult to detect without direct measurement. Together this means that poor treatment adherence is easily overlooked and, instead of addressing the cause of poor adherence, additional medicines may be prescribed. In other words, poor treatment adherence is a risk for the patient and adds cost to healthcare systems. In this article, we discuss the rationale for and the delivery of successful interventions to improve medication adherence in asthma. We contextualize these interventions by describing the causes of poor treatment adherence and how adherence is assessed. Finally, future perspectives on the design of new interventions are described.

Introduction: The simplified Pulmonary Embolism Severity Index (sPESI) risk stratifies patients with PE. Current guidelines support the establishment of PERT to inform treatment decisions, educate and guide local policy in PE management. The objective of this study was to determine the number of patients with PE that may benefit from review by PERT and/or consideration of catheter directed thrombolysis (CDT) in our institution. Methods: A retrospective analysis of all cases of PE diagnosed in 2018 at our institution was undertaken. Data in relation to sPESI score, cardiac biomarkers and evidence of right heart strain by echocardiogram/CT analysis was gathered. Results: PE was identified in 158/1121 (14.1%) CT Pulmonary Angiograms performed at our institution in 2018. Data was missing in 3 cases; 155 cases were included in analysis. Two cases received systemic thrombolysis (1 intermediate and 1 high risk). A significant proportion (79%) of cases had a high sPESI – categorised as intermediate or high risk PE. Most patients (70%) were managed by a primary physician without specialist training in cardiology or respiratory medicine. CDT may be considered in 26 (17%) of PE cases. Conclusion: Application of clinical risk stratification in our institution supports the establishment of PERT to promote guideline-based care, provide clinical input for PE treatment and guide uptake of novel therapies in select patients with PE.