Type 2 diabetes (T2DM) and cognitive impairment are common long-term chronic conditions affecting older people in hospital. Cognitive impairment can complicate glucose monitoring and lead to diabetes-related emergencies in T2DM. Traditionally, point of care test measurements of capillary blood glucose are conducted in-hospital for T2DM while continuous glucose monitoring (CGM) is not widely used.

To understand the feasibility, acceptability and tolerability of using CGM in older inpatients with T2DM and cognitive impairment.

32 older people (mean age=78.7±6.7 years) with comorbid T2DM and cognitive impairment (Abbreviated Mini-Mental Test ≤8/10 and Mini-Addenbrooke’s Cognitive Examination ≤22/30) were recruited within a tertiary care hospital in the UK. All participants were naive to CGM and were asked to wear blinded Dexcom G7 sensors for up to 10 days. Participants were asked about feasibility, acceptability and tolerability questions at the point of sensor removal.

29 participants (96%) reported no pain during CGM fitting. All participants (100%) agreed that they did not notice wearing the sensor, and it did not affect their day-to-day hospital activities. All participants (100%) found it ‘very easy’ or ‘easy’ to have the sensor fitted and wearing it for 10 days, with 27 participants (90%) finding CGM convenient. 17 participants (57%) reported favourable perceptions of the subcutaneous sensor sensation.

CGM use in older inpatients with T2DM and cognitive impairment is highly feasible and acceptable for patients. Future studies and trials are now needed to evaluate the clinical use of CGM for glucose monitoring in hospitalised or community-dwelling older individuals with T2DM and cognitive impairment.

To compare the diagnostic accuracy of four available automated electronic medical record (EMR) retrieval methods, including a large language model (LLM)-assisted workflow, against manual chart adjudication for identifying cardiovascular events.

Retrospective diagnostic accuracy study.

Three sites within a single US tertiary health system.

Two adult cohorts with previously adjudicated cardiovascular outcomes were included. Cohort 1 included 2258 patients treated with immune checkpoint inhibitors, and Cohort 2 included 1426 patients who underwent transcatheter aortic valve replacement.

The reference standard was clinician manual chart adjudication. Outcomes included ischaemic stroke or transient ischaemic attack, myocardial infarction (MI), heart failure (HF) exacerbation or hospitalisation and a composite major adverse cardiovascular events (MACE) outcome. Automated retrieval methods included International Classification of Diseases (ICD) codes, primary diagnosis, problem list and a zero-shot LLM workflow. Area under the (receiver operating characteristic) curve (AUC), sensitivity, specificity and net reclassification improvement were assessed.

In Cohort 1, the LLM achieved the highest AUC for stroke (0.920; 95% CI 0.881 to 0.958), MI (0.938; 95% CI 0.905 to 0.971) and composite MACE (0.880; 95% CI 0.854 to 0.907), whereas ICD-based retrieval had a higher AUC for HF (0.882; 95% CI 0.845 to 0.918 vs 0.873; 95% CI 0.831 to 0.914). In Cohort 2, the LLM achieved the highest AUC for all evaluated outcomes: stroke (0.915; 95% CI 0.862 to 0.968), MI (0.928; 95% CI 0.839 to 1.000), HF (0.844; 95% CI 0.803 to 0.884) and composite MACE (0.862; 95% CI 0.829 to 0.895). In Cohort 1, differences in AUC between the LLM and ICD methods were not statistically significant across outcomes, whereas in Cohort 2 the LLM showed significantly higher AUC for stroke and composite MACE.

In this multisite retrospective validation study, the LLM-assisted workflow showed strong but context-dependent performance for identifying cardiovascular events from the EMR. Performance varied by outcome and cohort, and ICD-based retrieval remained competitive for some use cases. These findings support a complementary role for LLM-assisted extraction in retrospective cardiovascular outcomes research.

Acne vulgaris is a chronic inflammatory condition primarily caused by Cutibacterium acnes, which disrupts skin homeostasis, thereby triggering immune responses and sebum metabolism. Dysbiosis is an imbalance in the skin and gut microbiota identified as a significant factor contributing to acne progression. Standard therapy often relies on antibiotics, but the long-term use has increased antibiotic resistance, including in Indonesia. Consequently, alternative methods, such as probiotics and mesenchymal stromal cell secretomes, are gaining attention for immunomodulatory and regenerative properties. These novel therapies have shown promising results in modulating the skin and gut microbiota while reducing inflammation.

A phase 2 double-blind randomised controlled trial will be conducted using a parallel group design with four arms, namely: (1) standard therapy with oral probiotics and topical secretome (placebo), (2) standard therapy with oral probiotics (placebo) and topical secretome, (3) standard therapy with oral probiotics and topical secretome and (4) standard therapy with oral probiotics (placebo) and topical secretome (placebo). Sixty-four patients with mild to moderate acne vulgaris will be randomly allocated to these groups. Interventions will be administered over a period of 8 weeks, with outcomes to be measured at baseline and post-therapy. This study will be conducted at the Dermatology and Venereology Department of Bali Mandara General Hospital (RSBM). The primary outcome will be the reduction of comedones and inflammatory lesions, assessed using the Yolov8 method. Secondary outcomes will include gut and skin health parameters, such as tryptophan metabolites, collagen, pH, moisture, sebum levels and IL-6, to explore the relationship between microbiome balance, skin condition and inflammation in acne.

This study will be conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and the International Conference on Harmonisation–Good Clinical Practice guidelines. Ethical approval has been granted by the Health Research Ethics Committee of Bali Mandara Regional Hospital (Approval Reference Number: 060/EA/KEPK.RSBM.DINKES/2024). All participants will provide written informed consent prior to enrolment. Data confidentiality and participant safety will be upheld throughout the trial. The results of this study will be disseminated through journals, scientific conferences and relevant academic platforms to ensure wide accessibility and to support further research and clinical application in the field of dermatology, particularly in addressing antibiotic resistance and microbiome-based acne therapies.

NCT06925386.

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, primarily due to diagnosis at advanced stages. Although low-dose computed tomography (LDCT) screening reduces lung cancer mortality in high-risk populations, current screening programmes are largely restricted to individuals defined by age and smoking history. This approach excludes never-smokers and individuals with non-smoking-related risk factors, limiting the equity, efficiency and scalability of lung cancer screening. The LUng Cancer risk factors and their Impact Assessment (LUCIA) project aims to overcome these limitations by developing personalised lung cancer risk prediction models and evaluating novel non-invasive technologies for early detection within a risk-adapted screening strategy.

LUCIA is a multicentre, observational, longitudinal cohort study that will recruit approximately 4000 participants across four European regions: Andalusia and the Basque Country (Spain), Liège (Belgium) and Riga (Latvia). The study population includes smokers, never-smokers and reduced smokers with low-to-moderate lung cancer risk. All participants will initially enter phase 1 (wide population screening) and may transition to phase 2 (precision screening) or phase 3 (diagnosis) based on LDCT findings, results from non-invasive screening devices and artificial intelligence-based risk prediction models. Participants will be followed up for 24 months, with assessments at baseline and at 6, 12 and 24 months. Data collection includes sociodemographic characteristics, medical history, environmental and occupational exposures, lifestyle factors, spirometry, multi-omics profiles and outputs from novel non-invasive devices, including a breath analyser, spectrometry-on-card and a skin-applied volatile organic compound sensing patch. The study will develop and validate integrated lung cancer risk prediction models and evaluate the diagnostic performance of these technologies to support population stratification and personalised screening.

The study will be conducted in accordance with the Declaration of Helsinki, Good Clinical Practice guidelines and applicable national and European regulations. Ethical approval has been obtained from the relevant ethics committees in all participating countries. Written informed consent will be obtained from all participants. Study findings will be disseminated through peer-reviewed open-access publications, scientific conferences and communication with public health stakeholders.

ClinicalTrials.gov, NCT06473870.