De-imFAR phase II project: a study protocol for a cluster randomised implementation trial to evaluate the effectiveness of de-implementation strategies to reduce low-value statin prescribing in the primary prevention of cardiovascular disease.

INTRODUCTION: This study aims to reduce potentially inappropriate prescribing (PIP) of statins and foster healthy lifestyle promotion in cardiovascular disease (CVD) primary prevention in low-risk patients. To this end, we will compare the effectiveness and feasibility of several de-implementation strategies developed following the structured design process of the Behaviour Change Wheel targeting key determinants of the clinical decision-making process in CVD prevention. METHODS AND ANALYSIS: A cluster randomised implementation trial, with an additional control group, will be launched, involving family physicians (FPs) from 13 Integrated Healthcare Organisations (IHOs) of Osakidetza-Basque Health Service with non-zero incidence rates of PIP of statins in 2021. All FPs will be exposed to a non-reflective decision assistance strategy based on reminders and decision support tools. Additionally, FPs from two of the IHOs will be randomly assigned to one of two increasingly intensive de-implementation strategies: adding a decision information strategy based on knowledge dissemination and a reflective decision structure strategy through audit/feedback. The target population comprises women aged 45-74 years and men aged 40-74 years with moderately elevated cholesterol levels but no diagnosed CVD and low cardiovascular risk (REGICOR<7.5%), who attend at least one appointment with any of the participating FPs (May 2022-May 2023), and will be followed until May 2024. We use the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework to evaluate outcomes. The main outcome will be the change in the incidence rate of PIP of statins and healthy lifestyle counselling in the study population 12 and 24 months after FPs' exposure to the strategies. Moreover, FPs' perception of their feasibility and acceptability, and patient experience regarding the quality of care received will be evaluated. ETHICS AND DISSEMINATION: The study was approved by the Basque Country Clinical Research Ethics Committee and was registered in ClinicalTrials.gov (NCT04022850). Results will be disseminated in scientific peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04022850.

Tear and ocular surface disease biomarkers: A diagnostic and clinical perspective for ocular allergies and dry eye disease.

Validated biomarkers to be used as biological tools for managing ocular surface diseases (OSDs) are still an unmet need in daily clinical practice. Many studies have contributed to the already extensive list of candidate biomarkers for these disorders. Dry eye (DE) and ocular allergy (OA) are complex and multifactorial diseases, often coexisting and with overlapping symptoms. The purpose of this review is to present a comprehensive updated revision of the most relevant biomarkers of DE and OA, with an emphasis on quantitative analyses and correlations with clinical parameter data. Analysis of biomarkers common for these pathologies has highlighted an important physiological process. Namely, the interleukin proteins (IL-1α, IL-1ß and IL-17), tumour necrotic factor (TNFα) and interferon gamma (IFNγ; Th1-Th7 pathway) and IL-4, IL-5 and IL-13 (Th2 pathway) seem to represent similar inflammatory mechanisms. Moreover, changes in the levels of mucins (MUC1, MUC2, MUC4, MUC5 and MUC16) are common alterations in the tear film mucous layer. We also examine the current state of medical devices and the main limitations to their use in clinical practice. Translational research in biomarkers for clinical practice depends on a feasible transition from the laboratory to the point-of-care. This requires large-scale, coordinated clinical validation campaigns to select the biomarkers with the highest specificity and sensitivity and significant correlation with clinical parameters. Moreover, technical limitations of multiplexed quantitation systems must be overcome to detect and measure the levels of several biomarkers in very small samples. To ensure the future of biomarker research, significant progress is necessary in a number of fields. There is an urgent need for global unification of clinical classification and diagnostics criteria. Widespread integration of proteomic and transcriptomic data is paramount for performing meaningful analyses using appropriate bioinformatics tools and artificial intelligence systems.