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Aims: The global older population is growing rapidly, and the rise in polypharmacy has increased potentially inappropriate medication (PIM) encounters. PIMs pose health risks, but detecting them automatically in large medical databases is complex. This review aimed to uncover PIM prevalence in individuals aged 65 years or older using health databases and emphasized the risk of underestimating PIM prevalence due to underutilization of detection tools. Methods: This study conducted a broad search on the Medline database to identify articles about the prevalence of PIMs in older adults using various databases. Articles published between January 2010 and June 2023 were included, and specific criteria were applied for study selection. Two literature reviews conducted before our study period were integrated to obtain a perspective from the 1990s to the present day. The selected papers were analysed for variables including database type, screening method, adaptations and PIM prevalence. The study categorized databases and original screening tools for clarity, examined adaptations and assessed concordance among different screening methods. Results: This study encompassed 48 manuscripts, covering 58 sample evaluations. The mean prevalence of PIMs within the general population aged over 65 years was 27.8%. Relevant heterogeneity emerged in both the utilized databases and the detection methods. Adaptation of original screening tools was observed in 86.2% (50/58) of cases. Half of the original screening tools used for assessing PIMs belonged to the simple category. About a third of the studies employed less than half of the original criteria after adaptation. Only three studies used over 75% of the original criteria and more than 50 criteria. Conclusions: This extensive review highlights PIM prevalence among the older adults, emphasizing method intricacies and the potential for underestimation due to data limitations and algorithm adjustments. The findings call for enhanced methodologies, transparent algorithms and a deeper understanding of intricate rules' impact on public health implications. [ABSTRACT FROM AUTHOR]

One Digital Health (ODH) merges the Digital Health and One Health approaches to create a comprehensive framework for future health ecosystems. In this rapidly evolving field, a standardized vocabulary is not just a convenience, but a necessity to ensure efficient communication. This research proposes the development of a "One Digital Health-Unified Terminology" (ODH-UT) to facilitate communication among researchers and practitioners in Digital Health and One Health, addressing this crucial need. [ABSTRACT FROM AUTHOR]

Thirteen standardized reasons for e-visits were implemented in March 2024 on a French telemedicine platform to improve the analysis of needs in telemedicine, educate patients on what is possible in e-visit and adapt the offer. Patients could select 1 to 3 reasons for consultations among a list of 13 reasons. Our aim was to evaluate their impact on use of e-visits. The main reasons for consultations in teleconsultations were more linked to acute care, specifically involving a large majority of upper respiratory tract infections, back pain, and urinary tract infections. They were mostly concordant with the physician’s conclusion and they may have simplified the preparation of the e-visits. [ABSTRACT FROM AUTHOR]

Suitable causal inference in biostatistics can be best achieved by knowledge representation thanks to causal diagrams or directed acyclic graphs. However, necessary and sufficient causes are not easily represented. Since existing ontologies do not fill this gap, we designed OntoBioStat in order to enable covariate selection support based on causal relation representations. OntoBioStat automatic ontological causal diagram construction and inferences are detailed in this study. OntoBioStat inferences are allowed by Semantic Web Rule Language rules and axioms. First, statements made by the users include outcome, exposure, covariate, and causal relation specification. Then, reasoning enable automatic construction using generic instances of Meta_Variable and Necessary_Variable classes. Finally, inferred classes highlighted potential bias such as confounder-like. Ontological causal diagram built with OntoBioStat was compared to a standard causal diagram (without OntoBioStat) in a theoretical study. It was found that confounding and bias were not completely identified by the standard causal diagram, and erroneous covariate sets were provided. Further research is needed in order to make OntoBioStat more usable. [ABSTRACT FROM AUTHOR]

Objective: A comprehensive understanding of professional and technical terms is essential to achieving practical results in multidisciplinary projects dealing with health informatics and digital health. The medical informatics multilingual ontology (MIMO) initiative has been created through international cooperation. MIMO is continuously updated and comprises over 3700 concepts in 37 languages on the Health Terminology/Ontology Portal (HeTOP). Methods: We conducted case studies to assess the feasibility and impact of integrating MIMO into real-world healthcare projects. In HosmartAI, MIMO is used to index technological tools in a dedicated marketplace and improve partners' communication. Then, in SaNuRN, MIMO supports the development of a "Catalog and Index of Digital Health Teaching Resources" (CIDHR) backing digital health resources retrieval for health and allied health students. Results: In HosmartAI, MIMO facilitates the indexation of technological tools and smooths partners' interactions. In SaNuRN within CIDHR, MIMO ensures that students and practitioners access up-to-date, multilingual, and high-quality resources to enhance their learning endeavors. Conclusion: Integrating MIMO into training in smart hospital projects allows healthcare students and experts worldwide with different mother tongues and knowledge to tackle challenges facing the health informatics and digital health landscape to find innovative solutions improving initial and continuous education., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objectives: Despite significant savings with biosimilars, their negative perception can lead to the occurrence of a nocebo effect (NE), therefore we aimed to quantify the NE in inflammatory rheumatism after switching from adalimumab or etanercept originators to biosimilars., Methods: This retrospective study was conducted in 4 hospitals in Normandy, France between January 2018 and July 2022. The study included patients with rheumatoid arthritis or spondyloarthritis in remission under adalimumab or etanercept originators before switching to biosimilars. The occurrence of a NE was considered in patients who did not maintain biosimilars at 12 months and who presented a subjective adverse event (AE). A comparative analysis of the quantitative data collected before and after switching was performed. The AE that led to biosimilar discontinuation was identified. Additional analyses were performed to identify potential risk factors for the occurrence of a NE., Results: Among 183 patients included,13.1% presented a NE. Objective AEs were observed, including rheumatism reactivation (15.3%), intolerance (8.2%), infection (1.6%) and allergic reactions (0.5%). Morning stiffness duration was significantly different before and after the switch in the spondyloarthritis group (p=0.01). No risk factors were associated with the occurrence of a NE within the limits of the studied parameters., Conclusions: The occurrence of a NE after switching to a biosimilar remains acceptable. It appears less frequent when the switch is supervised by the practitioner rather than being systematic (up to 33% in some countries). A shared medical decision seems to be essential in a subset of patients, which remains to be defined.

Objectives: To analyse in routine practice the efficacy of targeted therapies on joint involvement of patients with rheumatoid arthritis/systemic sclerosis (RA/SSc) overlap syndrome., Methods: This was a retrospective analysis of medical records of two academic centres over a 10-year period. Joint response to targeted therapies was measured according to EULAR criteria based on Disease Activity Score (DAS)-28. In addition, changes in CRP level and glucocorticoid consumption were recorded., Results: Nineteen patients were included. Methotrexate (n=11) and hydroxychloroquine (n=4) were the most used first-line treatments. Targeted therapies were frequently used (n=14). Tocilizumab was the most selected therapy (n=8), then rituximab (n=5), abatacept and anti-tumour necrosis factor (n=4). Twenty-one treatment sequences were assessed, including 18 with EULAR response criteria. Responses were "good" or "moderate" in 100% (4/4) of patients treated with abatacept, 80% (4/5) with rituximab, 40% (2/5) with tocilizumab, and 25% (1/4) with anti-TNF. T and B lymphocyte-targeted therapies (abatacept, rituximab) resulted more frequently in a "good" or "moderate" response compared to cytokine inhibitors (tocilizumab, etanercept, infliximab) with a significant decrease in DAS-28 at 6 months (-1.75; p=0.016) and a trend to a lower consumption of glucocorticoids., Conclusions: In patients with RA/SSc overlap syndrome refractory to conventional synthetic-DMARDs, T and B lymphocyte-targeted therapies seem to be a promising therapeutic option to control joint activity.