Pharmacist's geriatric assessment can provide valuable insights into potential deprescribing targets, while including important information on various health-related domains. Data collected from a geriatric assessment questionnaire, for 388 patients, from the Croatian cohort of the EuroAgeism H2020 ESR 7 international project, along with guideline-based deprescribing criteria, were used to analyse potentially inappropriate prescribing of four medication groups (benzodiazepines (BZN), proton pump inhibitors (PPI), opioids, and non-steroidal anti-inflammatory drugs (NSAID)), and to assess the deprescribing potential. Binary logistic regression was used to explore the effects of age, gender, number of medicines and diagnoses, self-reported health, frailty score, and healthcare utilization on the likelihood of needing deprescribing. More than half of participants (n = 216, 55.2%) are candidates for deprescribing, with 31.1% of PPI, 74.8% of NSAID, 75% of opioid, and 96.1% of BZN users meeting at least one criterion. Most common criteria for deprescribing were inappropriately long use and safety concerns. Women (aOR = 2.58; p < 0.001), those reporting poor self-reported health (aOR = 5.14; p < 0.001), and those exposed to polypharmacy (aOR = 1.29; p < 0.001) had higher odds of needing to have medicines deprescribed. The high rate of deprescribing potential warrants prompt action to increase patient safety and decrease polypharmacy. Pharmacist's geriatric assessment and deprescribing-focused medication review could be used to lead a personalised approach.

• Keywords
• Deprescribing, Geriatric assessment, Geriatrics, Healthy ageing, Polypharmacy,
• MeSH
• Anti-Inflammatory Agents, Non-Steroidal MeSH
• Deprescriptions * MeSH
• Pharmacists MeSH
• Geriatric Assessment MeSH
• Humans MeSH
• Inappropriate Prescribing prevention & control   MeSH
• Independent Living MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Anti-Inflammatory Agents, Non-Steroidal MeSH

AIMS: The aim of this study was to compare the clinical decision-making for benzodiazepine deprescribing between a healthcare provider (HCP) and an artificial intelligence (AI) chatbot GPT4 (ChatGPT-4). METHODS: We analysed real-world data from a Croatian cohort of community-dwelling benzodiazepine patients (n = 154) within the EuroAgeism H2020 ESR 7 project. HCPs evaluated the data using pre-established deprescribing criteria to assess benzodiazepine discontinuation potential. The research team devised and tested AI prompts to ensure consistency with HCP judgements. An independent researcher employed ChatGPT-4 with predetermined prompts to simulate clinical decisions for each patient case. Data derived from human-HCP and ChatGPT-4 decisions were compared for agreement rates and Cohen's kappa. RESULTS: Both HPC and ChatGPT identified patients for benzodiazepine deprescribing (96.1% and 89.6%, respectively), showing an agreement rate of 95% (κ = .200, P = .012). Agreement on four deprescribing criteria ranged from 74.7% to 91.3% (lack of indication κ = .352, P < .001; prolonged use κ = .088, P = .280; safety concerns κ = .123, P = .006; incorrect dosage κ = .264, P = .001). Important limitations of GPT-4 responses were identified, including 22.1% ambiguous outputs, generic answers and inaccuracies, posing inappropriate decision-making risks. CONCLUSIONS: While AI-HCP agreement is substantial, sole AI reliance poses a risk for unsuitable clinical decision-making. This study's findings reveal both strengths and areas for enhancement of ChatGPT-4 in the deprescribing recommendations within a real-world sample. Our study underscores the need for additional research on chatbot functionality in patient therapy decision-making, further fostering the advancement of AI for optimal performance.

• Keywords
• ChatGPT-4, artificial intelligence (AI), benzodiazepines, chatbot, deprescribing,
• MeSH
• Benzodiazepines adverse effects   MeSH
• Deprescriptions * MeSH
• Clinical Decision-Making MeSH
• Humans MeSH
• Artificial Intelligence * MeSH
• Health Personnel MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Benzodiazepines MeSH

Imiquimod (IMQ) is a potent immune response modifier with antiviral and antitumor properties. IMQ's low aqueous solubility and unsatisfactory cutaneous permeability limit its formulation into effective dosage forms. This work aimed to develop IMQ-loaded microemulsions (MEs) based on phospholipids and oleic acid to improve IMQ penetration into the epidermis. A pseudo-ternary phase diagram was constructed, and the microstructure of the formulations was examined by measuring the conductivity values. Selected MEs were characterized and studied for their ability to deliver IMQ into and through ex vivo human skin. ME1 with 1% IMQ (bicontinuous ME with Bingham rheology) delivered similar IMQ quantities to the human epidermis ex vivo as the commercial product while having a 5-fold lower IMQ dose. IMQ was not detected in the acceptor phase after the permeation experiment, suggesting a lower systemic absorption risk than the established product. Infrared spectroscopy of the stratum corneum revealed less ordered and less tightly packed lipids after ME1 application. The ME1-induced barrier disruption recovered within less than 5 h after the formulation removal, as detected by transepidermal water loss measurements. In conclusion, our findings demonstrate that phospholipid and oleic acid-based MEs could become a promising alternative for topical IMQ administration.

• Keywords
• dermal delivery, imiquimod, infrared spectroscopy, microemulsions, oleic acid, transepidermal water loss,
• Publication type
• Journal Article MeSH