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Abstract Introduction Chronic pain (CP) and depression/anxiety often coexist, worsening each other's symptoms. Treating this comorbidity is challenging. Tricyclic antidepressants and serotonin noradrenaline reuptake inhibitors are the first-line treatment options for this comorbidity, although sometimes they are not effective and/or well tolerated by patients, and there is little clinical evidence that selective serotonin reuptake inhibitors are useful for controlling CP. The antidepressant vortioxetine, with a multimodal mechanism that may help reduce pain, has proven clinical efficacy in patients with major depressive disorder (MDD). This study investigated vortioxetine's effectiveness for MDD and CP in clinical practice. Methods This was a 3-month, multicenter, prospective, open-label, non-interventional pharmacoepidemiologic study. Patients (n = 64) with MDD (9-item Patient Health Questionnaire [PHQ-9] score ≥ 15) and CP (visual analogue scale [VAS] score ≥ 4) were treated with vortioxetine for 3 months (initiated with 10 mg/day, with flexible dosing thereafter [5–20 mg/day]). VAS, Clinical Global Impression (CGI), and Patient Global Impression (PGI) scales were used at baseline and at 1 and 3 months. Brief Pain Inventory (BPI), PHQ-9 scale, and Satisfaction with Medicines Questionnaire (SATMED-Q) were used at baseline and at 3 months. Adverse Events (AEs) were recorded. Descriptive statistics, chi-square tests, and Student's t-tests were used for paired data. Results MDD patients showed a statistically significant improvement in VAS from baseline (mean [standard deviation (SD)]: 7.42 [0.69]) to 1 month (mean [SD]: 6.1 [0.81], P

Abstract Introduction Sublingual fentanyl tablets (SFTs) have been shown to be a safe and effective option in controlling breakthrough cancer pain (BTcP). However, further examination is required to investigate the use of SFTs among the elderly. The aim of this study was to examine the influence of age in BTcP management with SFTs in the elderly population. Methods We performed subgroup analyses of a recently completed trial in two subsets of individuals: patients aged 65–74 years (low age group) and patients ≥ 75 years (high age group). Pain intensity (PI), onset of pain relief, frequency and duration of BTcP episodes, and adverse events (AEs) were assessed at 3, 7, 15, and 30 days. Health status instruments used were the Hospital Anxiety and Depression Scale (HADS-A and HADS-D) and the Short Form 12, version 2 (SF-12v2) questionnaire. Results Levels of PI at the end of the study improved significantly as compared with baseline in both the low and the high age groups (30.0% and 27.7% reduction, respectively). The onset of analgesia at the end of the study began in

Background: A key driver of antimicrobial resistance (AMR) is patient demand for unnecessary antibiotics, which is driven by patients’ beliefs about antibiotics and AMR. Few interventions have targeted beliefs to reduce inappropriate demand.Objective: To examine whether a brief, online algorithm-based intervention can change beliefs that may lead to inappropriate antibiotic demand (i.e. perceptions of antibiotic necessity and lack of concern about antibiotic harm).Design: Pre- and post-intervention study.Participants: Participants were 18 years or older, and residing in the United Kingdom, who self-selected to participate via Amazon mTurk, an online survey plaform, and via research networks.Intervention: Participants were presented with a hypothetical situation of cold and flu symptoms, then exposed to the intervention. The online intervention comprised: 1) a profiling tool identifying individual beliefs (antibiotic necessity, concerns, and knowledge) driving inappropriate antibiotic demand; 2) messages designed to change beliefs and knowledge (i.e. reduce antibiotic necessity, and increase antibiotic concerns and knowledge), and 3) an algorithm linking specific messages to specific beliefs and knowledge.Main measures: The profiling tool was repeated immediately after the intervention and compared with baseline scores to assess change in beliefs. A paired samples t-test was used to determine intervention effect.Key Results: A total of 100 respondents completed the study. A significant change in beliefs relating to inappropriate demand was observed after the intervention, with a reduction in beliefs about antibiotic necessity (t = 7.254; p < 0.0001), an increase in antibiotic concerns (t = −7.214; p < 0.0001), and increases in antibiotic and AMR knowledge (t = −4.651; p < 0.0001).Conclusion: This study is the first to demonstrate that patient beliefs about antibiotics and AMR associated with inappropriate demand can be changed by a brief, tailored online intervention. This has implications for the design of future interventions to reduce unnecessary antimicrobial use.

The pandemic situation banned the presence of teachers and students in the classrooms disrupting the typical teaching process. Videoconferencing services have been used successfully for lectures, but they are insufficient for hands-on laboratories where the physical presence is a requirement (i.e. to access specific hardware). Enabling remote access to the equipment allows to overcome this issue, but the students must share resources (temporarily or physically) and lack full control on the equipment. This is not optimal for some subjects, such as the practical labs on datacenter management, which are increasingly being added into the IT higher education curriculum. In this paper, we present the design and implementation of a distributed laboratory environment, so-called Remote DasaLAB, to create and deploy virtual datacenters using the student's owned resources to support the practical training of students in remote (or hybrid) mode. This environment is flexible, cheap, easy to implement with available commodity resources (the students' computers) and provides full control over the platform. We also present a specific use case on leveraging Remote DasaLAB for the practical assignments of an Operating Systems subject, in which the students build a virtual datacenter composed of multiple nodes and can properly run a containerized application distributed in these nodes.