from the repository of Utrecht University: "OBJECTIVES: Antipsychotic drugs are frequently prescribed to elderly patients, but they are associated with serious adverse effects. The objective of the current study was to investigate the association between use of antipsychotics by elderly women and the risk of urinary tract infections (UTIs). COHORT STUDY SETTING: Dispensing data were obtained from the PHARMO Database Network for the period 1998-2008. PARTICIPANTS: Ambulatory Dutch women (≥65 years) with current and past use of antipsychotics. MEASUREMENTS: Incidence rates of UTIs, as defined by use of nitrofurantoin, was calculated within and outside the period of exposure to antipsychotic drugs. Cox proportional hazard regression analysis with Andersen-Gill extension for recurrent events was used to calculate crude and adjusted hazard ratios (HRs). RESULTS: During the study period, 18,541 women with a first prescription of an antipsychotic were identified. Current use of antipsychotics was associated with an increased risk of UTI compared to past use: HR, adjusted for age and history of UTIs, 1.33, 95% CI 1.27-1.39. A strong temporal relationship was found: the risk of being treated for a UTI was higher in the first week after the start of the treatment (adjusted HR 3.03, 95% CI 2.63-3.50) and decreased after 3 months (adjusted HR 1.22, 95% CI 1.17-1.28). Cumulative exposure was not associated with an increased risk of UTIs. There was no difference in effect between conventional and atypical antipsychotics. CONCLUSION: Our results show an increased risk of uncomplicated UTIs during antipsychotic use in older female patients, especially in the first week of treatment."
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BACKGROUND: Recent evidence suggests that an increase in baccalaureate-educated registered nurses (BRNs) leads to better quality of care in hospitals. For geriatric long-term care facilities such as nursing homes, this relationship is less clear. Most studies assessing the relationship between nurse staffing and quality of care in long-term care facilities are US-based, and only a few have focused on the unique contribution of registered nurses. In this study, we focus on BRNs, as they are expected to serve as role models and change agents, while little is known about their unique contribution to quality of care in long-term care facilities. METHODS: We conducted a cross-sectional study among 282 wards and 6,145 residents from 95 Dutch long-term care facilities. The relationship between the presence of BRNs in wards and quality of care was assessed, controlling for background characteristics, i.e. ward size, and residents' age, gender, length of stay, comorbidities, and care dependency status. Multilevel logistic regression analyses, using a generalized estimating equation approach, were performed. RESULTS: 57% of the wards employed BRNs. In these wards, the BRNs delivered on average 4.8 min of care per resident per day. Among residents living in somatic wards that employed BRNs, the probability of experiencing a fall (odds ratio 1.44; 95% CI 1.06-1.96) and receiving antipsychotic drugs (odds ratio 2.15; 95% CI 1.66-2.78) was higher, whereas the probability of having an indwelling urinary catheter was lower (odds ratio 0.70; 95% CI 0.53-0.91). Among residents living in psychogeriatric wards that employed BRNs, the probability of experiencing a medication incident was lower (odds ratio 0.68; 95% CI 0.49-0.95). For residents from both ward types, the probability of suffering from nosocomial pressure ulcers did not significantly differ for residents in wards employing BRNs. CONCLUSIONS: In wards that employed BRNs, their mean amount of time spent per resident was low, while quality of care on most wards was acceptable. No consistent evidence was found for a relationship between the presence of BRNs in wards and quality of care outcomes, controlling for background characteristics. Future studies should consider the mediating and moderating role of staffing-related work processes and ward environment characteristics on quality of care.
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Study Type – Aetiology (individual cohort)Level of Evidence 2bWhat's known on the subject? and What does the study add?Recent studies have already shown associations between generalized joint hypermobility (GJH) and voiding and defecation dysfunction and/or slow transit constipation. Changes in extracellular matrix composition in vesico‐ureteric junction of vesico‐ureteral reflux (VUR) patients were also observed previously.This study is the first to assess joint mobility as a parameter for connective tissue composition in vesico‐ureteral reflux. We convincingly demonstrate that VUR patients have significantly more hypermobile joints compared to controls and this provides a new angle to the intriguing subjects of development of VUR and susceptibility to VUR.OBJECTIVE•To assess whether there is an increased prevalence of joint hypermobility in patients with vesico‐ureteric reflux (VUR).MATERIALS AND METHODS•We studied 50 patients with primary VUR and matched controls drawn from a reference population.•Joint mobility was assessed using the Bulbena hypermobility score.RESULTS•We identified significantly more patients with VUR with generalized joint hypermobility than controls (24% vs 6.7%, P= 0.007).CONCLUSION•Our findings confirm our clinical observation of an increased rate of joint hypermobility in patients with VUR. We speculate that an altered composition of the connective tissue may contribute to the severity of the (pre‐existing) VUR phenotype.
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Background: Urban slums are characterised by unique challenging living conditions, which increase their inhabitants’ vulnerability to specific health conditions. The identification and prioritization of the key health issues occurring in these settings is essential for the development of programmes that aim to enhance the health of local slum communities effectively. As such, the present study sought to identify and prioritise the key health issues occurring in urban slums, with a focus on the perceptions of health professionals and community workers, in the rapidly growing city of Bangalore, India. Methods: The study followed a two-phased mixed methods design. During Phase I of the study, a total of 60 health conditions belonging to four major categories: - 1) non-communicable diseases; 2) infectious diseases; 3) maternal and women’s reproductive health; and 4) child health - were identified through a systematic literature review and semi-structured interviews conducted with health professionals and other relevant stakeholders with experience working with urban slum communities in Bangalore. In Phase II, the health issues were prioritised based on four criteria through a consensus workshop conducted in Bangalore. Results: The top health issues prioritized during the workshop were: diabetes and hypertension (non-communicable diseases category), dengue fever (infectious diseases category), malnutrition and anaemia (child health, and maternal and women’s reproductive health categories). Diarrhoea was also selected as a top priority in children. These health issues were in line with national and international reports that listed them as top causes of mortality and major contributors to the burden of diseases in India. Conclusions: The results of this study will be used to inform the development of technologies and the design of interventions to improve the health outcomes of local communities. Identification of priority health issues in the slums of other regions of India, and in other low and lower middle-income countries, is recommended.
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Five methods were compared to determine the best technique for accurate identification of coagulase-negative staphylococci (CoNS) (n=142 strains). MALDI-TOF MS showed the best results for rapid and accurate CoNS differentiation (correct identity in 99.3%). An alternative to this approach could be Vitek2 combined with partial tuf gene sequencing.
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Aims: Prescribing errors among junior doctors are common in clinical practice because many lack prescribing competence after graduation. This is in part due to inadequate education in clinical pharmacology and therapeutics (CP&T) in the undergraduate medical curriculum. To support CP&T education, it is important to determine which drugs medical undergraduates should be able to prescribe safely and effectively without direct supervision by the time they graduate. Currently, there is no such list with broad-based consensus. Therefore, the aim was to reach consensus on a list of essential drugs for undergraduate medical education in the Netherlands. Methods: A two-round modified Delphi study was conducted among pharmacists, medical specialists, junior doctors and pharmacotherapy teachers from all eight Dutch academic hospitals. Participants were asked to indicate whether it was essential that medical graduates could prescribe specific drugs included on a preliminary list. Drugs for which ≥80% of all respondents agreed or strongly agreed were included in the final list. Results: In all, 42 (65%) participants completed the two Delphi rounds. A total of 132 drugs (39%) from the preliminary list and two (3%) newly proposed drugs were included. Conclusions: This is the first Delphi consensus study to identify the drugs that Dutch junior doctors should be able to prescribe safely and effectively without direct supervision. This list can be used to harmonize and support the teaching and assessment of CP&T. Moreover, this study shows that a Delphi method is suitable to reach consensus on such a list, and could be used for a European list.
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Abstract Aims: Medical case vignettes play a crucial role in medical education, yet they often fail to authentically represent diverse patients. Moreover, these vignettes tend to oversimplify the complex relationship between patient characteristics and medical conditions, leading to biased and potentially harmful perspectives among students. Displaying aspects of patient diversity, such as ethnicity, in written cases proves challenging. Additionally, creating these cases places a significant burden on teachers in terms of labour and time. Our objective is to explore the potential of artificial intelligence (AI)-assisted computer-generated clinical cases to expedite case creation and enhance diversity, along with AI-generated patient photographs for more lifelike portrayal. Methods: In this study, we employed ChatGPT (OpenAI, GPT 3.5) to develop diverse and inclusive medical case vignettes. We evaluated various approaches and identified a set of eight consecutive prompts that can be readily customized to accommodate local contexts and specific assignments. To enhance visual representation, we utilized Adobe Firefly beta for image generation. Results: Using the described prompts, we consistently generated cases for various assignments, producing sets of 30 cases at a time. We ensured the inclusion of mandatory checks and formatting, completing the process within approximately 60 min per set. Conclusions: Our approach significantly accelerated case creation and improved diversity, although prioritizing maximum diversity compromised representativeness to some extent. While the optimized prompts are easily reusable, the process itself demands computer skills not all educators possess. To address this, we aim to share all created patients as open educational resources, empowering educators to create cases independently.
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At the department of electrical and electronic engineering of Fontys University of Applied Sciences we are defining a real-life learning context for our students, where the crossover with regional healthcare companies and institutes is maximized. Our innovative educational step is based on openly sharing electronic designs for health related measurement modalities as developed by our students. Because we develop relevant reference designs, the cross fertilization with society is large and so the learning cycle is short.
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Objective. Hospital in Motion is a multidimensional implementation project aiming to improve movement behavior during hospitalization. The purpose of this study was to investigate the effectiveness of Hospital in Motion on movement behavior. Methods. This prospective study used a pre-implementation and post-implementation design. Hospital in Motion was conducted at 4 wards of an academic hospital in the Netherlands. In each ward, multidisciplinary teams followed a 10-month step-by-step approach, including the development and implementation of a ward-specific action plan with multiple interventions to improve movement behavior. Inpatient movement behavior was assessed before the start of the project and 1 year later using a behavioral mapping method in which patients were observed between 9:00 am and 4:00 pm. The primary outcome was the percentage of time spent lying down. In addition, sitting and moving, immobility-related complications, length of stay, discharge destination home, discharge destination rehabilitation setting, mortality, and 30-day readmissions were investigated. Differences between pre-implementation and post-implementation conditions were analyzed using the chi-square test for dichotomized variables, the Mann Whitney test for non-normal distributed data, or independent samples t test for normally distributed data. Results. Patient observations demonstrated that the primary outcome, the time spent lying down, changed from 60.1% to 52.2%. For secondary outcomes, the time spent sitting increased from 31.6% to 38.3%, and discharges to a rehabilitation setting reduced from 6 (4.4%) to 1 (0.7%). No statistical differences were found in the other secondary outcome measures. Conclusion. The implementation of the multidimensional project Hospital in Motion was associated with patients who were hospitalized spending less time lying in bed and with a reduced number of discharges to a rehabilitation setting. Impact. Inpatient movement behavior can be influenced by multidimensional interventions. Programs implementing interventions that specifically focus on improving time spent moving, in addition to decreasing time spent lying, are recommended.
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Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult’s home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague
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