Development of a Tailored, Complex Intervention for Clinical Reflection and Communication about Suspected Urinary Tract Infections in Nursing Home Residents

Background: Inappropriate antibiotic treatments for urinary tract infections (UTIs) in nursing homes cause the development of resistant bacteria. Nonspecific symptoms and asymptomatic bacteriuria are drivers of overtreatment. Nursing home staff provide general practice with information about ailing residents; therefore, their knowledge and communication skills influence prescribing. This paper describes the development of a tailored, complex intervention for a cluster-randomised trial that targets the knowledge of UTI and communication skills in nursing home staff to reduce antibiotic prescriptions. Methods: A dialogue tool was drafted, drawing on participatory observations in nursing homes, interviews with stakeholders, and a survey in general practice. The tool was tailored through a five-phase process that included stakeholders. Finally, the tool and a case-based educational session were tested in a pilot study. Results: The main barriers were that complex patients were evaluated by healthcare staff with limited knowledge about disease and clinical reasoning; findings reported to general practice were insignificant and included vague descriptions; there was evidence of previous opinion bias; nonspecific symptoms were interpreted as UTI; intuitive reasoning led to the inappropriate suspicion of UTI. Conclusion: Sustainable change in antibiotic-prescribing behaviour in nursing homes requires a change in nursing home staff’s beliefs about and management of UTIs

Adherence to subcutaneous interferon beta-1a treatment using an electronic injection device:a prospective open-label Scandinavian noninterventional study (the ScanSmart study)

Background: Disease modifying drugs help control the course of relapsing remitting multiple sclerosis (RRMS); however, good adherence is needed for long-term outcomes. Objective: To evaluate patient adherence to treatment with subcutaneous interferon beta-1a using RebiSmart® and assess injection-site reactions and treatment satisfaction. Methods: This prospective, single-arm, open-label, noninterventional multicenter Phase IV trial included disease modifying drug-experienced mobile patients with RRMS. Adherence was measured over 12 weeks. Items 13–23, 35, 37, and 38 of the Multiple Sclerosis Treatment Concerns Questionnaire (injection-site reactions and treatment satisfaction) were recorded at 12 weeks. Results: Sixty patients were recruited (mean age 43.7 [±SD 7.9] years; 83% female; mean years since multiple sclerosis diagnosis 6.7 [SD 4.5]). Adherence data were obtained in 54 patients only due to technical problems with six devices. Over 12 weeks, 89% (n=48) of patients had ≥90% adherence to treatment. Most patients experienced mild influenza-like symptoms and injection-site reactions, and global side effects were minimal. Most patients (78%) rated the convenience as the most important aspect of the device, and most experienced no or mild pain. Conclusion: RRMS patients treated with subcutaneous interferon beta-1a, administered with RebiSmart, demonstrated generally good adherence, and the treatment was generally well tolerated

Comparison of two self-reported measures of physical work demands in hospital personnel: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Low back pain (LBP) is a frequent health complaint among health care personnel. Several work tasks and working postures are associated with an increased risk of LBP. The aim of this study was to compare two self-reported measures of physical demands and their association with LBP (the daily number of patient handling tasks and Hollmann's physical load index).</p> <p>Methods</p> <p>A questionnaire was distributed to 535 hospital employees in a psychiatric and an orthopedic ward in a Danish hospital. Of these 411 (77%) filled in and returned the questionnaire. Only the 373 respondents who had non-missing values on both measures of physical demands were included in the analyses. The distribution of physical demands in different job groups and wards are presented, variance analysis models are employed, and logistic regression analysis is used to analyze the association between measures of physical demands and LBP.</p> <p>Results</p> <p>In combination, hospital ward and job category explained 56.6% and 23.3% of the variance in the self-reported physical demands measured as the daily number of patient handling tasks and as the score on the physical load index, respectively. When comparing the 6% with the highest exposure the prevalence odds ratio (POR) for LBP was 5.38 (95% CI 2.03–14.29) in the group performing more than 10 patient handling tasks per day and 2.29 (95% CI 0.93–5.66) in the group with the highest score on the physical load index.</p> <p>Conclusion</p> <p>In specialized hospital wards the daily number of patient handling tasks seems to be a more feasible measure of exposure when assessing the risk of LBP compared to more advanced measures of physical load on the lower lumbar spine.</p

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition