Clinician-targeted interventions to reduce antibiotic prescribing for acute respiratory infections in primary care:An overview of systematic reviews

This is the protocol for a review and there is no abstract. The objectives are as follows: To systematically review the literature and appraise the existing evidence from systematic reviews regarding the effects of interventions, aimed at changing clinician behaviour, to reduce antibiotic prescribing for ARIs in primary care

Increasing access to consumer health organisations among patients with chronic disease - a randomised trial of a print-based intervention

To assess whether a print-based intervention led to increased contact with consumer health organisations (CHOs) by general practice patients with chronic disease. CHOs can enhance people's capacity to manage chronic illness by providing information, education and psychosocial support. However, these organisations appear to be grossly under-utilised by patients and clinicians. A total of 276 patients completed a computer-assisted telephone interview before randomisation to an intervention (n = 141) or control (n = 135) group. The intervention consisted of mailed printed materials designed to encourage contact with a CHO relevant to the patient's main diagnosed chronic condition. Follow-up interviews were conducted 4 and 12 months later. Patients with conditions other than diabetes who received the intervention were twice as likely as those in the control group to contact a consumer health organisation during the 12-month study period: 41% versus 21% (P < 0.001). No such effect was found for diabetes patients, probably because of pre-existing high levels of contact with diabetes organisations. The intervention package received strong patient endorsement. Low-intensity interventions may be effective in improving access to CHOs for patients with chronic disease

Clinician-targeted interventions to influence antibiotic prescribing behaviour for acute respiratory infections in primary care: An overview of systematic reviews

Background: Antibiotic resistance is a worldwide health threat. Interventions that reduce antibiotic prescribing by clinicians are expected to reduce antibiotic resistance. Disparate interventions to change antibiotic prescribing behaviour for acute respiratory infections (ARIs) have been trialled and meta-analysed, but not yet synthesised in an overview. This overview synthesises evidence from systematic reviews, rather than individual trials. Objectives: To systematically review the existing evidence from systematic reviews on the effects of interventions aimed at influencing clinician antibiotic prescribing behaviour for ARIs in primary care. Methods: We searched the Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (DARE), MEDLINE, Embase, CINAHL, PsycINFO, and Science Citation Index to June 2016. We also searched the reference lists of all included reviews. We ran a pre-publication search in May 2017 and placed additional studies in 'awaiting classification'. We included both Cochrane and non-Cochrane reviews of randomised controlled trials evaluating the effect of any clinician-focussed intervention on antibiotic prescribing behaviour in primary care. Two overview authors independently extracted data and assessed the methodological quality of included reviews using the ROBIS tool, with disagreements reached by consensus or by discussion with a third overview author. We used the GRADE system to assess the quality of evidence in included reviews. The results are presented as a narrative overview. Main results: We included eight reviews in this overview: five Cochrane Reviews (33 included trials) and three non-Cochrane reviews (11 included trials). Three reviews (all Cochrane Reviews) scored low risk across all the ROBIS domains in Phase 2 and low risk of bias overall. The remaining five reviews scored high risk on Domain 4 of Phase 2 because the 'Risk of bias' assessment had not been specifically considered and discussed in the review Results and Conclusions. The trials included in the reviews varied in both size and risk of bias. Interventions were compared to usual care. Moderate-quality evidence indicated that C-reactive protein (CRP) point-of-care testing (risk ratio (RR) 0.78, 95% confidence interval (CI) 0.66 to 0.92, 3284 participants, 6 trials), shared decision making (odds ratio (OR) 0.44, 95% CI 0.26 to 0.75, 3274 participants, 3 trials; RR 0.64, 95% CI 0.49 to 0.84, 4623 participants, 2 trials; risk difference -18.44, 95% CI -27.24 to -9.65, 481,807 participants, 4 trials), and procalcitonin-guided management (adjusted OR 0.10, 95% CI 0.07 to 0.14, 1008 participants, 2 trials) probably reduce antibiotic prescribing in general practice. We found moderate-quality evidence that procalcitonin-guided management probably reduces antibiotic prescribing in emergency departments (adjusted OR 0.34, 95% CI 0.28 to 0.43, 2605 participants, 7 trials). The overall effect of these interventions was small (few achieving greater than 50% reduction in antibiotic prescribing, most about a quarter or less), but likely to be clinically important. Compared to usual care, shared decision making probably makes little or no difference to reconsultation for the same illness (RR 0.87, 95% CI 0.74 to 1.03, 1860 participants, 4 trials, moderate-quality evidence), and may make little or no difference to patient satisfaction (RR 0.86, 95% CI 0.57 to 1.30, 1110 participants, 2 trials, low-quality evidence). Similarly, CRP testing probably has little or no effect on patient satisfaction (RR 0.79, 95% CI 0.57 to 1.08, 689 participants, 2 trials, moderate-quality evidence) or reconsultation (RR 1.08, 95% CI 0.93 to 1.27, 5132 participants, 4 trials, moderate-quality evidence). Procalcitonin-guided management probably results in little or no difference in treatment failure in general practice compared to normal care (adjusted OR 0.95, 95% CI 0.73 to 1.24, 1008 participants, 2 trials, moderate-quality evidence), however it probably reduces treatment failure in the emergency department compared to usual care (adjusted OR 0.76, 95% CI 0.61 to 0.95, 2605 participants, 7 trials, moderate-quality evidence). The quality of evidence for interventions focused on clinician educational materials and decision support in reducing antibiotic prescribing in general practice was either low or very low (no pooled result reported) and trial results were highly heterogeneous, therefore we were unable draw conclusions about the effects of these interventions. The use of rapid viral diagnostics in emergency departments may have little or no effect on antibiotic prescribing (RR 0.86, 95% CI 0.61 to 1.22, 891 participants, 3 trials, low-quality evidence) and may result in little to no difference in reconsultation (RR 0.86, 95% CI 0.59 to 1.25, 200 participants, 1 trial, low-quality evidence). None of the trials in the included reviews reported on management costs for the treatment of an ARI or any associated complications. Authors' conclusions: We found evidence that CRP testing, shared decision making, and procalcitonin-guided management reduce antibiotic prescribing for patients with ARIs in primary care. These interventions may therefore reduce overall antibiotic consumption and consequently antibiotic resistance. There do not appear to be negative effects of these interventions on the outcomes of patient satisfaction and reconsultation, although there was limited measurement of these outcomes in the trials. This should be rectified in future trials. We could gather no information about the costs of management, and this along with the paucity of measurements meant that it was difficult to weigh the benefits and costs of implementing these interventions in practice. Most of this research was undertaken in high-income countries, and it may not generalise to other settings. The quality of evidence for the interventions of educational materials and tools for patients and clinicians was either low or very low, which prevented us from drawing any conclusions. High-quality trials are needed to further investigate these interventions. </p

Reducing inappropriate polypharmacy: the process of deprescribing

Inappropriate polypharmacy, especially in older people, imposes a substantial burden of adverse drug events, ill health, disability, hospitalization, and even death. The single most important predictor of inappropriate prescribing and risk of adverse drug events in older patients is the number of prescribed drugs. Deprescribing is the process of tapering or stopping drugs, aimed at minimizing polypharmacy and improving patient outcomes. Evidence of efficacy for deprescribing is emerging from randomized trials and observational studies. A deprescribing protocol is proposed comprising 5 steps: (1) ascertain all drugs the patient is currently taking and the reasons for each one; (2) consider overall risk of drug-induced harm in individual patients in determining the required intensity of deprescribing intervention; (3) assess each drug in regard to its current or future benefit potential compared with current or future harm or burden potential; (4) prioritize drugs for discontinuation that have the lowest benefit-harm ratio and lowest likelihood of adverse withdrawal reactions or disease rebound syndromes; and (5) implement a discontinuation regimen and monitor patients closely for improvement in outcomes or onset of adverse effects. Whereas patient and prescriber barriers to deprescribing exist, resources and strategies are available that facilitate deliberate yet judicious deprescribing and deserve wider application

Mega-analysis of association between obesity and cortical morphology in bipolar disorders:ENIGMA study in 2832 participants

Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. Methods: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. Results: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. Conclusions: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.</p

Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data