Clinical metagenomics.

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health

UNDERSTANDING THE MECHANISMS OF PROTOCOL IMPLEMENTATION FOR THE EARLY RECOGNITION AND TREATMENT OF PROBABLE SEPSIS

The purpose of this research was to construct a program theory that identifies and describes the salient contexts and mechanisms that can lead to successful implementation of a sepsis screening intervention. Successful implementation of evidence-based clinical practice is governed by human and environmental factors that can differ between local settings (Sales, Smith, Curran, & Kochevar, 2006). Failed or partial implementation of clinical practices is common (Davies, Walker, & Grimshaw, 2010) impacting negatively on patient safety, patient outcomes, and systemic inefficiencies. A theory-based approach to implementation provides a structure that can allow local teams the ability to move away from ad hoc or intuitive planning (Eccles, Grimshaw, Walker, Johnston, & Pitts, 2002). A customized Rapid Realist Review was used to identify the hypothetical implementation resources, context, and mechanisms that are salient in causing successful implementation of sepsis screening interventions. This process included a rapid review of the literature using a realist analytical lens and multi-phase refinement of the theoretical propositions with 15 physicians and nurses. The final program theory included multiple outcomes that must be reached in order to achieve successful implementation. Successful implementation was defined as achieving fidelity and sustainability of the intervention. Salient implementation resources and context were identified that trigger three middle-range promoting mechanisms and two inhibiting mechanisms. Within each of these mechanisms there are multiple lower level mechanisms operating that are salient for all clinicians and professional sub-groups. The final program theory hypothesized the salient features of a complex reality that can be applied or adapted for the implementation of a sepsis screening intervention in other local contexts or for the implementation of other similar small-scale interventions

Emergent approaches to the meta-analysis of multiple heterogeneous complex interventions.

BACKGROUND: Multiple interventions meta-analysis has been recommended in the methodological literature as a tool for evidence synthesis when a heterogeneous set of interventions is included in the same review—and, more recently, when a heterogeneous set of complex interventions is included. However, there is little guidance on the use of this method with complex interventions. This article suggests two approaches to model complexity and heterogeneity through this method. DISCUSSION: 'Clinically meaningful units' groups interventions by modality or similar theory of change, whereas 'components and dismantling' separates out interventions into combinations of components and either groups interventions by the combination of components they demonstrate or extracts effects for each identified component and, possibly, interactions between components. Future work in systematic review methodology should aim to understand how to develop taxonomies of components or theories of change that are internally relevant to the studies in these multiple interventions meta-analyses. SUMMARY: Despite little meaningful prior guidance to its use in this context, multiple interventions meta-analysis has the potential to be a useful tool for synthesising heterogeneous sets of complex interventions. Researchers should choose an approach in accordance with their specific aims in their systematic review

Diagnostic stewardship in infectious diseases:a continuum of antimicrobial stewardship in the fight against antimicrobial resistance

Antimicrobial resistance (AMR) has been exacerbated by the inappropriate use of diagnostics, leading to excessive prescription of antimicrobials, and is an imminent threat to global health. Diagnostic stewardship (DS) is an auxiliary to antimicrobial stewardship (AMS) and comprises ordering the right tests, for the right patient, at the right time. It also promotes the judicious use of rapid and novel molecular diagnostic tools to enable the initiation of proper antibiotic therapy, while avoiding excessive use of broad-spectrum antibiotics. Proper interpretation of test results is crucial to avoid overdiagnosis and excessive healthcare costs. Although many rapid diagnostic tools have been developed with a high diagnostic yield, they are often limited by accessibility, cost, and lack of knowledge regarding their use. Careful consideration of clinical signs and symptoms with knowledge of the local epidemiology are essential for DS. This enables appropriate interpretation of microbiological results. Multidisciplinary teams that include well trained professionals should cooperate to promote DS. Challenges and barriers to the implementation of DS are mostly caused by scarcity of resources and lack of trained personnel and, most importantly, lack of knowledge. The lack of resources is often due to absence of awareness of the impact that good medical microbiology diagnostic facilities and expertise can have on the proper use of antibiotics.</p

The use of data in resource limited settings to improve quality of care

Quality improvement is driven by benchmarking between and within institutions over time and the collaborative improvement efforts that stem from these comparisons. Benchmarking requires systematic collection and use of standardized data. Low- and middle-income countries (LMIC) have great potential for improvements in newborn outcomes but serious obstacles to data collection, analysis, and implementation of robust improvement methodologies exist. We review the importance of data collection, internationally recommended neonatal metrics, selected methods of data collection, and reporting. The transformation from data collection to data use is illustrated by several select data system examples from LMIC. Key features include aims and measures important to neonatal team members, co-development with local providers, immediate access to data for review, and multidisciplinary team involvement. The future of neonatal care, use of data, and the trajectory to reach global neonatal improvement targets in resource-limited settings will be dependent on initiatives led by LMIC clinicians and experts