Group A Streptococcus (GAS) causes superficial and invasive infections and immune mediated post-infectious sequalae (including acute rheumatic fever/rheumatic heart disease). Acute rheumatic fever (ARF) and rheumatic heart disease (RHD) are important determinants of global cardiovascular morbidity and mortality. ARF is a multiorgan inflammatory disease that is triggered by GAS infection that activates the innate immune system. In susceptible hosts the response against GAS elicits autoimmune reactions targeting the heart, joints, brain, skin, and subcutaneous tissue. Repeated episodes of ARF—undetected, subclinical, or diagnosed—may progressively lead to RHD, unless prevented by periodic administration of penicillin. The recently modified Duckett Jones criteria with stratification by population risk remains relevant for the diagnosis of ARF and includes subclinical carditis detected by echocardiography as a major criterion. Chronic RHD is defined by valve regurgitation and/or stenosis that presents with complications such as arrhythmias, systemic embolism, infective endocarditis, pulmonary hypertension, heart failure, and death. RHD predominantly affects children, adolescents, and young adults in LMICs. National programs with compulsory notification of ARF/RHD are needed to highlight the role of GAS in the global burden of cardiovascular disease and to allow prioritisation of these diseases aimed at reducing health inequalities and to achieve universal health coverage.
Background
Healthcare systems in low-resource settings need simple, low-cost interventions to improve services and address gaps in care. Though routine data provide opportunities to guide these efforts, frontline providers are rarely engaged in analyzing them for facility-level decision making. The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages providers in use of facility-level data to promote systems-level thinking and quality improvement (QI) efforts within multi-step care cascades. SAIA was originally developed to address HIV care in resource-limited settings but has since been adapted to a variety of clinical care systems including cervical cancer screening, mental health treatment, and hypertension management, among others; and across a variety of settings in sub-Saharan Africa and the USA. We aimed to extend the growing body of SAIA research by defining the core elements of SAIA using established specification approaches and thus improve reproducibility, guide future adaptations, and lay the groundwork to define its mechanisms of action.
Methods
Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA-researchers, implementing agents and stakeholders using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor’s recommendations for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects.
Results
Based on this review and clarification of the operational definitions of the components of the SAIA, the four components of SAIA were mapped to 13 ERIC strategies. SAIA strategy meetings encompassed external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to three ERIC strategies: facilitating relay of clinical data to providers, use of audit and feedback of routine data with healthcare teams, and modeling and simulation of change. Process mapping matched to local needs assessment, local consensus discussions and assessment of readiness and identification of barriers and facilitators. Finally, continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change, and purposefully re-examining the implementation process.
Conclusions
Specifying the components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings.
This paper presents a case study of implementing a trauma registry in Mozambique, a low-income country with limited current trauma surveillance. An outline of the importance of trauma registries is presented followed by an evidence-based approach to building a sustainable and ethical partnership with local stakeholders.
Background
Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics.
Methods
We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case–control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses.
Results
Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls.
Conclusions
These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity.
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