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Multiple 'overviews of reviews' conducted on the same topic ("overlapping overviews") represent a waste of research resources and can confuse clinicians making decisions amongst competing treatments. We aimed to assess the frequency and characteristics of overlapping overviews. MEDLINE, Epistemonikos and Cochrane Database of Systematic Reviews were searched for overviews that: synthesized reviews of health interventions and conducted systematic searches. Overlap was defined as: duplication of PICO eligibility criteria, and not reported as an update nor a replication. We categorized overview topics according to 22 WHO ICD‐10 medical classifications, overviews as broad or narrow in scope, and overlap as identical, nearly identical, partial, or subsumed. Subsummation was defined as when broad overviews subsumed the populations, interventions and at least one outcome of another overview. Of 541 overviews included, 169 (31%) overlapped across similar PICO, fell within 13 WHO ICD‐10 medical classifications, and 62 topics. 148/169 (88%) overlapping overviews were broad in scope. Fifteen overviews were classified as having nearly identical overlap (9%); 123 partial overlap (73%), and 31 subsumed (18%) others. One third of overviews overlapped in content and a majority covered broad topic areas. A multiplicity of overviews on the same topic adds to the ongoing waste of research resources, time, and effort across medical disciplines. Authors of overviews can use this study and the sample of overviews to identify gaps in the evidence for future analysis, and topics that are already studied, which do not need to be duplicated. [ABSTRACT FROM AUTHOR]

Background: Our objective was to identify combination tests used to diagnose chronic periprosthetic joint infection (PJI) and develop a stepwise decision-making tool to facilitate diagnosis.Methods: We conducted a systematic review of existing combinations of serum, synovial, and tissue-based tests for diagnosing chronic PJI after hip or knee replacement. This work is an extension of our systematic review of single tests, from which we chose eligible studies that also described the diagnostic performance of combination tests.Results: Thirty-seven eligible articles described the performance of 56 combination tests, of which 8 combinations had at least 2 studies informing both sensitivity and specificity. We also identified 5 types of combination tests: (1) a type-I Boolean combination, which uses Boolean logic (AND, OR) and usually increases specificity at the cost of sensitivity; (2) a type-II Boolean combination, which usually increases sensitivity at the cost of specificity; (3) a triage-conditional rule, in which the value of 1 test serves to triage the use of another test; (4) an arithmetic operation on the values of 2 tests; and (5) a model-based prediction rule based on a fitted model applied to biomarker values.Conclusions: Clinicians can initiate their diagnostic process with a type-II Boolean combination of serum C-reactive protein (CRP) and interleukin-6 (IL-6). False negatives of the combination can be minimized when the threshold is chosen to reach 90% to 95% sensitivity for each test. Once a joint infection is suspected on the basis of serum testing, joint aspiration should be performed. If joint aspiration yields a wet tap, a leukocyte esterase (LER) strip is highly recommended for point-of-care testing, with a reading of ++ or greater indicating PJI; a reading below ++ should be followed by one of the laboratory-based synovial tests. If joint aspiration yields a dry tap, clinicians should rely on preoperative tissue culture and histological analysis for diagnosis. Combinations based on triage-conditional, arithmetic, and model-based prediction rules require further research.Level Of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Context: The process of knowledge translation (KT) in health research depends on the activities of a wide range of actors, including health professionals, researchers, the public, policymakers, and research funders. Little is known, however, about health research funding agencies' support and promotion of KT. Our team asked thirty-three agencies from Australia, Canada, France, the Netherlands, Scandinavia, the United Kingdom, and the United States about their role in promoting the results of the research they fund. Methods: Semistructured interviews were conducted with a sample of key informants from applied health funding agencies identified by the investigators. The interviews were supplemented with information from the agencies' websites. The final coding was derived from an iterative thematic analysis. Findings: There was a lack of clarity between agencies as to what is meant by KT and how it is operationalized. Agencies also varied in their degree of engagement in this process. The agencies' abilities to create a pull for research findings; to engage in linkage and exchange between agencies, researchers, and decision makers; and to push results to various audiences differed as well. Finally, the evaluation of the effectiveness of KT strategies remains a methodological challenge. Conclusions: Funding agencies need to think about both their conceptual framework and their operational definition of KT, so that it is clear what is and what is not considered to be KT, and adjust their funding opportunities and activities accordingly. While we have cataloged the range of knowledge translation activities conducted across these agencies, little is known about their effectiveness and so a greater emphasis on evaluation is needed. It would appear that “best practice” for funding agencies is an elusive concept depending on the particular agency's size, context, mandate, financial considerations, and governance structure. [ABSTRACT FROM AUTHOR]