How-To Create an Orthopaedic Systematic Review: A Step-by-step Guide Part II: Study Execution.

Systematic reviews are the apex of the evidence-based pyramid, representing the strongest form of evidence synthesizing results from multiple primary studies. In particular, a quantitative systematic review, or meta-analysis, pools results from multiple studies to help answer a respective research question. The aim of this review is to serve as a guide on how to: (1) design, (2) execute, and (3) publish an orthopaedic arthroplasty systematic review. In Part II, we focus on methods to assess data quality through the Cochrane Risk of Bias, Methodological Index for Nonrandomized Studies criteria, or Newcastle-Ottawa scale; enumerate various methods for appropriate data interpretation and analysis; and summarize how to convert respective findings to a publishable manuscript (providing a previously published example). Use of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines is recommended and standard in all scientific literature, including that of orthopedic surgery. Pooled analyses with forest plots and associated odds ratios and 95% confidence intervals are common ways to present data. When converting to a manuscript, it is important to consider and discuss the inherent limitations of systematic reviews, including their inclusion and/or exclusion criteria and overall quality, which can be limited based on the quality of individual studies (eg, publication bias, heterogeneity, search/selection bias). We hope our papers will serve as starting points for those interested in performing an orthopaedic arthroplasty systematic review.

How-To Create an Orthopaedic Systematic Review: A Step-by-Step Guide Part I: Study Design.

Systematic reviews are conducted through a consistent and reproducible method to search, appraise, and summarize information. Within the evidence-based pyramid, systematic reviews can be at the apex when incorporating high-quality studies, presenting the strongest form of evidence given their synthesis of results from multiple primary studies to level IV evidence, depending on the studies they incorporate. When combined and supplemented with a meta-analysis using statistical methods to pool the results of 3 or more studies, systematic reviews are powerful tools to help answer research questions. The aim of this review is to serve as a guide on how to: (1) design; (2) execute; and (3) publish an orthopaedic arthroplasty systematic review and meta-analysis. In Part I, we discuss how to develop an appropriate research question as well as source and screen databases. To date, commonly used databases to source studies include PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science. Although not all-encompassing, this paper serves as a starting point for those interested in performing and/or critically reviewing lower extremity arthroplasty systematic reviews and meta-analyses.

How-To Create an Orthopaedic Systematic Review: A Step-by-Step Guide. Part III: Executing a Meta-Analysis.

At the top of the evidence-based pyramid, systematic reviews stand out as the most powerful, synthesizing findings from numerous primary studies. Specifically, a quantitative systematic review, known as a meta-analysis, combines results from various studies to address a specific research question. This review serves as a guide on how to: (1) design; (2) perform; and (3) publish an orthopedic arthroplasty systematic review. In Part III, we focus on how to design and perform a meta-analysis. We delineate the advantages and disadvantages of meta-analyses compared to systematic reviews, acknowledging their potential challenges due to time constraints and the complexities posed by study heterogeneity and data availability. Despite these obstacles, a well-executed meta-analysis contributes precision and heightened statistical power, standing at the apex of the evidence-based pyramid. The design of a meta-analysis closely mirrors that of a systematic review, but necessitates the inclusion of effect sizes, variability measures, sample sizes, outcome measures, and overall study characteristics. Effective data presentation involves the use of forest plots, along with analyses for heterogeneities and subgroups. Widely-used software tools are common in this domain, and there is a growing trend toward incorporating artificial intelligence software. Ultimately, the intention is for these papers to act as foundational resources for individuals interested in conducting systematic reviews and meta-analyses in the context of orthopaedic arthroplasty, where applicable.

Clinical and Administrative Databases Used in Lower Extremity Arthroplasty Research.

BACKGROUND: The use of national databases in lower extremity arthroplasty research has grown rapidly in recent years. We aimed to better characterize available databases by: (1) quantifying the number of these studies in the highest impact arthroplasty journals; (2) comparing respective sample sizes; and (3) contrasting their measured variables/outcomes. METHODS: An extensive literature search was conducted to identify all database studies in the top 12 highest impact factor journals that published arthroplasty research between January 1, 2018 and December 31, 2019. A total of 5070 publications were identified. These studies were sorted by both database utilized and journal published. Tables were constructed to compare/contrast databases by metrics and measured outcome parameters including coding, patient sample size, preoperative comorbidities, postoperative complications, and limitations/barriers to their use. RESULTS: Four hundred twenty-six database studies (8.4%, range 0.4%-29.7% per journal) were identified, of which 139 were from non-English-speaking arthroplasty databases. Among English-speaking arthroplasty databases, the 5 most common sources were National Surgical Quality Improvement Project (n = 72), Medicare (n = 62, 39 from Medicare Claims and 23 from PearlDiver), Nationwide Inpatient Sample (n = 35), PearlDiver non-Medicare private insurance (n = 18), and Statewide Planning and Research Cooperative System (n = 18). Metrics, outcome parameters, and features of commonly used registries were reviewed. CONCLUSION: Database studies constitute an important part of arthroplasty-specific orthopedic research. Their use will continue to grow in the future, and it would be beneficial for clinicians/researchers to be aware of and familiarize themselves with their features to understand which are most appropriate for their work.