Low-calorie sweeteners and health outcomes: an evaluation of rapid versus traditional evidence mapping.

OBJECTIVE: Scientific evidence related to environmental exposures continues to mount. Tools such as evidence mapping support decision making, but can be resource- and time-intensive. We explored "rapid evidence mapping" to efficiently map scientific evidence using rigorous and transparent methodologies. We undertook a proof-of-concept case study on the topic of low-calorie sweeteners. Our intent was to conduct a traditional evidence map based on the same evidence base from a prior rapid evidence map case study to compare approaches, findings, and conclusions. We searched the literature, screened full text of studies, manually tagged and categorized articles, and created visualizations to map the evidence. RESULTS: We conducted full-text screening of studies from the prior rapid evidence map and identified 255 relevant studies. Our findings corroborated those of the rapid evidence map, identifying most studies as short-term conducted in healthy individuals studying outcomes of appetite, energy sensing and body weight. We identified gaps in research areas related to outcomes of appetite and dietary intake, particularly in study populations with diabetes. Our findings illustrate the promise of rapid evidence mapping as a rigorous approach that can summarize scientific evidence, identify knowledge gaps, and identify areas for a future systematic review in a time-efficient manner.

Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map.

Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public. Methods: We developed a protocol that includes a study goal, study questions, a PECO statement, and a process for screening literature by combining semi-automated machine learning with the expertise of our review team. We applied this protocol to reports within the COVID-19 Open Research Dataset (CORD-19) that were published in early 2020. SWIFT-Active Screener was used to prioritize records according to pre-defined inclusion criteria. Relevant studies were categorized by risk and protective status; susceptibility category (Behavioral, Physiological, Demographic, and Environmental); and affected sub-populations. Using tagged studies, we created an rEM for COVID-19 susceptibility that reveals: (1) current lines of evidence; (2) knowledge gaps; and (3) areas that may benefit from systematic review. Results: We imported 4,330 titles and abstracts from CORD-19. After screening 3,521 of these to achieve 99% estimated recall, 217 relevant studies were identified. Most included studies concerned the impact of underlying comorbidities (Physiological); age and gender (Demographic); and social factors (Environmental) on COVID-19 outcomes. Among the relevant studies, older males with comorbidities were commonly reported to have the poorest outcomes. We noted a paucity of COVID-19 studies among children and susceptible sub-groups, including pregnant women, racial minorities, refugees/migrants, and healthcare workers, with few studies examining protective factors. Conclusion: Using rEM analysis, we synthesized the recent body of evidence related to COVID-19 risk and protective factors. The results provide a comprehensive tool for rapidly elucidating COVID-19 susceptibility patterns and identifying resource-rich/resource-poor areas of research that may benefit from future investigation as the pandemic evolves.

Low-calorie sweeteners and health outcomes: A demonstration of rapid evidence mapping (rEM).

BACKGROUND: "Evidence Mapping" is an emerging tool that is increasingly being used to systematically identify, review, organize, quantify, and summarize the literature. It can be used as an effective method for identifying well-studied topic areas relevant to a broad research question along with any important literature gaps. However, because the procedure can be significantly resource-intensive, approaches that can increase the speed and reproducibility of evidence mapping are in great demand. METHODS: We propose an alternative process called "rapid Evidence Mapping" (rEM) to map the scientific evidence in a time-efficient manner, while still utilizing rigorous, transparent and explicit methodological approaches. To illustrate its application, we have conducted a proof-of-concept case study on the topic of low-calorie sweeteners (LCS) with respect to human dietary exposures and health outcomes. During this process, we developed and made publicly available our study protocol, established a PECO (Participants, Exposure, Comparator, and Outcomes) statement, searched the literature, screened titles and abstracts to identify potentially relevant studies, and applied semi-automated machine learning approaches to tag and categorize the included articles. We created various visualizations including bubble plots and frequency tables to map the evidence and research gaps according to comparison type, population baseline health status, outcome group, and study sample size. We compared our results with a traditional evidence mapping of the same topic published in 2016 (Wang et al., 2016). RESULTS: We conducted an rEM of LCS, for which we identified 8122 records from a PubMed search (January 1, 1946-May 1, 2014) and then utilized machine learning (SWIFT-Active Screener) to prioritize relevant records. After screening 2267 (28%) of the total set of titles and abstracts to achieve 95% estimated recall, we ultimately included 297 relevant studies. Overall, our findings corroborated those of Wang et al. (2016) and identified that most studies were acute or short-term in healthy individuals, and studied the outcomes of appetite, energy sensing and body weight. We also identified a lack of studies assessing appetite and dietary intake related outcomes in people with diabetes. The rEM approach required approximately 100 person-hours conducted over 7 calendar months. CONCLUSION: Rapid Evidence Mapping is an expeditious approach based on rigorous methodology that can be used to quickly summarize the available body of evidence relevant to a research question, identify gaps in the literature to inform future research, and contextualize the design of a systematic review within the broader scientific literature, significantly reducing human effort while yielding results comparable to those from traditional methods. The potential time savings of this approach in comparison to the traditional evidence mapping process make it a potentially powerful tool for rapidly translating knowledge to inform science-based decision-making.