Exploratory Data Analysis Recognizing Geometrical Patterns in Meta-analysis
Kimoto, K.; Yamakuchi, M.; Takenouchi, K.; Hashiguchi, T.
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BackgroundsStrange controversies have remained in thrombosis-related fields (travelers and COVID-19-related thrombosis), although travelers thrombosis is well-known even among non-professionals as "economy class syndrome." We hypothesized there might be something overlooked behind those strange situations. MethodsSince ordinary review methods (e.g., systematic review or meta-analysis) had already been conducted, we focused on reviewing a "previously published" "chart." Also, we developed a novel "review method" for the meta-regression analysis result. We applied those to some previously published and well-known data. ResultsWe newly found an approximately 28 days cycle of thrombosis onset over several weeks after travel in a figure. Also, we found an eighteen-day cycle of thrombosis onset in another chart. In COVID-19 cardiovascular biomarker studies, we newly extracted subgroup patterns in a scatterplot (Troponin T and NT-proBNP) that applied simple linear regression analysis. Also, these subgroups had already appeared in the cardiomyopathy study. ConclusionsTravelers thrombosis sometimes occurs over two months after leaving the risky in-flight environment. This phenomenon has been explained that the thrombus is formed in a cabin but dislodged after. However, from the cyclic patterns, explaining that the "high-risk period of thrombosis with Oral Contraceptive (OC) use initiation" coincided with "travel" is more reasonable (e.g., honeymoon and OC initiation). Regarding risk-benefit balance, it is conceivable that "spreading the risk" by starting the dosing away from the travel period is essential to ensure safer use because the in-flight environment may have a non-zero effect, and optimal care by a primary care physician (prescriber) is not available during the travel. In COVID-19, there seems to be a complex scatterplot structure that is unsuitable for usually used simple linear fitting. In a literature review, a pattern on a chart should be given more paying attention.
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