Selected article for: "sample size and study sample size"
Author: Cong-Ying Song; Jia Xu; Jian-Qin He; Yuan-Qiang Lu
Title: COVID-19 early warning score: a multi-parameter screening tool to identify highly suspected patients
  • Document date: 2020_3_8
    • ID: fcvstps9_43
    Snippet: There were also many shortcomings in our study that should be considered. Firstly, it was a retrospective study, which might contain selection bias, although we tried to avoid the bias through sorting patients by "Z-A" based on Chinese first name and strictly abide the inclusion and exclusion criteria. In addition, because of the incomplete of potentially valuable information, such as smoking history and basic diseases, we cannot conduct a compre.....
    Document: There were also many shortcomings in our study that should be considered. Firstly, it was a retrospective study, which might contain selection bias, although we tried to avoid the bias through sorting patients by "Z-A" based on Chinese first name and strictly abide the inclusion and exclusion criteria. In addition, because of the incomplete of potentially valuable information, such as smoking history and basic diseases, we cannot conduct a comprehensive analysis of these factors currently. Besides of that, additional multi-center, multi-ethnic and prospective studies are expected to revised our diagnostic model and COVID-19 EWS, and we also plan to implement a multi-center study with a larger sample size to further validate and optimize the model. More over, it is hoped that better statistical algorithms will make the diagnostic model more practical.

    Search related documents:
    Co phrase search for related documents
    • basic disease and diagnostic model: 1
    • basic disease and EWS diagnostic model: 1
    • basic disease and retrospective study: 1, 2, 3, 4, 5
    • basic disease and sample size: 1, 2, 3
    • basic disease and selection bias: 1
    • bias avoid and retrospective study: 1
    • bias avoid and sample size: 1, 2, 3
    • bias avoid and selection bias: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16