Selected article for: "logistic regression and training validation"

Author: Hui Xu; Li Yan; Chun (Martin) Qiu; Bo Jiao; Yanyan Chen; Xi Tan; Zhuo Chen; Ling Ai; Yaru Xiao; Ailin Luo; Shusheng Li
Title: Analysis and Prediction of False Negative Results for SARS-CoV-2 Detection with Pharyngeal Swab Specimen in COVID-19 Patients: A Retrospective Study
  • Document date: 2020_3_30
  • ID: 9edp04ud_46
    Snippet: In order to implement the out-of-sample prediction, 1,324 patients were randomly divided into training (1,059 cases) and validation samples (265 cases Table 2) . "GGO" was associated with a shorter window for testing positive: "GGO" (effect, -0.26, 95% CI, -0.38--0.12; P < 0.001), suggesting the detection of this characteristic will on average reduce the length of the time window of testing positive by 26%. In comparison, the detection of "consol.....
    Document: In order to implement the out-of-sample prediction, 1,324 patients were randomly divided into training (1,059 cases) and validation samples (265 cases Table 2) . "GGO" was associated with a shorter window for testing positive: "GGO" (effect, -0.26, 95% CI, -0.38--0.12; P < 0.001), suggesting the detection of this characteristic will on average reduce the length of the time window of testing positive by 26%. In comparison, the detection of "consolidation" (effect, 0.44; 95% CI, 0.1-0.88; P = 0.01) will on average extend the length of the time window by 44%. The results are consistent with the logistic regression. We also found that chest distress was associated with a longer window as well (effect, 0.4; 95% CI, 0.07-0.83; P = 0.01). Finally, two blood test items, basophils (effect, 0.23; 95% CI, 0.12-0.35; P < 0.001) and eosinophils (effect, 0.41; 95% CI, 0.15-0.74; P < 0.001) were also linked to a longer time window for testing All rights reserved. No reuse allowed without permission.

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