Volume 45 Issue 9
Sep.  2024
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Xing LIU, Weixian LI, Xiang ZHU, Mengxing LIU, Na LI, Jiawei XIA, Le ZHANG, Yan WU, Shenghao LI. Construction of a Nomogram Model of Tsutsugamushi Disease Complicated with Sepsis Based on Lasso Regression[J]. Journal of Kunming Medical University, 2024, 45(9): 35-41. doi: 10.12259/j.issn.2095-610X.S20240906
Citation: Xing LIU, Weixian LI, Xiang ZHU, Mengxing LIU, Na LI, Jiawei XIA, Le ZHANG, Yan WU, Shenghao LI. Construction of a Nomogram Model of Tsutsugamushi Disease Complicated with Sepsis Based on Lasso Regression[J]. Journal of Kunming Medical University, 2024, 45(9): 35-41. doi: 10.12259/j.issn.2095-610X.S20240906

Construction of a Nomogram Model of Tsutsugamushi Disease Complicated with Sepsis Based on Lasso Regression

doi: 10.12259/j.issn.2095-610X.S20240906
  • Received Date: 2024-03-22
    Available Online: 2024-06-04
  • Publish Date: 2024-09-25
  •   Objective  To establish a nomogram model for tsutsugamushi disease complicated with sepsis based on Lasso regression, so as to provide a reference for the diagnosis and treatment of tsutsugamushi disease complicated with sepsis.   Methods  We selected patients with scrub typhus patients admitted to Kunming Third People’ s Hospital from June 2012 to December 2023 as the research subjects (n = 235), with scrub typhus patients patients with sepsis as the experimental group (n = 138) and scrub typhus patients patients without sepsis as the control group (n = 97), Lasso regression was used to screen the influencing factors of scrub typhus combined with sepsis, and a nomogram model was constructed through logistic regression. The effectiveness of the model was evaluated using receiver operating characteristic(ROC) curves and calibration curves, and clinical utility analysis was performed using decision curve analysis(DCA).   Results  The results of multivariate analysis through logistic regression showed: that age (OR = 1.039, 95%CI: 1.017~1.061), PLT (OR = 0.995, 95%CI: 0.990~1.000), UA (OR = 1.004, 95%CI: 1.001~1.008) and IgA (OR = 0.680, 95%CI: 0.472~0.979) were independent influencing factors of scrub typhus combined with sepsis. The area under the ROC curve (AUC) was 0.721 (95%CI: 0.656~0.786, P < 0.001), the sensitivity of the model was 69.1%, and the specificity was 63.1%. The calibration curve indicates that the model had good consistency, and the DCA indicated that the model had a high net benefit value.   Conclusion  Patients with scrub typhus are associated with increased age and UA levels and decreased PLT and IgA levels, and have a higher risk of secondary sepsis.
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