Volume 22 Issue 6
Jun.  2024
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Article Navigation >  Chinese Journal of General Practice  > 2024  >  22(6): 1028-1032
ZENG Ge, LONG Jun, JIANG Junjie, CAI Hui, LI Qiaofeng. Predictive value of micro-blood flow imaging in the response of patients with rheumatoid arthritis to lguratimod therapy[J]. Chinese Journal of General Practice, 2024, 22(6): 1028-1032. doi: 10.16766/j.cnki.issn.1674-4152.003559
Citation: ZENG Ge, LONG Jun, JIANG Junjie, CAI Hui, LI Qiaofeng. Predictive value of micro-blood flow imaging in the response of patients with rheumatoid arthritis to lguratimod therapy[J]. Chinese Journal of General Practice, 2024, 22(6): 1028-1032. doi: 10.16766/j.cnki.issn.1674-4152.003559
shu

Predictive value of micro-blood flow imaging in the response of patients with rheumatoid arthritis to lguratimod therapy

doi: 10.16766/j.cnki.issn.1674-4152.003559

  • Department of Special Inspection Department, Huzhou Third Municipal Hospital, Wenzhou, Zhejiang 313000, China

Funds:

 2021KY1098

  • Received Date: 2023-12-15
    Available Online: 2024-07-22
    Abstract
  •   Objective  The response of patients with rheumatoid arthritis (RA) to Elamod therapy is significantly related to their prognosis. It is of great significance to identify patients who do not respond to treatment with Elamod at an early stage and adjust the treatment plan in time. Based on this, this study applied micro-blood flow imaging technology to the patients with RA treated by Elamod, and discussed its predictive value for the curative effect of Erasmus in the treatment of RA patients.  Methods  A total of 139 patients with RA who received Elamod in the Huzhou Third Municipal Hospital from January 2022 to January 2023 were divided into response group (n=88) and non-response group (n=51) according to their treatment response. The data of micro-blood flow imaging before treatment were collected, and the factors influencing non-response to RA Elamod treatment were screened by multivariate logistic regression, and a prediction model was constructed to analyze the predictive value of the model.  Results  Multivariate logistic regression analysis showed that high arterial resistance index (OR=0.362), blood flow grade 0 (OR=0.440), grade Ⅰ (OR=0.314), and grade Ⅱ (OR=0.120) were the protective factors for the non-response of RA' Elamod (P < 0.05). High ESR (OR=1.117), high DAS score (OR=1.367), and long-term morning stiffness (OR=1.159) were the risk factors (P < 0.05). Based on the prediction model of the above five indexes, the C-index and AUC of RA patients who did not respond to Elamod treatment were 0.816 and 0.816 (95% CI: 0.808-0.938), respectively.  Conclusion  Pulse resistance index, blood flow classification, ESR, DAS score, and morning stiffness time are the factors influencing treatment response of patients with RA, and the prediction model on them can be used to predict the risk of non-response of RA patients to treatment.

     

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