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ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Renal Pharmacology

Comparative Effectiveness and Pharmacological Fingerprints of Indobufen versus Rivaroxaban in Patients with Chronic Kidney Disease: A Single-Center, Real-World Study

Provisionally accepted
Lijun  ZhangLijun Zhang1Mingbo  LiuMingbo Liu2Tingting  HuangTingting Huang3He  ZhangHe Zhang1Chuanfu  HuangChuanfu Huang1Zhenbin  PanZhenbin Pan1Zhao  ChenZhao Chen1Jun  NingJun Ning1Jiameng  TangJiameng Tang2*
  • 1Department of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, China
  • 2Department of Laboratory Medicine, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, China
  • 3Department of Medical Statistics, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, China

The final, formatted version of the article will be published soon.

Abstract Introduction: Antithrombotic management in Chronic Kidney Disease (CKD) is a clinical dilemma. This study aimed to empirically evaluate the "de facto interchangeability" of the antiplatelet indobufen and the anticoagulant rivaroxaban by comparing their real-world effectiveness and safety in hospitalized CKD patients. Methods: In this retrospective cohort study (2020-2024), we analyzed CKD patients treated with indobufen or rivaroxaban. A multi-stage analysis first used machine learning to assess baseline cohort comparability, overcoming limitations of p-value-based tests. Subsequently, a Linear Mixed Model (LMM), adjusted for confounders including polypharmacy, assessed independent drug effects on in-hospital thrombosis, hemorrhage, and longitudinal laboratory markers. Results: Machine learning demonstrated the clinical comparability of the indobufen and rivaroxaban cohorts. The incidence of in-hospital thrombosis was numerically lower in the indobufen group (3.65% vs. 7.58%; P = 0.101), while hemorrhage rates were similar (2.19% vs. 2.27%; P = 1). The LMM analysis, beyond verifying indobfen's expected antiplatelet activity (modulating MPV, PDW), revealed pleiotropic effects (increased prealbumin, HDL-C) and a significant reduction in urine occult blood (P<0.001), suggesting renal safety. Notably, the model demonstrated that apparent effects on hemoglobin and eGFR were attributable to confounding by co-medications, not a direct drug effect. Conclusion: In this real-world CKD cohort, indobufen and rivaroxaban demonstrated comparable clinical effectiveness and safety. Combining machine learning with longitudinal models helps to statistically adjust for complex confounders like polypharmacy, thereby providing a more robust estimate of a drug's independent effect.

Keywords: Chronic kidney disease (CKD), Indobufen, rivaroxaban, Real-world study, large language model (LLM), Linear mixed model (LMM)

Received: 04 Sep 2025; Accepted: 06 Nov 2025.

Copyright: © 2025 Zhang, Liu, Huang, Zhang, Huang, Pan, Chen, Ning and Tang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Jiameng Tang, jiamengtang@126.com

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