PDF(Pubmed)
Abstract：
Previous studies have suggested an association between Proton Pump Inhibitors (PPIs) and the progression of chronic kidney disease (CKD). This study aims to assess the association between PPI use and CKD progression by analysing estimated glomerular filtration rate (eGFR) trajectories using a process mining approach. We conducted a retrospective cohort study from 1 January 2006 to 31 December 2011, utilising data from the Stockholm Creatinine Measurements (SCREAM). New users of PPIs and H2 blockers (H2Bs) with CKD (eGFR < 60) were identified using a new-user and active-comparator design. Process mining discovery is a technique that discovers patterns and sequences in events over time, making it suitable for studying longitudinal eGFR trajectories. We used this technique to construct eGFR trajectory models for both PPI and H2B users. Our analysis indicated that PPI users exhibited more complex and rapidly declining eGFR trajectories compared to H2B users, with a 75% increased risk (adjusted hazard ratio [HR] 1.75, 95% confidence interval [CI] 1.49 to 2.06) of transitioning from moderate eGFR stage (G3) to more severe stages (G4 or G5). These findings suggest that PPI use is associated with an increased risk of CKD progression, demonstrating the utility of process mining for longitudinal analysis in epidemiology, leading to an improved understanding of disease progression.
摘要：
先前的研究表明，质子泵抑制剂（PPI）与慢性肾脏疾病（CKD）的进展之间存在关联。本研究旨在通过使用过程挖掘方法分析估计的肾小球滤过率（eGFR）轨迹来评估PPI使用与CKD进展之间的关联。我们从2006年1月1日至2011年12月31日进行了一项回顾性队列研究，利用来自斯德哥尔摩肌酐测量（SCREAM）的数据。使用新用户和主动比较器设计确定了具有CKD（eGFR<60）的PPI和H2阻断剂（H2Bs）的新用户。过程挖掘发现是一种随着时间的推移发现事件中的模式和序列的技术，使其适合研究纵向eGFR轨迹。我们使用此技术为PPI和H2B用户构建了eGFR轨迹模型。我们的分析表明，与H2B用户相比，PPI用户表现出更复杂和快速下降的eGFR轨迹，从中度eGFR阶段（G3）过渡到更严重阶段（G4或G5）的风险增加了75％（调整后的风险比[HR]1.75，95％置信区间[CI]1.49至2.06）。这些研究结果表明，PPI的使用与CKD进展的风险增加有关。证明了过程挖掘在流行病学纵向分析中的实用性，提高对疾病进展的认识。
