METHODS: An anonymised dataset comprising 97,413 patients receiving DOAC therapy in a tertiary health setting was systematically extracted from the multidimensional electronic health records and prepared for analysis. Machine learning classifiers were applied to the prepared dataset to select the important features which informed covariate selection in multivariate logistic regression analysis.
RESULTS: For both CKD and non-CKD DOAC users, features such as length of stay, treatment days, and age were ranked highest for relevance to adverse outcomes like death and stroke. Patients with Stage 3a CKD had significantly higher odds of ischaemic stroke (OR 2.45, 95% Cl: 2.10-2.86; p = 0.001) and lower odds of all-cause mortality (OR 0.87, 95% Cl: 0.79-0.95; p = 0.001) on apixaban therapy. In patients with CKD (Stage 5) receiving apixaban, the odds of death were significantly lowered (OR 0.28, 95% Cl: 0.14-0.58; p = 0.001), while the effect on ischaemic stroke was insignificant.
CONCLUSIONS: A positive effect of DOAC therapy was observed in advanced CKD. Key factors influencing clinical outcomes following DOAC administration in patients in different stages of CKD were identified. These are crucial for designing more advanced studies to explore safer and more effective DOAC therapy for the population.
方法:从多维电子健康记录中系统地提取了一个匿名数据集,该数据集包含97,413名在三级健康环境中接受DOAC治疗的患者,并准备进行分析。将机器学习分类器应用于准备好的数据集以选择在多变量逻辑回归分析中告知协变量选择的重要特征。
结果:对于CKD和非CKDDOAC用户,特征,如停留时间,治疗天数,与死亡和卒中等不良结局的相关性最高.在阿哌沙班治疗下,3a期CKD患者发生缺血性卒中的几率显著较高(OR2.45,95%Cl:2.10-2.86;p=0.001),全因死亡率的几率较低(OR0.87,95%Cl:0.79-0.95;p=0.001)。在接受阿哌沙班的CKD(5期)患者中,死亡几率显着降低(OR0.28,95%Cl:0.14-0.58;p=0.001),而对缺血性卒中的影响微不足道。
结论:在晚期CKD中观察到DOAC治疗的积极作用。确定了不同阶段CKD患者DOAC给药后影响临床结局的关键因素。这些对于设计更先进的研究以探索更安全,更有效的DOAC治疗人群至关重要。