Cardona Fernando
Unitat de Genètica Molecular, Instituto de Biomedicina de Valencia - CSIC, Valencia 46010, Spain.
Centro de investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid 28029, Spain.
World J Clin Cases. 2024 Feb 16;12(5):1033-1035. doi: 10.12998/wjcc.v12.i5.1033.
This letter praises a recent article in the (Roles of biochemistry data, lifestyle, and inflammation in identifying abnormal renal function in old Chinese), examining factors affecting abnormal renal function in elderly Chinese using advanced machine learning. It highlights the importance of uric acid, age, hemoglobin, body mass index, sport hours, and systolic blood pressure. The study's holistic approach, integrating lifestyle and inflammation, offers a nuanced understanding of chronic kidney disease risk factors. The letter suggests exploring mechanistic pathways of hyperuricemia, the link between anemia and renal function, and the connection between body mass index and estimated glomerular filtration rate. It advocates investigating physical activity's impact on renal health and the independent effects of blood pressure. The study significantly contributes to chronic kidney disease understanding, proposing avenues for further exploration and interventions. Commendations are extended to the authors and the journal.
这封信赞扬了最近发表在《（生化数据、生活方式和炎症在识别中国老年人肾功能异常中的作用）》上的一篇文章，该文章使用先进的机器学习方法研究了影响中国老年人肾功能异常的因素。它强调了尿酸、年龄、血红蛋白、体重指数、运动时长和收缩压的重要性。该研究采用综合生活方式和炎症的整体方法，对慢性肾病风险因素提供了细致入微的理解。这封信建议探索高尿酸血症的机制途径、贫血与肾功能之间的联系以及体重指数与估计肾小球滤过率之间的关联。它主张研究身体活动对肾脏健康的影响以及血压的独立作用。该研究对慢性肾病的理解做出了重大贡献，提出了进一步探索和干预的途径。向作者和该期刊表示赞扬。
