Abstract
This letter praises a recent article in the World Journal of Clinical Cases (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.
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