Prediction of the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics - Takeaways - MDSpire

Prediction of the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics

  • By

  • Liyuan Xiang

  • Xi Jin

  • Yu Liu

  • Yucheng Ma

  • Zhongyu Jian

  • Zhitao Wei

  • Hong Li

  • Yi Li

  • Kunjie Wang

  • August 24, 2021

  • 0 min

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  • 1

    Calcium oxalate stones account for approximately 80% of kidney stones, with high oxalate concentrations contributing to their formation.

  • 2

    The gut microbiota plays a significant role in kidney stone pathogenesis, with differences observed between patients with and without stones.

  • 3

    Machine learning methods, particularly random forest, were evaluated for predicting calcium oxalate stone occurrence using clinical and microbiome data.

  • 4

    A total of 180 Chinese patients were included in the study, with 54 having kidney stones and 66 serving as non-stone controls.

  • 5

    Taxonomic analysis identified key genera associated with kidney stones, with predictive models achieving AUCs between 0.682 and 0.763.

Original Source(s)

Prediction of the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics

  • by Liyuan Xiang, Xi Jin, Yu Liu, Yucheng Ma, Zhongyu Jian, Zhitao Wei, Hong Li, Yi Li, Kunjie Wang

  • August 24, 2021

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