ArticleWorld journal of urology2022
Prediction of the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics.
Article in World journal of urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- The gut-kidney microbiome-oxalate axis in calcium oxalate nephrolithiasis: mechanisms and microbiome-based interventions.Frontiers in cellular and infection microbiology · 2026Pooled it
- The emerging role of the urinary microbiome in benign noninfectious urological conditions: an up-to-date systematic review.World journal of urology · 2023Pooled it
- Gut microbiota in patients with kidney stones: a systematic review and meta-analysis.BMC microbiology · 2023Pooled it
- Clinical presentation and management patterns of ureteral calculi in pregnancy: a 14-year single-institution retrospective study.Frontiers in medicine · 2026Article
- Article
- Gut microbiota-regulated unconjugated bilirubin metabolism drives renal calcium oxalate crystal deposition.Gut microbes · 2025Article
- Dietary baking soda (NaHCORenal failure · 2025Article
- Microbiota and kidney disease: the road ahead.Nature reviews. Nephrology · 2025Review
- Review
- A microbiota-based perspective on urinary stone disease: insights from 16S rRNA sequencing and machine learning models.Frontiers in cellular and infection microbiology · 2025Article
- How is the human microbiome linked to kidney stones?Frontiers in cellular and infection microbiology · 2025Review
- Dysbiotic Gut Microbiota Correlates with Altered Serum and Urinary Biomarkers in Recurrent Calcium Oxalate Stone Patients.International journal of general medicine · 2025Article
- Automatic kidney stone identification: an adaptive feature-weighted LSTM model based on urine and blood routine analysis.Urolithiasis · 2024Article
- Gut and Urinary Microbiota in Cats with Kidney Stones.Microorganisms · 2024Article
- Article
- Update on the Effect of the Urinary Microbiome on Urolithiasis.Diagnostics (Basel, Switzerland) · 2023Review
- Theranostic roles of machine learning in clinical management of kidney stone disease.Computational and structural biotechnology journal · 2023Review
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
purposeTo predict the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics.
methodsGut microbiota and clinical data from 180 subjects (120 for training set and 60 for validation) attending the West China Hospital (WCH) were collected between June 2018 and January 2021. Based on the gut microbiota and clinical data from 120 subjects (66 non-kidney stone individuals and 54 kidney stone patients), we evaluated eight machine learning methods to predict the occurrence of calcium oxalate kidney stones.
resultsWith fivefold cross-validation, the random forest method produced the best area under the curve (AUC) of 0.94. We further applied random forest to an independent validation dataset with 60 samples (34 non-kidney stone individuals and 26 kidney stone patients), which yielded an AUC of 0.88.
conclusionOur results demonstrated that clinical data combined with gut microbiota characteristics may help predict the occurrence of kidney stones.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.