ArticleKidney research and clinical practice2022
Mayo imaging classification is a good predictor of rapid progress among Korean patients with autosomal dominant polycystic kidney disease: results from the KNOW-CKD study.
Article in Kidney research and clinical practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 14 citations in OpenAlex.
- Evaluating the Safety and effectivenesS in adult KorEaN patients treated with Tolvaptan for management of autosomal domInAnt poLycystic kidney disease (ESSENTIAL): final report.Kidney research and clinical practice · 2026Article
- ADPKD Progression by Variant Type and Molecular Domain Among Participants in the HALT PKD Trial.Clinical journal of the American Society of Nephrology : CJASN · 2025Article
- Long-Term Effects of Tolvaptan Therapy on Total Kidney Volume and Renal Function in Patients with Autosomal Dominant Polycystic Kidney Disease: A Single-Center Experience.Journal of clinical medicine · 2025Article
- Comparison Between the Human-Sourced Ellipsoid Method and Kidney Volumetry Using Artificial Intelligence in Polycystic Kidney Disease.Journal of personalized medicine · 2025Article
- Kidney organoids demonstrate that PTH1R drives a cystogenic cAMP-pPKA-pCREB axis in developmental polycystic kidney disease.American journal of physiology. Renal physiology · 2025Article
- Feasibility of artificial intelligence-based decision supporting system in tolvaptan prescription for autosomal dominant polycystic kidney disease.Investigative and clinical urology · 2023Article
- Recent updates in therapeutic approach using tolvaptan for autosomal dominant polycystic kidney disease.The Korean journal of internal medicine · 2023Review
- Using the Mayo Imaging Classification to predict renal outcomes in Korean autosomal dominant polycystic kidney disease patients.Kidney research and clinical practice · 2022Article
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12 authors at 8 institutions in 1 country.
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Abstract
backgroundMayo imaging classification (MIC) is a useful biomarker to predict disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study was performed to validate MIC in the prediction of renal outcome in a prospective Korean ADPKD cohort and evaluate clinical parameters associated with rapid disease progression.
methodsA total of 178 ADPKD patients were enrolled and prospectively observed for an average duration of 6.2 ± 1.9 years. Rapid progressor was defined as MIC 1C through 1E while slow progressor was defined as 1A through 1B. Renal composite outcome (doubling of serum creatinine, 50% decline of estimated glomerular filtration rate [eGFR], or initiation of renal replacement therapy) as well as the annual percent change of height-adjusted total kidney volume (mHTKV-α), and eGFR decline (mGFR-α) were compared between groups.
resultsA total of 110 patients (61.8%) were classified as rapid progressors. These patients were younger and showed a higher proportion of male patients. Rapid progressor was an independent predictor for renal outcome (hazard ratio, 4.09; 95% confidence interval, 1.23-13.54; p = 0.02). The mGFR-α was greater in rapid progressors (-3.58 mL/min per year in 1C, -3.7 in 1D, and -4.52 in 1E) compared with that in slow progressors (-1.54 in 1A and -2.06 in 1B). The mHTKV-α was faster in rapid progressors (5.3% per year in 1C, 9.4% in 1D, and 11.7% in 1E) compared with that in slow progressors (1.2% in 1A and 3.8% in 1B).
conclusionMIC is a good predictive tool to define rapid progressors in Korean ADPKD patients.
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