Trial reportRenal failure2023
Using elastography-based multilayer perceptron model to evaluate renal fibrosis in chronic kidney disease.
Trial report in Renal failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis.Renal failure · 2024Pooled it
- Diagnostic accuracy of AI-augmented renal ultrasound for degenerative kidney disorders: a systematic review and meta-analysis.Future science OA · 2026Review
- Applications of Machine Learning for Early Diagnosis and Prognosis of Chronic Kidney Disease: Current Evidence.Diagnostics (Basel, Switzerland) · 2026Review
- Multiparametric Ultrasound and Machine Learning for Predicting Renal Scarring in Children.Diagnostics (Basel, Switzerland) · 2026Article
- Nomograms with arterial spin labeling for diagnosing early-stage chronic kidney disease.International urology and nephrology · 2026Article
- Artificial Intelligence in Nephrology-State of the Art on Theoretical Background, Molecular Applications, and Clinical Interpretation.International journal of molecular sciences · 2026Review
- From microtubule remodeling to clinical translation: the multifaceted roles of vasohibin-1 in disease modulation.Frontiers in immunology · 2026Review
- Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.Renal failure · 2025Article
- TGF-β1 induces ROS to activate ferroptosis via the ERK1/2-WISP1 pathway to promote the progression of renal tubular epithelial cell fibrosis.Cytotechnology · 2025Article
- Combining Super-Resolution Imaging and Shear Wave Elastography for Enhanced Risk Assessment of Moderate-to-Severe Renal Fibrosis in Chronic Kidney Disease Patients.International journal of nephrology and renovascular disease · 2025Article
- Advancements in the non-invasive diagnosis of renal fibrosis.Frontiers in medicine · 2025Review
- A versatile attention-based neural network for chemical perturbation analysis and its potential to aid surgical treatment: an experimental study.International journal of surgery (London, England) · 2024Article
- The association between renal medullary and cortical fibrosis, stiffness, and concentrating capacity: an observational, single-center cross-sectional study.Clinical and experimental nephrology · 2024Observational
- Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease.Journal of nephrology · 2024Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGiven its progressive deterioration in the clinical course, noninvasive assessment and risk stratification for the severity of renal fibrosis in chronic kidney disease (CKD) are required. We aimed to develop and validate an end-to-end multilayer perceptron (MLP) model for assessing renal fibrosis in CKD patients based on real-time two-dimensional shear wave elastography (2D-SWE) and clinical variables.
methodsFrom April 2019 to December 2021, a total of 162 patients with CKD who underwent a kidney biopsy and 2D-SWE examination were included in this single-center, cross-sectional, and prospective clinical study. 2D-SWE was performed to measure the right renal cortex stiffness, and the corresponding elastic values were recorded. Patients were categorized into two groups according to their histopathological results: mild and moderate-severe renal fibrosis. The patients were randomly divided into a training cohort (
resultsThe developed MLP model demonstrated good calibration and discrimination in both the training [area under the receiver operating characteristic curve (AUC) = 0.93; 95% confidence interval (CI) = 0.88 to 0.98] and test cohorts [AUC = 0.86; 95% CI = 0.75 to 0.97]. A decision curve analysis and a clinical impact curve also showed that the MLP model had a positive clinical impact and relatively few negative effects.
conclusionsThe proposed MLP model exhibited the satisfactory performance in identifying the individualized risk of moderate-severe renal fibrosis in patients with CKD, which is potentially helpful for clinical management and treatment decision-making.
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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 Socratic graph.