Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 5, 2025Open Access

Early prediction of severity progression in patients with chronic kidney disease: A Machine Learning Predictive Modelling analysis with retrospective data of a tertiary care hospital

View Full Paper
Ask AI
Bookmark
Share

Authors

SNSaurav NayakAll India Institute of Medical Sciences BhubaneswarGSGautom Kumar SahariaAll India Institute of Medical Sciences BhubaneswarSPSandip Kumar PandaAll India Institute of Medical Sciences Bhubaneswar

Discussion

Loading...

Member takes

Overview

Retrospective analysis reveals serum C3 and C4 as biomarkers in predicting chronic kidney disease severity, suggesting better management strategies.

Key Points

  • Serum complements C3 and C4 can predict chronic kidney disease severity effectively.
  • The Random Forest model achieved an outstanding F1 score of 0.984 and accuracy of 0.991.
  • Influential predictors included age, serum C3 levels, and the C3/C4 ratio in the predictive modeling.
  • A web-based tool was developed to aid clinicians in estimating chronic kidney disease severity based on key markers.

Cite This Study

Nayak et al. (2025) studied this question.

synapsesocial.com/papers/68bb4d2d6d6d5674bcd016fbhttps://doi.org/10.21203/rs.3.rs-7198292/v1
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Comparing the Performance of Machine Learning Models in Predicting the Risk of Chronic Kidney Disease2024 · 1 citations
  2. 2Predictive Analysis of Chronic Kidney Disease in Machine Learning2025 · 1 citations
  3. 3Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study2026
  4. 4Analytical Prediction for Chronic Kidney Disease: A Comparison of Machine Learning Methods2025
  5. 5Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.2025 · 2 citations