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September 16, 2025

Identifying and Characterising a Chronic Kidney Disease Electronic-Phenotype Using Electronic Health Record-Derived Data: A Narrative Review of Strategies and Applications.

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Authors

CSChristopher Noel SparksThe Royal Melbourne HospitalASAdam SteinbergThe Royal Melbourne HospitalNTNigel D. ToussaintThe Royal Melbourne Hospital

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Overview

Narrative review highlights strategies for developing CKD e-phenotype using electronic health record data, suggesting new applications.

Key Points

  • Identifying a reliable CKD e-phenotype can optimize patient management and treatment outcomes, with data from electronic health records being pivotal.
  • Using criteria like eGFR and proteinuria, alongside ICD codes, forms a reliable basis for defining CKD e-phenotypes, enhancing data accuracy.
  • The narrative review evaluates various strategies, including machine learning and natural language processing, for algorithm development.
  • Future applications of CKD e-phenotypes include their role in public health and clinical trial recruitment, emphasizing their importance for healthcare.

Cite This Study

Sparks et al. (2025) studied this question.

synapsesocial.com/papers/68c93fe601120bef803bb0d3https://doi.org/10.1111/nep.70118
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