ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014
Development and validation of an electronic phenotyping algorithm for chronic kidney disease.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Effects of Testing and Disclosing Ancestry-Specific Genetic Risk for Kidney Failure on Patients and Health Care Professionals: A Randomized Clinical Trial.JAMA network open · 2022Trial
- A method for characterizing disease progression from acute kidney injury to chronic kidney disease.Journal of biomedical informatics · 2025Article
- The computerized algorithm for renal assessment improves diagnostic accuracy of renal impairment in hospitalized patients.Scientific reports · 2025Article
- Towards automated phenotype definition extraction using large language models.Genomics & informatics · 2024Article
- A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.Scientific reports · 2024Article
- Preeclampsia and Long-term Kidney Outcomes: An Observational Cohort Study.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2023Observational
- A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.medRxiv : the preprint server for health sciences · 2023Article
- Refining Clinical Phenotypes to Improve Clinical Decision Support and Reduce Alert Fatigue: A Feasibility Study.Applied clinical informatics · 2023Article
- High unmet treatment needs in patients with chronic kidney disease and type 2 diabetes: real-world evidence from a US claims database.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2023Article
- Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.Scientific reports · 2023Article
- Predicting hypertension onset from longitudinal electronic health records with deep learning.JAMIA open · 2022Article
- Development and validation of algorithms to identify patients with chronic kidney disease and related chronic diseases across the Northern Territory, Australia.BMC nephrology · 2022Article
- Big Data in Nephrology.Nature reviews. Nephrology · 2021Review
- A strategy for validation of variables derived from large-scale electronic health record data.Journal of biomedical informatics · 2021Article
- Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies.NPJ digital medicine · 2021Article
- Similarity-based health risk prediction using Domain Fusion and electronic health records data.Journal of biomedical informatics · 2021Article
- Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.JMIR medical informatics · 2021Article
- Derivation and validation of genome-wide polygenic score for urinary tract stone diagnosis.Kidney international · 2020Article
- Optimized Identification of Advanced Chronic Kidney Disease and Absence of Kidney Disease by Combining Different Electronic Health Data Resources and by Applying Machine Learning Strategies.Journal of clinical medicine · 2020Article
- Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. CKD is frequently undiagnosed and patients are unaware, hampering intervention. A tool for accurate and timely identification of CKD from electronic medical records (EMR) could improve healthcare quality and identify patients for research. As members of eMERGE (electronic medical records and genomics) Network, we developed an automated phenotyping algorithm that can be deployed to identify rapidly diabetic and/or hypertensive CKD cases and controls in health systems with EMRs It uses diagnostic codes, laboratory results, medication and blood pressure records, and textual information culled from notes. Validation statistics demonstrated positive predictive values of 96% and negative predictive values of 93.3. Similar results were obtained on implementation by two independent eMERGE member institutions. The algorithm dramatically outperformed identification by ICD-9-CM codes with 63% positive and 54% negative predictive values, respectively.
Indexed as
Identifiers
25954398PMC4419875What OpenQuestion holds
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.