Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.

doi:10.2215/CJN.07810621

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Community

Back to search

Article

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.

Clinical journal of the American Society of Nephrology : CJASN - 1 Jan 2022

Wenderfer Scott E, Chang Joyce C, Goodwin Davies Amy, Luna Ingrid Y, Scobell Rebecca, Sears Cora, Magella Bliss, Mitsnefes Mark, Stotter Brian R, Dharnidharka Vikas R, Nowicki Katherine D, Dixon Bradley P, Kelton Megan, Flynn Joseph T, Gluck Caroline, Kallash Mahmoud, Smoyer William E, Knight Andrea, Sule Sangeeta, Razzaghi Hanieh, Bailey L Charles, Furth Susan L, Forrest Christopher B, Denburg Michelle R, Atkinson Meredith A

Abstract excerpt

BACKGROUND AND OBJECTIVES: Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Adolescent

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Algorithms

Share to Child

Share to Child, Preschool

Share to Infant

Share to Lupus Erythematosus, Systemic

Share to Lupus Nephritis

Share to Young Adult

Source

Open in PubMed Open full text

Identifiers

PMID: 34732529
DOI: 10.2215/CJN.07810621
PMCID: PMC8763148

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.PMID 34732529Read ↗

Validating a Computable Phenotype for Nephrotic Syndrome in Children and Adults Using PCORnet Data.Semantic proximity Read ↗

Development and validation of a multi-institutional electronic juvenile idiopathic arthritis phenotype.Semantic proximity Read ↗

Phenotype Risk Score but Not Genetic Risk Score Aids in Identifying Individuals With Systemic Lupus Erythematosus in the Electronic Health Record.Semantic proximity Read ↗

Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.Semantic proximity Read ↗

Update on the pathogenesis and treatment of childhood-onset systemic lupus erythematosus.Semantic proximity Read ↗

A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program.Semantic proximity Read ↗

A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER programSemantic proximity Read ↗

Phenotype Systemic Lupus Erythematosus Patients from EPIC Cosmos.Semantic proximity Read ↗

The U.S. National Registry for Childhood Interstitial and Diffuse Lung Disease: Report of Study Design and Initial Enrollment CohortSemantic proximity Read ↗

A Computable Phenotype for Autosomal Dominant Polycystic Kidney Disease.Semantic proximity Read ↗

Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease.Semantic proximity Read ↗

Application of machine learning algorithm for the prediction of lupus nephritis using SNP data, polygenic risk score, and electronic health record.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.