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Developing and evaluating pediatric phecodes (Peds-Phecodes) for high-throughput phenotyping using electronic health records.
Grabowska, Monika E; Van Driest, Sara L; Robinson, Jamie R; Patrick, Anna E; Guardo, Chris; Gangireddy, Srushti; Ong, Henry H; Feng, QiPing; Carroll, Robert; Kannankeril, Prince J; Wei, Wei-Qi.
  • Grabowska ME; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Van Driest SL; Department of Pediatrics and the Center for Pediatric Precision Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Robinson JR; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Patrick AE; Department of Pediatric Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Guardo C; Department of Pediatrics and the Center for Pediatric Precision Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Gangireddy S; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Ong HH; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Feng Q; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Carroll R; Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Kannankeril PJ; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Wei WQ; Department of Pediatrics and the Center for Pediatric Precision Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
J Am Med Inform Assoc ; 31(2): 386-395, 2024 Jan 18.
Article en En | MEDLINE | ID: mdl-38041473
ABSTRACT

OBJECTIVE:

Pediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients. MATERIALS AND

METHODS:

We adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes.

RESULTS:

The Peds-Phecodes aggregate 15 533 ICD-9-CM codes and 82 949 ICD-10-CM codes into 2051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 vs 192 out of 687 SNPs, P < .001).

DISCUSSION:

We introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations.

CONCLUSION:

Peds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Registros Electrónicos de Salud Límite: Child / Humans Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Registros Electrónicos de Salud Límite: Child / Humans Idioma: En Año: 2024 Tipo del documento: Article