Children with Pulmonary Embolism

Zelinski, Ally

Phenotype

Children with Pulmonary Embolism

Variable Name

dx_pe

Created

2024-10-14

Refreshed

2024-10-14

Developers

Zelinski, Ally

Affiliation(s)

PEDSnet Data Coordinating Center

Files

Validation Method

Data Model

Phenotype Description

Pediatric pulmonary embolism (PE) research has been limited by rarity at individual centers and a lack of multi-center data sources to investigate treatments and outcomes. The goal of this work was to develop a computable phenotype and utilize it in PEDSnet to compare management strategies and outcomes in a validated cohort of children with PE to improve PE care in children.

Algothrithm Description

This computable phenotype is based on the ASPECT algorithm developed for adult PE with removed exclusion criteria from Version 1. The algorithm was used to identify a pediatric pulmonary embolism (PE) cohort from electronic health records (EHR) and evaluate the accuracy of diagnostic and treatment code combinations using EHR data to diagnose pediatric PE at a single center, the Children’s Hospital of Philadelphia.

Performance based on chart review:

sensitivity = 96%
specificity = 88%
PPV = 90%
NPV = 95%

Inclusion Criteria:

PE diagnosis code associated with an inpatient or emergency department visit;
CT or perfusion scans performed during or <= 2 days prior to the visit;
Anticoagulant dispensed or prescribed during the visit.

Exclusion Criteria:

None

Development Population

Vocabulary

Clinical Subjects Headings

Provenance

This computable phenotype was created for the pilot study, Computable phENotype To Identify Pulmonary Embolism in chilDrEn (CENTIPEDE).

Study

Computable phENotype To Identify Pulmonary Embolism in chilDrEn (CENTIPEDE), Phase II

Study Dates:2025-04 - PresentSponsor Site:Cincinnati Children's Hospital Medical Center

This phase II study is intended to further validate a computable phenotype (CP) developed in phase I which identifies a pediatric pulmonary embolism (PE) cohort from EHR. The accuracy of diagnostic and treatment code combinations using EHR data to diagnose pediatric PE was tested at a single center, the Children"s Hospital of Philadelphia. However, this CP had a high rate of false negatives in children with cardiac disease, likely due to differences in diagnosis and management. This study aims to validate the CP for PE at two additional PEDSnet centers and identify risk categories, develop a CP specific for PE in cardiac patients, and identify PE interventions and outcomes in PEDSnet. This work will allow for comparative effectiveness research and prospective studies using the CP for cohort identification.