Children with Pulmonary Embolism

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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.

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Provenance

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

Algothrithm Description

This computable phenotype is based on the ASPECT algorithm developed for adult PE. 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 = 88%
specificity = 90%
PPV = 91%
NPV = 88%

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
  • Patients with an anticoagulant dispensed or prescribed >= 7 and <= 365 days prior to the visit.

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Computable phENotype To Identify Pulmonary Embolism in chilDrEn (CENTIPEDE)
Central Michigan University; Children's Hospital of Philadelphia
Study to test the classification accuracy of an algorithm that has been previously validated in adult pulmonary embolism (PE) patients (“ASPECT”). The algorithm was used to identify a pediatric PE cohort from 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.

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Version History

Now showing 1 - 2 of 2
VersionDateSummary
2025-03-25 14:20:18
Removed an exclusion criteria from original resulting in better performance.
1*
2024-12-20 11:17:26
* Selected version