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Glomerular Disease, SNOMED-Only Codes
| dc.contributor.advisor | Denburg, Michelle |
| dc.contributor.advisor | Razzaghi, Hanieh |
| dc.contributor.advisor | Bailey, Charles |
| dc.contributor.author | Goodwin Davies, Amy |
| dc.contributor.other | Children's Hospital of Philadelphia |
| dc.date | 2021-03-01 |
| dc.date.accessioned | 2024-06-10T19:03:24Z |
| dc.date.available | 2024-06-10T19:03:24Z |
| dc.date.created | 2019 |
| dc.description | This concept set contains codes pertaining to glomerular disease, glomerulonephritis, nephritic syndrome, and nephrotic syndrome. It is intended to identify a cohort of patients with glomerular disease when incorporated into the computational phenotype originally developed and validated by Denburg et al 2019 (DOI: 10.1681/ASN.2019040365). Validation indicated that this computational phenotype had excellent classification accuracy across PEDSnet: sensitivity, 96% (95% CI, 94% to 97%); specificity, 93% (95% CI, 91% to 94%); positive predictive value (PPV), 89% (95% CI, 86% to 91%); negative predictive value, 97% (95% CI, 96% to 98%). The computational phenotype identifies patients via two pathways: two or more glomerular inclusion diagnoses on different days of service, OR (one or more glomerular inclusion diagnosis AND one or more kidney biopsy which is not post-transplant). Codes flagged with "other_code_req" alone are not sufficient for a patient to be included in the cohort, i.e., these codes must be accompanied by another code without this flag or a kidney biopsy which is not post-transplant. Codes flagged with "neph_req" must be associated with a nephrology specialty visit. The concept set was developed by mapping a list of ICD-9-CM codes provided by Michelle Denburg (clinician) to SNOMED. It is limited to SNOMED-CT-only diagnosis codes. |
| dc.description.abstract | This concept set is inteded to identify patients with a diagnosis of glomerular disease. |
| dc.identifier.uri | https://hdl.handle.net/20.500.14642/545 |
| dc.language.iso | en-US |
| dc.provenance | This concept set was developed for the Membranoproliferative Glomerulonephritis (MPGN) in PEDSnet study. |
| dc.publisher | PEDSnet |
| dc.relation.isreferencedby | Denburg, Michelle R.; Razzaghi, Hanieh; Bailey, L. Charles; Soranno, Danielle E.; Pollack, Ari H.; Dharnidharka, Vikas R.; Mitsnefes, Mark M.; Smoyer, William E.; Somers, Michael J. G.; Zaritsky, Joshua J.; Flynn, Joseph T.; Claes, Donna J.; Dixon, Bradley P.; Benton, Maryjane; Mariani, Laura H.; Forrest, Christopher B.2; Furth, Susan L. Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research. JASN 30(12):p 2427-2435, December 2019. | DOI: [10.1681/ASN.2019040365](https://doi.urg/10.1681/ASN.2019040365) |
| dc.relation.uri | https://atlassian.chop.edu/bitbucket/projects/PRP/repos/denburg_mpgn/browse/descriptives_tbl4/specs/glean_inclusion.csv |
| dc.rights | a CC-BY Attribution 4.0 License. |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ |
| dc.subject | Cohort Definition |
| dc.subject.mesh | Glomerulonephritis |
| dc.subject.mesh | Nepritis |
| dc.subject.mesh | Kidney Diseases |
| dc.subject.mesh | Urologic Diseases |
| dc.subject.other | SNOMED |
| dc.title | Glomerular Disease, SNOMED-Only Codes |
| dspace.entity.type | ConceptSet |
| local.subject.DataModel | PCORnet Data Model |
| local.subject.EvalType | Clinician Reviewed |
| relation.isConceptSetOfConceptSet | 0f62d22d-ebb0-4656-97ca-5a10ef85fa2d |
| relation.isConceptSetOfConceptSet.latestForDiscovery | 0f62d22d-ebb0-4656-97ca-5a10ef85fa2d |
| relation.isStudyOfConceptSet | b9ba1a84-3c64-47c4-a896-53957d51d720 |
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