{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T19:57:31Z","timestamp":1786132651878,"version":"build-2736575974"},"reference-count":18,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"12","funder":[{"DOI":"10.13039\/100014468","name":"Mallinckrodt Pharmaceuticals","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014468","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["CDRN1306-01556"],"award-info":[{"award-number":["CDRN1306-01556"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive Kidney Diseases,","doi-asserted-by":"publisher","award":["K23DK093556"],"award-info":[{"award-number":["K23DK093556"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["PPRN1306-04903"],"award-info":[{"award-number":["PPRN1306-04903"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JASN"],"published-print":{"date-parts":[[2019,12]]},"abstract":"\n Significance Statement<\/jats:title>\n Clinical advances in glomerular disease have been stymied by the rarity of these health conditions, making identification of sufficient numbers of patients with glomerular disease for enrollment in research studies challenging, particularly in the pediatric setting. We leveraged the PEDSnet pediatric health system population of >6.5 million children to develop and evaluate a highly sensitive and specific electronic health record (EHR)\u2013based computable phenotype algorithm to identify the largest cohort of children with glomerular disease to date. This tool for rapid cohort identification applied to a robust resource of multi-institutional longitudinal EHR data offers great potential to enhance and accelerate comparative effectiveness and health outcomes research in glomerular disease.<\/jats:p>\n <\/jats:sec>\n \n Background<\/jats:title>\n The rarity of pediatric glomerular disease makes it difficult to identify sufficient numbers of participants for clinical trials. This leaves limited data to guide improvements in care for these patients.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n The authors developed and tested an electronic health record (EHR) algorithm to identify children with glomerular disease. We used EHR data from 231 patients with glomerular disorders at a single center to develop a computerized algorithm comprising diagnosis, kidney biopsy, and transplant procedure codes. The algorithm was tested using PEDSnet, a national network of eight children\u2019s hospitals with data on >6.5 million children. Patients with three or more nephrologist encounters (\n n<\/jats:italic>\n =55,560) not meeting the computable phenotype definition of glomerular disease were defined as nonglomerular cases. A reviewer blinded to case status used a standardized form to review random samples of cases (\n n<\/jats:italic>\n =800) and nonglomerular cases (\n n<\/jats:italic>\n =798).\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The final algorithm consisted of two or more diagnosis codes from a qualifying list or one diagnosis code and a pretransplant biopsy. Performance characteristics among the population with three or more nephrology encounters were 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%); and area under the receiver operating characteristics curve, 94% (95% CI, 93% to 95%). Requiring that the sum of nephrotic syndrome diagnosis codes exceed that of glomerulonephritis codes identified children with nephrotic syndrome or biopsy-based minimal change nephropathy, FSGS, or membranous nephropathy, with 94% sensitivity and 92% PPV. The algorithm identified 6657 children with glomerular disease across PEDSnet, \u226550% of whom were seen within 18 months.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n The authors developed an EHR-based algorithm and demonstrated that it had excellent classification accuracy across PEDSnet. This tool may enable faster identification of cohorts of pediatric patients with glomerular disease for observational or prospective studies.<\/jats:p>\n <\/jats:sec>","DOI":"10.1681\/asn.2019040365","type":"journal-article","created":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T14:29:18Z","timestamp":1573828158000},"page":"2427-2435","source":"Crossref","is-referenced-by-count":43,"title":["Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research"],"prefix":"10.1681","volume":"30","author":[{"given":"Michelle R.","family":"Denburg","sequence":"first","affiliation":[{"name":"Division of Nephrology,"},{"name":"Center for Pediatric Clinical Effectiveness,"},{"name":"Department of Pediatrics and"},{"name":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanieh","family":"Razzaghi","sequence":"additional","affiliation":[{"name":"Applied Clinical Research Center, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L. Charles","family":"Bailey","sequence":"additional","affiliation":[{"name":"Applied Clinical Research Center, and"},{"name":"Department of Biomedical and Health Informatics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania;"},{"name":"Department of Pediatrics and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danielle E.","family":"Soranno","sequence":"additional","affiliation":[{"name":"Renal Section, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ari H.","family":"Pollack","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, Seattle Children\u2019s Hospital, University of Washington, Seattle, Washington;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vikas R.","family":"Dharnidharka","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, St. Louis Children\u2019s Hospital, Washington University in St. Louis, St. Louis, Missouri;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark M.","family":"Mitsnefes","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, Cincinnati Children\u2019s Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1982-9938","authenticated-orcid":false,"given":"William E.","family":"Smoyer","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, Nationwide Children\u2019s Hospital, The Ohio State University, Columbus, Ohio;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J. G.","family":"Somers","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Medicine, Boston Children\u2019s Hospital, Harvard Medical School, Boston, Massachusetts;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua J.","family":"Zaritsky","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Nemours\/Alfred I. DuPont Hospital for Children, Wilmington, Delaware; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph T.","family":"Flynn","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, Seattle Children\u2019s Hospital, University of Washington, Seattle, Washington;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donna J.","family":"Claes","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Pediatrics, Cincinnati Children\u2019s Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bradley P.","family":"Dixon","sequence":"additional","affiliation":[{"name":"Renal Section, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryjane","family":"Benton","sequence":"additional","affiliation":[{"name":"Division of Nephrology,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura H.","family":"Mariani","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, Michigan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1252-068X","authenticated-orcid":false,"given":"Christopher B.","family":"Forrest","sequence":"additional","affiliation":[{"name":"Applied Clinical Research Center, and"},{"name":"Department of Biomedical and Health Informatics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania;"},{"name":"Department of Pediatrics and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan L.","family":"Furth","sequence":"additional","affiliation":[{"name":"Division of 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