{"id":"https://openalex.org/W4396998306","doi":"https://doi.org/10.1681/asn.20203110s1187c","title":"Development and Validation of a Predictive Model to Identify Patients with Undiagnosed CKD","display_name":"Development and Validation of a Predictive Model to Identify Patients with Undiagnosed CKD","publication_year":2020,"publication_date":"2020-10-01","ids":{"openalex":"https://openalex.org/W4396998306","doi":"https://doi.org/10.1681/asn.20203110s1187c"},"language":"en","primary_location":{"id":"doi:10.1681/asn.20203110s1187c","doi":"https://doi.org/10.1681/asn.20203110s1187c","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1681/asn.20203110s1187c","pdf_url":null,"source":{"id":"https://openalex.org/S115693375","display_name":"Journal of the American Society of Nephrology","issn_l":"1046-6673","issn":["1046-6673","1533-3450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315620","host_organization_name":"American Society of Nephrology","host_organization_lineage":["https://openalex.org/P4310315620"],"host_organization_lineage_names":["American Society of Nephrology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Society of Nephrology","raw_type":"journal-article"},"volume":null,"type":"conference-abstract","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025097124","display_name":"Steven M. Brunelli","orcid":"https://orcid.org/0000-0001-8017-1069","observed_orcids":["https://orcid.org/0000-0001-8017-1069"]},"institutions":[{"id":"https://openalex.org/I4210148841","display_name":"DaVita Clinical Research (United States)","ror":"https://ror.org/04m8yw794","country_code":"US","type":"education","lineage":["https://openalex.org/I4210148841"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven M. Brunelli","raw_affiliation_strings":["Davita Clinical Research, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Davita Clinical Research, Minneapolis, MN","institution_ids":["https://openalex.org/I4210148841"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000101753","display_name":"Adam G. Walker","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148841","display_name":"DaVita Clinical Research (United States)","ror":"https://ror.org/04m8yw794","country_code":"US","type":"education","lineage":["https://openalex.org/I4210148841"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam G. Walker","raw_affiliation_strings":["Davita Clinical Research, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Davita Clinical Research, Minneapolis, MN","institution_ids":["https://openalex.org/I4210148841"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083129580","display_name":"Kathryn S. Gray","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148841","display_name":"DaVita Clinical Research (United States)","ror":"https://ror.org/04m8yw794","country_code":"US","type":"education","lineage":["https://openalex.org/I4210148841"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathryn S. Gray","raw_affiliation_strings":["Davita Clinical Research, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Davita Clinical Research, Minneapolis, MN","institution_ids":["https://openalex.org/I4210148841"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210148841"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"10S","first_page":"187","last_page":"187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10408","display_name":"Chronic Kidney Disease and Diabetes","score":0.42160001397132874,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10408","display_name":"Chronic Kidney Disease and Diabetes","score":0.42160001397132874,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.21119999885559082,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14400","display_name":"Medical Coding and Health Information","score":0.18129999935626984,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/chronic-kidney-disease","display_name":"chronic kidney disease","score":0.9890000224113464},{"id":"https://openalex.org/keywords/undiagnosed-ckd","display_name":"undiagnosed CKD","score":0.9539999961853027},{"id":"https://openalex.org/keywords/claims-based-algorithm","display_name":"claims-based algorithm","score":0.6639999747276306},{"id":"https://openalex.org/keywords/predictive-model","display_name":"prediction model","score":0.5580000281333923},{"id":"https://openalex.org/keywords/medicare-claims-data","display_name":"Medicare claims data","score":0.7059999704360962},{"id":"https://openalex.org/keywords/ckd-stages-3-5","display_name":"CKD stages 3-5","score":0.7110000252723694},{"id":"https://openalex.org/keywords/end-stage-renal-disease","display_name":"end-stage renal disease","score":0.6679999828338623},{"id":"https://openalex.org/keywords/dialysis","display_name":"dialysis","score":0.7099999785423279},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.5860000252723694},{"id":"https://openalex.org/keywords/risk-stratification","display_name":"risk stratification","score":0.6320000290870667},{"id":"https://openalex.org/keywords/positive-predictive-value","display_name":"positive predictive value","score":0.6159999966621399}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5034739375114441},{"id":"https://openalex.org/C3019813237","wikidata":"https://www.wikidata.org/wiki/Q65089264","display_name":"Model validation","level":2,"score":0.4212651252746582},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.4202519655227661},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.3716003894805908},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3214259147644043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24762657284736633},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.1937825083732605}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1681/asn.20203110s1187c","doi":"https://doi.org/10.1681/asn.20203110s1187c","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1681/asn.20203110s1187c","pdf_url":null,"source":{"id":"https://openalex.org/S115693375","display_name":"Journal of the American Society of Nephrology","issn_l":"1046-6673","issn":["1046-6673","1533-3450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315620","host_organization_name":"American Society of Nephrology","host_organization_lineage":["https://openalex.org/P4310315620"],"host_organization_lineage_names":["American Society of Nephrology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Society of Nephrology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.98580002784729,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4396992620","https://openalex.org/W4386888241","https://openalex.org/W4397289826","https://openalex.org/W2001422312","https://openalex.org/W2078346178","https://openalex.org/W4323566462","https://openalex.org/W4283778962","https://openalex.org/W7214230576","https://openalex.org/W2435880461","https://openalex.org/W3155357286"],"abstract_inverted_index":{"Background:":[0],"Chronic":[1],"kidney":[2,98,152],"disease":[3,99,153],"(CKD)":[4],"is":[5],"a":[6,65,127,191,275],"common":[7],"condition":[8],"and":[9,23,52,62,80,114,172,234,246],"often":[10],"goes":[11],"undiagnosed.":[12],"Unmanaged":[13],"CKD":[14,35,41,131,294],"can":[15],"progress":[16],"rapidly,":[17],"resulting":[18],"in":[19,44,138,159,221,230],"poor":[20],"clinical":[21,203],"outcomes":[22,51],"increased":[24],"health":[25,54],"care":[26,55],"costs.":[27,56],"Identification":[28],"of":[29,40,64,96,126,140,167,183,237,277],"individuals":[30],"who":[31,261],"may":[32],"have":[33,266,293],"undiagnosed":[34],"would":[36,292],"allow":[37],"for":[38,102,130,151],"implementation":[39],"management":[42],"practices":[43],"order":[45],"to":[46,68,134,179,211,258,265,274],"slow":[47],"progression,":[48],"potentially":[49],"improving":[50],"reducing":[53],"Here,":[57],"we":[58],"report":[59],"the":[60,124,143,147,160,164,168,181,222,231,241,270,283],"development":[61],"validation":[63,115,223],"claims-based":[66],"algorithm":[67,194,253,271],"identify":[69,259,282],"CKD.":[70,268],"Methods:":[71],"This":[72],"model":[73,189,206,242],"was":[74,123,190,217,243],"developed":[75,251],"using":[76],"Medicare":[77],"Part":[78,81],"A":[79],"B":[82],"claims":[83,101,257],"from":[84,89,201],"calendar":[85],"year":[86],"2017.":[87],"Data":[88],"378,460":[90],"unique":[91],"patients":[92,141,238,260,285],"with":[93],"no":[94],"evidence":[95],"end-stage":[97],"or":[100],"dialysis":[103],"through":[104],"April":[105],"2017":[106],"were":[107,154,177,272],"split":[108],"into":[109],"derivation":[110],"(n":[111,116],"=":[112,117,214,226],"189,203)":[113],"189,257)":[118],"sets.":[119],"The":[120,187,205,228],"predicted":[121],"outcome":[122],"presence":[125],"diagnosis":[128],"code":[129],"stages":[132],"3":[133],"5,":[135],"which":[136,216],"occurred":[137],"4.4%":[139],"within":[142],"data.":[144],"To":[145],"simulate":[146],"use":[148],"case,":[149],"codes":[150],"not":[155],"eligible":[156],"as":[157],"predictors":[158],"model.":[161],"Area":[162],"under":[163],"curve":[165,171],"(AUC)":[166],"receiver":[169],"operating":[170],"positive":[173],"predictive":[174],"value":[175],"(PPV)":[176],"used":[178],"assess":[180],"performance":[182],"candidate":[184],"models.":[185],"Results:":[186],"best":[188],"logistic":[192],"regression":[193],"based":[195],"on":[196],"94":[197],"input":[198],"terms":[199],"derived":[200],"13":[202],"constructs.":[204],"demonstrated":[207],"an":[208,252],"excellent":[209],"ability":[210],"discriminate":[212],"(AUC":[213,225],"0.90),":[215],"stable":[218],"when":[219],"tested":[220],"set":[224],"0.90).":[227],"PPV":[229],"top":[232,235],"1%":[233],"2%":[236],"identified":[239],"by":[240],"approximately":[244],"72%":[245],"59%,":[247],"respectively.":[248],"Conclusions:":[249],"We":[250],"that":[254],"uses":[255],"medical":[256],"are":[262],"most":[263],"likely":[264],"unrecognized":[267],"If":[269],"applied":[273],"population":[276],"10,000":[278],"patients,":[279],"it":[280],"could":[281],"100":[284],"at":[286],"highest":[287],"risk,":[288],"among":[289],"whom":[290],"72":[291],"if":[295],"tested.":[296]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2024-05-18T00:00:00"}