{"id":"https://openalex.org/W4396998514","doi":"https://doi.org/10.1681/asn.20203110s1210c","title":"Predicting Rapid eGFR Decline Using Electronic Health Record (EHR) Data Despite High Missingness in the CURE-CKD Registry","display_name":"Predicting Rapid eGFR Decline Using Electronic Health Record (EHR) Data Despite High Missingness in the CURE-CKD Registry","publication_year":2020,"publication_date":"2020-10-01","ids":{"openalex":"https://openalex.org/W4396998514","doi":"https://doi.org/10.1681/asn.20203110s1210c"},"language":"en","primary_location":{"id":"doi:10.1681/asn.20203110s1210c","doi":"https://doi.org/10.1681/asn.20203110s1210c","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1681/asn.20203110s1210c","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","is_traditional":false,"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/A5062819529","display_name":"Tyler A. Davis","orcid":"https://orcid.org/0000-0002-5088-0486","observed_orcids":["https://orcid.org/0000-0002-5088-0486"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tyler A. Davis","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029948058","display_name":"Panayiotis Petousis","orcid":"https://orcid.org/0000-0002-0696-608X","observed_orcids":["https://orcid.org/0000-0002-0696-608X"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panayiotis Petousis","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059876162","display_name":"Davina J. Zamanzadeh","orcid":"https://orcid.org/0000-0002-9360-0069","observed_orcids":["https://orcid.org/0000-0002-9360-0069"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Davina J. Zamanzadeh","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381772","display_name":"Xiaoyan Wang","orcid":"https://orcid.org/0000-0001-7997-8025","observed_orcids":["https://orcid.org/0000-0001-7997-8025"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyan Wang","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051133604","display_name":"Keith C. Norris","orcid":"https://orcid.org/0000-0003-3071-0700","observed_orcids":["https://orcid.org/0000-0003-3071-0700"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keith C. Norris","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007517849","display_name":"Obidiugwu Kenrik Duru","orcid":"https://orcid.org/0000-0001-8825-9460","observed_orcids":["https://orcid.org/0000-0001-8825-9460"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Obidiugwu Duru","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046793050","display_name":"Katherine R. Tuttle","orcid":"https://orcid.org/0000-0002-2235-0103","observed_orcids":["https://orcid.org/0000-0002-2235-0103"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katherine R. Tuttle","raw_affiliation_strings":["Providence St Joseph Health, Spokane, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Providence St Joseph Health, Spokane, WA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056478657","display_name":"Alex A. T. Bui","orcid":"https://orcid.org/0000-0002-4702-1373","observed_orcids":["https://orcid.org/0000-0002-4702-1373"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex Bui","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009102261","display_name":"Susanne B. Nicholas","orcid":"https://orcid.org/0000-0003-3535-9120","observed_orcids":["https://orcid.org/0000-0003-3535-9120"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Susanne B. Nicholas","raw_affiliation_strings":["University of California Los Angeles, Los Angeles, CA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Los Angeles, Los Angeles, CA;","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":null,"display_name":"CURE-CKD Registry Study Team","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"CURE-CKD Registry Study Team","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"210","last_page":"210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.6395999789237976,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.6395999789237976,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10408","display_name":"Chronic Kidney Disease and Diabetes","score":0.30709999799728394,"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":0.03280000016093254,"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":0.8370000123977661},{"id":"https://openalex.org/keywords/risk-prediction","display_name":"risk prediction","score":0.6959999799728394},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.8560000061988831},{"id":"https://openalex.org/keywords/electronic-health-records","display_name":"electronic health records","score":0.8349999785423279},{"id":"https://openalex.org/keywords/missing-data","display_name":"missing data","score":0.5820000171661377},{"id":"https://openalex.org/keywords/systolic-blood-pressure","display_name":"systolic blood pressure","score":0.7670000195503235},{"id":"https://openalex.org/keywords/type-2-diabetes","display_name":"type 2 diabetes","score":0.859000027179718},{"id":"https://openalex.org/keywords/hba1c","display_name":"HbA1c","score":0.8209999799728394},{"id":"https://openalex.org/keywords/ace-inhibitors-and-arbs","display_name":"ACE inhibitors and ARBs","score":0.8799999952316284},{"id":"https://openalex.org/keywords/kidney-failure-progression","display_name":"kidney failure progression","score":0.7850000262260437},{"id":"https://openalex.org/keywords/risk-stratification","display_name":"risk stratification","score":0.5080000162124634},{"id":"https://openalex.org/keywords/big-data-analytics-in-healthcare","display_name":"big data analytics in healthcare","score":0.38999998569488525},{"id":"https://openalex.org/keywords/automated-clinical-decision-support","display_name":"automated clinical decision support","score":0.4180000126361847}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7531343698501587},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.653823733329773},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6462014317512512},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.5929320454597473},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.36921489238739014},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.3547349274158478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.17623072862625122},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.13677474856376648},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1681/asn.20203110s1210c","doi":"https://doi.org/10.1681/asn.20203110s1210c","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1681/asn.20203110s1210c","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":[{"id":"https://metadata.un.org/sdg/3","score":0.9940000176429749,"display_name":"Good health and well-being"}],"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/W4396990442","https://openalex.org/W4397041384","https://openalex.org/W3214363017","https://openalex.org/W4397024563","https://openalex.org/W7206184324","https://openalex.org/W4281690773","https://openalex.org/W7161764469","https://openalex.org/W3087296896","https://openalex.org/W4396998309","https://openalex.org/W3120001827"],"abstract_inverted_index":{"Background:":[0],"Patients":[1],"with":[2,100,108,175,225,308,315],"rapid":[3,40,57,245,297,320],"eGFR":[4,41,46,109,246,298,321],"decline":[5,23,42,58,180,247,299],"tend":[6],"to":[7,9,312],"progress":[8],"kidney":[10,91],"failure.":[11],"Automated":[12],"tools":[13],"can":[14],"identify":[15,313],"individuals":[16],"at":[17,53],"risk":[18,38,55,141,161,167,178,230,251,259,294,318],"of":[19,39,56,82,143,154,179,205,218,244],"severe":[20],"renal":[21],"function":[22],"and":[24,50,79,103,116,126,158,213,220,234,281,303],"facilitate":[25],"disease":[26,92],"mitigation.":[27],"We":[28,114,138,238,287],"describe":[29],"a":[30,118,121,127,134,289,293],"deep":[31],"neural":[32],"network":[33],"(DNN)":[34],"for":[35,105,296,319],"predicting":[36],"the":[37,60,80,140,155,164,170,176,184,200,208,240,249,254,261,265,309],"(>40%":[43],"decrease":[44],"in":[45],"over":[47,111],"2":[48,85,112],"years)":[49],"identified":[51,182,239],"populations":[52],"higher":[54,258],"using":[59,133,169,183,300],"CURE-CKD":[61],"Registry.":[62],"Methods:":[63],"Variables":[64],"include:":[65],"age,":[66],"sex,":[67],"race/ethnicity,":[68],"ACE":[69],"inhibitor/ARB":[70],"use,":[71],"eGFR,":[72],"systolic":[73],"blood":[74],"pressure":[75],"(SBP),":[76],"hemoglobin":[77],"A1C,":[78],"diagnosis":[81],"hypertension,":[83],"type":[84],"diabetes":[86],"(DM),":[87],"pre-DM":[88],"or":[89],"chronic":[90],"(CKD)":[93],"based":[94,147],"on":[95,148,188,207],"EHR":[96],"coding":[97],"from":[98],"patients":[99],"CKD":[101,106,268],"(N=93,567)":[102],"at-risk":[104],"(N=913,289)":[107],"\u226515ml/min/1.73m2":[110],"years.":[113],"trained":[115],"validated":[117],"5-layer":[119],"DNN,":[120],"logistic":[122],"regression":[123],"(LR)":[124],"model,":[125],"gradient":[128],"boosted":[129],"tree":[130],"(GBT)":[131],"model":[132,295],"60/20/20":[135],"train/test/validation":[136],"split.":[137],"computed":[139],"distribution":[142,162,168],"all":[144,149],"25,475":[145],"subpopulations,":[146],"possible":[150],"expert":[151],"defined":[152],"combinations":[153],"above":[156],"variables,":[157],"compared":[159],"this":[160],"against":[163],"whole":[165],"population's":[166],"Kolmogorov-Smirnov":[171],"(KS)":[172],"test.":[173],"Subgroups":[174],"highest":[177,190,227,250],"were":[181,236,264],"KS":[185,310],"test":[186,209],"(p<0.05)":[187],"our":[189],"performing":[191],"model.":[192],"Results:":[193],"The":[194,211,223],"DNN":[195],"achieved":[196,215],"an":[197,216],"area":[198],"under":[199],"receiver":[201],"operating":[202],"curve":[203],"(AUC-ROC)":[204],"0.75":[206],"set.":[210],"LR":[212],"GBT":[214],"AUC-ROC":[217],"0.72":[219],"0.73,":[221],"respectively.":[222],"subpopulations":[224,260,314],"significantly":[226,257,316],"average":[228],"predicted":[229],"across":[231,248],"training,":[232],"validation,":[233],"testing":[235],"17,734.":[237],"most":[241,266],"frequent":[242],"predictors":[243],"populations.":[252],"Of":[253],"top":[255],"100":[256],"following":[262],"variables":[263],"frequent:":[267],"(100%),":[269],"SBP":[270],">":[271,283],"140":[272],"mmHg":[273],"(72%),":[274],"age":[275],"45-66":[276],"years":[277],"(56%),":[278],"DM":[279],"(52%),":[280],"A1C":[282],"8":[284],"(50%).":[285],"Conclusions:":[286],"developed":[288],"methodology":[290],"that":[291],"uses":[292],"big":[301],"data":[302],"used":[304],"its":[305],"predictions,":[306],"along":[307],"test,":[311],"high":[317],"decline.":[322],"Funding:":[323],"Other":[324],"NIH":[325],"Support":[326],"-":[327],"NIMHD":[328]},"counts_by_year":[],"updated_date":"2026-09-22T06:50:58.402377","created_date":"2024-05-18T00:00:00"}
