{"id":"https://openalex.org/W4397045501","doi":"https://doi.org/10.1681/asn.20233411s194b","title":"Machine Learning-Based Risk Prediction Model for ICU Survival After Continuous Renal Replacement Therapy Initiation: A WEROCK Study","display_name":"Machine Learning-Based Risk Prediction Model for ICU Survival After Continuous Renal Replacement Therapy Initiation: A WEROCK Study","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4397045501","doi":"https://doi.org/10.1681/asn.20233411s194b"},"language":"en","primary_location":{"id":"doi:10.1681/asn.20233411s194b","doi":"https://doi.org/10.1681/asn.20233411s194b","is_oa":false,"landing_page_url":"https://doi.org/10.1681/asn.20233411s194b","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/A5030629237","display_name":"Shina Menon","orcid":"https://orcid.org/0000-0001-8473-0307","observed_orcids":["https://orcid.org/0000-0001-8473-0307"]},"institutions":[{"id":"https://openalex.org/I1295499534","display_name":"Seattle Children's Hospital","ror":"https://ror.org/01njes783","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1295499534"]},{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shina Menon","raw_affiliation_strings":["Seattle Children's Hospital, Seattle, WA;","University of Washington, Seattle, WA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seattle Children's Hospital, Seattle, WA;","institution_ids":["https://openalex.org/I1295499534"]},{"raw_affiliation_string":"University of Washington, Seattle, WA;","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088942765","display_name":"Sameer V. Thadani","orcid":"https://orcid.org/0000-0001-5178-9839","observed_orcids":["https://orcid.org/0000-0001-5178-9839"]},"institutions":[{"id":"https://openalex.org/I181547552","display_name":"Baylor College of Medicine","ror":"https://ror.org/02pttbw34","country_code":"US","type":"education","lineage":["https://openalex.org/I181547552","https://openalex.org/I2801539370"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sameer Thadani","raw_affiliation_strings":["Baylor College of Medicine, Houston, TX"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baylor College of Medicine, Houston, TX","institution_ids":["https://openalex.org/I181547552"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052889588","display_name":"Katja M. Gist","orcid":"https://orcid.org/0000-0002-7427-670X","observed_orcids":["https://orcid.org/0000-0002-7427-670X"]},"institutions":[{"id":"https://openalex.org/I1285204247","display_name":"Cincinnati Children's Hospital Medical Center","ror":"https://ror.org/01hcyya48","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1285204247"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katja M. Gist","raw_affiliation_strings":["Cincinnati Children's Hospital Medical Center, Cincinnati, OH;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cincinnati Children's Hospital Medical Center, Cincinnati, OH;","institution_ids":["https://openalex.org/I1285204247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066720542","display_name":"Danielle Elise Soranno","orcid":"https://orcid.org/0000-0001-7019-809X","observed_orcids":["https://orcid.org/0000-0001-7019-809X"]},"institutions":[{"id":"https://openalex.org/I4394709130","display_name":"Indiana University School of Medicine","ror":"https://ror.org/02ets8c94","country_code":"US","type":"education","lineage":["https://openalex.org/I4394709130","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danielle E. Soranno","raw_affiliation_strings":["Indiana University School of Medicine, Indianapolis, IN;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University School of Medicine, Indianapolis, IN;","institution_ids":["https://openalex.org/I4394709130"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081589882","display_name":"Danny T Y Wu","orcid":"https://orcid.org/0000-0002-7658-3754","observed_orcids":["https://orcid.org/0000-0002-7658-3754"]},"institutions":[{"id":"https://openalex.org/I1285204247","display_name":"Cincinnati Children's Hospital Medical Center","ror":"https://ror.org/01hcyya48","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1285204247"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danny T. Wu","raw_affiliation_strings":["Cincinnati Children's Hospital Medical Center, Cincinnati, OH;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cincinnati Children's Hospital Medical Center, Cincinnati, OH;","institution_ids":["https://openalex.org/I1285204247"]}]},{"author_position":"last","author":{"id":null,"display_name":"WE-ROCK.","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"WE-ROCK.","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":"34","issue":"11S","first_page":"94","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10684","display_name":"Acute Kidney Injury Research","score":0.9984999895095825,"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/T10684","display_name":"Acute Kidney Injury Research","score":0.9984999895095825,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.00039999998989515007,"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/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/continuous-renal-replacement-therapy","display_name":"continuous renal replacement therapy","score":0.9990000128746033},{"id":"https://openalex.org/keywords/pediatric-acute-kidney-injury","display_name":"pediatric acute kidney injury","score":0.6380000114440918},{"id":"https://openalex.org/keywords/fluid-overload","display_name":"fluid overload","score":0.9909999966621399},{"id":"https://openalex.org/keywords/hospital-discharge-prediction","display_name":"hospital discharge prediction","score":0.9229999780654907},{"id":"https://openalex.org/keywords/risk-prediction-model","display_name":"risk prediction model","score":0.7480000257492065},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8550000190734863},{"id":"https://openalex.org/keywords/critically-ill-children","display_name":"critically ill children","score":0.7570000290870667},{"id":"https://openalex.org/keywords/machine-learning-prediction-models","display_name":"machine learning prediction models","score":0.5329999923706055},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.4339999854564667},{"id":"https://openalex.org/keywords/survival-to-hospital-discharge","display_name":"survival to hospital discharge","score":0.9679999947547913}],"concepts":[{"id":"https://openalex.org/C2779541074","wikidata":"https://www.wikidata.org/wiki/Q185643","display_name":"Renal replacement therapy","level":2,"score":0.9048442840576172},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5385014414787292},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.43767282366752625}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1681/asn.20233411s194b","doi":"https://doi.org/10.1681/asn.20233411s194b","is_oa":false,"landing_page_url":"https://doi.org/10.1681/asn.20233411s194b","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","display_name":"Good health and well-being","score":1.0}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4405463783","https://openalex.org/W4389729995","https://openalex.org/W4397045472","https://openalex.org/W3005219125","https://openalex.org/W4416782643","https://openalex.org/W4416878088","https://openalex.org/W4401707926","https://openalex.org/W7084124284","https://openalex.org/W4400089652","https://openalex.org/W4289547282"],"abstract_inverted_index":{"Background:":[0],"Continuous":[1],"renal":[2],"replacement":[3],"therapy":[4],"(CRRT)":[5],"is":[6,30,73,237,374,385],"preferred":[7],"in":[8,26,68,123,233,250,263,376,387,396],"critically":[9,264],"ill":[10,265],"pediatric":[11,251],"patients":[12,27,92,252],"with":[13,97,147,161],"acute":[14],"kidney":[15],"injury":[16],"(AKI)":[17],"and/or":[18,101],"fluid":[19],"overload":[20],"(FO).":[21],"Prediction":[22],"of":[23,63,126,184,192],"clinical":[24,34],"outcomes":[25,106],"on":[28,197],"CRRT":[29,98],"challenging":[31],"given":[32],"heterogeneous":[33],"practices":[35],"and":[36,50,111,136,157,164,247,287,378,389],"study":[37,72,78],"population.":[38],"Our":[39,83],"aim":[40],"was":[41,116,176,201,211,257],"to":[42,45,109,169,230,242,245,259,302,326,401],"predict":[43,243],"survival":[44,108,244],"intensive":[46],"care":[47],"unit":[48],"(ICU)":[49],"hospital":[51,248],"(HOSP)":[52],"discharge":[53,249,304,403],"using":[54,203],"machine":[55],"learning":[56,289],"(ML)":[57],"techniques.":[58],"Methods:":[59],"The":[60,130,139,173,190,255],"Worldwide":[61],"Exploration":[62],"Renal":[64],"Replacement":[65],"Outcomes":[66],"Collaborative":[67],"Kidney":[69],"Disease":[70],"(WE-ROCK)":[71,222],"a":[74,279],"retrospective":[75],"international":[76],"multicenter":[77],"(32":[79],"centers,":[80],"7":[81],"nations).":[82],"methods":[84],"have":[85],"been":[86],"published":[87,261,375,386],"previously.":[88],"We":[89,267],"included":[90,142],"991":[91],"aged":[93],"0-25":[94],"years":[95],"treated":[96],"for":[99,366],"AKI":[100],"FO":[102],"from":[103],"2018-2021.":[104],"Primary":[105],"were":[107,132],"ICU":[110,246,303,367,402],"HOSP":[112],"discharge.":[113],"Feature":[114],"selection":[115],"done":[117],"manually":[118],"through":[119],"team":[120],"discussions,":[121],"resulting":[122],"61":[124],"out":[125],"119":[127],"demographics":[128],"variables.":[129],"data":[131],"split":[133],"into":[134],"training(80%)":[135],"testing(20%)":[137],"subsets.":[138],"ML":[140,240,286,363],"process":[141],"5":[143],"algorithms":[144],"(Logistic":[145],"Regression":[146],"L2":[148],"regularization,":[149],"Decision":[150],"Tree,":[151],"Random":[152,209,308,317,332,341],"Forest,":[153],"Gradient":[154,352],"Boosting":[155],"Machine,":[156],"Support":[158],"Vector":[159],"Machine":[160],"linear":[162],"kernel)":[163],"used":[165],"5-fold":[166],"cross":[167],"validation":[168],"train":[170],"the":[171,179,182,185,193,198,238,275,397],"models.":[172],"model":[174,196,241,364],"performance":[175,191,256,365],"determined":[177],"by":[178,273],"Area":[180],"Under":[181],"Curve":[183],"Receiver":[186],"Operating":[187],"Characteristic":[188],"(AUCROC).":[189],"best":[194],"trained":[195],"testing":[199],"dataset":[200],"reported":[202,395],"standard":[204],"metrics":[205],"(Table":[206],"1).":[207],"Results:":[208],"Forest":[210,309,318,333,342],"our":[212,220,271],"highest":[213],"performing":[214],"algorithm.":[215],"Table":[216,361,404],"1":[217,405],"shows":[218],"that":[219],"models":[221,262,272],"achieved":[223],"comparable":[224],"or":[225],"slightly":[226],"higher":[227],"AUROC":[228],"compared":[229],"previous":[231],"studies":[232],"adults.":[234,266],"Conclusions:":[235],"This":[236],"first":[239],"requiring":[253],"CRRT.":[254],"similar":[258],"previously":[260],"will":[268],"continue":[269],"refining":[270],"expanding":[274],"input":[276],"variables,":[277],"conducting":[278],"more":[280],"sophisticated":[281],"feature":[282],"selection,":[283],"experimenting":[284],"advanced":[285],"deep":[288],"algorithms.":[290],"-":[291],"Source":[292],"Best":[293],"Model":[294],"AUC":[295],"Sensitivity":[296],"Specificity":[297],"Precision":[298],"Accuracy":[299],"F1-score":[300],"Survival":[301,325,400],"Kang":[305,329,371],"et":[306,330,350,372,383],"al.":[307,331,351,373,384],"0.784":[310],"NR":[311,312,313,335,336,337],"0.690":[314],"0.762":[315],"WE-ROCK":[316,340],"0.799":[319],"0.922":[320],"0.648":[321],"0.720":[322],"0.719":[323,346],"0.808":[324],"Hospital":[327,369],"dischange":[328],"0.768":[334],"0.711":[338],"0.790":[339],"0.788":[343],"0.887":[344],"0.573":[345],"0.714":[347],"0.794":[348],"Hung":[349],"Boost":[353],"0.823":[354],"0.742":[355],"0.787":[356],"0.881":[357],"0.756":[358],"0.801":[359],"Models":[360],"1.":[362],"&":[368],"mortality":[370],"2020":[377],"available":[379,390],"at":[380,391],"https://doi.org/10.1186/s13054-020-2752-7":[381],"Huang":[382],"2022":[388],"https://doi.org/10.3390/diagnostics12061496":[392],"NR:":[393],"Not":[394],"paper":[398],"ICU-D:":[399]},"counts_by_year":[],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2024-05-19T00:00:00"}