{"id":"https://openalex.org/W53458235","doi":null,"title":"Predicting hemodialysis mortality utilizing blood pressure trends.","display_name":"Predicting hemodialysis mortality utilizing blood pressure trends.","publication_year":2008,"publication_date":"2008-11-06","ids":{"openalex":"https://openalex.org/W53458235","mag":"53458235","pmid":"https://pubmed.ncbi.nlm.nih.gov/18999118","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/2655936"},"language":"en","primary_location":{"id":"pmid:18999118","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18999118","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","raw_type":"Journal Article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC2655936/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054080485","display_name":"Ronilda C. Lacson","orcid":"https://orcid.org/0000-0003-3300-1176","observed_orcids":["https://orcid.org/0000-0003-3300-1176"]},"institutions":[{"id":"https://openalex.org/I1283280774","display_name":"Brigham and Women's Hospital","ror":"https://ror.org/04b6nzv94","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I121934306","https://openalex.org/I1283280774","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ronilda Lacson","raw_affiliation_strings":["Decision Systems Group, Brigham and Women's Hospital, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Decision Systems Group, Brigham and Women's Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I1283280774"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5054080485"],"corresponding_institution_ids":["https://openalex.org/I1283280774"],"apc_list":null,"apc_paid":null,"fwci":2.5495,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.87445887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"369","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10291","display_name":"Dialysis and Renal Disease Management","score":0.9932000041007996,"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/T10291","display_name":"Dialysis and Renal Disease Management","score":0.9932000041007996,"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":0.004800000227987766,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hemodialysis","display_name":"hemodialysis","score":0.9110000133514404},{"id":"https://openalex.org/keywords/mortality-prediction","display_name":"mortality prediction","score":0.9950000047683716},{"id":"https://openalex.org/keywords/systolic-blood-pressure","display_name":"systolic blood pressure","score":0.8539999723434448},{"id":"https://openalex.org/keywords/blood-pressure-trends","display_name":"blood pressure trends","score":0.996999979019165},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9309999942779541},{"id":"https://openalex.org/keywords/end-stage-renal-disease","display_name":"end-stage renal disease","score":0.8199999928474426}],"concepts":[{"id":"https://openalex.org/C2778063415","wikidata":"https://www.wikidata.org/wiki/Q391744","display_name":"Hemodialysis","level":2,"score":0.7346621155738831},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.6759576201438904},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6609383225440979},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5664675235748291},{"id":"https://openalex.org/C2779978075","wikidata":"https://www.wikidata.org/wiki/Q202301","display_name":"Dialysis","level":2,"score":0.53593510389328},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.5253654718399048},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.42292213439941406},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41398999094963074},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4120906591415405},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.40503937005996704},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25962305068969727},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25495707988739014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.21976661682128906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17483830451965332},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.06821808218955994}],"mesh":[{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006435","descriptor_name":"Renal Dialysis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007676","descriptor_name":"Kidney Failure, Chronic","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D007676","descriptor_name":"Kidney Failure, Chronic","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":false},{"descriptor_ui":"D007676","descriptor_name":"Kidney Failure, Chronic","qualifier_ui":"Q000517","qualifier_name":"prevention & control","is_major_topic":false},{"descriptor_ui":"D012307","descriptor_name":"Risk Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014481","descriptor_name":"United States","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015994","descriptor_name":"Incidence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015996","descriptor_name":"Survival Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016016","descriptor_name":"Proportional Hazards Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016019","descriptor_name":"Survival Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016896","descriptor_name":"Treatment Outcome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":3,"locations":[{"id":"pmid:18999118","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18999118","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:2655936","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC2655936/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AMIA Annu Symp Proc","raw_type":"Text"},{"id":"mag:53458235","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18999118","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"PubMed","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:2655936","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC2655936/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AMIA Annu Symp Proc","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":1.0}],"study_designs":[{"display_name":"Observational Study","id":"https://openalex.org/study-designs/observational-study"}],"awards":[{"id":"https://openalex.org/G6463986645","display_name":"Assessing quality of individual predictions in medical decision support systems","funder_award_id":"7r01lm009520-04","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G9000904321","display_name":"Biomedical Informatics and Data Science Research Training Program (BIRT)","funder_award_id":"T15LM007092","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1711367045","https://openalex.org/W2019472680","https://openalex.org/W2025589168","https://openalex.org/W2033634242","https://openalex.org/W2035360618","https://openalex.org/W2082891347","https://openalex.org/W2098577659","https://openalex.org/W2113375444","https://openalex.org/W2172073485"],"related_works":["https://openalex.org/W4253547026","https://openalex.org/W3155682230","https://openalex.org/W2966021322","https://openalex.org/W7164377381","https://openalex.org/W2082891347","https://openalex.org/W2240349756","https://openalex.org/W2061882292","https://openalex.org/W2346680732","https://openalex.org/W4323537687","https://openalex.org/W3011119737"],"abstract_inverted_index":{"BACKGROUND:":[0],"Mean":[1],"Systolic":[2],"Blood":[3],"Pressure":[4],"(SBP)":[5],"is":[6,17],"a":[7,38,73,99,131],"predictor":[8],"of":[9,29,34,91,138],"mortality":[10,143],"in":[11,41,52,98,145],"hemodialysis":[12],"(HD)":[13],"patients.":[14,147],"The":[15,104,125,136],"hypothesis":[16],"that":[18],"transforming":[19],"SBP":[20,59,139],"measurements":[21],"to":[22,72,118],"reflect":[23],"trends":[24,140],"would":[25],"improve":[26],"the":[27,42,107,121],"quality":[28],"predictions.":[30],"METHOD:":[31],"Data":[32],"consisted":[33],"4,500":[35],"patients":[36],"from":[37],"dialysis":[39],"provider":[40],"US":[43],"with":[44],"at":[45],"least":[46],"six":[47,55],"months":[48],"follow-up.":[49],"Relative":[50],"Difference":[51],"Percentage":[53],"yielded":[54],"transformed":[56,110],"variables,":[57],"representing":[58],"trends.":[60],"Models":[61],"were":[62,70],"constructed":[63],"using":[64,109],"Support":[65],"Vector":[66],"Machine":[67],"(SVM).":[68],"RESULTS":[69],"compared":[71,117],"baseline":[74,122],"model":[75,108,123],"utilizing":[76],"six-month":[77],"mean":[78],"SBP.":[79],"All":[80],"models":[81],"included":[82],"age,":[83],"gender,":[84],"race,":[85],"diabetes,":[86],"vintage,":[87],"and":[88],"BMI.":[89],"Pooling":[90],"repeated":[92,96],"observations":[93,97],"incorporated":[94],"all":[95],"generalized":[100],"person-month":[101],"approach.":[102],"RESULTS:":[103],"AUC":[105,126],"for":[106,120],"variables":[111],"on":[112],"unseen":[113],"data":[114,133],"was":[115,127],"0.70,":[116],"0.63":[119],"(p<0.00001).":[124],"0.69":[128],"when":[129],"modeling":[130],"pooled":[132],"set.":[134],"CONCLUSION:":[135],"use":[137],"significantly":[141],"improved":[142],"prediction":[144],"HD":[146]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
