{"id":"https://openalex.org/W7202149795","doi":"https://doi.org/10.21203/rs.3.rs-9463379/v1","title":"Statistical learning and prediction of diseases associated with the occurrence of death in the emergency department: An observational study on administrative data from Saint Joseph Hospital in Kinshasa-DRC","display_name":"Statistical learning and prediction of diseases associated with the occurrence of death in the emergency department: An observational study on administrative data from Saint Joseph Hospital in Kinshasa-DRC","publication_year":2026,"publication_date":"2026-08-10","ids":{"openalex":"https://openalex.org/W7202149795","doi":"https://doi.org/10.21203/rs.3.rs-9463379/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-9463379/v1","doi":"https://doi.org/10.21203/rs.3.rs-9463379/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-9463379/v1","pdf_url":"https://www.researchsquare.com/article/rs-9463379/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-9463379/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070474962","display_name":"Richard Ingwe Chuy","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Richard Ingwe Chuy","raw_affiliation_strings":["Health knowledge center in DR. Congo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health knowledge center in DR. Congo","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098537139","display_name":"Kalombola Didier Chuy","orcid":"https://orcid.org/0009-0009-1679-0311","observed_orcids":["https://orcid.org/0009-0009-1679-0311"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Didier Chuy Kalombola","raw_affiliation_strings":["Health knowledge center in DR. Congo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health knowledge center in DR. Congo","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120507451","display_name":"Julien Neze-Sebakunzi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julien Neze-Sebakunzi","raw_affiliation_strings":["Community of Sant\u2019Egidio, DREAM Program DRC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Community of Sant\u2019Egidio, DREAM Program DRC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5146423580","display_name":"Jo\u00ebl Ekofo Yombo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jo\u00ebl Ekofo Yombo","raw_affiliation_strings":["Health knowledge center in DR. Congo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health knowledge center in DR. Congo","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076382961","display_name":"Chrispin Kabanga","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chrispin Kabanga Mbala","raw_affiliation_strings":["Health knowledge center in DR. Congo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health knowledge center in DR. Congo","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103436224","display_name":"Faustin Chenge Mukalenge","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Faustin Chenge Mukalenge","raw_affiliation_strings":["Health knowledge center in DR. Congo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health knowledge center in DR. Congo","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.37279999256134033,"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":0.37279999256134033,"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/T11095","display_name":"Emergency and Acute Care Studies","score":0.3596000075340271,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"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":0.1761000007390976,"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/in-hospital-mortality","display_name":"in-hospital mortality","score":0.7459999918937683},{"id":"https://openalex.org/keywords/emergency-department","display_name":"emergency department","score":0.8130000233650208},{"id":"https://openalex.org/keywords/mortality-prediction","display_name":"mortality prediction","score":0.8100000023841858},{"id":"https://openalex.org/keywords/disease-specific-mortality","display_name":"disease-specific mortality","score":0.38999998569488525},{"id":"https://openalex.org/keywords/shock","display_name":"shock","score":0.40700000524520874},{"id":"https://openalex.org/keywords/sepsis","display_name":"sepsis","score":0.9990000128746033},{"id":"https://openalex.org/keywords/tuberculosis","display_name":"tuberculosis","score":0.6859999895095825},{"id":"https://openalex.org/keywords/pneumonia","display_name":"pneumonia","score":0.9570000171661377},{"id":"https://openalex.org/keywords/coma","display_name":"coma","score":0.9160000085830688},{"id":"https://openalex.org/keywords/meningoencephalitis","display_name":"meningoencephalitis","score":0.9829999804496765},{"id":"https://openalex.org/keywords/cancer","display_name":"cancer","score":0.9710000157356262},{"id":"https://openalex.org/keywords/statistical-learning-models","display_name":"statistical learning models","score":0.4909999966621399},{"id":"https://openalex.org/keywords/hospital-administrative-data","display_name":"hospital administrative data","score":0.5139999985694885},{"id":"https://openalex.org/keywords/emergency-department-crowding","display_name":"emergency department overcrowding","score":0.4000000059604645}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.7835000157356262},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7197999954223633},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.5898000001907349},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5074999928474426},{"id":"https://openalex.org/C2780724011","wikidata":"https://www.wikidata.org/wiki/Q1295316","display_name":"Emergency department","level":2,"score":0.4781000018119812},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.4544999897480011},{"id":"https://openalex.org/C179755657","wikidata":"https://www.wikidata.org/wiki/Q58702","display_name":"Mortality rate","level":2,"score":0.38280001282691956},{"id":"https://openalex.org/C29374701","wikidata":"https://www.wikidata.org/wiki/Q1931388","display_name":"Cause of death","level":3,"score":0.3637999892234802},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.3434999883174896},{"id":"https://openalex.org/C65409693","wikidata":"https://www.wikidata.org/wiki/Q425265","display_name":"Statistical significance","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C167135981","wikidata":"https://www.wikidata.org/wiki/Q2146302","display_name":"Retrospective cohort study","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C191093355","wikidata":"https://www.wikidata.org/wiki/Q9250577","display_name":"Exact test","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C187212893","wikidata":"https://www.wikidata.org/wiki/Q123028","display_name":"Pediatrics","level":1,"score":0.2897999882698059},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C545288138","wikidata":"https://www.wikidata.org/wiki/Q860447","display_name":"Emergency medical services","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C156957248","wikidata":"https://www.wikidata.org/wiki/Q1862216","display_name":"Odds ratio","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-9463379/v1","doi":"https://doi.org/10.21203/rs.3.rs-9463379/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-9463379/v1","pdf_url":"https://www.researchsquare.com/article/rs-9463379/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-9463379/v1","doi":"https://doi.org/10.21203/rs.3.rs-9463379/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-9463379/v1","pdf_url":"https://www.researchsquare.com/article/rs-9463379/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[{"score":0.9940000176429749,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[{"id":"https://openalex.org/study-designs/observational-study","display_name":"Observational Study"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202149795.pdf","grobid_xml":"https://content.openalex.org/works/W7202149795.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1831050183","https://openalex.org/W2022731453","https://openalex.org/W2101049618","https://openalex.org/W2200122354","https://openalex.org/W2508223490","https://openalex.org/W2531244858","https://openalex.org/W2535684812","https://openalex.org/W2566334045","https://openalex.org/W2595085771","https://openalex.org/W2623788409","https://openalex.org/W2753476025","https://openalex.org/W2809519794","https://openalex.org/W2888688603","https://openalex.org/W2888715561","https://openalex.org/W2898812155","https://openalex.org/W2901133597","https://openalex.org/W2912813892","https://openalex.org/W2914367087","https://openalex.org/W2945217603","https://openalex.org/W2946391707","https://openalex.org/W2964010563","https://openalex.org/W2967527181","https://openalex.org/W2970368518","https://openalex.org/W2982007159","https://openalex.org/W2991565024","https://openalex.org/W3000897776","https://openalex.org/W3005418035","https://openalex.org/W3015738796","https://openalex.org/W3033440222"],"related_works":["https://openalex.org/W4406425609","https://openalex.org/W3011090946","https://openalex.org/W2968557641","https://openalex.org/W4387406237","https://openalex.org/W2900149836","https://openalex.org/W3197153878","https://openalex.org/W3107932444","https://openalex.org/W7139916598","https://openalex.org/W2978091192","https://openalex.org/W2787651455"],"abstract_inverted_index":{"Abstract":[0],"Objective":[1],"The":[2,23,89,137,175,206,274],"determinants,":[3],"timing":[4],"and":[5,82,118,124,139,166,190,200,229,269,293,338],"predictive":[6,51,110],"tools":[7],"of":[8,52,55,65,72,91,114,126,149,161,178,278,297,329,332,348],"mortality":[9],"in":[10,20,32,38,76,103,225,231,281,326,345],"emergency":[11,33,70,105],"departments":[12,34,71],"for":[13,121],"specific":[14],"diseases":[15,24,47,325],"have":[16,35],"already":[17],"been":[18,36],"evaluated":[19],"several":[21],"studies.":[22],"that":[25,309],"are":[26,49],"most":[27],"likely":[28],"to":[29,44,68,145,321,341],"cause":[30],"death":[31,56,333],"studied":[37],"limited":[39],"numbers.":[40],"This":[41],"study":[42],"aimed":[43],"identify":[45],"the":[46,53,69,104,115,147,153,173,179,188,193,214,226,232,241,244,298,311,314,322,327,330,346],"which":[48],"possibly":[50],"occurrence":[54,90,331],"by":[57],"using":[58],"statistical":[59],"learning":[60,318],"methods.":[61],"Methods":[62],"Administrative":[63],"data":[64,134,155],"patients":[66],"admitted":[67],"Saint":[73],"Joseph":[74],"Hospital":[75],"Kinshasa":[77],"between":[78],"January":[79],"1st":[80],"2018":[81],"December":[83],"31st":[84],"2019":[85],"were":[86,112,119,130,143,170,196,248,284],"reviewed":[87],"retrospectively.":[88],"death,":[92],"defined":[93],"as":[94,249],"a":[95,99,306],"patient":[96],"who":[97],"had":[98],"\"deceased\"":[100],"outcome":[101],"reported":[102],"registers,":[106],"was":[107,182,305],"predicted.":[108],"Nineteen":[109],"conditions":[111],"modalities":[113],"'diagnosis'":[116],"variable":[117],"adjusted":[120],"age,":[122],"gender":[123],"number":[125],"diagnoses.":[127],"Six":[128],"models":[129,300],"run":[131],"on":[132,152],"this":[133],"set,":[135,156],"70%.":[136],"AUC":[138],"its":[140],"confidence":[141],"interval":[142],"used":[144],"evaluate":[146],"performance":[148],"each":[150,239],"model":[151,308],"test":[154,191,215,233],"30%.":[157],"Results":[158],"A":[159],"total":[160],"five":[162],"thousand":[163],"one":[164],"hundred":[165],"seventy-two":[167],"(5172)":[168],"subjects":[169],"incorporated":[171],"into":[172],"analyses.":[174],"average":[176],"age":[177],"complete":[180],"dataset":[181,208,216],"47.9":[183],"\u00b1":[184,198,202],"20.0":[185],"years.":[186],"In":[187],"training":[189,207,227],"datasets,":[192],"mean":[194],"ages":[195],"48.0":[197],"20.2":[199],"47.4":[201],"20.4":[203],"years,":[204],"respectively.":[205],"comprised":[209],"50%":[210],"male":[211,219],"patients,":[212],"while":[213],"included":[217],"48.8%":[218],"patients.":[220,349],"Among":[221],"these":[222],"individuals,":[223],"7.5%":[224],"group":[228,234],"7.4%":[230],"did":[235],"not":[236],"survive.":[237],"For":[238],"model,":[240],"area":[242,312],"under":[243,313],"curve":[245],"(AUC)":[246],"values":[247],"follows:":[250],"ElasticNet":[251,304],"0.746":[252],"[0.689\u20130.784],":[253],"logistic":[254],"regression":[255],"0.735":[256,260],"[0.687\u20130.783],":[257,261,264],"neural":[258],"networks":[259],"xGboost":[262],"0.734":[263],"decision":[265],"trees":[266],"0.50":[267],"[0.50\u20130.50],":[268],"random":[270],"forest":[271],"0.428":[272],"[0.391\u20130.464].":[273],"six":[275,299],"primary":[276],"predictors":[277],"mortality,":[279],"listed":[280],"descending":[282],"order,":[283],"shock":[285],"states,":[286],"sepsis,":[287],"tuberculosis":[288],"or":[289],"pneumonia,":[290],"coma,":[291],"meningoencephalitis,":[292],"cancer.":[294],"Conclusions":[295],"Four":[296],"used,":[301],"performed":[302],"well.":[303],"network":[307],"maximized":[310],"ROC":[315],"curve.":[316],"Statistical":[317],"methods":[319],"applied":[320],"twelve":[323],"potential":[324],"prediction":[328],"could":[334],"help":[335],"policy":[336],"makers":[337],"health":[339],"professionals":[340],"approach":[342],"optimal":[343],"decisions":[344],"management":[347]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-08-11T00:00:00"}