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Development and validation of an interpretable model for predicting sepsis mortality across care settings

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dc.contributor.author조재화-
dc.date.accessioned2025-02-03T08:59:33Z-
dc.date.available2025-02-03T08:59:33Z-
dc.date.issued2024-06-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/202075-
dc.description.abstractThere are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients' needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model's performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765-0.792; validation dataset AUC: 0.787, 95% CI 0.765-0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748-0.788; validation dataset AUC: 0.729, 95% CI 0.687-0.770). The calculator, accessible at https://avonlea76.shinyapps.io/shiny_app_up/ , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherNature Publishing Group-
dc.relation.isPartOfSCIENTIFIC REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAged-
dc.subject.MESHAged, 80 and over-
dc.subject.MESHArea Under Curve-
dc.subject.MESHCommunity-Acquired Infections / mortality-
dc.subject.MESHFemale-
dc.subject.MESHHospital Mortality-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPrognosis-
dc.subject.MESHROC Curve-
dc.subject.MESHRisk Assessment / methods-
dc.subject.MESHSepsis* / diagnosis-
dc.subject.MESHSepsis* / mortality-
dc.titleDevelopment and validation of an interpretable model for predicting sepsis mortality across care settings-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorYoung Seok Lee-
dc.contributor.googleauthorSeungbong Han-
dc.contributor.googleauthorYe Eun Lee-
dc.contributor.googleauthorJaehwa Cho-
dc.contributor.googleauthorYoung Kyun Choi-
dc.contributor.googleauthorSun-Young Yoon-
dc.contributor.googleauthorDong Kyu Oh-
dc.contributor.googleauthorSu Yeon Lee-
dc.contributor.googleauthorMi Hyeon Park-
dc.contributor.googleauthorChae-Man Lim-
dc.contributor.googleauthorJae Young Moon-
dc.contributor.googleauthorKorean Sepsis Alliance (KSA) Investigators-
dc.identifier.doi10.1038/s41598-024-64463-0-
dc.contributor.localIdA05674-
dc.relation.journalcodeJ02646-
dc.identifier.eissn2045-2322-
dc.identifier.pmid38871785-
dc.subject.keywordModeling-
dc.subject.keywordMortality-
dc.subject.keywordPoint system-
dc.subject.keywordPrognosis-
dc.subject.keywordSepsis-
dc.contributor.alternativeNameCho, Jaehwa-
dc.contributor.affiliatedAuthor조재화-
dc.citation.volume14-
dc.citation.startPage13637-
dc.identifier.bibliographicCitationSCIENTIFIC REPORTS, Vol.14 : 13637, 2024-06-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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