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Prediction of urine culture results by automated urinalysis with digital flow morphology analysis

DC Field Value Language
dc.contributor.author김도균-
dc.contributor.author김윤정-
dc.contributor.author박용정-
dc.contributor.author유창승-
dc.contributor.author정석훈-
dc.date.accessioned2021-04-29T17:21:04Z-
dc.date.available2021-04-29T17:21:04Z-
dc.date.issued2021-03-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/182299-
dc.description.abstractTo investigate the association between the results of urinalysis and those of concurrent urine cultures, and to construct a prediction model for the results of urine culture. A total of 42,713 patients were included in this study. Patients were divided into two independent groups including training and test datasets. A novel prediction algorithm, designated the UTOPIA value, was constructed with the training dataset, based on an association between the results of urinalysis and those of concurrent urine culture. The diagnostic performance of the UTOPIA value was validated with the test dataset. Six variables were selected for the equation of the UTOPIA value: age of higher UTI risk [odds ratio (OR), 2.069125], female (OR, 1.400648), nitrite (per 1 grade; OR, 3.765457), leukocyte esterase (per 1 grade; OR, 1.701586), the number of WBCs (per 1 × 106/L; OR, 1.000121), and the number of bacteria (per 1 × 106/L; OR, 1.004195). The UTOPIA value exhibited an area under the curve value of 0.837 when validated with the independent test dataset. The UTOPIA value displayed good diagnostic performance for predicting urine culture results, which would help to reduce unnecessary culture. Different cutoffs can be used according to the clinical indication.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherNature Publishing Group-
dc.relation.isPartOfSCIENTIFIC REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titlePrediction of urine culture results by automated urinalysis with digital flow morphology analysis-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Laboratory Medicine (진단검사의학교실)-
dc.contributor.googleauthorDokyun Kim-
dc.contributor.googleauthorSeoung Chul Oh-
dc.contributor.googleauthorChangseung Liu-
dc.contributor.googleauthorYoonjung Kim-
dc.contributor.googleauthorYongjung Park-
dc.contributor.googleauthorSeok Hoon Jeong-
dc.identifier.doi10.1038/s41598-021-85404-1-
dc.contributor.localIdA04891-
dc.contributor.localIdA00793-
dc.contributor.localIdA01582-
dc.contributor.localIdA05704-
dc.contributor.localIdA03619-
dc.relation.journalcodeJ02646-
dc.identifier.eissn2045-2322-
dc.identifier.pmid33727643-
dc.contributor.alternativeNameKim, Dokyun-
dc.contributor.affiliatedAuthor김도균-
dc.contributor.affiliatedAuthor김윤정-
dc.contributor.affiliatedAuthor박용정-
dc.contributor.affiliatedAuthor유창승-
dc.contributor.affiliatedAuthor정석훈-
dc.citation.volume11-
dc.citation.number1-
dc.citation.startPage6033-
dc.identifier.bibliographicCitationSCIENTIFIC REPORTS, Vol.11(1) : 6033, 2021-03-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Laboratory Medicine (진단검사의학교실) > 1. Journal Papers

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