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dc.contributor.author정미애-
dc.date.accessioned2017-08-18T04:37:56Z-
dc.date.available2017-08-18T04:37:56Z-
dc.date.issued2015-11-
dc.identifier.citationTRANSFUSION, v. 55, NO 11, Page. 2582-2589en_US
dc.identifier.issn0041-1132-
dc.identifier.issn1537-2995-
dc.identifier.urihttp://onlinelibrary.wiley.com/doi/10.1111/trf.13202/abstract-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/28573-
dc.description.abstractBACKGROUNDTransfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) are leading causes of transfusion-related mortality. An electronic medical record-based screening classification and regression tree (CART) algorithm was previously developed for predicting transfusion-related pulmonary complications. In the Republic of Korea, TRALI is not sufficiently recognized and an accurate TRALI incidence has not been reported. Therefore, we carried out this study to assess the incidence of TRALI and to determine whether the CART algorithm can be applied to our hospital data. STUDY DESIGN AND METHODSA retrospective analysis of all patients who received any type of transfusion during anesthesia was performed. After the patients were diagnosed by the relevant diagnostic criteria, they were reclassified by the CART algorithm. The validity of the algorithm was evaluated with sensitivity, specificity, likelihood ratios, and misclassification rate. RESULTSAmong 1948 patients who had received 11,269 units of transfusion, 26 TRALI and 20 TACO cases were identified. The incidence of TRALI among the transfused patients was 1.33% and per unit of transfused blood product was 0.23%. The sensitivity and specificity of the TRALI algorithm were estimated to be 73.1% (95% confidence interval [CI], 53.9%-86.3%) and 57.0% (95% CI, 52.5%-61.4%). For TACO, the sensitivity and specificity were 90.0% (95% CI, 69.9%-97.2%) and 56.0% (95% CI, 51.6%-60.4%), respectively. CONCLUSIONSLow specificity of the CART algorithm adopted previously indicated its limited diagnostic value in the Republic of Korea. A new algorithm is needed to facilitate the detection of transfusion-related complications.en_US
dc.language.isoenen_US
dc.publisherWILEY-BLACKWELLen_US
dc.subjectACUTE LUNG INJURYen_US
dc.subjectSURVEILLANCEen_US
dc.subjectHYPOXEMIAen_US
dc.subjectSURGERYen_US
dc.subjectSYSTEMen_US
dc.subjectTRALIen_US
dc.titleThe usefulness of a classification and regression tree algorithm for detecting perioperative transfusion-related pulmonary complicationsen_US
dc.typeArticleen_US
dc.relation.no11-
dc.relation.volume55-
dc.identifier.doi10.1111/trf.13202-
dc.relation.page2582-2589-
dc.relation.journalTRANSFUSION-
dc.contributor.googleauthorKim, Kyu Nam-
dc.contributor.googleauthorKim, Dong Won-
dc.contributor.googleauthorJeong, Mi Ae-
dc.relation.code2015000815-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF MEDICINE[S]-
dc.sector.departmentDEPARTMENT OF MEDICINE-
dc.identifier.pidmacheong-
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COLLEGE OF MEDICINE[S](의과대학) > MEDICINE(의학과) > Articles
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