The usefulness of a classification and regression tree algorithm for detecting perioperative transfusion-related pulmonary complications.

Background: Transfusion-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 predicti...

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Publicado en:Transfusion Vol. 55; no. 11; pp. 2582 - 2590
Autores principales: Kim, Kyu Nam, Kim, Dong Won, Jeong, Mi Ae
Formato: algorithm research tables/charts Journal Article
Publicado: Wiley-Blackwell Nov2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/trf.13202
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        atl: The usefulness of a classification and regression tree algorithm for detecting perioperative transfusion-related pulmonary complications.
      aug:
        au:
          Kim, Kyu Nam
          Kim, Dong Won
          Jeong, Mi Ae
        affil: Department of Anesthesiology and Pain Medicine, Hanyang University Hospital, Seoul Republic of Korea
      sug:
        subj:
          Blood Transfusion Reaction Diagnosis
          Acute Lung Injury Etiology
          Algorithms
          Male
          Intraoperative Period
          Adult
          Middle Age
          Aged
          Retrospective Design
          Female
          Human
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Background: Transfusion-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 Methods: A 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.Results: Among 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.Conclusions: Low 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.
      pubtype: Academic Journal
      doctype:
        algorithm
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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