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 predictin...

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Veröffentlicht in:	Transfusion (Philadelphia, Pa.) Jg. 55; H. 11; S. 2582 - 2589
Hauptverfasser:	Kim, Kyu Nam, Kim, Dong Won, Jeong, Mi Ae
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Blackwell Publishing Ltd 01.11.2015 Wiley Subscription Services, Inc
Schlagworte:	Acute Lung Injury - etiology Adult Aged Algorithms Confidence intervals Female Humans Male Middle Aged Perioperative Period Retrospective Studies Transfusion Reaction - diagnosis
ISSN:	0041-1132, 1537-2995
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Abstract	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.
AbstractList	BACKGROUNDTransfusion-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. 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. 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. 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. 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. 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. 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.
Author	Jeong, Mi Ae Kim, Dong Won Kim, Kyu Nam
Author_xml	– sequence: 1 givenname: Kyu Nam surname: Kim fullname: Kim, Kyu Nam organization: Department of Anesthesiology and Pain Medicine, Hanyang University Hospital, Seoul, Republic of Korea – sequence: 2 givenname: Dong Won surname: Kim fullname: Kim, Dong Won email: dongwkim@hanyang.ac.kr organization: Department of Anesthesiology and Pain Medicine, Hanyang University Hospital, Seoul, Republic of Korea – sequence: 3 givenname: Mi Ae surname: Jeong fullname: Jeong, Mi Ae organization: Department of Anesthesiology and Pain Medicine, Hanyang University Hospital, Seoul, Republic of Korea
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Snippet	BACKGROUND Transfusion‐related acute lung injury (TRALI) and transfusion‐associated circulatory overload (TACO) are leading causes of transfusion‐related... Transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) are leading causes of transfusion-related mortality. An... BACKGROUND Transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) are leading causes of transfusion-related... BACKGROUNDTransfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) are leading causes of transfusion-related...
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SubjectTerms	Acute Lung Injury - etiology Adult Aged Algorithms Confidence intervals Female Humans Male Middle Aged Perioperative Period Retrospective Studies Transfusion Reaction - diagnosis
Title	The usefulness of a classification and regression tree algorithm for detecting perioperative transfusion-related pulmonary complications
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