BACKGROUND: It is well recognized that increased transfusion volumes are associated with increased morbidity and mortality, but dose-response relations between high- and very-high-dose transfusion and clinical outcomes have not been described previously. In this study, the authors assessed (1) the dose-response relation over a wide range of transfusion volumes for morbidity and mortality and (2) other clinical predictors of adverse outcomes. METHODS: The authors retrospectively analyzed electronic medical records for 272,592 medical and surgical patients (excluding those with hematologic malignancies), 3,523 of whom received transfusion (10 or greater erythrocyte units throughout the hospital stay), to create dose-response curves for transfusion volumes and in-hospital morbidity and mortality. Prehospital comorbidities were assessed in a risk-adjusted manner to identify the correlation with clinical outcomes. RESULTS: For patients receiving high- or very-high-dose transfusion, infections and thrombotic events were four to five times more prevalent than renal, respiratory, and ischemic events. Mortality increased linearly over the entire dose range, with a 10% increase for each 10 units of erythrocytes transfused and 50% mortality after 50 erythrocyte units. Independent predictors of mortality were transfusion dose (odds ratio [OR], 1.037; 95% CI, 1.029 to 1.044), the Charlson comorbidity index (OR, 1.209; 95% CI, 1.141 to 1.276), and a history of congestive heart failure (OR, 1.482; 95% CI, 1.062 to 2.063). CONCLUSIONS: Patients receiving high- or very-high-dose transfusion are at especially high risk for hospital-acquired infections and thrombotic events. Mortality increased linearly over the entire dose range and exceeded 50% after 50 erythrocyte units.
BACKGROUND: It is well recognized that increased transfusion volumes are associated with increased morbidity and mortality, but dose-response relations between high- and very-high-dose transfusion and clinical outcomes have not been described previously. In this study, the authors assessed (1) the dose-response relation over a wide range of transfusion volumes for morbidity and mortality and (2) other clinical predictors of adverse outcomes. METHODS: The authors retrospectively analyzed electronic medical records for 272,592 medical and surgical patients (excluding those with hematologic malignancies), 3,523 of whom received transfusion (10 or greater erythrocyte units throughout the hospital stay), to create dose-response curves for transfusion volumes and in-hospital morbidity and mortality. Prehospital comorbidities were assessed in a risk-adjusted manner to identify the correlation with clinical outcomes. RESULTS: For patients receiving high- or very-high-dose transfusion, infections and thrombotic events were four to five times more prevalent than renal, respiratory, and ischemic events. Mortality increased linearly over the entire dose range, with a 10% increase for each 10 units of erythrocytes transfused and 50% mortality after 50 erythrocyte units. Independent predictors of mortality were transfusion dose (odds ratio [OR], 1.037; 95% CI, 1.029 to 1.044), the Charlson comorbidity index (OR, 1.209; 95% CI, 1.141 to 1.276), and a history of congestive heart failure (OR, 1.482; 95% CI, 1.062 to 2.063). CONCLUSIONS:Patients receiving high- or very-high-dose transfusion are at especially high risk for hospital-acquired infections and thrombotic events. Mortality increased linearly over the entire dose range and exceeded 50% after 50 erythrocyte units.
Authors: Nadia B Hensley; Megan P Kostibas; William W Yang; Todd C Crawford; Kaushik Mandal; Pranjal B Gupta; Steven M Frank; Charles H Brown Journal: Transfusion Date: 2017-10-08 Impact factor: 3.157
Authors: Caroline X Qin; Lekha V Yesantharao; Kevin R Merkel; Dheeraj K Goswami; Alejandro V Garcia; Glenn J R Whitman; Steven M Frank; Melania M Bembea Journal: Anesth Analg Date: 2020-09 Impact factor: 6.627
Authors: Alexander Bautista; Theodore B Wright; Janice Meany; Sunitha K Kandadai; Benjamin Brown; Kareim Khalafalla; Saeed Hashem; Jason W Smith; Tayyeb M Ayyoubi; Jarrod E Dalton; Anupama Wadhwa; Daniel I Sessler; Detlef Obal Journal: Biomed Res Int Date: 2017-05-14 Impact factor: 3.411
Authors: Emma Viikinkoski; Juho Jalkanen; Jarmo Gunn; Tuija Vasankari; Joonas Lehto; Mika Valtonen; Fausto Biancari; Sirpa Jalkanen; K E Juhani Airaksinen; Maija Hollmén; Tuomas O Kiviniemi Journal: Sci Rep Date: 2021-11-15 Impact factor: 4.379
Authors: Aryeh Shander; Susan M Goobie; Matthew A Warner; Matti Aapro; Elvira Bisbe; Angel A Perez-Calatayud; Jeannie Callum; Melissa M Cushing; Wayne B Dyer; Jochen Erhard; David Faraoni; Shannon Farmer; Tatyana Fedorova; Steven M Frank; Bernd Froessler; Hans Gombotz; Irwin Gross; Nicole R Guinn; Thorsten Haas; Jeffrey Hamdorf; James P Isbister; Mazyar Javidroozi; Hongwen Ji; Young-Woo Kim; Daryl J Kor; Johann Kurz; Sigismond Lasocki; Michael F Leahy; Cheuk-Kwong Lee; Jeong Jae Lee; Vernon Louw; Jens Meier; Anna Mezzacasa; Manuel Munoz; Sherri Ozawa; Marco Pavesi; Nina Shander; Donat R Spahn; Bruce D Spiess; Jackie Thomson; Kevin Trentino; Christoph Zenger; Axel Hofmann Journal: Anesth Analg Date: 2020-07 Impact factor: 5.108