BACKGROUND: Transfusion-associated circulatory overload (TACO) is a largely preventable transfusion complication that results in significant morbidity and mortality. Cancers, related treatments, and comorbidities are among the factors that can predispose patients to TACO, but currently there are limited data on this topic in the literature. METHODS: We collected data retrospectively from the electronic health records of 93 adult patients with cancer who met Centers for Disease Control and Prevention (CDC) criteria for TACO from July 1, 2019, through October 31, 2020. The parameters we studied included demographics, comorbidities, treatment modalities, transfusion practices, and outcomes. We summarized data by means and ranges for continuous variables, and proportions for categorical variables. RESULTS: During the study period, the incidence of TACO among oncology patients was 0.84 per 1000 transfusions (95% CI, 0.68-1.02), representing 6.6% of all reactions. This percentage is high, compared with 1%-6% among other populations. Unique characteristics such as hematology malignancy (75.3%), receipt of cardiotoxic chemotherapy (87.1%), pneumonia (57.0%), preexisting oxygen use (59.1%), dyspnea (62.4%), hypertension (55.9%), renal insufficiency (46.2%), daily use of corticosteroids (43.0%), daily use of diuretics (40.9%), daily use of beta-blockers (36.6%), and elevated NT-proBNP (33.3%) were frequently observed in these group of oncology patients. CONCLUSIONS: Our study indicates that oncology patients have unique factors that may lead to diagnosis of TACO. Developing appropriate guidelines that apply to oncology patients, in addition to those set forth by the CDC, should be considered. Implementation by ordering healthcare providers of a tools that can predict TACO can help in early recognition and mitigation of TACO.
BACKGROUND: Transfusion-associated circulatory overload (TACO) is a largely preventable transfusion complication that results in significant morbidity and mortality. Cancers, related treatments, and comorbidities are among the factors that can predispose patients to TACO, but currently there are limited data on this topic in the literature. METHODS: We collected data retrospectively from the electronic health records of 93 adult patients with cancer who met Centers for Disease Control and Prevention (CDC) criteria for TACO from July 1, 2019, through October 31, 2020. The parameters we studied included demographics, comorbidities, treatment modalities, transfusion practices, and outcomes. We summarized data by means and ranges for continuous variables, and proportions for categorical variables. RESULTS: During the study period, the incidence of TACO among oncology patients was 0.84 per 1000 transfusions (95% CI, 0.68-1.02), representing 6.6% of all reactions. This percentage is high, compared with 1%-6% among other populations. Unique characteristics such as hematology malignancy (75.3%), receipt of cardiotoxic chemotherapy (87.1%), pneumonia (57.0%), preexisting oxygen use (59.1%), dyspnea (62.4%), hypertension (55.9%), renal insufficiency (46.2%), daily use of corticosteroids (43.0%), daily use of diuretics (40.9%), daily use of beta-blockers (36.6%), and elevated NT-proBNP (33.3%) were frequently observed in these group of oncology patients. CONCLUSIONS: Our study indicates that oncology patients have unique factors that may lead to diagnosis of TACO. Developing appropriate guidelines that apply to oncology patients, in addition to those set forth by the CDC, should be considered. Implementation by ordering healthcare providers of a tools that can predict TACO can help in early recognition and mitigation of TACO.
Authors: Nareg H Roubinian; Jeanne E Hendrickson; Darrell J Triulzi; Jerome L Gottschall; Michael Michalkiewicz; Dhuly Chowdhury; Daryl J Kor; Mark R Looney; Michael A Matthay; Steven H Kleinman; Donald Brambilla; Edward L Murphy Journal: Crit Care Med Date: 2018-04 Impact factor: 7.598
Authors: Joachim J Bosboom; Robert B Klanderman; Yazan Migdady; Barbara Bolhuis; Denise P Veelo; Bart F Geerts; Michael F Murphy; Alexander P J Vlaar Journal: Transfus Med Rev Date: 2019-02-07
Authors: Joachim J Bosboom; Robert B Klanderman; Maarten Zijp; Markus W Hollmann; Denise P Veelo; Jan M Binnekade; Bart F Geerts; Alexander P J Vlaar Journal: Transfusion Date: 2017-12-13 Impact factor: 3.157
Authors: Cristina Gutierrez; Colleen McEvoy; Laveena Munshi; R Scott Stephens; Michael E Detsky; Joseph L Nates; Stephen M Pastores Journal: Crit Care Med Date: 2020-01 Impact factor: 7.598
Authors: M Menis; S A Anderson; R A Forshee; S McKean; C Johnson; L Holness; R Warnock; R Gondalia; C M Worrall; J A Kelman; R Ball; H S Izurieta Journal: Vox Sang Date: 2013-07-12 Impact factor: 2.144