Abstract
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.
Keywords: oncology patients, transfusion-associated circulatory overload, risk factors, cardio-toxic chemotherapy, outcomes, blood transfusion
Transfusion-associated circulatory overload (TACO) is the leading cause of transfusion-related death and transfusion-related sequelae, such as increased length of hospital stay2 (including longer ICU stay) and incidence of mechanical ventilation.1-2 The Centers for Disease Control and Prevention (CDC) defines TACO as any 3 of the following conditions occurring within 6 hours of transfusion: acute respiratory distress, elevated NT-proBNP, elevated central venous pressure, evidence of left-sided heart failure, evidence of positive fluid balance, and radiographic evidence of pulmonary edema.3 According to the US Food and Drug Administration, between 2014 and 2018, TACO accounted for 32% of reported transfusion-related deaths.2
Despite its high mortality rate, TACO remains one of the most underreported and possibly preventable transfusion-related reactions.4 Barriers in diagnosing TACO include delay in the appearance of specific symptoms, the multifactorial nature of circulatory overload, and the broadness of the guidelines set forth by the CDC.1,4 Clinicians are more likely to diagnose TACO in patients with contributing comorbidities, such as renal and cardiac dysfunction, and transfusion of multiple units of blood products. In contrast, clinicians are less likely to diagnose TACO based on vital-sign changes such as hypertension and tachycardia, which may indicate early signs of fluid overload.
Oncology patients possess unique factors that may increase their risk for TACO. Many chemotherapies and immunotherapies are associated with cardiotoxicity and/or nephrotoxicity.5 The multiple blood-component transfusions used to correct pancytopenia due to cytotoxic chemotherapies, combined with the use of other intravenous therapies (eg, anti-infective agents), increase the risk of fluid overload. In this descriptive study, our aims are to characterize TACO occurrence among oncology patients, to identify variables unique to this patient population, and to reevaluate transfusion practices.
Materials and Methods
This descriptive study is based on retrospective auditing of all inpatient and ambulatory clinical encounters for patients aged 18 years and older who received a blood component transfusion (packed red blood cells [PRBCs], platelets, or thawed plasma) and developed TACO from July 1, 2019 to October 31, 2020 at the M.D. Anderson Cancer Center in Houston, TX. The institutional review board of that institution approved the study. Data were summarized by means and ranges for continuous variables and proportions for categorical variables. We used R software, version 3.6.1 (http://www.r-project.org) for data analysis. There was no control group for summary statistics. We did not compare TACO cases with non-TACO cases due to the large database of transfusions. Also, a noncancer, non-TACO control group would have been infeasible, given that we conducted this study in a cancer care institution.
We monitored each transfusion using a digital dashboard that alerts a hemovigilance nurse that the patient may be experiencing a transfusion reaction. When the hemovigilance nurse receives such alerts, that person deploys an advanced practice healthcare provider to the bedside for assessment and examination of the patient in real time. Supportive care is provided and laboratory tests are ordered if a diagnosis of TACO (and or other transfusion reaction) is suspected. The transfusion medicine physician then performs a medical records review and documents a diagnosis in those records.
A transfusion medicine board-certified physician, using the CDC guidelines, diagnosed TACO among our study population. The threshold for diagnosis was defined as new onset or exacerbation of 3 or more of the following within 6 hours of cessation of transfusion: acute respiratory distress (dyspnea, orthopnea, and/or cough), elevated NT-proBNP, elevated central venous pressure, evidence of left-sided heart failure, evidence of positive fluid balance, and radiographic evidence of pulmonary edema.3
Inclusion criteria included adult patients aged 18 years and older with a diagnosis of TACO that involved an imputability rating of definite, probable, or possible. Exclusion criteria included clinical encounters involving blood component transfusions without an ordered transfusion reaction panel and without a diagnosis of TACO. Encounters with an imputability classification of doubtful (n = 6) were excluded, given that cases were volume-overloaded, which led to adverse events (these events, however, were unlikely to be transfusion-related). Encounters involving massive bleeding requiring multiple transfusions simultaneously (n = 3) were excluded, to account for outliers who had been given resuscitation processes, several blood products, and other fluids. We also excluded encounters for patients younger than 18 years (n = 2; small group, age outlier) and multiple TACO events from a single patient (n = 6; to negate duplicate demographics).
Data on patients with TACO were manually collected by hemovigilance nurses (L.E.M.) from patient electronic health records (EHRs) using paper forms and were validated for completeness and accuracy by a transfusion specialist nurse practitioner (M.M.). Data collected included patient demographics of age, sex, race, ethnicity, cancer diagnosis, weight at hospital admission, weight at time of transfusion, and inpatient or outpatient. Additional variables abstracted included comorbidities and cancer treatment modalities, to help identify oncology-specific associations that contribute to the development of TACO. Comorbidities included history of congestive heart failure (CHF), diastolic/systolic dysfunction, coronary-artery disease, acute myocardial infarction, valvular heart disease, atrial fibrillation, type 2 diabetes, hypertension, and obesity (BMI ≥30). We also noted daily use of certain medications such as corticosteroids, diuretics, and antihypertensives.
We also collected data regarding history of treatment with cardiotoxic chemotherapy or radiation to the breast or chest. In addition, we collected the results of laboratory and diagnostic tests, including pre-/post-transfusion high-sensitivity troponin T higher than the normal range using the institutional laboratory range (≤18 ng/L) as the standard, along with pre-/post-transfusion echocardiogram with left ventricular ejection fraction ≤50%, and NT-proBNP higher than the normal range between 24 and 72 hours after transfusion using the institutional laboratory range (≤125 pg/mL) as the standard.
We reviewed clinical variables to determine whether they were risk factors for TACO, included renal insufficiency, hemodialysis, and pre-existing positive fluid balance ≥1000 mL since admission and 24 hours before transfusion. We also reviewed pre-/post-transfusion creatinine level (0.67–1.17 mg/dL), glomerular filtration rate (≥60 mL/min/1.73 m2), and blood urea nitrogen (6–23 mg/dL) levels out of normal range (using the institution laboratory range as the standard).
Additional clinical variables we reviewed included pneumonia, chronic obstructive pulmonary disease, graft-versus-host disease of the lung, diffused alveolar hemorrhage, preexisting supplemental oxygen use, preexisting dyspnea, and preexisting evidence of pulmonary edema with an indication on chest radiography of opacities attributed to pulmonary edema, enlarged cardiac silhouette, and/or pleural effusions related to oncotic pressure. We retrieved data on the transfusion practices used during each clinical encounter to help examine the impact on the occurrence of TACO, on clinical characteristics of the reaction, and on patient outcomes.
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. There were 111,285 transfusions, defined as the total number of units issued. Blood products were issued from a single blood bank in our cancer hospital. There were 1401 transfusion reactions diagnosed, including 240 allergic (17.1%), 1032 febrile nonhemolytic (73.7%), 10 hypotensive (0.7%), 9 transfusion-associated dyspnea (0.6%), and 110 TACO (7.8%) cases. Of these, 17 were excluded (see the Materials and Methods section), and 93 TACO cases were used for this study. The transfusion medicine physician (M.C.M., F. M., A.M.K.C., K.K., and J.M.K.) determined the imputability category of TACO diagnoses to be “possible” in 48.4% of these clinical encounters, “probable” in 37.6%, and “definite” in the remaining 14.0%.
The demographics of the study patients who developed TACO are listed in Table 1. Although we did not compare TACO cases with non-TACO cases, Tables 1–5 allow for observation of variables that are typical in TACO cases. Comorbidities present in oncology patients before diagnosis with TACO are listed in Table 2. The treatment modalities used for oncologic patients before they developed TACO are listed in Table 3.
Table 1.
Demographics of the 93 Study Patients Who Developed TACOa
| Variable | Category | |
|---|---|---|
| Age, y, mean (range) | 62.8 (18–86) | |
| Sex, No. (%) | Female | 46 (49.5%) |
| Male | 47 (50.5%) | |
| Race, No. (%) | White | 64 (68.8%) |
| Black | 11 (11.8%) | |
| Asian | 6 (6.4%) | |
| Other | 9 (9.7%) | |
| Not reported | 3 (3.2%) | |
| Ethnic group, No. (%) | Hispanic/Latino | 16 (17.2%) |
| Not Hispanic/Latino | 70 (75.3%) | |
| Declined to answer | 7 (7.5%) | |
| Cancer diagnosis, No. (%) | Hematologic malignancy | 70 (75.3%) |
| Solid tumor | 23 (24.7%) | |
| Location, No. (%) | Inpatient | 85 (91.4%) |
| Outpatient | 8 (8.6%) |
Abbreviation: TACO, transfusion-associated circulatory overload.
aPercentages may not total 100% because of rounding.
Table 5.
Outcomes After Development of TACO in the 93 Studied Patients
| Variable | No. (%) |
|---|---|
| Length of hospital stay (total admission), d | 28.8 (7.5%) |
| Length of hospital stay before TACO, d | 11.7 (15.1%) |
| Ambulatory TACO needing higher level of care | 7 (7.5%) |
| Admission to ICU related to TACO | 14 (15.0%) |
| Death 30 d after TACO (other causes not related to TACO) | 34 (36.6%) |
Abbreviation: TACO, transfusion-associated circulatory overload.
Table 2.
Comorbidities Present in the 93 Studied Patients Before They Developed TACO
| Category | Variable | No. (%) |
|---|---|---|
| Pretransfusion NT-proBNP | 31 (33.3%) | |
| Hypertension | 52 (55.9%) | |
| BMI ≥30 | 30 (32.3%) | |
| Congestive heart failure | 26 (28.0%) | |
| Type 2 diabetes mellitus | 23 (24.7%) | |
| Coronary artery disease | 22 (23.7%) | |
| Atrial fibrillation | 14 (15.0%) | |
| Acute myocardial infarction | 4 (4.3%) | |
| Valvular heart disease | 3 (3.2%) | |
| Pretransfusion LVEF ≤50 | 5 (5.4%) | |
| Renala | Renal insufficiency | 43 (46.2%) |
| Pretransfusion creatinine higher than normal range | 40 (43.0%) | |
| Pretransfusion GFR lower than normal range | 37 (39.8%) | |
| Hemodialysis | 8 (8.6%) | |
| Positive fluid balance ≥1000 mL (since hospital admission) | 70 (75.2%) | |
| Positive fluid balance ≥1000 mL (24 h pre-TACO) | 43 (46.2%) | |
| Pulmonary | Pneumonia | 53 (57.0%) |
| Chronic obstructive pulmonary disease | 7 (7.5%) | |
| GVHD of the lungs | 0 | |
| Diffused alveolar hemorrhage | 4 (4.3%) | |
| Preexisting supplemental oxygen | 55 (59.1%) | |
| Preexisting dyspnea | 58 (62.4%) | |
| Preexisting pulmonary edema via chest x-ray | 11 (11.8%) | |
| History of radiation of chest/breast | 10 (10.8%) |
Abbreviations: TACO, transfusion-associated circulatory overload; LVEF, left ventricular ejection fraction; GFR, glomerular filtration rate; GVHD, graft-versus-host disease.
aAdmission weight (mean average), 76.9 kg; weight at time of transfusion, kg (mean average), 79.3 kg.
Table 3.
Treatment Modalities Used Before Development of TACO in the 93 Study Patients
| Drug Class | No. (%) |
|---|---|
| Cardiotoxic chemotherapy | 81 (87.1%) |
| Antimetabolites | 57 (61.3%) |
| Alkylating agents | 47 (50.5%) |
| Anthracyclines | 37 (39.8%) |
| Kinase inhibitors | 13 (14.0%) |
| Antimicrotubule agents | 12 (13.0%) |
| Proteasome inhibitors | 7 (7.5%) |
| Monoclonal antibodies | 6 (6.4%) |
| Corticosteroids | 40 (43.0%) |
| Diuretics | 38 (40.9%) |
| Beta-blockers | 34 (36.6%) |
| Calcium-channel blockers | 25 (26.9%) |
| ACE inhibitors | 13 (14.0%) |
| Antiarrhythmic | 9 (9.7%) |
Abbreviations: TACO, transfusion-associated circulatory overload; ACE, angiotensin-converting enzyme.
Clinical Characteristics
TACO was more commonly observed in inpatients (n = 85; representing 91.4% of all TACO cases), compared with ambulatory patients (n = 8; representing 8.6% of all TACO cases). The primary cancer diagnoses of patients with TACO were hematologic malignancy (70 [75.3%]) and solid tumor (23 [24.7%]). The average length of stay for patients who developed TACO was 28.8 days (total hospital stay) and 11.7 days before TACO.
The mean hemoglobin before PRBC transfusion was 7.7 g/L, compared with the mean hemoglobin count of 8.7 g/L after PRBC transfusion. The median platelet count before apheresis platelet transfusion (single-donor platelets [SDP]) or pooled platelet (random-donor platelets [RDPs]) transfusion was 20,000 × 103/μL, compared with the median platelet count of 26,000 × 103/μL after platelet transfusion.
The mean laboratory values before the administration of thawed plasma were prothrombin time of 27.3 seconds, partial thromboplastin time of 48.7 seconds, and international normalized ratio of 2.6, compared with 19.9 seconds, 43.3 seconds, and 1.74 seconds, respectively, after thawed plasma administration. The mean admission weight was 76.9 kg, and the mean weight at the time of transfusion was 79.3 kg.
Transfusion Practices
The clinical service assigned to patients at the time of TACO diagnosis included leukemia (48 [51.6%]), stem cell transplant (14 [15.0%]), general internal medicine (13 [14.0%]), lymphoma (7 [7.5%]), emergency medicine (2 [2.2%]), gynecologic oncology (2 [2.2%]), sarcoma (2 [2.2%]), urology (1 [1.1%]), and colorectal surgery (1 [1.1%]). The type of blood component ordered and administered that resulted in the highest incidence of TACO was PRBCs, leading to 60 TACO cases (64.5%). The most common indications for ordering PRBCs, platelets, and plasma, respectively, were low hemoglobin levels, low platelet counts, and high international normalized ratio.
Blood administration orders with the indication “Other” require the ordering provider to discuss the clinical indication with the transfusion medicine physician before approval and blood product release. Premedications had been ordered in 40 of clinical encounters (43.0%) with patients in whom transfusions resulted in a TACO diagnosis.
The mean volume of blood components transfused in the 24 hours before the TACO event was 629.6 mL. Those who developed TACO had a mean of 2.5 units of blood products transfused in the 24 hours before the event. Repeat laboratory values after transfusion were ordered for 45 patients (48.4%). The types of repeat laboratory tests ordered were hemoglobin and hematocrit (n = 4), platelet count (n = 6), complete blood count (n = 34), and coagulation factors (n = 4). See Table 4 for the characteristic symptoms of TACO in our study population.
Table 4.
Characteristic Symptoms of TACO in the 93 Study Patients
| Variable | No. (%) |
|---|---|
| Shortness of breath | 82 (88.2%) |
| Hypoxemia (increase of 5% SpO2 from baseline and/or increase in oxygen requirements) | 66 (71.0%) |
| Tachypnea (RR change >25%) | 66 (71.0%) |
| Edema | 63 (67.7%) |
| Tachycardia (pulse change >25%) | 52 (55.9%) |
| Crackles/rales | 50 (53.8%) |
| Hypertension (SBP >30 from baseline) | 44 (47.3%) |
| Cough | 37 (39.8%) |
| Wheezing | 22 (23.7%) |
| Orthopnea | 13 (14.0%) |
| Chest tightness | 12 (12.9%) |
| Jugular venous distention | 4 (4.3%) |
| S3 Gallop | 3 (3.2%) |
| TACO occurring during transfusion | 36 (38.7%) |
| TACO occurring after transfusion (as long as 6 h) | 56 (60.2%) |
| TACO severity | |
| Nonsevere | 53 (57.0%) |
| Severe | 39 (41.9%) |
| Not determined | 1 (1.1%) |
| Confidence level of diagnosis | |
| Possible | 45 (48.4%) |
| Probable | 35 (37.6%) |
| Definitive | 13 (14.0%) |
Abbreviations: TACO, transfusion-associated circulatory overload; RR, respiratory rate; SBP, systolic blood pressure.
Outcomes
Patient outcomes after development of TACO are described in Table 5. Of the 93 patients diagnosed with TACO, 14 patients (15.0%) were admitted to the ICU because of TACO, and 34 patients (36.6%) died within 30 days of TACO diagnosis due to other causes, none of which were deemed to be a result of TACO.
Discussion
A descriptive study of oncology patients who developed TACO revealed characteristics unique to this patient population. Developing appropriate guidelines that apply to oncology patients, in addition to those set forth by the CDC, should be considered. Also, implementation by ordering providers of a predictive TACO tool can help in early recognition and mitigation of TACO.
The incidence of TACO among oncology patients is high, compared with 1%–6% among other populations.6-9 The higher proportion of transfusion reactions diagnosed as TACO is likely due to real-time hemovigilance monitoring in combination with a higher-acuity population. We observed that 91.4% of cases of TACO occurred in the inpatient setting; a hematology malignancy diagnosis was made in 75.3% of all patients with TACO and a solid tumor diagnosis in the remaining 24.7%. This finding may suggest that inpatients are more susceptible to TACO events, possibly related to baseline clinical status. Also, identifying medical history, comorbidities, and unique factors common among oncology patients who develop TACO is critical information that healthcare providers can use to help prevent reactions and mitigate the severity of those reactions.
The oncology patients in our study who were diagnosed with TACO had similar incidences of CHF, hypertension, diabetes mellitus, coronary artery disease, and kidney dysfunction as cohort patients in previous works of research.10-13 However, unique characteristics such as preexisting hematologic malignancy, receipt of cardiotoxic chemotherapy, pneumonia, preexisting oxygen use, preexisting dyspnea, daily use of corticosteroids, daily use of beta-blockers, daily use of diuretics, and elevated NT-proBNP levels were observed in our study, which may lead to a diagnosis of TACO.
Most patients who developed TACO in our study had received a PRBC transfusion. Most of the blood products were ordered 1 unit at a time (53.8%), with indication of hemoglobin ≤8 g/L (91.4%). A study report by Daurat et al13 also stated that 53% of patients diagnosed with TACO developed symptoms after receiving 1 unit of RBC, indicating that fluid status can change quickly.
In our study, intravenous furosemide was the most common diuretic administered on the day of the adverse event; it was administered after the completion of transfusion to help manage TACO reactions. This observation indicates a need for further research on preemptive use of diuretics. Implementation of more-thorough examination of susceptible patients and review of their EHRs by the ordering clinicians would be beneficial.
In a case-control study, Li et al6 observed that patients diagnosed with TACO were more likely to have a larger volume transfused at a faster rate than patients with similar characteristics receiving their transfusions in the ICU. Standardizing orders to transfuse 1 unit at a time, along with required repeat laboratory tests before ordering more products for susceptible patients, would allow for the reassessment of volume status and the need for additional blood products in such patients. Addressing gaps in transfusion practices is critical in reducing and mitigating a preventable reaction in an already-vulnerable population.
Our study was limited by its retrospective nature and the lack of a control group. However, assembling a noncancer, non-TACO control group was infeasible, given that we conducted our study in a cancer institution. Nevertheless, we believe that our results provide useful preliminary data. We hope that future researchers can conduct further studies of this topic, involving larger sample sizes, to validate our findings.
Acknowledgments
This work was supported in part by the NIH/NCI Cancer Center support grant (award No. P30 CA016672) and involved the work of the Biostatistics Resource Group. J.M.K. received funding from the Amon G. Carter Foundation. We acknowledge the contribution of Anecita P. Fadol, PhD, APRN, FNP, FAANP, FAAN, for her cardiology expertise and input with cardiology risk factors in development of our data-abstraction tool. Also, we thank Cory Wongsa, BSN, and Nancy Tomczak, BSN, for their assistance with data collection and data entry. We thank Yimin Geng, MS, in the Research Medical Library at MD Anderson Cancer Center, for her assistance with literature review. We thank Bryan Tutt, MA, in the Research Medical Library at MD Anderson Cancer Center for his editorial support. Lastly, we would like to thank Luisa Gallardo, MSN.
Glossary
Abbreviations
- TACO
transfusion-associated circulatory overload
- CDC
Centers for Disease Control and Prevention
- PRBCs
packed red blood cells
- EHRs
electronic health records
- CHF
congestive heart failure
- SDP
single-donor platelets
- RPDs
random-donor platelets
- LVEF
left ventricular ejection fraction
- GFR
glomerular filtration rate
- GVHD
graft-versus-host disease
- ACE
angiotensin-converting enzyme
- RR
respiratory rate
- SBP
systolic blood pressure
Contributor Information
Marisol Maldonado, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Colleen E Villamin, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Leah E Murphy, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Amitava Dasgupta, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Roland L Bassett, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Mayrin Correa Medina, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Tonita S Bates, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Fernando Martinez, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Adriana M Knopfelmacher Couchonal, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
Kimberly Klein, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
James M Kelley, Hemovigilance Unit, Department of Laboratory Medicine, Division of Pathology and Laboratory Medicine; The University of Texas MD Anderson Cancer Center, Houston, Texas.
References
- 1. Bosboom JJ, Klanderman RB, Migdady Y, et al. Transfusion-associated circulatory overload: a clinical perspective. Transfus Med Rev. 2019;33(2):69–77. [DOI] [PubMed] [Google Scholar]
- 2. United States Food and Drug Administration. Fatalities reported to FDA following blood collection and transfusion: annual summary for fiscal year 2017. https://www.fda.gov/media/124796/download. Accessed January 6, 2022.
- 3. The National Healthcare Safety Network Biovigilance Component Hemovigilance Module Surveillance Protocol (version 2.5). Division of Healthcare Quality Promoting, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention; 2021. https://www.cdc.gov/nhsn/pdfs/biovigilance/bv-hv-protocol-current.pdf.
- 4. Raval JS, Mazepa MA, Russell SL, Immel CC, Whinna HC, Park YA. Passive reporting greatly underestimates the rate of transfusion-associated circulatory overload after platelet transfusion. Vox Sang. 2015;108(4):387–392. [DOI] [PubMed] [Google Scholar]
- 5. Gutierrez C, McEvoy C, Munshi L, et al. Critical care management of toxicities associated with targeted agents and immunotherapies for cancer. Crit Care Med. 2020;48(1):10–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Li G, Rachmale S, Kojicic M, et al. Incidence and transfusion risk factors for transfusion-associated circulatory overload among medical intensive care unit patients. Transfusion. 2011;51(2):338–343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Menis M, Anderson SA, Forshee RA, et al. Transfusion-associated circulatory overload (TACO) and potential risk factors among the inpatient US elderly as recorded in Medicare administrative databases during 2011. Vox Sang. 2014;106(2):144–152. [DOI] [PubMed] [Google Scholar]
- 8. Popovsky MA, Audet AM, Andrzejewski C Jr. Transfusion-associated circulatory overload in orthopedic surgery patients: a multi-institutional study. Immunohematology. 1996;12(2):87–89. [PubMed] [Google Scholar]
- 9. Bierbaum BE, Callaghan JJ, Galante JO, Rubash HE, Tooms RE, Welch RB. An analysis of blood management in patients having a total hip or knee arthroplasty. J Bone Joint Surg Am. 1999;81(1):2–10. [DOI] [PubMed] [Google Scholar]
- 10. Lieberman L, Maskens C, Cserti-Gazdewich C, et al. A retrospective review of patient factors, transfusion practices, and outcomes in patients with transfusion-associated circulatory overload. Transfus Med Rev. 2013;27(4):206–212. [DOI] [PubMed] [Google Scholar]
- 11. Roubinian NH, Hendrickson JE, Triulzi DJ, et al. Contemporary risk factors and outcomes of transfusion-associated circulatory overload. Crit Care Med. 2018;46(4):577–585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Bosboom JJ, Klanderman RB, Zijp M, et al. Incidence, risk factors, and outcome of transfusion-associated circulatory overload in a mixed intensive care unit population: a nested case-control study. Transfusion. 2018;58(2):498–506. [DOI] [PubMed] [Google Scholar]
- 13. Daurat A, Grenie J, Roger C, et al. Outcomes and risk factors of transfusion-associated circulatory overload: a case control study. Transfusion. 2019;59(1):191–195. [DOI] [PubMed] [Google Scholar]