0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Caring for the Critically Ill Patient |

Anemia and Blood Transfusion in Critically Ill Patients FREE

Jean Louis Vincent, MD, PhD, FCCP; Jean-François Baron, MD; Konrad Reinhart, MD; Luciano Gattinoni, MD; Lambert Thijs, MD, PhD; Andrew Webb, MD; Andreas Meier-Hellmann, MD; Guy Nollet, MD; Daliana Peres-Bota, MD; for the ABC Investigators
[+] Author Affiliations

Author Affiliations: Department of Intensive Care, Erasme University Hospital, Brussels, Belgium (Drs Vincent and Peres-Bota); Department of Anesthesiology, Hôpital Broussais, Paris, France (Dr Baron); Department of Anesthesiology, Klinikum FSU Jena, Jena, Germany (Drs Reinhart and Meier-Hellmann); Istituto di Anestesia e Rianimazione, Ospedale Maggiore di Milano, Milan, Italy (Dr Gattinoni); Medical Intensive Care Unit, VU ziekenhuis, Amsterdam, the Netherlands (Dr Thijs); Department of Intensive Care, University College London Hospitals, London, England (Dr Webb); Department of Anesthesiology and Intensive Care, Onze Lieve Vrouwziekenhuis, Aalst, Belgium (Dr Nollet).


Caring for the Critically Ill Patient Section Editor: Deborah J. Cook, MD, Consulting Editor, JAMA.


JAMA. 2002;288(12):1499-1507. doi:10.1001/jama.288.12.1499.
Text Size: A A A
Published online

Context Anemia is a common problem in critically ill patients admitted to intensive care units (ICUs), but the consequences of anemia on morbidity and mortality in the critically ill is poorly defined.

Objectives To prospectively define the incidence of anemia and use of red blood cell (RBC) transfusions in critically ill patients and to explore the potential benefits and risks associated with transfusion in the ICU.

Design Prospective observational study conducted November 1999, with 2 components: a blood sampling study and an anemia and blood transfusion study.

Setting and Patients The blood sampling study included 1136 patients from 145 western European ICUs, and the anemia and blood transfusion study included 3534 patients from 146 western European ICUs. Patients were followed up for 28 days or until hospital discharge, interinstitutional transfer, or death.

Main Outcome Measures Frequency of blood drawing and associated volume of blood drawn, collected over a 24-hour period; hemoglobin levels, transfusion rate, organ dysfunction (assessed using the Sequential Organ Failure Assessment score), and mortality, collected throughout a 2-week period.

Results The mean (SD) volume per blood draw was 10.3 (6.6) mL, with an average total volume of 41.1 (39.7) mL during the 24-hour period. There was a positive correlation between organ dysfunction and the number of blood draws (r = 0.34; P<.001) and total volume drawn (r = 0.28; P<.001). The mean hemoglobin concentration at ICU admission was 11.3 (2.3) g/dL, with 29% (963/3295) having a concentration of less than 10 g/dL. The transfusion rate during the ICU period was 37.0% (1307/3534). Older patients and those with a longer ICU length of stay were more commonly transfused. Both ICU and overall mortality rates were significantly higher in patients who had vs had not received a transfusion (ICU rates: 18.5% vs 10.1%, respectively; χ2 = 50.1; P<.001; overall rates: 29.0% vs 14.9%, respectively; χ2 = 88.1; P<.001). For similar degrees of organ dysfunction, patients who had a transfusion had a higher mortality rate. For matched patients in the propensity analysis, the 28-day mortality was 22.7% among patients with transfusions and 17.1% among those without (P = .02); the Kaplan-Meier log-rank test confirmed this difference.

Conclusions This multicenter observational study reveals the common occurrence of anemia and the large use of blood transfusion in critically ill patients. Additionally, this epidemiologic study provides evidence of an association between transfusions and diminished organ function as well as between transfusions and mortality.

Figures in this Article

Anemia is a common problem in critically ill patients admitted to intensive care units (ICUs).1 Deleterious effects of anemia include increased risk of cardiac-related morbidity2 and mortality,2,3 as well as a generalized decrease in oxygen-carrying capacity. Consequences of anemia may be compounded in this population since critical illness often increases metabolic demands.

Among the many causes of anemia in the critically ill, some of the most important are sepsis,4 overt or occult blood loss (including frequent blood sampling5), decreased production of endogenous erythropoietin, and immune-associated functional iron deficiency.6 However, the specific impact of anemia on ICU patient morbidity and mortality is poorly defined, as is the optimal hemoglobin level for this population.

Anemia is typically treated with blood transfusions to help maintain adequate oxygen delivery. Groeger et al7 found that 16% of patients in medical ICUs and 27% of those in surgical ICUs are transfused on any given day. In a retrospective chart review in the United States, 85% of patients with an ICU length of stay greater than 1 week received at least 1 blood transfusion, and the mean number of units of blood transfused per patient was 9.5.8 More than two thirds of ICU transfusions were not associated with acute blood losses.8

While blood transfusions are prevalent among ICU patients, the criteria for optimal anemia management are not clearly defined.9 A randomized controlled trial by the Canadian Critical Care Trials Group10 comparing restrictive (ie, target hemoglobin level, 7-9 g/dL) and liberal (target level, 10-12 g/dL) transfusion strategies in ICU patients indicated that the liberal use of transfusions may have resulted in higher hospital mortality rates.

The use of blood includes health risk and has significant administrative, logistic, and economic implications. Allogeneic blood transfusion is associated with risk of allergic reaction,11 infection transmission,12 and immunosuppression.11,13,14 Additionally, blood transfusion in the critically ill, particularly with "old" stored cells, does not consistently improve tissue oxygenation.15

The use of blood transfusions for the treatment of anemia in critically ill patients warrants further evaluation. This prospective observational study was designed to determine the frequency of blood drawing and the volume of blood lost from blood drawing, and to estimate the incidence of anemia and the use of red blood cell (RBC) transfusions in critically ill patients throughout western Europe. Such data could provide an objective basis for the future study of anemia management strategies.

Study Design

This prospective, observational study had 2 components: a blood sampling study, and an anemia and blood transfusion study. Institutional recruitment for participation was by open invitation from the study steering committee to academic and nonacademic ICUs. Institutional participation was limited to general medical and/or surgical ICUs in western Europe. Additionally, participation required a minimum of at least 6 beds to limit any variability in staffing, technology, or practice associated with smaller ICUs. Since this epidemiologic observational study did not require any deviation from routine medical practice, institutional review board approval was either waived or expedited in participating institutions and informed consent was not required.

Blood Sampling Study

The purpose of the blood sampling study was to determine the frequency of blood drawing and the associated volume of blood lost. The number of blood draws and volume per draw was recorded for all patients in each ICU for a 24-hour period 1 week prior to the anemia and blood transfusion study. Data were also collected for the Sequential Organ Failure Assessment (SOFA) score.16

Anemia and Blood Transfusion Study

For all patients admitted to participating ICUs during a 2-week period (November 15, 1999, through November 29, 1999), data were collected daily for a maximum of 28 days or until hospital discharge, interinstitutional transfer, or death. Data collected at ICU admission included demographics, type of admission, type of surgery (if applicable), primary diagnostic category, comorbidities, history of anemia and recent acute blood loss, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, SOFA score, and history of recombinant human erythropoietin therapy. Data collected daily included morning hemoglobin, hematocrit, RBC count, SOFA score, indication for transfusion, pretransfusion hemoglobin (if different from the patient's morning value), and number of units transfused. The primary indication for transfusion (assessed by the attending physician) and pretransfusion hemoglobin levels were collected for the first transfusion of the day only.

Data Management and Statistical Evaluation

Data collected using preprinted case report forms (CRFs) were verified using a series of domain and consistency edits as defined by the study steering committee. Intensive care units were queried when data values were either questionable or were missing for required fields. The CRFs were then scanned electronically using TELEform scanning software (Cardiff Software Inc, Vista, Calif) and a database was created using SPSS v9.01 (SPSS Inc, Chicago, Ill). Unanswered queries concerning required fields were treated as missing and resulted in an overall loss of 0.06% of data.

Descriptive statistics were computed for all study variables. Bivariate and multivariate distributions were evaluated for normality using standard statistical methods and by examining stratified distribution plots. Nonparametric measures of comparison were used for variables evaluated as not normally distributed. Difference testing between groups was performed using the 2-tailed t test, analysis of variance (with Bonferroni post-hoc analyses), or χ2 test. Significance for main effects was tested at the α = .05 level. Logistic regression was conducted to assess determinants of mortality. Kaplan-Meier survival analyses were conducted on the entire sample as well as on a sample of matched pairs of patients (transfused and nontransfused) who were matched on their propensity to receive a transfusion. Propensity scores were obtained through logistic regression of patient characteristics on transfusion status (ie, actual receipt of a transfusion). A greedy matching technique17 was used to match unique transfused patients with unique nontransfused patients based on propensity scores. The best-match propensity score was identical to 6 digits. Once a match was made, the control patient was removed from the pool. This process was then repeated using 5-digit matching, then 4-digit matching, etc. If a transfused patient matched with more than 1 control, a match was randomly selected. The process proceeded sequentially to a single-digit match on propensity score. If a match was not obtained at this point, the transfused patient was excluded.

Cohorts reflecting patient groups of specific clinical interest were created post hoc. In particular, cohort was defined of those patients with acute bleeding as an indicator for transfusion at any time or having hemorrhagic shock on admission.

Table 1 describes the country participation and the characteristics of the participating ICUs.

Table Graphic Jump LocationTable 1. Summary of Participating Institutions*
Blood Sampling Study

Twenty-four–hour blood sampling data were collected on 1136 patients from 145 participating western European ICUs (see list at end of article). The number and volume of blood samples drawn in the 24-hour period varied widely across patients. A total of 45.9% of patients had 5 or more blood samples drawn. The mean (SD) number of draws per patient was 4.6 (3.2), the mean volume per draw was 10.3 (6.6) mL, and the average total volume was 41.1 (39.7) mL for the 24-hour period. There was a significant positive correlation between organ dysfunction (as measured by the SOFA score) and number of blood draws (r = 0.34; P<.001) and total volume drawn (r = 0.28; P<.001).

Anemia and Blood Transfusion Study
Demographics

Anemia and blood transfusion study data were collected on 3534 patients from 146 ICUs. Mean (SD) patient age was 61 (17) years, with 33.4% older than 70 years. The majority of patients (62%) were men. Table 2 presents the primary clinical data on admission to the ICU. The mean admitting APACHE II score was 14.8 (7.9) and the mean admitting SOFA score was 5.2 (3.8). Overall mean ICU length of stay was 4.5 (6.7) days (≤1 day, 46.6% of patients; 2-3 days, 21.4%; 4-7 days, 14.2%; and >7 days, 17.8%).

Course of Anemia

The mean (SD) admitting hemoglobin level was 11.3 (2.3) g/dL, with 63% (2078/3295) of patients having an admitting hemoglobin level less than 12 g/dL and 29% (963/3295) less than 10 g/dL. Admitting hemoglobin was correlated with age (r = −0.11; P < .001). The mean admitting hemoglobin level was 11.7 g/dL for patients younger than 50 years (n = 726), but 11.0 g/dL in patients aged 80 through 90 years (n = 298), and 9.9 g/dL in patients older than 90 years (n = 23) (F = 6.6; P<.001).

On admission, approximately 13% of patients had a recent history of anemia; of those patients, 36.6% had an admitting hemoglobin less than 10 g/dL. Of all patients with an admitting hemoglobin level less than 10 g/dL, 48.9% had neither a history of anemia nor of acute bleeding.

Hemoglobin patterns over the 28-day period, stratified by the day 1 hemoglobin level, are illustrated in Figure 1, revealing a convergence of hemoglobin levels over time, irrespective of the admitting hemoglobin level. Hemoglobin evolution was similar both for the cohort of patients without acute bleeding (75% of patients, n = 2655) and the cohort with acute bleeding (data not shown). There were weak negative correlations between admitting hemoglobin level and admitting SOFA score (r = −0.21, P<.001) and ICU length of stay (r = −0.25, P<.001).

Figure 1. Course of Hemoglobin (Hb) Patterns by Admitting Hb Level Category
Graphic Jump Location
Numbers do not total 3534 because of missing data (some forms incomplete).
Transfusions

The transfusion rate (proportion of 3534 patients transfused) during the ICU period was 37.0%, and the post-ICU transfusion rate was 12.7% (proportion of all patients initially admitted to the ICU). The overall transfusion rate (including both ICU and post-ICU timeframes) was 41.6% over the 28-day period. The mean (SD) age of blood transfused in the ICUs was 16.2 (6.7) days. Leukocyte-depleted blood was used most of the time by 46% of the ICUs surveyed, some of the time in 35%, and never in 19%. Transfusion rates differed significantly by hospital type, with community hospitals transfusing at a rate of 36.4%, regional hospitals at a rate of 39.8%, and academic hospitals at the highest rate of 44.2% (χ2 = 12.1; P<.002), which reflected the differences in severity of the patient populations as measured by mean admitting SOFA score across the hospital types (4.5 for patients in community hospitals, 5.1 for patients in regional hospitals, and 5.4 for patients in academic hospitals; F = 9.2; P<.001).

Two thirds of patients transfused within 24 hours prior to ICU admission had subsequent transfusions during the survey. Patients admitted for emergency surgery were transfused more frequently (57.5%), followed by those admitted for trauma (48.0%), elective surgery (42.1%), and medical reasons (32.0%). These differences were statistically significant (χ2 = 115.0; P<.001).

Transfusion rates increased consistently by age group, from 29.9% (18-30 years) to 54.2% (>80 years) (χ2 = 63.2; P<.001). However, differences in the mean number of units transfused by age, during both the ICU stay and throughout the 28-day survey, were not statistically significant.

Transfused patients were older, had higher admitting SOFA and APACHE II scores, lower admitting hemoglobin levels, and longer hospital lengths of stay (Table 3).

Table Graphic Jump LocationTable 3. Patient Characteristics by Transfusion Status*

The overall mean pretransfusion hemoglobin levels were 8.4 (1.3) g/dL for the entire population and 8.5 (1.1) g/dL for those without acute bleeding. Table 4 shows the distribution of indications for transfusion as well as the pretransfusion hemoglobin levels for both the ICU and the post-ICU periods. There were no significant differences in the mean pretransfusion hemoglobin levels by age, primary admitting diagnosis, or indication for transfusion (data not shown). Pretransfusion hemoglobin concentrations exceeded 9 g/dl in less than 30% of cases.

Table Graphic Jump LocationTable 4. Summary of Indications for Transfusion*

Higher transfusion rates were associated with increased ICU length of stay (Table 5). Mean ICU length of stay for transfused patients was 7.2 (median = 3) days compared with 2.6 (median = 1) days for nontransfused patients. Nearly 70% of all transfused patients received their first transfusion within the first 2 days in the ICU. Patients whose ICU length of stay was longer than 7 days had an overall transfusion rate of 73.3%, with a transfusion rate of 52.6% during the first 2 days in the ICU.

Table Graphic Jump LocationTable 5. Intensive Care Unit (ICU) Transfusion Rate and Mean Number of Units Transfused by ICU Length of Stay (LOS)

The association between transfusion rates and degree of organ failure, as assessed by the SOFA score, was statistically significant (χ2 = 358.5; P<.001). When transfused and nontransfused patients were paired within strata of their admitting SOFA scores, transfused patients had lower mean admitting hemoglobin levels than nontransfused patients at every admitting SOFA category (t tests significant at P<.05 within each SOFA category). Within each admitting SOFA category, the nontransfused groups consistently showed greater improvement in organ function over time than the transfused groups (data not shown). Mean daily SOFA scores were significantly higher in transfused patients than in nontransfused patients across the entire 28-day survey (P<.01 on all 28 days). Transfused patients both with and without bleeding had similar SOFA evolution (data not shown). The last recorded SOFA score, irrespective of length of stay, was significantly lower in the nontransfused group than in the transfused group (2.8 vs 4.8; t = −12.8; P<.001).

Mortality

ICU mortality was 13.5% and 28-day overall mortality was 20.2%. Both ICU and overall mortality rates were significantly higher for transfused vs nontransfused patients (ICU: 18.5% vs 10.1%, respectively; χ2 = 50.1; P<.001; overall: 29.0% vs 14.9%, respectively; χ2 = 88.1; P<.001). Higher 28-day mortality rates in transfused patients than in nontransfused patients persisted across all SOFA categories in all but the sickest patients (data not shown).

The 28-day survival curves differed significantly by admitting hemoglobin category in transfused patients (Kaplan-Meier log-rank = 30.3; P<.001) but not in nontransfused patients. Mortality rates were higher in transfused patients than in nontransfused patients at every hemoglobin category. There was a dose-response relationship between the number of RBC units transfused and mortality, with patients receiving the most units having the highest mortality rates (Table 6).

Table Graphic Jump LocationTable 6. Difference in Mortality by Number of Units Transfused

Hierarchical logistic regression was conducted to determine the associations between various patient characteristics and death in the ICU. In the first step, patients' admission characteristics (age, admitting hemoglobin level, APACHE II score, and SOFA score) were entered into the model; in the second step, transfusion status (yes/no) was entered. In this model (Table 7), the associations of transfusion, APACHE II, SOFA, and age with mortality were statistically significant but admitting hemoglobin level was not. Receipt of a transfusion in the ICU increased a patient's odds of dying by a factor of 1.37 (95% confidence interval, 1.02-1.84).

Table Graphic Jump LocationTable 7. Summary of Logistic Regression on Mortality*

To examine the specific association between transfusion and mortality, propensity scores18 were used to adjust for differences in all observed background characteristics in the estimation of the effects of transfusion.19 A logistic regression model was used to generate a propensity score that reflected the probability of being transfused for each patient. Variables chosen were age, sex, admission type, diagnosis on admission, admitting SOFA score, admitting APACHE II score, day 1 hemoglobin concentration, recent history of anemia, recent acute blood loss, whether the patient was in shock on admission, and hospital length of stay. The logistic regression model was able to correctly classify 76% of patients and produced a Nagelkerke R2 of 0.415. The probability of being transfused ranged from 0.01 to 0.97.

The matching process yielded 516 unique transfused and 516 unique nontransfused patients who were matched by their propensity scores. Postmatched comparisons of patient characteristics (from Table 3) are presented in Table 8 and illustrate that the differences between transfused and nontransfused patients along these parameters were no longer evident.

Table Graphic Jump LocationTable 8. Patient Characteristics by Transfusion Status for Propensity-Matched Patients*

Among the matched patients, 205 died during the 28-day follow-up period. Mortality of the transfused patients was 22.7% vs 17.1% for nontransfused patients (χ21 = 5.1; P = .02). In other words, of those who died, 57.1% were transfused, and 42.9% were not. Figure 2 illustrates the different survival curves for the matched transfused and nontransfused patients. The Kaplan-Meier log-rank statistic testing the equality of the survival distributions for the matched groups was 3.99 (df = 1; P = .05), indicating significantly different survival patterns.

Figure 2. Survival Analysis by Transfusion Status Among Propensity-Matched Patients
Graphic Jump Location
Course of Anemia

This large, epidemiologic study in European ICUs validates the common occurrence of anemia in critically ill patients and also reports that lower mean hemoglobin levels were associated with higher SOFA scores, longer lengths of stay, and higher mortality rates.

Our findings also underline that blood loss through blood sampling is considerable, averaging 41 mL per day. Sicker patients had more blood draws per 24 hours resulting in a higher total loss of blood than patients of lower acuity. Mechanisms to reduce blood sampling losses can include use of point-of-care testing20 and microchemistry techniques, use of tubing that eliminates the need for discard,21 a thorough knowledge and communication of the minimum volume needed for each laboratory test, and storage of blood specimens for potential subsequent use.22 Education and guideline development on such sparing mechanisms may lead to greater implementation.

Transfusion

The overall transfusion rate during the 28-day study period was 42%, with an ICU transfusion rate of 37%. While most transfusions were given within the first week of ICU admission, many transfusions continued to be given throughout the 28-day follow-up period. In patients with ICU length of stay longer than 1 week, 73% received a blood transfusion. This is slightly lower than the rate found in a 1995 study by Corwin et al,8 in which 85% of US patients with length of stay longer than 1 week received a blood transfusion.

The overall mean pretransfusion hemoglobin level was 8.4 g/dL, a value perhaps lower than expected. Actually, the distribution of pretransfusion hemoglobin levels indicated that transfusions were given at a hemoglobin level greater than 9 g/dL in less than 30% of cases. The important results of the Canadian Critical Care Trials Group10 have probably influenced practice. Surprisingly, there was no significant difference in the mean pretransfusion hemoglobin by age, primary admitting diagnosis, or indication for transfusion. Even patients whose transfusion indication was acute bleeding had pretransfusion hemoglobin levels similar to those of patients who had other indications for transfusion. Hence, it seems that the hemoglobin value is still the major determinant of the decision to transfuse.

While elderly patients had pretransfusion hemoglobin levels similar to those of younger patients, they had lower daily mean hemoglobin levels than younger patients (ie, had a higher incidence of reaching the transfusion trigger) and higher transfusion rates than younger patients. In addition to acute blood loss, common causes of anemia in elderly patients can include iron deficiency, chronic disorders, cancer, and nutritional or metabolic disorders.23 Aging itself may influence erythropoiesis, with possible contributors being a reduction in pluripotent hematopoetic stem cell reserve, reduced production of growth factors, reduced sensitivity of stem cells and progenitors to growth factors, and microenvironmental abnormalities.24

Transfused patients had longer ICU length of stay, more severe organ failure, and higher mortality rates than nontransfused patients, but these associations may be explained by different underlying clinical conditions. An altered or blunted erythropoietic response characteristic of anemia of chronic disease may also contribute to anemia in these sickest patients.1,4

We found that mortality rates differed significantly by organ failure and transfusion status. As expected, mortality increased in all patients as organ failure increased, but mortality was higher for transfused patients at all levels of organ dysfunction with the exception of those with the most severe organ failure.

Transfused patients had higher mortality rates at every admitting hemoglobin level when compared with nontransfused patients. Mortality rates also differed significantly by admitting hemoglobin group for transfused, but not for nontransfused, patients. There was a dose-response relationship with increasing mortality rates as the number of RBC units transfused increased. Receipt of a blood transfusion increased the risk of dying by a factor of 1.4 (all other variables being equal). Matching patients by their propensity scores for receipt of a transfusion (and hence controlling for age, admission type, diagnosis, admitting SOFA score, admitting APACHE II score, and length of stay) likewise revealed higher mortality rates in transfused patients.

Of the deleterious effects of RBC transfusion, the likely contributing factor to mortality in the critically ill population is related to immunosuppression as opposed to allergic reaction or infectious transmission. Red blood cell transfusion has been associated with a higher incidence of postoperative infection in various populations.2527 The use of leukodepleted blood may result in shorter lengths of stay and fewer complications.28,29 At the time of this study, the use of deleukocyted blood in participating institutions was variable. Variability in storage techniques may also contribute to RBC deformability that may influence cell oxygen availability.

Due to the risks associated with blood transfusions, alternative treatments of anemia in the critically ill are being explored. The administration of exogenous human recombinant erythropoietin (epoetin alfa) has been shown to raise reticulocyte counts26,27 and hematocrit levels, and to reduce the total number of units of transfused blood required in critically ill patients.28

Interpretation of findings from this observational study should be limited to identification and description of associations between variables of interest. No intervention was implemented, no attempt to control or influence provision of care was made, and the physicians were not blinded to the study purpose. Additionally, the illnesses and treatments of the critically ill are complex and confounded by a multitude of factors. Moreover, data collection in studies of this design is necessarily limited, and not all factors that may have influenced physicians' transfusing practice may not have been collected. Therefore, no causal inferences for associations can be drawn.

The findings from this study reveal that anemia in critically ill patients is common. Transfusions are also common, especially in elderly patients and those with longer ICU lengths of stay. Even though transfusions currently seem to be given primarily in response to decreased hemoglobin levels, the trigger for blood transfusions averaged only 8.4 g/dL. This study provides evidence of the associations between transfusion and diminished organ function as well as between low hemoglobin level, transfusion, and mortality. Clearly, further study is needed to clarify the place of transfusion in critically ill patients and to evaluate other treatments for anemia that reduce the need for blood transfusions, such as the use of recombinant human erythropoietin (epoetin alfa).

von Ahsen N, Muller C, Serke S, Frei U, Eckardt KU. Important role of nondiagnostic blood loss and blunted erythropoietic response in the anemia of medical intensive care patients.  Crit Care Med.1999;27:2630-2639.
Nelson AH, Fleisher LA, Rosenbaum SH. Relationship between postoperative anemia and cardiac morbidity in high-risk vascular patients in the intensive care unit.  Crit Care Med.1993;21:860-866.
Hébert PC, Wells G, Tweeddale M.  et al. for the Transfusion Requirements in Critical Care (TRICC) Investigators and the Canadian Critical Care Trials Group.  Does transfusion practice affect mortality in critically ill patients?  Am J Respir Crit Care Med.1997;155:1618-1623.
Rogiers P, Zhang H, Leeman M.  et al.  Erythropoietin response is blunted in critically ill patients.  Intensive Care Med.1997;23:159-162.
Burnum JF. Medical vampires.  N Engl J Med.1986;314:1250-1251.
Viljoen M, Coetzee IH, Roux JJ, Pretorius JP. Anemia in surgical intensive care patients.  Haematologica.1994;79:19-24.
Groeger JS, Guntupalli KK, Strosberg M.  et al.  Descriptive analysis of critical care units in the United States: patient characteristics and intensive care unit utilization.  Crit Care Med.1993;21:279-291.
Corwin HL, Parsonnet KC, Gettinger A. RBC transfusion in the ICU: is there a reason?  Chest.1995;108:767-771.
Goodnough LT, Despotis GJ, Hogue Jr CW, Ferguson Jr TB. On the need for improved transfusion indicators in cardiac surgery.  Ann Thorac Surg.1995;60:473-480.
Hébert PC, Wells G, Blajchman MA.  et al. for the Transfusion Requirements in Critical Care Investigators, Canadian Critical Care Trials Group.  A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care.  N Engl J Med.1999;340:409-417.
Brunson ME, Alexander JW. Mechanisms of transfusion-induced immunosuppression.  Transfusion.1990;30:651-658.
Stevens CE, Aach RD, Hollinger FB.  et al.  Hepatitis B virus antibody in blood donors and the occurrence of non-A, non-B hepatitis in transfusion recipients: an analysis of the Transfusion-Transmitted Viruses Study.  Ann Intern Med.1984;101:733-738.
Blumberg N, Heal JM, Murphy P, Agarwal MM, Chuang C. Association between transfusion of whole blood and recurrence of cancer.  Br Med J (Clin Res Ed).1986;293:530-533.
Blumberg N, Heal JM. Immunomodulation by blood transfusion: an evolving scientific and clinical challenge.  Am J Med.1996;101:299-308.
Marik PE, Sibbald WJ. Effect of stored-blood transfusion on oxygen delivery in patients with sepsis.  JAMA.1993;269:3024-3029.
Vincent JL, Moreno R, Takala J.  et al.  The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure.  Intensive Care Med.1996;22:707-710.
Gum PA, Thamilarasan M, Watanabe J, Blackstone EH, Lauer MS. Aspirin use and all-cause mortality among patients being evaluated for known or suspected coronary artery disease.  JAMA.2001;286:1187-1194.
Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score.  J Am Stat Assoc.1984;79:516-524.
Rubin DB. Estimating causal effects from large data sets using propensity scores.  Ann Intern Med.1997;127:757-763.
Schallom L. Point of care testing in critical care.  Crit Care Nurs Clin North Am.1999;11:99-106.
Silver MJ, Li YH, Gragg LA, Jubran F, Stoller JK. Reduction of blood loss from diagnostic sampling in critically ill patients using a blood-conserving arterial line system.  Chest.1993;104:1711-1715.
Dale JC, Pruett SK. Phlebotomy—a minimalist approach.  Mayo Clin Proc.1993;68:249-255.
Ania BJ, Suman VJ, Fairbanks VF, Rademacher DM, Melton III LJ. Incidence of anemia in older people: an epidemiologic study in a well defined population.  J Am Geriatr Soc.1997;45:825-831.
Balducci L, Hardy CL. Anemia of aging: a model of erythropoiesis in cancer patients.  Cancer Control.1998;5:17-21.
Jensen LS, Andersen AJ, Christiansen PM.  et al.  Postoperative infection and natural killer cell function following blood transfusion in patients undergoing elective colorectal surgery.  Br J Surg.1992;79:513-516.
Jensen LS, Hokland M, Nielsen HJ. A randomized controlled study of the effect of bedside leucocyte depletion on the immunosuppressive effect of whole blood transfusion in patients undergoing elective colorectal surgery.  Br J Surg.1996;83:973-977.
Tartter PI, Mohandas K, Azar P, Endres J, Kaplan J, Spivack M. Randomized trial comparing packed red cell blood transfusion with and without leukocyte depletion for gastrointestinal surgery.  Am J Surg.1998;176:462-466.
Gott JP, Cooper WA, Schmidt FE.  et al.  Modifying risk for extracorporeal circulation: trial of four antiinflammatory strategies.  Ann Thorac Surg.1998;66:747-753.
van de Watering LM, Hermans J, Houbiers JG.  et al.  Beneficial effects of leukocyte depletion of transfused blood on postoperative complications in patients undergoing cardiac surgery: a randomized clinical trial.  Circulation.1998;97:562-568.
Gabriel A, Kozek S, Chiari A.  et al.  High-dose recombinant human erythropoietin stimulates reticulocyte production in patients with multiple organ dysfunction syndrome.  J Trauma.1998;44:361-367.
van Iperen CE, Gaillard CA, Kraaijenhagen RJ, Braam BG, Marx JJ, van de Wiel A. Response of erythropoiesis and iron metabolism to recombinant human erythropoietin in intensive care unit patients.  Crit Care Med.2000;28:2773-2778.
Corwin HL, Gettinger A, Rodriguez RM.  et al.  Efficacy of recombinant human erythropoietin in the critically ill patient: a randomized, double-blind, placebo-controlled trial.  Crit Care Med.1999;27:2346-2350.

Figures

Figure 1. Course of Hemoglobin (Hb) Patterns by Admitting Hb Level Category
Graphic Jump Location
Numbers do not total 3534 because of missing data (some forms incomplete).
Figure 2. Survival Analysis by Transfusion Status Among Propensity-Matched Patients
Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Summary of Participating Institutions*
Table Graphic Jump LocationTable 3. Patient Characteristics by Transfusion Status*
Table Graphic Jump LocationTable 4. Summary of Indications for Transfusion*
Table Graphic Jump LocationTable 5. Intensive Care Unit (ICU) Transfusion Rate and Mean Number of Units Transfused by ICU Length of Stay (LOS)
Table Graphic Jump LocationTable 6. Difference in Mortality by Number of Units Transfused
Table Graphic Jump LocationTable 7. Summary of Logistic Regression on Mortality*
Table Graphic Jump LocationTable 8. Patient Characteristics by Transfusion Status for Propensity-Matched Patients*

References

von Ahsen N, Muller C, Serke S, Frei U, Eckardt KU. Important role of nondiagnostic blood loss and blunted erythropoietic response in the anemia of medical intensive care patients.  Crit Care Med.1999;27:2630-2639.
Nelson AH, Fleisher LA, Rosenbaum SH. Relationship between postoperative anemia and cardiac morbidity in high-risk vascular patients in the intensive care unit.  Crit Care Med.1993;21:860-866.
Hébert PC, Wells G, Tweeddale M.  et al. for the Transfusion Requirements in Critical Care (TRICC) Investigators and the Canadian Critical Care Trials Group.  Does transfusion practice affect mortality in critically ill patients?  Am J Respir Crit Care Med.1997;155:1618-1623.
Rogiers P, Zhang H, Leeman M.  et al.  Erythropoietin response is blunted in critically ill patients.  Intensive Care Med.1997;23:159-162.
Burnum JF. Medical vampires.  N Engl J Med.1986;314:1250-1251.
Viljoen M, Coetzee IH, Roux JJ, Pretorius JP. Anemia in surgical intensive care patients.  Haematologica.1994;79:19-24.
Groeger JS, Guntupalli KK, Strosberg M.  et al.  Descriptive analysis of critical care units in the United States: patient characteristics and intensive care unit utilization.  Crit Care Med.1993;21:279-291.
Corwin HL, Parsonnet KC, Gettinger A. RBC transfusion in the ICU: is there a reason?  Chest.1995;108:767-771.
Goodnough LT, Despotis GJ, Hogue Jr CW, Ferguson Jr TB. On the need for improved transfusion indicators in cardiac surgery.  Ann Thorac Surg.1995;60:473-480.
Hébert PC, Wells G, Blajchman MA.  et al. for the Transfusion Requirements in Critical Care Investigators, Canadian Critical Care Trials Group.  A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care.  N Engl J Med.1999;340:409-417.
Brunson ME, Alexander JW. Mechanisms of transfusion-induced immunosuppression.  Transfusion.1990;30:651-658.
Stevens CE, Aach RD, Hollinger FB.  et al.  Hepatitis B virus antibody in blood donors and the occurrence of non-A, non-B hepatitis in transfusion recipients: an analysis of the Transfusion-Transmitted Viruses Study.  Ann Intern Med.1984;101:733-738.
Blumberg N, Heal JM, Murphy P, Agarwal MM, Chuang C. Association between transfusion of whole blood and recurrence of cancer.  Br Med J (Clin Res Ed).1986;293:530-533.
Blumberg N, Heal JM. Immunomodulation by blood transfusion: an evolving scientific and clinical challenge.  Am J Med.1996;101:299-308.
Marik PE, Sibbald WJ. Effect of stored-blood transfusion on oxygen delivery in patients with sepsis.  JAMA.1993;269:3024-3029.
Vincent JL, Moreno R, Takala J.  et al.  The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure.  Intensive Care Med.1996;22:707-710.
Gum PA, Thamilarasan M, Watanabe J, Blackstone EH, Lauer MS. Aspirin use and all-cause mortality among patients being evaluated for known or suspected coronary artery disease.  JAMA.2001;286:1187-1194.
Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score.  J Am Stat Assoc.1984;79:516-524.
Rubin DB. Estimating causal effects from large data sets using propensity scores.  Ann Intern Med.1997;127:757-763.
Schallom L. Point of care testing in critical care.  Crit Care Nurs Clin North Am.1999;11:99-106.
Silver MJ, Li YH, Gragg LA, Jubran F, Stoller JK. Reduction of blood loss from diagnostic sampling in critically ill patients using a blood-conserving arterial line system.  Chest.1993;104:1711-1715.
Dale JC, Pruett SK. Phlebotomy—a minimalist approach.  Mayo Clin Proc.1993;68:249-255.
Ania BJ, Suman VJ, Fairbanks VF, Rademacher DM, Melton III LJ. Incidence of anemia in older people: an epidemiologic study in a well defined population.  J Am Geriatr Soc.1997;45:825-831.
Balducci L, Hardy CL. Anemia of aging: a model of erythropoiesis in cancer patients.  Cancer Control.1998;5:17-21.
Jensen LS, Andersen AJ, Christiansen PM.  et al.  Postoperative infection and natural killer cell function following blood transfusion in patients undergoing elective colorectal surgery.  Br J Surg.1992;79:513-516.
Jensen LS, Hokland M, Nielsen HJ. A randomized controlled study of the effect of bedside leucocyte depletion on the immunosuppressive effect of whole blood transfusion in patients undergoing elective colorectal surgery.  Br J Surg.1996;83:973-977.
Tartter PI, Mohandas K, Azar P, Endres J, Kaplan J, Spivack M. Randomized trial comparing packed red cell blood transfusion with and without leukocyte depletion for gastrointestinal surgery.  Am J Surg.1998;176:462-466.
Gott JP, Cooper WA, Schmidt FE.  et al.  Modifying risk for extracorporeal circulation: trial of four antiinflammatory strategies.  Ann Thorac Surg.1998;66:747-753.
van de Watering LM, Hermans J, Houbiers JG.  et al.  Beneficial effects of leukocyte depletion of transfused blood on postoperative complications in patients undergoing cardiac surgery: a randomized clinical trial.  Circulation.1998;97:562-568.
Gabriel A, Kozek S, Chiari A.  et al.  High-dose recombinant human erythropoietin stimulates reticulocyte production in patients with multiple organ dysfunction syndrome.  J Trauma.1998;44:361-367.
van Iperen CE, Gaillard CA, Kraaijenhagen RJ, Braam BG, Marx JJ, van de Wiel A. Response of erythropoiesis and iron metabolism to recombinant human erythropoietin in intensive care unit patients.  Crit Care Med.2000;28:2773-2778.
Corwin HL, Gettinger A, Rodriguez RM.  et al.  Efficacy of recombinant human erythropoietin in the critically ill patient: a randomized, double-blind, placebo-controlled trial.  Crit Care Med.1999;27:2346-2350.

Letters

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 575

Related Content

Customize your page view by dragging & repositioning the boxes below.

See Also...
Articles Related By Topic
Related Collections
PubMed Articles