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Original Contribution |

Perioperative Blood Transfusion and Postoperative Mortality FREE

Jeffrey L. Carson, MD; Amy Duff, MHS; Jesse A. Berlin, ScD; Valerie A. Lawrence, MD, MSc; Roy M. Poses, MD; Elizabeth C. Huber, MD; Dorene A. O'Hara, MD, MSE; Helaine Noveck, MPH; Brian L. Strom, MD, MPH
[+] Author Affiliations

From the Division of General Internal Medicine, Departments of Medicine (Dr Carson and Mss Duff and Noveck) and Anesthesia (Dr O'Hara), University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick; Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology (Drs Berlin and Strom), and Division of General Internal Medicine, Department of Medicine (Dr Strom), University of Pennsylvania School of Medicine, Philadelphia; Division of General Medicine, Audie Murphy Division, South Texas Veterans Health Care System and Department of Medicine, University of Texas at San Antonio (Dr Lawrence); Division of General Internal Medicine, Department of Medicine, Brown University School of Medicine, Providence, RI, and Memorial Hospital of Rhode Island, Pawtucket (Dr Poses); and Division of General Internal Medicine, Medical College of Virginia, Richmond (Dr Huber).


JAMA. 1998;279(3):199-205. doi:10.1001/jama.279.3.199.
Text Size: A A A
Published online

Context.— The risks of blood transfusion have been studied extensively but the benefits and the hemoglobin concentration at which patients should receive a transfusion have not.

Objective.— To determine the effect of perioperative transfusion on 30- and 90-day postoperative mortality.

Design.— Retrospective cohort study.

Setting.— A total of 20 US hospitals between 1983 and 1993.

Participants.— A total of 8787 consecutive hip fracture patients, aged 60 years or older, who underwent surgical repair.

Main Outcome Measures.— Primary outcome was 30-day postoperative mortality; secondary outcome was 90-day postoperative mortality. The "trigger" hemoglobin level was defined as the lowest hemoglobin level prior to the first transfusion during the time period or, for patients in the nontranfused group, as the lowest hemoglobin level during the time period.

Results.— Overall 30-day mortality was 4.6% (n=402; 95% confidence interval [CI], 4.1%-5.0%); overall 90-day mortality was 9.0% (n=788; 95% CI, 8.4%-9.6%). A total of 42% of patients (n=3699) received a postoperative transfusion. Among patients with trigger hemoglobin levels between 80 and 100 g/L (8.0 and 10.0 g/dL), 55.6% received a transfusion, while 90.5% of patients with hemoglobin levels less than 80 g/L (8.0 g/dL) received postoperative transfusions. Postoperative transfusion did not influence 30- or 90-day mortality after adjusting for trigger hemoglobin level, cardiovascular disease, and other risk factors for death: for 30-day mortality, the adjusted odds ratio (OR) was 0.96 (95% CI, 0.74-1.26); for 90-day mortality, the adjusted hazard ratio was 1.08 (95% CI, 0.90-1.29). Similarly, 30-day mortality after surgery did not differ between those who received a preoperative transfusion and those who did not (adjusted OR, 1.23; 95% CI, 0.81-1.89).

Conclusions.— Perioperative transfusion in patients with hemoglobin levels 80 g/L (8.0 g/dL) or higher did not appear to influence the risk of 30- or 90-day mortality in this elderly population. At hemoglobin concentrations of less than 80 g/L (8.0 g/dL), 90.5% of patients received a transfusion, precluding further analysis of the association of transfusion and mortality.

Figures in this Article

BLOOD TRANSFUSIONS, like all other medical treatments, should be prescribed only after consideration of the risks vs the benefits of the therapy. While the potential risks associated with blood transfusions are well described,1,2 much less is known about the benefits of blood transfusion. The practice of giving a patient a transfusion for a hemoglobin level less than 100 g/L (10 g/dL) or a hematocrit less than 0.30 is no longer uniformly accepted.3

We know of only 5 randomized clinical trials, including a total of 207 patients, that have contrasted transfusion triggers.48 No differences in mortality or morbidity were found between high and low transfusion thresholds. However, even collectively, these trials followed too few patients to evaluate the effect of lower transfusion triggers on clinically important outcomes. Published observational studies did not adequately control for risk factors for death or explore transfusion at hemoglobin levels other than 100 g/L (10.0 g/dL).9,10 The lack of adequate studies on the efficacy of red blood cell transfusion may help explain the great variation in transfusion practices.11

We evaluated 30- and 90-day postoperative mortality in patients with hip fracture, comparing those who received preoperative and postoperative transfusions with similar patients who did not receive transfusions. The goals of this study were to determine whether red blood cell transfusion influences mortality at different preoperative and postoperative hemoglobin levels.

Study Population

The study population included consecutive hip fracture patients, aged 60 years or older, who underwent surgical repair at one of the study hospitals between 1983 and 1993. Patients were excluded if they refused blood transfusion, had metastatic cancer, or underwent a surgical procedure involving a site other than the hip. The 20 participating hospitals were drawn from 4 metropolitan areas: New Brunswick, NJ; San Antonio, Tex; Philadelphia, Pa; and Richmond, Va. These hospitals included university, community, and Veterans Affairs medical centers and were selected based on their willingness to have their medical records reviewed.

Study Design and Outcome Variable

We performed a retrospective cohort study. The primary study outcome was defined as death within 30 days of the operative procedure. The secondary outcome was death within 90 days of the operative procedure. A National Death Index search was used to identify deaths that occurred after discharge but within 90 days of the operation.

Data Collection

A retrospective chart review was conducted using standardized, pretested forms and an explicit abstraction process. Quality assurance was performed by reviewing a random sample of medical records. We collected information on demographic characteristics (age, sex, race, insurance, preadmission residence, hospital admission year), comorbid conditions (see below), habits (smoking, alcohol use), medications used prior to admission and during the preoperative and postoperative time periods, preoperative physical examination (vital signs, cardiac examination, mental status, motor strength, whether the patient was malnourished or cachectic, or presence of decubitus ulcer), laboratory results (electrocardiogram, chest radiograph, arterial blood gas values, echocardiogram, blood glucose, creatinine, and liver enzyme levels, coagulation tests), cointerventions (preoperative admission to the intensive care unit, thromboembolism prophylaxis, antibiotic prophylaxis, physical therapy, respiratory therapy, preoperative consultations), hip fracture treatment (type of hip fracture, surgical procedure, use of cement, physical and occupational therapy), operative events (type and duration of anesthesia, hypotension, tachycardia, arrhythmias, use of pressors, Swan-Ganz catheter pressures, operative blood loss and intraoperative transfusions), postoperative complications, and deaths. Detailed information on hemoglobin levels and timing of transfusion was also collected. The cause of death is not reported because it was not available in the charts.

Perioperative transfusion was defined as a transfusion occurring within 7 days before or after the surgical repair of the hip fracture. The patient's perioperative transfusion status was defined separately for the preoperative and postoperative time periods. In the preoperative transfusion analysis, patients who received 1 or more transfusions within 7 days prior to the operative procedure were compared with patients who did not receive a transfusion during the corresponding time period. Similarly, for the postoperative analysis, patients who received 1 or more transfusions within 7 days after the operative procedure were compared with patients who did not receive a transfusion during the corresponding time period.

For patients receiving a preoperative transfusion, the preoperative trigger hemoglobin level was defined as the lowest hemoglobin level prior to the first transfusion and within 7 days prior to surgery. For those who did not receive a preoperative transfusion, the preoperative trigger was the lowest hemoglobin level within 7 days prior to surgery. For patients who received a postoperative transfusion, the postoperative trigger hemoglobin level was defined as the lowest hemoglobin level prior to the first transfusion. For those who did not receive a postoperative transfusion, the postoperative trigger was the lowest hemoglobin level within 7 days after surgery. We did not study intraoperative transfusions because hemoglobin levels are not routinely measured during the intraoperative time period.

Information on the presence of many comorbid conditions was collected. Cardiovascular disease was defined as history of any of the following: myocardial infarction, angina or ischemic chest pain, coronary artery disease, coronary artery bypass surgery, percutaneous transluminal coronary angioplasty, history of congestive heart failure, or history of peripheral vascular disease. Data were collected on the following other comorbid conditions: history of valvular heart disease, arrhythmia, hypertension, diabetes mellitus, dementia, stroke or transient ischemic attack, thromboembolism, chronic lung disease, malignancy, gastrointestinal bleeding, swallowing disorder, liver disease, arthritis, hospitalizations within the preceding month, and prior hip fracture.

We also collected information to calculate the Charlson comorbidity index score,12 the acute physiology score (APS) of the Acute Physiology and Chronic Health Evaluation (APACHE) II index,13 and the 30-day sickness at admission scale score.14 The APACHE II index is predictive of in-hospital mortality for critically ill patients.15 The APS was calculated without the hemoglobin points because hemoglobin is an important a priori confounding variable and therefore was included as a separate variable in all models. The Charlson index incorporates many common, serious comorbid conditions and is a predictor of mortality for medical inpatients.13 We did not include cardiovascular disease points in the total Charlson score so that we could evaluate the independent effect of cardiovascular disease. We also used the 30-day sickness at admission scale that was developed specifically to predict mortality in hip fracture patients and the American Society of Anesthesiologists (ASA) physical status classification system that predicts postoperative mortality.16,17 For the postoperative transfusion analysis, the APS was analyzed as a continuous variable and the Charlson index score as a dichotomous variable (no points vs any points), and the ASA classifications were grouped into 3 categories (1 or 2; 3; 4 or 5).

Statistical Analysis

We performed 3 separate analyses: (1) postoperative transfusion and 30-day mortality, (2) postoperative transfusion and 90-day mortality, and (3) preoperative transfusion and 30-day mortality. Preoperative transfusion by 90-day mortality was not examined because there was no a priori reason that this would relate to long-term mortality. Detailed descriptive information in the tables is only presented for postoperative transfusion and 30-day mortality for the purposes of brevity and clarity. The results for the other analyses were very similar.

For each of the separate analyses described above, the unadjusted relationships between outcome and transfusion status and potential confounders (including trigger hemoglobin levels, cardiovascular disease, and other patient characteristics) were assessed using an independent sample t test or a χ2 test.18 We calculated the unadjusted odds ratio (OR) for the effect of transfusion instead of the relative risk, so it could be compared with the adjusted OR generated by a logistic regression model.

Logistic regression (30-day mortality) and Cox proportional hazards models (90-day mortality) were used to describe the effect of transfusion on mortality after adjusting for potential confounders. The trigger hemoglobin and cardiovascular disease variables were included in all models because of strong a priori hypotheses about their relationships with transfusion and death.1922 In the postoperative transfusion analyses, the trigger hemoglobin level was included in the model as a continuous variable with values greater than 110 g/L (11.0 g/dL) set to 110 g/L (11.0 g/dL), because we assumed a priori that there would be no further decrease in risk with increases in hemoglobin levels above 110 g/L (11.0 g/dL) and to reduce any undue influence of the small number of very high hemoglobin values. Repeating the analyses without grouping hemoglobin levels greater than 110 g/L (11.0 g/dL) resulted in similar results. In the preoperative analysis, the relationship between trigger hemoglobin and 30-day mortality was not linear, and, therefore, hemoglobin was grouped as follows: less than 80 g/L (8.0 g/dL), 80 through 89 g/L (8.0-8.9 g/dL), 90 through 99 g/L (9.0-9.9 g/dL), and 100 g/L or more (≥10.0 g/dL). The assumption that the hazard ratios are proportional could not be rejected.

Potential confounding variables included characteristics that met all the following criteria: (1) had a statistically significant univariate relationship with death (P≤.05), (2) were present in at least 5% of the population, and (3) had no expected value less than 5 in the contingency table analysis. Any variable meeting these criteria was added individually to a model with transfusion status, trigger hemoglobin, and cardiovascular disease. All variables maintaining a P value of .10 or less were included in the final model. The potential confounding variables considered are listed in the data collection portion of the "Methods" section.

Logistic regression (30-day mortality) and Cox proportional hazards models (90-day mortality) were also used to determine whether the effect of transfusion differed according to trigger hemoglobin level and cardiovascular disease status. We constructed regression models with a term for the 3-way interaction among transfusion status, trigger hemoglobin level, and cardiovascular disease status along with all second-order interactions and main effect variables. In the postoperative transfusion analysis of 30-day mortality, the results suggested a possible 3-way interaction. Therefore, subanalyses using procedures identical to the overall analysis were performed within hemoglobin stratum and within cardiovascular disease stratum.

In addition to controlling for confounding in the logistic regression model as described above, we also stratified patients based on their predicted probability of receiving a transfusion. First, we constructed a predictive model for postoperative transfusion. Candidate variables for the model included those that were clinically plausible, occurred in more than 5% of patients, and had a significant univariate relationship with transfusion. Stepwise regression was then used to identify variables for the final model. The probability of transfusion for each patient was generated using the final predictive model. We then divided patients into quintiles based on their predicted probability of receiving a transfusion. We used the Breslow-Day test across quintiles of predicted transfusion probability to assess homogeneity of the ORs23 and then calculated the common OR using the Mantel-Haenszel procedure.24

All analyses were performed using SAS version 6.11.25

Effect of Postoperative Transfusion on 30-Day Mortality

Of the 9598 patients eligible for the study, 806 were excluded because a postoperative hemoglobin trigger could not be defined. Of these excluded patients, 591 received a transfusion, and a hemoglobin level was not recorded prior to the first postoperative transfusion; 215 of these patients did not receive a transfusion, and no hemoglobin level was recorded within 7 days after surgery (30-day mortality was 6.3% and 8.8%, respectively). Five patients had a postoperative transfusion during a subsequent operative procedure and were also excluded from the postoperative analysis. The 8787 patients included in this analysis are described in Table 1. The mean age was 80.3 years (SD, 8.7; range, 60-106). The overall 30-day mortality was 4.6% (n=402; 95% confidence interval [CI], 4.1%-5.0%).

Table Graphic Jump LocationTable 1.—Description of Patient Population and Univariate Relationship With 30-Day Mortality

A total of 3699 (42%) of the 8787 patients received a transfusion within 7 days of the surgical repair. The greatest variability in transfusion practice occurred in patients who received a postoperative transfusion with trigger hemoglobin levels between 80 and 99 g/L (8.0-9.9 g/dL), in which 2474 (55.6%) of 4452 patients received a transfusion (Table 2). The vast majority of patients (1014 [90.5%] of 1120) with a trigger hemoglobin level less than 80 g/L (8.0 g/dL) received a transfusion. In contrast, only 211 (6.6%) of 3195 patients with a trigger hemoglobin level greater than 100 g/L (10.0 g/dL) received a transfusion. The clinical characteristics of the transfused and nontransfused patients are shown in Table 3.

Table Graphic Jump LocationTable 2.—Postoperative Hemoglobin Trigger and 30-Day Mortality
Table Graphic Jump LocationTable 3.—Patient Characteristics by Postoperative Transfusion Status

The death rate at 30 days in the postoperative transfused group was 5.3%, compared with 4.0% in the nontransfused group (OR, 1.34; 95% CI, 1.10-1.64). After adjusting for trigger hemoglobin level using logistic regression analysis, the OR for 30-day postoperative death after postoperative transfusion vs no transfusion decreased to 1.15 (95% CI, 0.89-1.48). Adjusting for cardiovascular disease did not substantially change the OR (OR, 1.11; 95% CI, 0.86-1.44). The following variables maintained a P value of .10 or less and were included in the final model with transfusion, trigger hemoglobin level, and cardiovascular disease: APS (continuous), Charlson comorbidity index (any points vs no points), sickness at admission scale (quartiles), age (grouped as ages 60-69 years, 70-79 years, 80-89 years, and ≥90 years), sex, history of atrial fibrillation, history of anemia within 1 year of admission, whether the patient was malnourished or cachectic on physical examination, presence of decubiti at admission, abnormal preoperative chest radiograph, intraoperative tachycardia, preoperative transfusion, and hospital (categorical). The OR for postoperative transfusion controlling for all these variables further declined to 0.96 (95% CI, 0.74-1.26). Operative blood loss and intraoperative transfusion had a P value greater than .10 and were not included in the final model.

We then evaluated whether the effect of transfusion on mortality was different for patients with different hemoglobin levels and cardiovascular disease status. We found a borderline significant result for the 3-way interaction term among trigger hemoglobin level, cardiovascular disease, and transfusion status in the unadjusted model (P=.07), with little change in a fully adjusted model (P=.06). Therefore, we performed subgroup analyses within 3 hemoglobin strata: 100 g/L or more (≥10.0 g/dL), 80 to 99 g/L (8.0-9.9 g/dL), and 70 to 79 g/L (7.0-7.9 g/dL), and by cardiovascular disease status. The results for each of the strata were similar to one another and to the results of the overall analysis (Table 4). The cardiovascular disease by transfusion interaction was not significant within the hemoglobin strata subgroups (P>.2).

Table Graphic Jump LocationTable 4.—The 30-Day Mortality for Patients Receiving Postoperative Transfusion Compared With Those Not Receiving Transfusion, Both Unadjusted and Adjusted for Potential Confounding Variables*

We also stratified patients by their likelihood of receiving a transfusion. The variables included in the final logistic regression model to predict postoperative transfusion were trigger hemoglobin level (divided into 5 groups: ≥110 g/L [≥11.0 g/dL], 100-109 g/L [10.0-10.9 g/dL], 90-99 g/L [9.0-9.9 g/dL], 80-89 g/L [8.0-8.9 g/dL], and <80 g/L [<8.0 g/dL]); hospital (added as 18 indicator variables); surgical procedure (divided into 4 groups: internal fixation with pinning, internal fixation other than pinning, hemiarthroplasty, and total arthroplasty); age (as a continuous variable); anesthesia time (divided into quartiles); cardiovascular disease; Parkinson disease; anemia within 1 year of admission; tachycardia in the operating room; blood loss (divided into 3 groups: ≤500 mL or missing, 501-1000 mL, and >1000 mL); femoral neck fracture; subtrochanteric fracture; and admission year (entered as a continuous variable). Model discrimination to predict who would receive a transfusion was excellent (C-statistic=0.90).

The results from the analysis stratified by quintiles defined by probability of transfusion are presented in Table 5. The common OR was 1.02 (95% CI, 0.78-1.34). We repeated this analysis excluding patients with missing values for blood loss, and the results were essentially the same.

Table Graphic Jump LocationTable 5.—Results of Analysis Stratified by Likelihood of Transfusion
Effect of Postoperative Transfusion on 90-Day Mortality

The overall 90-day mortality was 9.0% (n=788; 95% CI, 8.4%-9.6%). The hazard ratio for transfusion was 1.34 (95% CI, 1.16-1.54), adjusted for hemoglobin level was 1.18 (95% CI, 0.98-1.41), and adjusted for hemoglobin level and cardiovascular disease was 1.15 (95% CI, 0.96-1.37). The fully adjusted hazards ratio (using the same procedure as for 30-day mortality) was 1.08 (95% CI, 0.90-1.29). The 3-way interaction among postoperative trigger hemoglobin level, cardiovascular disease, and transfusion status was not significant (P=.40) nor were any of the 2-way interactions. The adjusted mortality curves for the transfused and nontransfused groups are displayed in Figure 1.

Graphic Jump Location
The 90-day mortality curve in 8787 patients with hip fracture stratified by transfusion status. Variables adjusted for in the postoperative transfusion 90-day mortality analysis included race; sex; age; acute physiology score of the Acute Physiology and Chronic Health Evaluation II index; Charlson comorbidity index; sickness at admission scale; history of atrial fibrillation; hypertension; history of anemia within 1 year of admission; history of confusion; patient found to be malnourished or cachectic on physical examination; any malignancy; abnormal preoperative chest radiograph; intraoperative tachycardia; preoperative transfusion; and hospital.
Effect of Preoperative Transfusion on 30-Day Mortality

A total of 9474 patients were included in the preoperative transfusion analysis. Of the 9598 patients eligible for the study, 2 were excluded because their preoperative transfusion status could not be determined from the available data. An additional 122 were excluded because a preoperative trigger hemoglobin level could not be defined. A total of 682 (7.2%) patients underwent a preoperative transfusion.

The results of the preoperative transfusion analysis were similar to those of the postoperative transfusion analysis. The unadjusted OR for preoperative transfusion was 2.49 (95% CI, 1.90-3.26). After adjusting for preoperative transfusion trigger hemoglobin, cardiovascular disease, and other confounding variables, the adjusted OR was 1.24 (95% CI, 0.81-1.90). The 3-way interaction among preoperative trigger hemoglobin level, cardiovascular disease, and transfusion status was not significant (P=.11) nor were any of the 2-way interactions.

We studied the effect of transfusion in a large, high-risk, elderly population with extensive comorbidity and were unable to demonstrate that transfusion was associated with a reduced 30- or 90-day postoperative mortality. These results suggest that patients who had hemoglobin levels as low as 80 g/L (8.0 g/dL) and did not receive a transfusion were no more likely to die than those with similar hemoglobin levels who received a transfusion. With a hemoglobin level less than 80 g/L (8.0 g/dL), nearly all patients received a transfusion, the effect of which could not be calculated.

We did not confirm prior studies that suggested there might be differences in the effect of anemia in patients with and without cardiovascular disease. In a study of 1958 patients who refused blood transfusion for religious reasons, patients with cardiovascular disease had a greater risk of death than patients without cardiovascular disease at hemoglobin levels less than 100 g/L (10.0 g/dL).23 Similarly, anemic dogs showed ischemic ST segment changes and locally depressed cardiac function at higher hemoglobin levels (70-100 g/L [7.0-10.0 g/dL]) with experimentally created coronary stenoses varying from 50% to 80%21,26,27 more than normal animals (30-50 g/L [3.0-5.0 g/dL]).2022

The most important potential limitation of an observational study evaluating the effect of transfusion on mortality is that transfused patients may systematically differ from nontransfused patients in ways that cannot be ascertained or controlled for by a retrospective chart review. Great effort was made to identify and control for factors that might be associated with transfusion status and death. Information was collected on a vast array of comorbid conditions. In addition to information on individual comorbid conditions, we calculated 4 widely used indexes predictive of short-term mortality (ASA classification, Charlson comorbidity index, the APACHE II APS, and sickness at admission scale). Intraoperative events, surgical procedure, and type of anesthesia were assessed. Despite the extensive and careful assessment of potential confounding variables, it is still possible that important factors were not captured, and there may be residual confounding by indication.

Several other limitations should be considered when interpreting the results of this study. First, the data were collected by medical record review; however, retrospective data collection should not substantially bias ascertainment of the 3 primary study variables: transfusion status, hemoglobin level, and postoperative death. Second, despite the large sample size (this is the largest study to date to examine this question), inadequate power may still explain our inability to detect a reduction in mortality related to transfusion; we may have missed up to a 25% reduction in mortality. However, we estimate that the study would need to be about 10 times larger to detect a 10% difference in 30-day mortality with 80% power. Third, this study evaluated the effect of transfusion on mortality, and it is possible that transfusion may affect other outcomes such as morbidity, readmission to the hospital, speed of recovery, and functional status. Fourth, we were unable to analyze the hemoglobin level that a physician would aim for when giving a patient a transfusion because of lack of relevant hemoglobin levels. Fifth, the data for the study were collected over an 11-year period from 20 different hospitals in 4 geographic regions. Data from earlier admissions may not be entirely comparable with data from more recent admissions since surgical procedures, anesthetic technique, physical therapy, and length of hospital stay may have changed. However, year of admission was not related to either 30- or 90-day mortality, and adjustment for hospital did not substantively change the results. Sixth, the results may not generalize to other populations of patients or surgical procedures. Seventh, the hemoglobin levels during the preoperative and immediate postoperative periods may not always be accurate because of either dehydration or overhydration. However, these hemoglobin levels are used by the surgeon to make transfusion decisions.

We have found no evidence that transfusion improves survival in these elderly hip fracture patients with a high burden of chronic disease and hemoglobin levels greater than 80 g/L (8.0 g/dL). Since there is good evidence about the risks of transfusion, physicians should reconsider whether transfusion is warranted for such patients, keeping in mind the lack of evidence about the possible benefits, such as improving physical function and accelerating recovery after surgery. A randomized clinical trial is needed to establish definitively if and when transfusion is indicated in surgical patients with moderate anemia.

Dodd RY. The risk of transfusion-transmitted infection.  N Engl J Med.1992;327:419-421.
Schreiber GB, Busch MP, Kleinman SH, Korelitz JJ. Retrovirus Epidemiology Donor Study: the risk of transfusion-transmitted viral infections.  N Engl J Med.1996;334:1685-1690.
Office of Medical Applications of Research, National Institutes of Health.  Perioperative red blood cell transfusion.  JAMA.1988;260:2700-2703.
Topley E, Fisher MR. The illness of trauma.  Br J Clin Pract.1956;1:770-776.
Blair SD, Janvrin SB, McCollum CN, Greenhalgh RM. Effect of early blood transfusion on gastrointestinal haemorrhage.  Br J Surg.1986;73:783-785.
Weisel RD, Charlesworth DC, Micklebourough LL.  et al.  Limitations of blood conservation.  J Thorac Cardiovasc Surg.1984;88:26-38.
Johnson RG, Thurer RL, Kruskall MS.  et al.  Comparison of two transfusion strategies after elective operations for myocardial revascularization.  J Thorac Cardiovasc Surg.1992;104:307-314.
Herbert PC, Wells G, Marshall J.  et al.  Transfusion requirements in critical care.  JAMA.1995;273:1439-1444.
Lunn JN, Elwood PC. Anaemia and surgery.  BMJ.1970;3:71-73.
Rawstron ER. Anemia and surgery: a retrospective clinical study.  Aust N Z J Surg.1970;39:425-432.
Goodnough LT, Johnston MFM, Toy PTCY.and the Transfusion Medicine Group.  The variability of transfusion practice in coronary artery bypass surgery.  JAMA.1991;265:86-90.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis.1987;40:373-383.
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system.  Crit Care Med.1985;13:818-829.
Keeler EB, Kahn KL, Draper D.  et al.  Changes in sickness at admission following the introduction of the prospective payment system.  JAMA.1990;264:1962-1968.
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. An evaluation of outcome from intensive care in major medical centers.  Ann Intern Med.1986;104:410-418.
Dripps RD, Lamont A, Eckenhoff JE. The role of anesthesia in surgical mortality.  JAMA.1961;178:261.
 New classification of physical status.  Anesthesiology.1963;24:111.
Feinberg SE. The Analysis of Cross Classified Data.  Cambridge, Mass: The MIT Press; 1977:9.
Wilkerson DK, Rosen AL, Sehgal LR, Gould SA, Sehgal HL, Moss GS. Limits of cardiac compensation in anemic baboons.  Surgery.1988;103:665-670.
Hagl S, Heimisch W, Meisner H, Erben R, Baum M, Mendler N. The effect of hemodilution on regional myocardial function in the presence of coronary stenosis.  Basic Res Cardiol.1977;72:344-364.
Yoshikawa H, Powell WJ, Bland JHL, Lowenstein E. Effect of acute anemia on experimental myocardial ischemia.  Am J Cardiol.1973;32:670-678.
Carson JL, Duff A, Berlin JA.  et al.  Effect of anemia and cardiovascular disease on surgical mortality and morbidity.  Lancet.1996;348:1055-1060.
Breslow NE, Day NE. Statistical Methods in Cancer Research, Vol 1: The Analysis of Case-Control Studies.  Lyon, France: International Agency for Research on Cancer; 1980:142.
Mantel N, Haenszel W. Statistical aspects of the analyses of data from retrospective studies of disease: from retrospective chart reviews.  J Natl Cancer Inst.1959;22:719.
 SAS/STAT User's Guide: Version 6, 4th Edition.  Cary, NC: SAS Institute Inc; 1990.
Geha AS, Baue AE. Graded coronary stenosis and coronary flow during acute normovolemic anemia.  World J Surg.1978;2:645-652.
Anderson HT, Kessinger JM, McFarland WJ, Laks H, Geha AS. Response of the hypertrophied heart to acute anemia and coronary stenosis.  Surgery.1978;84:8-15.

Figures

Graphic Jump Location
The 90-day mortality curve in 8787 patients with hip fracture stratified by transfusion status. Variables adjusted for in the postoperative transfusion 90-day mortality analysis included race; sex; age; acute physiology score of the Acute Physiology and Chronic Health Evaluation II index; Charlson comorbidity index; sickness at admission scale; history of atrial fibrillation; hypertension; history of anemia within 1 year of admission; history of confusion; patient found to be malnourished or cachectic on physical examination; any malignancy; abnormal preoperative chest radiograph; intraoperative tachycardia; preoperative transfusion; and hospital.

Tables

Table Graphic Jump LocationTable 1.—Description of Patient Population and Univariate Relationship With 30-Day Mortality
Table Graphic Jump LocationTable 2.—Postoperative Hemoglobin Trigger and 30-Day Mortality
Table Graphic Jump LocationTable 3.—Patient Characteristics by Postoperative Transfusion Status
Table Graphic Jump LocationTable 4.—The 30-Day Mortality for Patients Receiving Postoperative Transfusion Compared With Those Not Receiving Transfusion, Both Unadjusted and Adjusted for Potential Confounding Variables*
Table Graphic Jump LocationTable 5.—Results of Analysis Stratified by Likelihood of Transfusion

References

Dodd RY. The risk of transfusion-transmitted infection.  N Engl J Med.1992;327:419-421.
Schreiber GB, Busch MP, Kleinman SH, Korelitz JJ. Retrovirus Epidemiology Donor Study: the risk of transfusion-transmitted viral infections.  N Engl J Med.1996;334:1685-1690.
Office of Medical Applications of Research, National Institutes of Health.  Perioperative red blood cell transfusion.  JAMA.1988;260:2700-2703.
Topley E, Fisher MR. The illness of trauma.  Br J Clin Pract.1956;1:770-776.
Blair SD, Janvrin SB, McCollum CN, Greenhalgh RM. Effect of early blood transfusion on gastrointestinal haemorrhage.  Br J Surg.1986;73:783-785.
Weisel RD, Charlesworth DC, Micklebourough LL.  et al.  Limitations of blood conservation.  J Thorac Cardiovasc Surg.1984;88:26-38.
Johnson RG, Thurer RL, Kruskall MS.  et al.  Comparison of two transfusion strategies after elective operations for myocardial revascularization.  J Thorac Cardiovasc Surg.1992;104:307-314.
Herbert PC, Wells G, Marshall J.  et al.  Transfusion requirements in critical care.  JAMA.1995;273:1439-1444.
Lunn JN, Elwood PC. Anaemia and surgery.  BMJ.1970;3:71-73.
Rawstron ER. Anemia and surgery: a retrospective clinical study.  Aust N Z J Surg.1970;39:425-432.
Goodnough LT, Johnston MFM, Toy PTCY.and the Transfusion Medicine Group.  The variability of transfusion practice in coronary artery bypass surgery.  JAMA.1991;265:86-90.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis.1987;40:373-383.
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