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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Circ Cardiovasc Qual Outcomes. Author manuscript; available in PMC 2012 June 27.
Published in final edited form as:
PMCID: PMC3384714
NIHMSID: NIHMS382335

Incidence, Correlates and Outcomes of Acute, Hospital-acquired Anemia in Patients with Acute Myocardial Infarction

Abstract

Background

Anemia is common among patients hospitalized with acute myocardial infarction (AMI), and is associated with poor outcomes. Less is known about the incidence, correlates, and prognostic implications of acute, hospital-acquired anemia (HAA).

Methods and Results

We identified 2909 patients with AMI who had normal hemoglobin (Hgb) on admission in the multi-center TRIUMPH registry. We used hierarchical Poisson regression to identify independent correlates of HAA, and multivariable proportional hazards regression to identify the association of HAA with mortality and health status. At discharge, 1321 (45.4%) patients had HAA, of whom 348 (26.3%) developed moderate-severe anemia (Hgb 9.1–11). The incidence of HAA varied substantially across hospitals (range: 33.3% to 69.2%, median rate ratio for HAA development 1.13 (95% CI 1.07–1.23) controlling for patient characteristics). Although documented bleeding was more frequent with more severe HAA, fewer than half of patients with moderate-severe HAA had any documented bleeding. Independent correlates of HAA included age, female gender, white race, chronic kidney disease, ST segment elevation MI, acute renal failure, use of glycoprotein IIb/IIIa inhibitors, in-hospital complications (cardiogenic shock, bleeding and bleeding severity), and length of stay. After adjustment for GRACE score and bleeding, patients with moderate-severe HAA had higher mortality (HR 1.82 (95% CI 1.11–2.98) vs. no HAA), as well as poorer health status at 1-year.

Conclusions

HAA develops in nearly half of AMI hospitalizations, commonly in the absence of documented bleeding, and is associated with worse mortality and health status. Better understanding of how HAA can be prevented, and whether its prevention can improve patient outcomes is needed.

Keywords: myocardial infarction, anemia, hemoglobin, outcomes

INTRODUCTION

Anemia is common in patients hospitalized with acute myocardial infarction (AMI) and is associated with increased mortality,14 higher hospitalization rates,5 and worse health-related quality of life.6 However, most prior studies of anemia in the setting of AMI have evaluated chronic anemia (present at admission), or short-term changes in hemoglobin during hospitalization.7 Little research has focused on hospital-acquired anemia (HAA), which develops acutely during AMI admission in those with normal baseline hemoglobin (Hgb). Although the etiology of HAA, an acute phenomenon, is likely to be different from that of chronic anemia, its risk factors and prognostic implications have not been explored.

Chronic anemia is often due to nutritional deficiencies, chronic inflammation, as well as renal and bone marrow disorders, and can be difficult to manage. In contrast, HAA may be more likely to result from in-hospital treatments and processes of care. If associated with adverse outcomes, HAA may be preventable and could represent an actionable target for hospital-based quality improvement efforts. Potential benefits of preventing HAA may include reducing patients' exposure to the risks from acute anemia treatments such as blood transfusion,8 improving clinical outcomes, and reducing costs. However, before resources are directed to HAA prevention, it is necessary to better understand the incidence and predictors of HAA, and its association with clinically relevant outcomes.

To address these gaps in knowledge, we sought to describe the incidence and predictors of HAA, the variation in HAA prevalence between hospitals, and its relationship with subsequent mortality and health status outcomes in the Translational Research Investigating Underlying disparities in acute Myocardial infarction Patients' Health Status study (TRIUMPH); a prospective 24-center observational registry of AMI treatment and outcomes. TRIUMPH provided an ideal opportunity to address these important questions, as it collected detailed patient data on in-hospital hemoglobin, hospital-based treatments, complications and processes of care, as well as serial assessments of patient outcomes after discharge.

METHODS

TRIUMPH Study

A total of 4340 patients were enrolled in TRIUMPH between April, 11 2005 and December 31, 2008. Patients were ≥18 years of age, with elevated cardiac biomarkers (troponin or creatine kinase-MB fraction assessed within 24 hours of admission), and supporting evidence of AMI (electrocardiographic ST-segment changes or prolonged ischemic signs/symptoms). Participants were required to either present to the enrolling institution or to have been transferred within 24 hours of symptom onset so that the primary clinical decision making occurred at the enrolling center. Patients with elevated cardiac biomarkers resulting from an elective coronary revascularization were excluded. Trained data collectors performed detailed baseline chart abstractions to document patients' medical history, the processes of inpatient care, laboratory results and treatments. Each patient underwent a standardized interview by research staff to document sociodemographic and clinical data. Patients were contacted for follow-up interviews at 1, 6 and 12-months after AMI. All patients signed an informed consent approved by the participating institution and Institutional Review Board approval was obtained at each participating center.

Study Population

The goals of this study were to describe the incidence, correlates and outcomes of HAA in patients surviving AMI hospitalization. To identify patients who developed HAA from the full TRIUMPH cohort (n=4340), we excluded patients who underwent coronary artery bypass surgery during the index admission (n=405), since anemia is an expected result to the surgery itself and accordingly these patients represent a clinically distinct population.

In addition, we then also excluded patients who did not survive to hospital discharge (n=17) and those with chronic anemia at admission (n=950) because our principal focus was development of HAA and it's impact on post-discharge outcomes. Additionally, there were missing admission and/or discharge hemoglobin levels for 59 patients, resulting in a final population of 2909 patients. To contrast the outcomes of HAA with chronic anemia, we included the 950 patients with baseline chronic anemia in our outcomes analyses. Vital status data at 12-months was available for the vast majority of patients (3837 of 3859, 99.4%); SF-12 PCS scores were available for 1880 patients at 1-month, 1714 at 6-months and 1664 at 12-months.

Definitions

Hemoglobin values were abstracted by trained data collectors at each center. Admission hemoglobin was defined as the first in-hospital hemoglobin (g/dl) value available for each patient. If a patient was transferred to a TRIUMPH center from another hospital, the initial hemoglobin at the transferring facility was obtained and used as the admission value. Discharge hemoglobin was defined as the last hemoglobin value obtained within 48 hours of discharge from the hospital. HAA was defined as absence of anemia on admission, but development of anemia at discharge. For our primary analyses, anemia was defined using age, gender, and race specific criteria was described by Beutler and Waalen as a hemoglobin value less than 13.7 g/dl for white men aged 20 to 59, 13.2 g/dl for white men ≥ 60 years, 12.9 g/dl for black men aged 20–59, 12.7 g/dl for black men ≥ 60 years, 12.2 g/dl for white women and 11.5 g/dl for black women. This classification has been previously shown to be more accurate than the World Health Organization definition (WHO).9 In light of its common use in prior cardiovascular literature, we also conducted sensitivity analyses using WHO diagnostic criteria for anemia (Hgb < 13.0 g/dl in men, Hgb < 12.0 g/dl in women).10 HAA was defined as absence of anemia on admission, but development of anemia at discharge using these criteria. Anemia was further categorized as severe (Hgb ≤9.0 g/dl), moderate (Hgb 9.1 to 11.0 g/dl) or mild (Hgb > 11.0 g/dl).6 Since using discharge hemoglobin to define anemia severity could result in misclassification of a patients' anemia severity among those who received a blood transfusion while hospitalized, we subtracted the number of units transfused (1 g/dl Hgb per unit transfused) from the discharge hemoglobin and used this derived value to assign patients to the appropriate anemia severity category.

Bleeding episodes were recorded by data abstracters using the Thrombolysis In Myocardial Infarction (TIMI) classification.11 TIMI major bleeding was defined as intracranial hemorrhage, retroperitoneal hemorrhage, or a Hgb decline ≥ 5 g/dl. TIMI minor bleeding was assigned if the drop in Hgb was 3 to 5 g/dl in the setting of observed bleeding. Any bleeding episode with a decline in Hgb < 3 g/dl was classified as TIMI minimal bleeding. All TIMI categories accounted for blood transfusion, with adjustment of Hgb values by 1 g/dl per unit transfused. Bleeding site was recorded as cardiac catheterization site, gastrointestinal, retroperitoneal, or other.

Health status was assessed using the Short Form-12 Physical Component Summary score (SF-12 PCS). The SF-12 is a valid and reliable instrument with scores ranging from 0–100, with higher scores representing better health status.12 A score of 50 is normalized to the mean health status of the US population and each 10 points represents 1 standard deviation from that mean.

Statistical Analyses

Baseline characteristics, in-hospital treatments, in-hospital complications, and lab values of patients who developed HAA were compared to those who did not have anemia at either admission or discharge. We also compared the frequency of in-hospital bleeding among those with and without HAA, as well as within categories of HAA severity. For the 12-month outcome analyses, we divided HAA into mild and moderate-severe anemia, comparing each HAA category to a reference category of no anemia. We also included patients with chronic anemia at admission in outcome analyses, comparing them to those without anemia. For descriptive purposes, we present categorical data as frequencies and differences between groups were compared using chi-square or Fisher's exact tests, as appropriate. Continuous variables were reported as the mean ± standard deviation and differences were compared using independent t-tests. The Wilcoxon rank-sum test was used to compare patients' length of stay due to its skewed distribution, and results are reported as the median and interquartile range.

We used hierarchical modified Poisson regression within hospital site to identify patient characteristics independently associated with HAA. Variables included in the model were either identified a priori as clinically important or differed between the groups in bivariate comparisons (p<0.05). These included enrolling hospital, age, gender, race (white vs. other), diabetes, hypertension, chronic kidney disease, history of chronic heart failure, left ventricular ejection fraction less than 40%, prior coronary artery bypass grafting, pre-hospital use of aspirin or clopidogrel, acute non-cardiac condition on arrival, in-hospital acute renal failure, MI type (ST segment elevation vs. non-ST segment elevation), in hospital percutaneous coronary intervention, in hospital treatment with GP IIb/IIIa inhibitor, antiplatelet agents, or anticoagulants, cardiogenic shock, in hospital bleeding in each TIMI category and length of stay. Additionally, these models were repeated after including baseline Hgb as a continuous variable to understand the influence of initial Hgb on identification of independent correlates of anemia.

Variation in HAA rates across hospitals was quantified by the median rate ratio, the median value of the relative risk for HAA development for two patients with identical characteristics admitted to two randomly selected hospitals.13

Finally, to evaluate the association between HAA and long-term outcomes, we used log-rank tests and generated Kaplan-Meier curves for crude morality analyses and compared crude SF-12 PCS scores using 1-way ANOVA. To better understand the contribution of in-hospital bleeding on HAA-associated mortality risk, Kaplan-Meier curves were also generated for the subgroups of patients with HAA who did and did not have documented bleeding, and their 12-month mortality was compared using log-rank test. We then used multivariable proportional hazards regression models for 12-month mortality and multivariable repeated measures regression with autoregressive covariance structure for Short Form-12 physical component scores (SF-12 PCS) that incorporated 1-, 6-, and 12-month health status assessments. These models were adjusted for hospital site and the GRACE discharge to 6-month mortality risk score,14 which is strongly predictive of long-term mortality and incorporates important potential confounders. Variables included in GRACE score are age, heart rate, systolic blood pressure, creatinine, history of CHF, prior MI, in hospital PCI or CABG, ST-segment depression on the initial electrocardiogram and elevated cardiac biomarkers). Presence and severity of bleeding were also included in the models, using dummy variables for TIMI major, minor and minimal bleeding to understand whether the prognostic impact of HAA is independent of bleeding presence and severity. The models evaluating the relationship between SF-12 PCS scores and HAA also adjusted for baseline SF-12 PCS. Finally, several additional sensitivity analyses were conducted. First, models were repeated using the WHO definition of anemia. Second, analyses were repeated after excluding patients who received blood transfusion. Finally, we examined the association between HAA and 12-month mortality after adjusting for baseline Hgb. All analyses were conducted with SAS version 9.1.3 (SAS Institute, Cary, NC) and R version 2.7.2 (R Development Core Team (2006) – R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org).

RESULTS

HAA Incidence, Severity and Baseline Patient Characteristics

Among 2909 AMI patients without anemia at admission, 1321 (45.4%) developed HAA. Baseline demographics, co-morbidities, in-hospital characteristics and treatments of patients with and without HAA are compared in Table 1. Hemoglobin at admission, discharge and change during hospitalization are presented in Table 2. Hgb declined by a mean of 2.6±1.4 g/dl during hospitalization among patients with HAA, but also declined modestly (by 1.0±1.3 g/dl) in those who did not develop HAA (p<0.001). The majority of cases of HAA were mild (973, 73.7%), while 292 (22.1%) had moderate anemia and 56 (4.24%) had severe anemia.

TABLE 1
Characteristics of AMI patients with and without hospital acquired anemia
Table 2
Hemoglobin by severity of hospital-acquired anemia

Bleeding and HAA

While documented in-hospital bleeding was more common in patients with vs. without HAA, the majority (1143 of 1321 patients, 86.5%) of patients with HAA did not have any documented in-hospital bleeding (Table 3). The mean hemoglobin decline in patients with recorded bleeding was 3.1±1.9 g/dl, as compared with 1.6±1.4 in those who did not have a bleeding episode. As the severity of HAA increased among patients with documented bleeding, a greater proportion of bleeding events were classified as TIMI major and TIMI minor bleeds. Although in-hospital bleeding was significantly more common in patients with severe HAA than those with less severe or no HAA, nearly half of patients with severe HAA still had no recorded bleeding episode.

Table 3
In-hospital bleeding by hospital-acquired anemia status

Independent Correlates of HAA

Independent correlates of HAA are presented in Figure 1. In-hospital bleeding was associated with a greater likelihood of developing HAA (TIMI minimal bleeding: RR of 1.36 (95% confidence interval (CI) 1.25–1.48); TIMI minor: RR 1.72 (95% CI 1.39–2.13); TIMI major bleeding RR 1.72 (95% CI 1.46–2.02). Additional patient characteristics associated with developing HAA included age, female gender, white race and chronic kidney disease as well as development of cardiogenic shock, acute renal failure, and presentation withSTEMI.and treatment with glycoprotein IIb/IIIa inhibitors. Longer length of stay was also associated with HAA.

Figure 1
Independent correlates of hospital acquired anemia

We also ran this model with the addition of baseline Hgb. Baseline Hgb value was also a strong correlate of HAA (RR 0.70 (95% CI 0.66–0.75) per 1 g/dl increase in baseline Hgb). Since we used diagnostic thresholds for anemia that were age, gender and race specific and thus accounted for the lower normal Hgb values in African Americans, older patients and women, the inclusion of baseline Hgb in the models artificially altered the point estimates for these demographic variables as predictors of HAA (e.g., female gender was associated with less risk of HAA while white race was more strongly associated with HAA after inclusion of baseline Hgb). The addition of baseline Hgb to the model did not substantially alter point estimates for any other HAA correlates.

Variability in HAA Across Hospitals

The incidence of HAA across all participating TRIUMPH sites enrolling more than 20 patients ranged from 33.3 to 69.2% (Figure 2). The median rate ratio for site was 1.13 (95% CI 1.07–1.23), indicating that two patients with identical demographic and clinical characteristics presenting to two randomly selected hospitals can be 13% more or less likely to develop HAA.

Figure 2
Variation in the Incidence of Hospital-acquired Anemia Across Hospitals

Outcomes Associated with Hospital-acquired Anemia

To assess the prognostic significance of HAA, we compared outcomes across the different severities of HAA and among those with chronic anemia on admission. Important differences in 12-month survival were associated with the development and severity of HAA. Mortality was lowest in those without HAA (40 of 1581, 2.6%), rising progressively in those with mild HAA (34 of 966, 3.6%), moderate-severe HAA (29 of 345, 8.4%) and chronic anemia (117 of 945, 12.6%) (p<0.001; Figure 3a). Among patients who developed HAA, survival did not differ based on presence or absence of documented bleeding (Figure 3b).

Figure 3
12-month Kaplan-Meier mortality estimates

Using no anemia as the reference group, there was no unadjusted or multivariable-adjusted association between mild HAA and mortality (Figure 4). In contrast, moderate-severe HAA and chronic anemia were strongly associated with mortality. Even after adjusting for GRACE 6-month mortality score and the presence and severity of bleeding, patients with moderate-severe HAA was associated with an increased risk of death in comparison to those without anemia (HR 1.82 (95% CI 1.11–2.98) Similarly, chronic anemia was strongly and independently associated with 12-month mortality (HR 2.31 (95% CI 1.57–3.40).

Figure 4
12-month unadjusted and adjusted Mortality among patients with mild HAA, moderate-severe HAA and chronic anemia

At baseline, the SF-12 PCS scores were higher in those without anemia and in patients with mild HAA, and lower in those with moderate-severe HAA and chronic anemia (no anemia: 44.9 ± 11.6, mild HAA: 44.2 ± 11.6, moderate-severe HAA: 40.1 ± 12.6, chronic anemia: 37.3 ± 12.8; p<0.001). Adjusting for baseline health status and incorporating 1, 6 and 12-month SF-12 scores, follow up SF-12 PCS scores were lower in those with chronic anemia with a trend toward lower scores in those with moderate-severe HAA in comparison to those without anemia (Figure 5). Patients with mild HAA and no anemia had similar SF-12 PCS scores.

Figure 5
Association between mild HAA, moderate-severe HAA and chronic anemia with physical functioning across time over 12 months of follow-up

We conducted sensitivity analyses includingusing the WHO definition of anemia, excluding patients who received blood transfusion, and adjusting outcomes models for baseline Hgb; none of these resulted in significantly different study findings (data not shown).

DISCUSSION

We found that almost half of patients who had normal hemoglobin at admission developed anemia by hospital discharge in this large, prospective, multi-center AMI cohort. Although inpatient bleeding was a strong independent predictor of HAA, most patients with HAA did not have a documented bleeding event during hospitalization, suggesting that HAA is not simply a surrogate for in-hospital bleeding events. Importantly, moderate-severe HAA was associated with increased long-term mortality independent of AMI severity, and regardless of presence and extent of bleeding, suggesting that HAA is prognostically important in its own right and may represent a target for prevention efforts. Supporting that there is opportunity to minimize the risk of developing HAA, we observed substantial variability in incidence of HAA across hospital sites.

Prior studies have established the short and long-term prognostic significance of chronic anemia,25 and more recent reports have examined the association between changes in Hgb during hospitalization and outcomes.7 Aronson and colleagues found that declines in Hgb during AMI hospitalization were independently associated with mortality, however, their analyses included both patients with baseline anemia and new-onset anemia during hospitalization.7 Since patients with chronic anemia presumably have poorer hematopoetic reserve or greater baseline co-morbidity, potentially predisposing them to large Hgb declines, it unclear from these data whether the relationship between inpatient Hgb decline and survival is present among those with normal baseline Hgb. Our work extends these insights by defining a population with acute anemia, a potentially preventable condition, and observing that moderate-severe HAA is associated with an increased risk of mortality of similar magnitude to those with chronic anemia, even after adjustment for the presence and severity of bleeding. Our findings also extend prior observations by Sattur and colleagues who reported, in a single-center study, that incident anemia in PCI patients was independently associated with long-term mortality.15 The anemia threshold used in that study (Hgb <10 g/dl) was relatively low, potentially leading to over-estimation of the association between anemia and outcomes. Our study provides new insights by examining a large, contemporary, multi-center cohort, focusing on patients with AMI, and using standard definitions of anemia. Moreover, our analyses include a broad range of outcomes (including health status), and provide important new data about the variability of HAA across hospitals.

Our findings have important clinical implications. Several of the correlates of HAA are also associated with chronic anemia and bleeding in AMI patients (such as age, female gender, acute heart failure and chronic kidney disease),2, 7, 16, 17 and likely identify a high risk population with poor hematopoetic reserve. On the other hand, some independent correlates are hospital-based variables (use of glycoprotein IIb/IIIa inhibitors and bleeding) – and could be targets for prevention efforts. Several of these variables are associated with bleeding,1618 and the use of bleeding avoidance measures, such as radial artery access for PCI, smaller sheaths, or alternative antithrombotic agents such as bivalirudin in place of heparin and a glycoprotein IIb/IIIa inhibtor, present potential opportunities for improvement.1922 Additionally, the strong association between moderate-severe HAA and 12-month mortality, even after adjusting for the presence and severity of bleeding, indicates that HAA is distinct from bleeding and is clinically important in its own right. Although the major causes of HAA among those without documented bleeding remain unclear, it is possible that it is related to subclinical blood loss (such as frequent phlebotomy), undetected bleeding, minor periprocedural bleeding, inadequate hematopoietic response or a combination of processes. Our findings indicate that additional emphasis on prevention of HAA, a process distinct from overt bleeding in many cases, could be just as important as prevention of bleeding. Further studies are needed to define specific causes of HAA and determine whether HAA prevention is feasible and improves patient outcomes.

Our findings should be interpreted in the context of their potential limitations. We used discharge hemoglobin values to define HAA as nadir hemoglobin values were not available. This approach may underestimate the prevalence of HAA; however, given the relatively short duration of hospitalization (median 3.0 days, (IQR) 2.0 – 4.0) it is unlikely that a substantial proportion of HAA cases were missed. More importantly, our goal was to examine prognosis after discharge, and discharge Hgb is the most accurate assessment of patients' anemia status at that time. It is also possible that undetected, mild bleeding episodes were not detected despite careful prospective collection of bleeding data. Even if this were the case, however, the association between bleeding and adverse outcomes has only been demonstrated for more severe categories of bleeding. Accordingly, our data could be viewed s providing novel insights that indicate further investigation of the outcomes associated with mild bleeding are need. Another possible limitation is that some misclassification of anemia severity occurred in patients with in HAA who received blood transfusions before discharge hemoglobin assessment. However, we adjusted the discharge hemoglobin values for in-hospital blood transfusion to minimize this issue and performed sensitivity analyses excluding patients who received a blood transfusion. Our definition of chronic anemia was any anemia present at admission, which could have captured sub-acute cases in addition to those with long term anemia. Finally, these observational data do not allow us to draw conclusions about causal relationships between HAA and mortality and it remains unclear whether HAA is a marker for, or a mediator of, poor outcomes.

In conclusion, we found that HAA is common in patients hospitalized with AMI and varies substantially across hospitals. Development of moderate-severe HAA is associated with higher mortality and worse health status in the first year after AMI, independent of documented in-hospital bleeding. Better understanding of whether prevention of HAA is feasible and can improve patient outcomes is needed.

ACKNOWLEDGEMENTS/FUNDING SOURCES

Dr. Salisbury is funded, in part, by the American Heart Association-PRT Outcomes Research Fellowship Program.

ABBREVIATIONS

AMI
Acute myocardial infarction
HAA
Hospital acquired anemia
Hgb
Hemoglobin
PCI
Percutaneous coronary intervention
NSTEMI
Non-ST segment elevation myocardial infarction
SF-12 PCS
Short Form-12 Physical Component Summary score
STEMI
ST-segment elevation myocardial infarction
TIMI
Thrombolysis in Myocardial Infarction
WHO
World Health Organization

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