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J Thorac Cardiovasc Surg 1998;116:460-464
© 1998 Mosby, Inc.

Surgery for Adult Cardiovascular Disease

Hematocrit value on intensive care unit entry influences thefrequency of q-wave myocardial infarction after coronary artery bypass grafting

The Institutions of the Multicenter Study of Perioperative Ischemia(McSPI) Research Group

See Appendixes 1 and 2 for list of McSPIinvestigators and central analysis group members.

	Abstract

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
Objectives: No data exist regarding"the best" hematocrit value after coronary artery bypass graftsurgery. Transfusion practice varies, because neither an optimal hematocritvalue nor a uniform transfusion trigger criterion has been determined.
Methods: To investigate the optimal hematocrit value, westudied 2202 patients undergoing coronary bypass. The hematocrit value on entryinto the intensive care unit (IHCT) was categorized into three groups: high (34%),medium (25% to 33%), and low (24%). Characteristics andadverse events (outcomes) were compared, and the effect of IHCT on the risk ofmyocardial infarction was determined by logistic regression.
Results: High IHCT (34%) was associated with anincreased rate of myocardial infarction (8.3% vs 5.5% vs 3.6%;P 0.03, high, medium vs low) and with moresevere left ventricular dysfunction (11.7% vs 7.4% and 5.7%;P = 0.006, high, medium vs low). Mortalityrate increased with higher IHCT when all the high-risk subgroups were combined(8.6% vs 4.5% vs 3.2%; P <0.001, high, medium vs low). By multivariate analysis, IHCT remained the mostsignificant predictor of adverse outcomes (relative risk high vs low 2.22, 95%confidence interval: 1.04 to 4.76). No characteristic, event, medication, ortransfusion therapy confounded the relationship between IHCT and outcome.
Conclusion: High IHCT is associated with a higher rate ofmyocardial infarction and is an independent predictor of infarction. On thebasis of the risk of myocardial infarction, there is no rationale fortransfusion to an arbitrary level after coronary artery bypass grafting. (JThorac Cardiovasc Surg 1998;116:460-7)

	Introduction

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
No data exist regarding the "best" hematocrit (HCT) valueafter cardiopulmonary bypass. Clinicians have assumed that anemia increases therisk of myocardial ischemia after coronary artery bypass graft (CABG)operations. Several recent studies have suggested that there might not be anassociation between anemia and morbidity after CABG. ^1,2Therefore no safe lower limit of HCT has been established, yet the risks oftransfusion are well delineated. ³A wide variability exists in blood use for CABG operations. ^4,5The difference in transfusion practice is probably a reflection of the lack ofadequate data regarding morbidity and mortality risks for HCT levels after CABG.Any new data regarding relative outcome risks and HCT may have an impact onnational blood use and costs (15% to 20% of blood is used incardiopulmonary bypass). ^6-8

In the patient undergoing CABG, the highest risk period for adversemyocardial ischemic events is in the immediate perioperative period. ^9,10Recent data have shown that the period within 1 to 2 hours after protamineadministration is associated with the largest number of electrocardiographicchanges of ischemia. ¹⁰ The HCTduring these first several hours after CABG represents the sum total ofpreoperative HCT, hemodilution, blood loss, fluid administration, transfusiontherapy, and the transfusion philosophy (transfusion HCT trigger). Arepresentative HCT of that time interval is the HCT on entry to the intensivecare unit (IHCT). In a large-scale multicenter study, the relationship betweenIHCT and adverse clinical outcomes was examined in an effort to answer thequestion: Is there a "best" IHCT after CABG?

	Methods

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
Patients
The Multicenter Study of Perioperative Ischemia (McSPI)Cardiac Surgery Database was a prospective observational study of 2417 patientsin the United States undergoing elective CABG operations with or without otherconcurrent cardiac procedures. The study was designed to assess the frequency ofadverse postoperative outcomes and to determine the presence of preoperativepatient characteristics. ¹¹Between 100 and 108 patients were enrolled at each of 24 centers from September1991 to September 1993 with the use of a standardized questionnaire that hasbeen previously well described. ¹³The volume of intraoperative crystalloid and colloid was measured, as was theuse of transfusion (red blood cells [RBCs], platelets, fresh frozen plasma, orcryoprecipitate) during and after the operation. Blood loss was assessed bychest tube drainage.

Postbypass morbidity was defined as (1) low cardiac index (<1.5 L/min|b1 m ²) or hypotension(arterial systolic pressure < 80 mm Hg for  10 minutes), or theadministration of three or more inotropic agents; (2) the presence of myocardialischemia by ST segment deviation or the use of intravenous nitroglycerin; (3)hypertension (systolic blood pressure > 180 mm Hg for  10minutes), or tachycardia (heart rate > 100 beats/min for at least 10minutes).

Adverse events
Adverse postoperative events included Q-wave myocardial infarction (MI),death, renal failure (necessitating hemodialysis), adverse central nervoussystem outcome (stroke, transient ischemic attack, or stupor/coma at discharge),or severe left ventricular dysfunction necessitating the use of an intraaorticballoon pump. To determine the presence of a new Q-wave MI, one preoperative andtwo postoperative 12-lead electrocardiograms (one collected on postoperativedays 0 to 3 and one on days 4 to 10) were analyzed according to Minnesota Codecriteria by three electrocardiographers at a central core facility (IschemiaResearch and Education Foundation [IREF], San Francisco, Calif.), who wereblinded to patients' identities and clinical courses. ¹²

HCT
HCT values were recorded at hospital admission, on arrival in theintensive care unit (ICU), and at discharge. The minimum and maximumpostoperative values were also noted. The changes in HCT from admission to ICUentry and from ICU entry to discharge were calculated for each patient. Previousstudies either considered an HCT of 25% as a lower limit or were vagueregarding a transfusion trigger. Experimental data suggest that HCT exceeding 33%may be associated with decreased tissue oxygen delivery. ¹³ We thus defined three groups ofpatients on the basis of IHCT: low (24%), medium (25% to 33%),and high HCT (34%).

Association of IHCT and intraoperative and postoperative variables
To identify any differences among patients with low, normal, and highIHCT values, we examined preoperative and intraoperative characteristics in eachIHCT group. Because IHCT was thought to be a consequence of many intraoperativefactors, operative events including blood and fluid loss, postbypass morbidity,and the use of transfusion were carefully examined for the three IHCT groups.Rates of adverse postoperative outcomes were compared across IHCT groups. Inaddition, these outcomes were examined in subgroups of patients at high risk foradverse events (patients with unstable angina, emergency CABG, reoperation, or acombination of these factors). ^9,14-17All associations were examined by means of the ² test for categoric variables andeither general linear modeling or the Kruskal-Wallis test for continuousvariables. ¹⁸ All tests weretwo-tailed.

Multivariate analysis
We limited multivariate analyses to Q-wave MI, because this was the onlyoutcome with a blinded diagnosis. First, we examined the effect of IHCT on riskof MI after adjustment for single variables. We also examined the effect of siteon the relationship between IHCT and MI. Because no variable appeared toconfound the relationship between IHCT and MI, we constructed a stepwiselogistic regression model using variables previously reported in the literature(age, sex, history of MI, smoking, and reoperation CABG). ^14-17The entry and stay level were both set at 0.2 in this analysis (variablewill remain if p  0.2 and will be removedif p > 0.2). All IHCT levels wereforced to remain in the model at all times. The Hosmer-Lemeshow test measuringgoodness-of-fit was used to validate the final stepwise logistic regressionmodel. ¹⁹

	Results

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
Patients
Interpretable electrocardiographic and HCT values were available for atotal of 2202 patients. The demographic, preoperative, and intraoperativecharacteristics of the three IHCT groups are presented in Table I. Patients'ages ranged from 28 to 95 years (mean ± standard deviation: 64.6 ±10.3 years), with 32% older than 70 years of age. CABG was performed onan emergency basis in nearly 25% of cases, and approximately 16%of patients underwent an additional cardiac procedure, primarily valve repair orreplacement.

View larger version (15K): [in this window] [in a new window]   Fig. 1. Level (mean ± standard deviation) of HCT on admission, on entry to the ICU, and at discharge according to IHCT group. Note that the three subgroups were similar at hospital entry and discharge. L, Low HCT (24%); M, medium HCT (35% to 33%); H, high HCT (34%).

Association between HCT and transfusion variables
Differences in HCT level from admission to ICU entry were not explainedby intraoperative RBC transfusion (Table II).The percentage of patients who received either platelets or fresh frozen plasmawas higher in the low IHCT group. Among those who did receive hemostaticproducts, the median number of units used was not different (8 units ofplatelets per recipient for all IHCT groups, p =0.55) (fresh frozen plasma low IHCT = 4 units; median IHCT = 2 units;high IHCT = 2 units, p = 0.15).Intraoperative crystalloid and colloid administration showed a statisticallysignificant difference (Table II), with the low IHCT group receiving more, butthe difference between the low and high IHCT groups of 430 ml is clinicallyinsignificant. Mean chest tube drainage (Table II) was greatest in the low IHCTgroups but, again, was not of clinical significance (136 ml difference betweenlow IHCT and high IHCT). However, a higher proportion of patients with low IHCThad chest tube drainages exceeding 1500 ml on the day of the operation (highIHCT  = 3.4%; median IHCT = 5.0%; low IHCT = 8.5%,p = 0.02).

Postoperatively, patients with low IHCT were most likely to receive RBCtransfusion. Patients who received non-RBC transfusion in the operating roomwere more likely to receive a transfusion in the ICU. The proportion of patientsreturning to the operating room for hemorrhage did not differ between groups(low: 3%; medium: 3%; high: 1%; p =0.23).

Association of IHCT with adverse outcome
Postoperative adverse events differed between the IHCT groups (TableIII).Rates of Q-wave MI and severe left ventricular failure were lowest in patientswith low IHCT and significantly higher in those with high IHCT (p = 0.03). Rates of postoperative central nervoussystem dysfunction and renal failure did not differ between groups: centralnervous system dysfunction: high IHCT = 4.4%, medium = 3.5%,low = 4.4% (p = 0.59); renalfailure: high IHCT = 6.6%, medium = 5.4%, low = 7.7%(p = 0.29). In the whole sample, mortalityrates were similar in the low and high IHCT groups. However, high-risk patientstended toward increased all-cause mortality in the high IHCT group (high =8.6%, medium = 3.2%, low = 4.5%,p < 0.001). In patients with a historyof unstable angina, high IHCT was associated with a threefold increase inmortality.

View larger version (25K): [in this window] [in a new window]   Fig. 2. Frequency of Q-wave MI,severe left ventricular dysfunction (intraaortic balloon pump use), all-causemortality, and combined (all three) adverse ischemic outcome by the IHCT group.Low, HCT 24%; Medium,HCT 25% to 33%; High, HCT 34%.

Multivariate analyses
Institution did not confound the relationship between level of IHCT andrisk of MI. Logistic regression models of Q-wave MI risk in each IHCT group withcovariates showed that none demonstrated different odds ratios (Table IV). Ourfinal stepwise regression model (Table V) showed that IHCT was the mostimportant predictor of Q-wave MI. Patients withhigh IHCT were more than twice as likely to have a Q-wave MI as patients withlow IHCT (p = 0.04) and 1.4 times morelikely than patients with a medium IHCT (p =0.31). In additional models including intraoperative variables such as (1) RBCtransfusion requirements (2) postbypass signs of hemodynamic instability (e.g.,hypotension, low cardiac index), and (3) site, the magnitude and significance ofthese odds ratios for IHCT did not change.

	Discussion

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

Confounding variables
The finding that low IHCT was associated with fewer ischemic events wasunexpected. Therefore it was of paramount importance that confounding variablesbe examined. Transfusion and fluid administration were not greatly differentbetween groups, and no independent relationship was detected between transfusionor fluid administration and MI. Although crystalloid fluid administration didstatistically differ between low and high IHCT groups, the difference in volume(430 ml) was not clinically important. Although lower IHCT did appear to affectthe use of hemostatic components and to be associated with increased bleeding,no relationship was identified between the use of these blood components and MIrates. Decreasing the value of the cut point for low HCT below or above 24%did not alter our findings.

If more severely ill patients (preoperatively or intraoperatively) werepreferentially maintained at a higher IHCT (e.g., through transfusion,hemoconcentration, fluid restriction), then the association between high IHCTand adverse outcome could be easily explained. Therefore we examined whetherpatients with clinical signs of postbypass morbidity (low cardiac index,hypotension, hypertension, tachycardia, ischemia, or requirement for inotropicmedications or intravenous nitroglycerin) were more likely to have higher IHCTlevels. These seriously ill patients were equally distributed among the threeIHCT groups. Thus perioperative morbidity was not a confounder.

Limitations
Limitations of our study include the definition of outcome. New Q waveswere chosen as a very strict and exclusive definition of MI. If other, perhapsmore liberal definitions of MI (e.g., creatine kinase MB, troponin, myoglobin,or echocardiographic findings) had been used, the frequency of these events byIHCT group may well have been different. No association was found between IHCTand other ischemic adverse outcomes such as stroke and renal failure. Inaddition, our study did not examine fibrinolytic state, platelet number, orfunction, and HCT was examined at only five time points. More HCT values withextensive hematologic correlates could potentially provide more informationconcerning cause and effect for the relationship found.

Prior work and potential causes
Prior research in animal models of anemia with both acute and chroniccoronary obstruction has been performed. ^20-22 Ischemia occurs across a widerange of HCT values from 17% to 42.5%. ^20-22Previous case reports and single-center studies support our findings that anemiaalone does not increase the risk of MI after CABG. ¹ In two studies of eight and 224patients, HCT levels did not affect myocardial lactate flux, a measure ofischemia. ^23,24 In a small study of 14 patients,the oxygen content of the coronary sinus did not change with either hemodilution(to 23%) or subsequent transfusion to 34%. ²⁵ A case report of a patient with anHCT level of 5% described diffuse myocardial dysfunction, relieved withtransfusion, but no postoperative MI. ²In our study, even in patients with IHCT levels between 13% and 18%(n = 13), no Q-wave MI or ventriculardysfunction occurred, nor were there any deaths.

Perioperative MI and dysfunction are likely the result of multiplecauses. ⁹ An increased IHCTlevel may precipitate ischemic injury via several mechanisms: (1) Increasedblood viscosity may require additional work by the myocardium, as well asdecreasing tissue oxygen delivery. ¹⁶(2) Shear forces between the vessel walls and the blood increase as theconcentration of red blood cells increases. In addition, platelets exposed tothese greater shear forces are more likely to be activated, and increasedlateral platelet migration exists. ²⁶Therefore the number of interactions per unit time between platelets and theendothelial walls increases. ²⁷These interactions between altered endothelium and activated platelets may beimportant. ²⁸ (3) Withincreased IHCT, the availability of nitric oxide, an inhibitor of platelet andneutrophil binding to endothelial cells, ²⁹may be decreased. (4) Liberated hemoglobin taken up by endothelial cellsincreases free radical production, ³⁰perhaps worsening endothelial dysfunction.

In conclusion, on the basis of this study of 2202 patients, low IHCT (<24%)at the conclusion of CABG operations appears to protect against Q-wave MI.Therefore our data do not support arbitrary transfusion of RBC products toincrease oxygen-carrying capacity after CABG. Furthermore, allowing a low IHCTto occur after CABG might decrease the morbidity and cost associated withtransfusion and also preserve a scarce resource (allogeneic blood). Futurerandomized prospective trials will be required to discover the mechanismsinvolved, as well as to examine associations between IHCT and creatine kinase MBor ischemia by ST-T wave analysis.

	Appendix 1

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
Participating McSPI institutions and investigators. Anil Aggarwal, MD, VA Medical Center, Milwaukee, Wis.; Wayne H. Bellows, MD, Gary Roach, MD, Kaiser-Permanente Medical Center, San Francisco, Calif.; Simon Body, MD, Rosemarie Maddi, MD, Brigham and Women's Hospital, Boston, Mass.; Randall Clark, MD, Patrick E. Curling, MD, Salwa Shenaq, MD, Baylor College of Medicine, Houston, Tex.; Mark E. Comunale, MD, Beth Israel Hospital, Boston, Mass.; Michael N. D'Ambra, MD, Massachusetts General Hospital, Boston, Mass.; Judith Fabian, MD, Richard Wolman, MD, Medical College of Virginia, Richmond, Va.; Richard Fine, MD, Onofrio Patafio, MD, Cornell University Medical Center, New York, N.Y.; Arnold S. Friedman, MD, Cedars-Sinai Medical Center, Los Angeles, Calif.; Mark Goldstein, MD, Stephen Slogoff, MD, Texas Heart Institute, Houston, Tex.; Marc Kanchuger, MD, Katherine E. Marschall, MD, New York University Medical Center, New York, N.Y.; Colleen Koch, MD, Norman J. Starr, MD, The Cleveland Clinic Foundation, Cleveland, Ohio; William Lell, MD, University of Alabama at Birmingham, Birmingham, Ala.; Joseph P. Mathew, MD, Yale University School of Medicine, New Haven, Conn.; Christina Mora Mangano, MD, James G. Ramsay, MD, Emory University School of Medicine, Atlanta, Ga.; Gerard M. Ozanne, MD, VA Medical Center, San Francisco, Calif.; Allan F. Ross, MD, University of Iowa, Iowa City, Iowa; Joseph S. Savino, MD, University of Pennsylvania, Philadelphia, Pa.; Bruce Spiess, MD, University of Washington, Seattle, Wash.; Thomas E. Stanley, MD, Duke University Medical Center, Durham, N.C.; E. Price Stover, MD, Lawrence C. Sigel, MD, Stanford University Medical Center, Stanford, Calif.; Kenneth J. Tuman, MD, Rush–Presbyterian–St. Luke's Medical Center, Chicago, Ill.; Joyce Wahr, MD, University of Michigan, Ann Arbor, Mich.; Winnie Ruo, MD, Mark Trankina, MD, University of Chicago, Chicago, Ill.

	Appendix 2

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 
Core analysis group. Director: Dennis T. Mangano, PhD, MD. Data Management/Statistical Analysis: Catherine Ley, PhD, Long Ngo, MS, Fong Liu, MSPH, Elizabeth Li, MS. Clinican Design Consultant: Gerard M. Ozanne, MD. Electrocardiographic Analysis: Uday Jain, PhD, MD, Adam Zhang, MD, Vladimir Titov, MD, PhD, Tatiana Titov, MD, PhD, Marilena Mirica, MD. Editorial Assistants: Winnifred von Ehrenburg, Diane Beatty, Mark Riddle.

	Acknowledgments

 
We acknowledge the assistance of Sonja Kapitan, MPH, incollecting and entering data, as well as the excellent secretarial assistance ofDonna J. Rowe, BA. We also thank Long Ngo and Reg Parks for additionalstatistical insights.

	References

Top Abstract Introduction Methods Results Discussion Appendix 1 Appendix 2 References

 

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