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Transfusion Risk and Clinical Knowledge (TRACK) Score and Cardiac Surgery in Patients Refusing Transfusion
Transfusion Risk and Clinical Knowledge (TRACK) Score and Cardiac Surgery in Patients Refusing Transfusion Tae Sik Kim, MD,* Jong Hyun Lee, MD,† Hyonggin An, PhD,‡ and Chan-Young Na, MD§ Objective: The Transfusion Risk and Clinical Knowledge (TRACK) score is a simple tool to predict the chance of undergoing blood transfusion in cardiac surgery. The authors evaluated the relationship between the TRACK score and clinical outcomes of cardiac surgery in patients who refused blood transfusion. Design: An observational study. Setting: A single hospital. Participants: Seventy-six adult Jehovah’s Witnesses refusing blood transfusion who underwent cardiac surgeries. Interventions: Patients were divided into 2 groups according to their TRACK score: low-risk group (n ¼ 57, TRACK score of less than 13) and high-risk group (n ¼ 19, TRACK score of 13 or more). Perioperative and longterm clinical outcomes were compared between the 2 groups.
Measurements and Main Results: The operative mortality was 0% in the low-risk group, and 21.1% (n ¼ 4) in the highrisk group (p ¼ 0.003). The incidence of major postoperative complications was higher in the high-risk group (57.9%) than in the low-risk group (17.5%) (p ¼ 0.002). The high-risk group had more postoperative bleeding-related complications (21.1%) than did the low-risk group (1.8%) (p ¼ 0.013). There were no significant differences of predictive performance in mortality and morbidity between the TRACK score and EuroSCORE II. Conclusion: In cardiac surgery patients refusing transfusions, the TRACK score predicted postoperative morbidity and mortality of cardiac surgery. & 2016 Elsevier Inc. All rights reserved.
A
One of the authors (C.-Y.N.) conducted all the cardiac surgeries for Jehovah’s Witness patients during the study period. All Jehovah’s Witness patients refused transfusion of all alternatives and products of blood. Patients younger than 18 years of age (n ¼ 22) were excluded from the study, resulting in the inclusion of 76 adult Jehovah’s Witness patients who underwent cardiac surgery without blood transfusion. The patient population was divided into 2 groups according to the TRACK score. Patients who had a TRACK score of less than 13 were categorized into the low-risk group (n ¼ 57), and patients who had a TRACK score of 13 or more were categorized into the high-risk group (n ¼ 19). A TRACK score of 13 corresponded with a transfusion risk of 60% in the development series of the previous report.11 The mean TRACK score for the study population was 6.2 in the low-risk group and 16.5 in the high-risk group (Table 1). The mean preoperative hematologic values in both groups were within the normal range multiple-valve surgery, coronary bypass surgery with valve surgery, and ascending aorta or aortic root surgery. The following surgeries were performed: valve surgery (n ¼ 17), coronary bypass surgery (n ¼ 28),
LLOGENEIC BLOOD TRANSFUSIONS during or after cardiac surgeries are associated with increased postoperative mortality and morbidity.1–6 Blood products seem to be transfused in cases of very low hemoglobin or hematocrit level during or after the surgery. However, some patients, such as Jehovah’s Witnesses, refuse blood transfusions on the basis of their religious belief, even in cases of severe anemia. Several scoring models have been developed to predict the rate of transfusion in cardiac surgery and thus prevent unnecessary transfusion and help in making the practical decision for transfusion.7–13 Using these scoring systems, practitioners can predict the rate of blood transfusion after cardiac surgery. For example, a patient with a higher score has a greater chance of requiring blood transfusion. In other words, perioperative blood transfusion may be essential for such a patient to maintain health and/or quality of life. The authors hypothesized that patients with a higher transfusion risk score who refuse blood transfusion might have worse clinical outcomes after cardiac surgery. In essence, the transfusion risk scoring system was believed to serve as a predictive tool of clinical outcomes in cardiac surgery for patients who do not receive a transfusion. Among the transfusion predictive scoring models, Ranucci et al11 proposed a simple scoring system, known as Transfusion Risk and Clinical Knowledge (TRACK). To predict the transfusion rate in cardiac surgery, the TRACK score uses the following 5 preoperative variables: age, weight, sex, complex surgery, and preoperative hematocrit level. The authors evaluated the relationship between the TRACK score and perioperative and long-term clinical outcomes of cardiac surgery in patients who refused blood transfusion. MATERIALS AND METHODS
Patient Characteristics The authors reviewed the records of 98 Jehovah’s Witness patients, who underwent cardiac surgery from January 2003 to February 2014, from the database of the authors’ institution.
KEY WORDS: blood transfusion, perioperative care, cardiac surgery, cardiopulmonary bypass, adult
From the *Department of Thoracic and Cardiovascular Surgery, Korea University Medical Center, Seoul, Republic of Korea; †Department of Anesthesiology, Sejong General Hospital, Bucheon, Republic of Korea; ‡Department of Biostatistics, Korea University Medical Center, Seoul, Republic of Korea; and §Department of Thoracic and Cardiovascular Surgery, Keimyung University Dongsan Medical Center, Daegu, Republic of Korea. This study was presented at the International Society for Minimally Invasive Cardiothoracic Surgery Annual Meeting during June 2015 in Berlin, Germany. Address reprint requests to Tae Sik Kim, MD, Department of Thoracic and Cardiovascular Surgery, Anam Hospital, Korea University Medical Center, 73, Inchon-ro, Seongbuk-gu, Seoul 02841, Republic of Korea. E-mail: [email protected] © 2016 Elsevier Inc. All rights reserved. 1053-0770/2601-0001$36.00/0 http://dx.doi.org/10.1053/j.jvca.2015.11.004
Journal of Cardiothoracic and Vascular Anesthesia, Vol 30, No 2 (April), 2016: pp 373–378
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Table 1. Preoperative and Operative Characteristics Low-Risk Group Variables
TRACK score Age (yr) Weight (kg) Female Diabetes mellitus Hypertension Stroke Hyperlipidemia Peripheral artery disease Chronic renal disease EuroSCORE II NYHA class Previous cardiac surgery Ejection fraction (%) Hemoglobin (g/dL) Hematocrit (%) Creatinine (mg/dL) Complex surgery CPB time (min) ACC time (min) Use of CPB Second CPB Emergency ANH Lowest Hct during CPB (%)
*
(n ¼ 57)
High-Risk Group (n ¼ 19)
*
p Value†
6.2 53.0 64.3 25 14 21 2 15 2
⫾ 3.6 ⫾ 12.7 ⫾ 9.6 (43.9%) (24.6%) (36.8%) (3.5%) (26.3%) (3.5%)
16.5 62.5 54.4 16 3 6 2 4 2
⫾ 3.4 ⫾ 12.0 ⫾ 7.7 (84.2%) (15.8%) (31.6%) (10.5%) (21.1%) (10.5%)
o0.001 0.005 o0.001 0.003 0.537 0.786 0.259 0.766 0.259
1 1.58 2.3 3
(1.8%) ⫾ 1.52 ⫾ 0.7 (5.3%)
1 2.74 2.6 2
(5.3%) ⫾ 1.94 ⫾ 0.7 (10.5%)
0.440 0.009 0.130 0.594
60.8 13.5 40.2 1.0 7 113.6 77.2 40 0 0 5 24.7
⫾ 12.0 ⫾ 1.2 ⫾ 3.5 ⫾ 0.2 (12.3%) ⫾ 58.9 ⫾ 46.4 (70.2%) (0.0%) (0.0%) (12.5%) ⫾ 3.1
56.3 12.0 36.5 0.9 13 152.1 114.7 16 2 3 6 21.3
⫾ 11.3 ⫾ 1.5 ⫾ 4.4 ⫾ 0.3 (68.4%) ⫾ 60.8 ⫾ 41.3 (84.2%) (12.5%) (15.8%) (37.5%) ⫾ 2.6
0.157 o0.001 o0.001 0.780 o0.001 0.033 0.007 0.367 0.078 0.014 0.059 o0.001
NOTE: Data are presented as mean ⫾ standard deviation for continuous variables and as number and percentage for categoric variables. Abbreviations: ACC, aortic cross-clamping; ANH, acute normovolemic hemodilution; CPB, cardiopulmonary bypass; EuroSCORE, European System for Cardiac Operative Risk Evaluation; Hct, hematocrit; NYHA, New York Heart Association; TRACK, Transfusion Risk and Clinical Knowledge. *Low-risk group includes patients with a TRACK score of less than 13; high-risk group includes patients with a TRACK score of 13 or more. †Student’s t-test for continuous variables; Fisher’s exact test for categoric variables.
ascending aorta surgery (n ¼ 1), aortic root surgery (n ¼ 2), myxoma removal (n ¼ 3), atrial septal defect closure (n ¼ 5), ventricular septal defect closure (n ¼ 3), and maze procedure (n ¼ 1) in the low-risk group and valve surgery (n ¼ 13), coronary bypass surgery (n ¼ 6), atrial septal defect closure (n ¼ 1), and maze procedure (n ¼ 1) in the high-risk group. Preoperative and operative data in the low-risk and high-risk groups are depicted in Table 1. This study was reviewed and approved by the Institutional Review Board of the authors’ institution. The requirement for individual patient consent was waived. Perioperative and Operative Management Since the early 2000s, the authors have applied a comprehensive multimodality program for performing surgeries without blood transfusion in Jehovah’s Witness patients
undergoing cardiac surgery. This blood conservation strategy without transfusion has been developed and modified in the authors’ institution with reference to other studies.14–16 During the study period, the cases of these patients were managed according to the authors’ blood conservation strategy and clinical protocols as described in the following. Any intake of alcohol, medications, or supplements that might increase the risk of bleeding (eg, celecoxib, vitamin E, ginkgo supplements, garlic) was discontinued 7 days before surgery. In all patients, aspirin (3 to 5 days before surgery) and clopidogrel (7 days before surgery) were withheld. Patients who received warfarin had their prothrombin time/international normalized ratio (PT/INR) normalized for conversion to unfractionated heparin. Heparin infusion was adjusted to maintain an activated partial thromboplastin time of 50 to approximately 70 seconds. Just after a patient was admitted for surgery, erythropoietin (500 U/kg/d every other day) was injected subcutaneously, as indicated, to achieve a goal hemoglobin level of 13 g/dL (male) or 12g/dL (female). Supplements of iron, folate, calcium, and vitamin C also were administered to these patients. Low-volume acute normovolemic hemodilution (5 to 8 mL/kg) was performed if hemoglobin level was greater than 13 g/dL in male and 12 g/dL in female patients.17 After anesthetic induction, venous blood was drained into a collecting bag through a central venous line, and the same volume of colloid solution was replaced through another venous line at the same time. During the surgery, the patient’s blood in the collecting bag was stored at room temperature and was re-transfused after protamine administration. All patients underwent moderate hypothermia (321C) and alpha-stat pH management during surgery. A centrifugal pump with a hollow-fiber oxygenator and polymethylpentene-coated cardiopulmonary bypass (CPB) circuits (CAPIOX; Terumo, Ann Arbor, MI) were used during all the surgeries. An initial dose of heparin (300 U/kg) was given to achieve and maintain an activated clotting time greater than 480 seconds. The activated clotting time was measured every hour during CPB. Heparin and protamine administration were monitored using a dose-response assay. The authors performed the retrograde autologous priming technique, which is the modified protocol from previous studies.18,19 Myocardial protection was achieved using cold antegrade crystalloid cardioplegia (histidine-tryptophan-ketoglutarate solution) or cold retrograde blood cardioplegia (1:4), according to surgeons’ preferences, supplemented by topical cooling with cold saline solution. Blood in an operative field was aspirated to a cardiotomy pump sucker during CPB and to a cell saving device (autoLog Autotransfusion System; Medtronic, Minneapolis, MN) before and after CPB. Field blood was not discarded using suckers. All the sponges were wrung in a bowl, and the drainage was directed to a cellsaving device. Modified ultrahemofiltration during CPB was used to concentrate the blood in all the cases whenever feasible. After separation from CPB, heparin was neutralized with protamine sulfate (1 mg/100 U of heparin) to achieve an activated clotting time within 10% of baseline. After the surgery and during the intensive care unit stay, shed mediastinal and pleural blood
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collected in a reservoir was reinfused into the patients using a cell-saving device. After the surgery, patients were transferred to the intensive care unit and their cases were managed according to the unit protocol. Antifibrinolytic drugs, such as tranexamic acid, were used immediately after surgery in the intensive care unit. On the first postoperative day, anticoagulation was started, as indicated. After cardiac valve surgery using a mechanical valve, warfarin medication was started with a target PT/INR of 2.0 to 3.0, which requires lifelong administration. In patients with a history of atrial fibrillation or thromboembolism, PT/ INR with warfarin was maintained within a range between 2.5 and 3.5. Patients with biologic valves were advised to take warfarin for the first 3 months, which was discontinued during the follow-up period. After the coronary bypass surgery, aspirin and clopidogrel were prescribed for life-long use. Follow-Up The clinical follow-up data were collected retrospectively from the medical records of the authors’ institution or by telephone interviews. The date of the last inquiry was between January and May 2014. The mean duration of follow-up was 73.0 ⫾ 40.0 months and 63.5 ⫾ 48.7 months in the low-risk and the high-risk groups, respectively (p = 0.440); 98.7% (n = 75) of hospital survivors completed the follow-up. Statistical Analysis Descriptive statistics are described as the mean ⫾ standard deviation for continuous variables and as frequency and percentage for categoric variables. Differences between groups for the continuous variables and the categoric variables were tested using Student’s t-test and Fisher’s exact test, respectively. Results with p values o0.05 were considered statistically significant. Long-term survival and event-free survival were analyzed using the Kaplan-Meier survival method. To compare survival curves between the groups, log-rank test was used. To evaluate the predictive performance between the TRACK and EuroSCORE scoring systems, the area under receiver operating characteristic (AUROC) curve was compared between the 2 systems. The SPSS software 20.0 program (IBM Corp, Armonk, NY) was used for statistical analyses, except for the AUROC curve analysis. AUROC curve analysis was performed using MedCalc for Windows, version 15.6 (MedCalc Software, Ostend, Belgium). RESULTS
Postoperative Outcomes The operative mortality was 0% in the low-risk group and 21.1% (n = 4) in the high-risk group (p = 0.003). The main causes of operative death were right ventricle failure (n = 1), arrhythmia (n = 1), renal failure (n = 1), and sepsis (n = 1). Ten patients (17.5%) in the low-risk group and 11 patients (57.9%) in the high-risk group experienced major postoperative complications (p = 0.002). In the low-risk group, major postoperative complications (multiple counting for a patient) included new-onset left ventricular dysfunction (n = 4), newonset supraventricular arrhythmia (n = 2), systemic infection
with positive blood culture results (n = 1), renal insufficiency (n = 2), and gastrointestinal bleeding (n = 1). In the high-risk group, major postoperative complications (multiple counting for a patient) included extracorporeal membrane oxygenation support (n = 1), new-onset left ventricular dysfunction (n = 3), new-onset supraventricular arrhythmia (n = 1), resternotomy for other reasons excluding bleeding control (n = 2), sternal wound infection including mediastinitis (n = 2), systemic infection with positive blood culture results (n = 1), renal insufficiency (n = 2), renal failure requiring dialysis (n = 2), pneumonia (n = 1), operative bleeding control (n = 3), and intracranial hemorrhage (n = 1). The high-risk group (n = 4; 21.1%) experienced more postoperative bleeding-related complications than did the lowrisk group (n = 1; 1.8%) (p = 0.013). The degree of postoperative changes of hemoglobin and hematocrit level was within the acceptable range for both groups (Table 2). Postoperative hemoglobin and hematocrit levels were checked on the first postoperative day. The postoperative creatinine level (highest level for the first 3 postoperative days) as an indicator of renal injury did not demonstrate a significant difference between both groups. Long-Term Outcomes There were 5 late overall deaths during the follow-up period —4 in the low-risk group and 1 in the high-risk group (see Table 2). The main causes of late death in the low-risk group were severe brain damage after reoperation (n ¼ 1), intracranial hemorrhage (n ¼ 2), and gastrointestinal bleeding (n ¼ 1). In the high-risk group, 1 patient died as a result of acute heart failure after reoperation (second-time valve replacement) in another hospital. The late morbidities (multiple counting for a patient) included congestive heart failure (n ¼ 2), supraventricular arrhythmia (n ¼ 3), ischemic heart disease (n ¼ 2), pneumonia (n ¼ 2), reoperation (n ¼ 1), percutaneous coronary intervention (n ¼ 1), intracranial hemorrhage (n ¼ 2), and gastrointestinal bleeding (n ¼ 1) in the low-risk group and reoperation (n ¼ 1) and gastrointestinal bleeding (n ¼ 1) in the high-risk group. There were no significant differences in the actuarial rates of overall survival, late morbidity-free survival, and late bleedingrelated morbidity-free survival between both groups (Table 3). Comparison with EuroSCORE II There were no significant differences of predictive performance in operative mortality, major postoperative complications, and postoperative bleeding-related complications between the TRACK score and EuroSCORE II (Table 4). The AUC in major postoperative complications for the 2 models is represented in Fig 1. DISCUSSION
The major finding of this study was that the TRACK score might predict postoperative clinical outcomes of cardiac surgery for patients who decline blood transfusion. Also, there were no significant differences of predictive performance in operative mortality, major postoperative complications, and
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Table 2. Postoperative Data and Clinical Outcomes Low-Risk Variables
Postoperative data Postoperative Hb (g/dL)‡ Postoperative Hct (%)‡ Postoperative Cr (mg/dL)‡ Postoperative LVEF (%) Postoperative LOS (day) Difference (preop Hb – postop Hb) Difference (preop Hct – postop Hct) Difference (preop Hct – lowest Hct during CPB) Lowest Hct (%) during CPB Postoperative outcomes Operative death Postoperative complications Postoperative bleedingrelated complications Long-term outcomes Late death Late morbidity Bleeding-related morbidity
High-Risk
Group*
Group*
(n ¼ 57)
(n ¼ 19)
12.4 37.1 1.1 58.3 15.8 1.1
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
1.3 3.8 0.3 12.4 8.0 1.1
Table 4. Area Under Receiver Operating Characteristic Curve for the TRACK Score and EuroSCORE II
10.6 31.7 1.2 53.5 21.1 1.4
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
p Value†
1.6 4.4 0.6 9.7 15.8 1.1
o0.001 o0.001 0.411 0.148 0.176 0.220
3.1 ⫾ 3.0
4.8 ⫾ 3.6
0.044
15.6 ⫾ 3.7
15.2 ⫾ 3.9
0.688
24.7 ⫾ 3.1
21.3 ⫾ 2.6
o0.001
0 (0%) 10 (17.5%) 1 (1.8%)
4 (21.1%) 11 (57.9%) 4 (21.1%)
0.003 0.002 0.013
4 (7.0%) 13 (22.8%) 3 (5.3%)
1 (6.7%) 2 (13.3%) 1 (6.7%)
0.893 0.658 0.708
NOTE: Data are presented as mean ⫾ standard deviation for continuous variables and as number and percentage for categoric variables. Abbreviations: CPB, cardiopulmonary bypass; Cr, creatinine; Hb, hemoglobin; Hct, hematocrit; LVEF, left ventricular ejection fraction; LOS, length of stay. *Low-risk group includes patients with a TRACK score of less than 13; high-risk group includes patients with a TRACK score of 13 or more. †Student’s t-test for postoperative data, Fisher’s exact test for postoperative outcomes, and log-rank test for long-term outcomes. ‡Lowest hemoglobin and hematocrit levels at the first postoperative day; highest creatinine levels for the first 3 postoperative days.
postoperative bleeding-related complications between the TRACK score and EuroSCORE II. To predict the rate of transfusion in cardiac surgery, several scoring models have been proposed.7–13 The TRACK scoring model offers a simple method to predict the transfusion rate in cardiac surgery.11 This simple transfusion risk model that is based on 5 preoperative variables had a similar or better accuracy and validation in quantifying the transfusion rate during cardiac surgery than the other models. The 5 predictors
Operative mortality TRACK score EuroSCORE II Major postoperative complications TRACK score EuroSCORE II Postoperative bleeding-related complications TRACK score EuroSCORE II
AUROC
95% CI
0.877 0.774
0.781-0.941 0.664-0.862
0.695 0.700
0.579-0.795 0.584-0.799
p Value
0.4169
0.9547
1.0000 0.728 0.728
0.614-0.824 0.614-0.824
Abbreviations: AUROC, area under receiver operating characteristic; CI, confidence interval; EuroSCORE, European System for Cardiac Operative Risk Evaluation; TRACK, Transfusion Risk and Clinical Knowledge.
of age, weight, sex, complex surgery, and hematocrit level constitute the TRACK score. This score has a distribution range between 0 and 32. The authors’ study population was divided into the following 2 groups according to their TRACK score: patients with a TRACK score of less than 13 (low-risk group) and those with a TRACK score of 13 (high-risk group). A TRACK score of 13 corresponded to a transfusion risk of 60% in the development series.11 In the Transfusion Risk Understanding Scoring Tool model, a total score of 3 was interpreted as a high chance of receiving blood transfusion and corresponded to the predictive rate of transfusion between 0.60 and 0.79.9 Also, the score of 4 to 8 was interpreted as very high risk of exposure to transfusion (0.80-1.00). The Al-Khabori et al13 model showed that the probabilities of transfusion of 42%, 63%, and 91% were equivalent to a score of less than 2, between 2 and 5, and more than 5, respectively. Those authors believed that the value of risk probability of 60% seemed to be a cutoff point for grouping. Of course, the 2 groups in this study had significant differences in 5 preoperative variables: age (p ¼ 0.005), weight (p o 0.001), sex (p ¼ 0.003), hematocrit level (p o 0.001), and complex surgery (p o 0.001) (see Table 1). The grouping of the patients in this study was considered to be appropriate. Interestingly, Ranucci et al11 excluded Jehovah’s Witness patients and surgery without CPB in their study population of the TRACK scoring model. However, the entire population of this study was comprised of Jehovah’s Witnesses, and a quarter of the population underwent cardiac surgeries without
Table 3. Long-Term Clinical Outcomes Low-Risk Group* (n ¼ 57) Variables
Overall survival Morbidity-free survival Bleeding-related morbidity-free survival
1 year
5 years
High-Risk Group* (n ¼ 19) 10 years
1 year
5 years
10 years
98.2% ⫾ 1.8% 98.2% ⫾ 1.8% 91.9% ⫾ 3.9% 92.3% ⫾ 7.4% 92.3% ⫾ 7.4% 92.3% ⫾ 7.4% 90.6% ⫾ 4.0% 79.7% ⫾ 6.3% 64.6% ⫾ 8.6% 92.3% ⫾ 7.4% 84.6% ⫾ 10.0% 84.6% ⫾ 10.0% 98.1% ⫾ 1.9% 93.0% ⫾ 4.0% 93.0% ⫾ 4.0% 100.0% ⫾ 0.0% 91.7% ⫾ 8.0% 91.7% ⫾ 8.0%
p Value†
0.893 0.658 0.708
*Low-risk group includes patients with a TRACK score of less than 13, and high-risk group includes patients with a TRACK score of 13 or more. †Log-rank test for long-term clinical outcomes.
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postoperative hospital stay in this study demonstrated a tendency to be longer in the high-risk group (21.1 days) than in the low-risk group (15.8 days). Unfortunately, intensive care unit length of stay was not included in this study. This variable will be included in the next study with a larger series of patients. In the low-risk group, only 2 patients experienced renal insufficiency (2/57; 3.5%). In the high-risk group, 2 patients experienced renal insufficiency and 2 patients required dialysis for renal failure (4/19; 21.1%). Similarly to use of the EuroSCORE II, practitioners can use the TRACK score to predict the perioperative clinical outcomes after cardiac surgery in patients refusing transfusions. Study Limitations Fig 1. Area under receiver operating characteristic curve in major postoperative complications for the TRACK score and EuroSCORE II.
CPB (see Table 1). Because the TRACK score serves as a predictive value for patients undergoing transfusion, this score may be applied to predict postoperative outcomes for patients who do not undergo transfusion. The lowest hematocrit level during CPB was significantly less in the high-risk group than in the low-risk group (see Table 1). This difference might be due to the lower preoperative hematocrit level in the high-risk group than that in the low-risk group. Loor et al20 recently reported that preoperative anemia is the most significant risk factor for a low nadir hematocrit level during CPB. In this study, the high-risk group with a lower nadir hematocrit level during CPB (21.3%) experienced worse clinical outcomes after cardiac surgeries than did the low-risk group (24.7%; p o 0.001). The lowest hematocrit level during CPB was believed to be strongly associated with adverse postoperative clinical outcomes in other studies.20–25 The lowest hematocrit value less than 22% significantly increased the incidence of stroke, myocardial infarction, low cardiac output, prolonged ventilation, pulmonary edema, reoperation due to bleeding, and multiorgan failure.21 Ranucci et al22 also suggested that the lowest hematocrit value during CPB was an independent risk factor for postoperative renal failure. In their study, the hematocrit cutoff value for renal failure was 23%. Interestingly, these findings were similar to the data presented in this study (21.3% versus 24.7%). The operative mortality was 0% in the low-risk group and 21.1% (n ¼ 4) in the high-risk group (p ¼ 0.003). In addition, 5 late overall deaths occurred during the follow-up period: 4 in the low-risk group and 1 in the high-risk group (p ¼ 0.893). In this study, patients with a higher TRACK score had higher operative mortality but not long-term mortality. The length of
This study had several limitations that are inherent in retrospective reviews in a single medical institution. The long-term clinical outcomes of this study had low statistical power due to the low number of events. However, the authors could obtain meaningful results with respect to postoperative outcomes by performing statistical analysis. Unfortunately, the authors could not determine whether blood transfusion in patients in the high-risk group would have produced better clinical results. However, the authors found evidence of severe anemia in patients with accompanying mortality or morbidity who declined blood transfusion even in adverse situations. Recently, some noteworthy studies about the balance between anemia and blood transfusion have been published.26,27 Although blood transfusion is associated with increased morbidity risk, anemia also is a significant risk factor for adverse outcomes. Loor et al20 mentioned that it is unclear whether tolerating the anemia would be riskier than treating it with a blood transfusion once perioperative anemia has occurred. Indeed, this situation seems to be like 2 sides of the same coin. CONCLUSION
The most noticeable finding of this study was that the TRACK score might predict postoperative clinical outcomes of cardiac surgery in a specific population such as Jehovah’s Witnesses refusing blood transfusion. For the first time, this study identified the TRACK score as a predictor of clinical outcomes in cardiac surgery for patients who do not undergo transfusion. In addition, the TRACK score had predictive performance in operative mortality, major postoperative complications, and postoperative bleeding-related complications compared with EuroSCORE II. However, further investigations with a larger series of patients are required to draw more powerful conclusions on the predictive power of the TRACK score in terms of postoperative outcomes.
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5. Horvath KA, Acker MA, Chang H, et al: Blood transfusion and infection after cardiac surgery. Ann Thorac Surg 95:2194-2201, 2013 6. Leal-Noval SR, Rincón-Ferrari MD, García-Curiel A, et al: Transfusion of blood components and postoperative infection in patients undergoing cardiac surgery. Chest 119:1461-1468, 2001 7. Magovern JA, Sakert T, Benckart DH, et al: A model for predicting transfusion after coronary artery bypass grafting. Ann Thoracic Surg 61:27-32, 1996 8. Litmathe J, Boeken U, Feindt P, et al: Predictors of homologous blood transfusion for patients undergoing open heart surgery. Thorac Cardiovasc Surg 51:17-21, 2003 9. Alghamdi AA, Davis A, Brister S, et al: Development and validation of Transfusion Risk Understanding Scoring Tool (TRUST) to stratify cardiac surgery patients according to their blood transfusion needs. Transfusion 46:1120-1129, 2006 10. Karkouti K, Wijeysundera DN, Beattie WS, et al: Variability and predictability of large-volume red blood cell transfusion in cardiac surgery: A multicenter study. Transfusion 47:2081-2088, 2007 11. Ranucci M, Castelvecchio S, Frigiola A, et al: Predicting transfusions in cardiac surgery: The easier, the better: the Transfusion Risk and Clinical Knowledge score. Vox Sang 96:324-332, 2009 12. Simeone F, Franchi F, Cevenini G, et al: A simple clinical model for planning transfusion quantities in heart surgery. BMC Med Inform Decis Mak 11:44, 2011 13. Al-Khabori M, Al-Riyami AZ, Mukaddirov M, et al: Transfusion indication predictive score: A proposed risk stratification score for perioperative red blood cell transfusion in cardiac surgery. Vox Sang 107:269-275, 2014 14. Rosengart TK, Helm RE, DeBois WJ, et al: Open heart operations without transfusion using a multimodality blood conservation strategy in 50 Jehovah’s Witness patients: Implications for a “bloodless” surgical technique. J Am Coll Surg 184:618-629, 1997 15. Helm RE, Rosengart TK, Gomez M, et al: Comprehensive multimodality blood conservation: 100 consecutive CABG operations without transfusion. Ann Thorac Surg 65:125-136, 1998 16. Spahn DR, Casutt M: Eliminating blood transfusions: new aspects and perspectives. Anesthesiology 93:242-255, 2000
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17. Casati V, Speziali G, D’Alessandro C, et al: Intraoperative lowvolume acute normovolemic hemodilution in adult open-heart surgery. Anesthesiology 97:367-373, 2002 18. Shapira OM, Aldea GS, Treanor PR, et al: Reduction of allogeneic blood transfusions after open heart operations by lowering cardiopulmonary bypass prime volume. Ann Thorac Surg 65: 724-730, 1998 19. Rosengart TK, DeBois W, O’Hara M, et al: Retrograde autologous priming for cardiopulmonary bypass: A safe and effective means of decreasing hemodilution and transfusion requirements. J Thorac Cardiovasc Surg 115:426-438, 1998 20. Loor G, Li L, Sabik JF 3rd, et al: Nadir hematocrit during cardiopulmonary bypass: End-organ dysfunction and mortality. J Thorac Cardiovasc Surg 144:654-662, 2012 21. Habib RH, Zacharias A, Schwann TA, et al: Adverse effects of low hematocrit during cardiopulmonary bypass in the adult: Should current practice be changed? J Thorac Cardiovasc Surg 125: 1438-1450, 2003 22. Ranucci M, Biagioli B, Scolletta S, et al: Lowest hematocrit on cardiopulmonary bypass impairs the outcome in coronary surgery: An Italian multicenter study from the National Cardioanesthesia Database. Tex Heart Inst J 33:300-305, 2006 23. DeFoe GR, Ross CS, Olmstead EM, et al: Lowest hematocrit on bypass and adverse outcomes associated with coronary artery bypass grafting. Northern New England Cardiovascular Disease Study Group. Ann Thorac Surg 71:769-776, 2001 24. Swaminathan M, Phillips-Bute BG, Conlon PJ, et al: The association of lowest hematocrit during cardiopulmonary bypass with acute renal injury after coronary artery bypass surgery. Ann Thorac Surg 76:784-792, 2003 25. Karkouti K, Djaiani G, Borger MA, et al: Low hematocrit during cardiopulmonary bypass is associated with increased risk of perioperative stroke in cardiac surgery. Ann Thorac Surg 80:1381-1387, 2005 26. Nalla BP, Freedman J, Hare GM, et al: Update on blood conservation for cardiac surgery. J Cardiothorac Vasc Anesth 26: 117-133, 2012 27. Loor G, Koch CG, Sabik JF, et al: Implications and management of anemia in cardiac surgery: Current state of knowledge. J Thorac Cardiovasc Surg 144:538-546, 2012
Measurements and Main Results: The operative mortality was 0% in the low-risk group, and 21.1% (n ¼ 4) in the highrisk group (p ¼ 0.003). The incidence of major postoperative complications was higher in the high-risk group (57.9%) than in the low-risk group (17.5%) (p ¼ 0.002). The high-risk group had more postoperative bleeding-related complications (21.1%) than did the low-risk group (1.8%) (p ¼ 0.013). There were no significant differences of predictive performance in mortality and morbidity between the TRACK score and EuroSCORE II. Conclusion: In cardiac surgery patients refusing transfusions, the TRACK score predicted postoperative morbidity and mortality of cardiac surgery. & 2016 Elsevier Inc. All rights reserved.
A
One of the authors (C.-Y.N.) conducted all the cardiac surgeries for Jehovah’s Witness patients during the study period. All Jehovah’s Witness patients refused transfusion of all alternatives and products of blood. Patients younger than 18 years of age (n ¼ 22) were excluded from the study, resulting in the inclusion of 76 adult Jehovah’s Witness patients who underwent cardiac surgery without blood transfusion. The patient population was divided into 2 groups according to the TRACK score. Patients who had a TRACK score of less than 13 were categorized into the low-risk group (n ¼ 57), and patients who had a TRACK score of 13 or more were categorized into the high-risk group (n ¼ 19). A TRACK score of 13 corresponded with a transfusion risk of 60% in the development series of the previous report.11 The mean TRACK score for the study population was 6.2 in the low-risk group and 16.5 in the high-risk group (Table 1). The mean preoperative hematologic values in both groups were within the normal range multiple-valve surgery, coronary bypass surgery with valve surgery, and ascending aorta or aortic root surgery. The following surgeries were performed: valve surgery (n ¼ 17), coronary bypass surgery (n ¼ 28),
LLOGENEIC BLOOD TRANSFUSIONS during or after cardiac surgeries are associated with increased postoperative mortality and morbidity.1–6 Blood products seem to be transfused in cases of very low hemoglobin or hematocrit level during or after the surgery. However, some patients, such as Jehovah’s Witnesses, refuse blood transfusions on the basis of their religious belief, even in cases of severe anemia. Several scoring models have been developed to predict the rate of transfusion in cardiac surgery and thus prevent unnecessary transfusion and help in making the practical decision for transfusion.7–13 Using these scoring systems, practitioners can predict the rate of blood transfusion after cardiac surgery. For example, a patient with a higher score has a greater chance of requiring blood transfusion. In other words, perioperative blood transfusion may be essential for such a patient to maintain health and/or quality of life. The authors hypothesized that patients with a higher transfusion risk score who refuse blood transfusion might have worse clinical outcomes after cardiac surgery. In essence, the transfusion risk scoring system was believed to serve as a predictive tool of clinical outcomes in cardiac surgery for patients who do not receive a transfusion. Among the transfusion predictive scoring models, Ranucci et al11 proposed a simple scoring system, known as Transfusion Risk and Clinical Knowledge (TRACK). To predict the transfusion rate in cardiac surgery, the TRACK score uses the following 5 preoperative variables: age, weight, sex, complex surgery, and preoperative hematocrit level. The authors evaluated the relationship between the TRACK score and perioperative and long-term clinical outcomes of cardiac surgery in patients who refused blood transfusion. MATERIALS AND METHODS
Patient Characteristics The authors reviewed the records of 98 Jehovah’s Witness patients, who underwent cardiac surgery from January 2003 to February 2014, from the database of the authors’ institution.
KEY WORDS: blood transfusion, perioperative care, cardiac surgery, cardiopulmonary bypass, adult
From the *Department of Thoracic and Cardiovascular Surgery, Korea University Medical Center, Seoul, Republic of Korea; †Department of Anesthesiology, Sejong General Hospital, Bucheon, Republic of Korea; ‡Department of Biostatistics, Korea University Medical Center, Seoul, Republic of Korea; and §Department of Thoracic and Cardiovascular Surgery, Keimyung University Dongsan Medical Center, Daegu, Republic of Korea. This study was presented at the International Society for Minimally Invasive Cardiothoracic Surgery Annual Meeting during June 2015 in Berlin, Germany. Address reprint requests to Tae Sik Kim, MD, Department of Thoracic and Cardiovascular Surgery, Anam Hospital, Korea University Medical Center, 73, Inchon-ro, Seongbuk-gu, Seoul 02841, Republic of Korea. E-mail: [email protected] © 2016 Elsevier Inc. All rights reserved. 1053-0770/2601-0001$36.00/0 http://dx.doi.org/10.1053/j.jvca.2015.11.004
Journal of Cardiothoracic and Vascular Anesthesia, Vol 30, No 2 (April), 2016: pp 373–378
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Table 1. Preoperative and Operative Characteristics Low-Risk Group Variables
TRACK score Age (yr) Weight (kg) Female Diabetes mellitus Hypertension Stroke Hyperlipidemia Peripheral artery disease Chronic renal disease EuroSCORE II NYHA class Previous cardiac surgery Ejection fraction (%) Hemoglobin (g/dL) Hematocrit (%) Creatinine (mg/dL) Complex surgery CPB time (min) ACC time (min) Use of CPB Second CPB Emergency ANH Lowest Hct during CPB (%)
*
(n ¼ 57)
High-Risk Group (n ¼ 19)
*
p Value†
6.2 53.0 64.3 25 14 21 2 15 2
⫾ 3.6 ⫾ 12.7 ⫾ 9.6 (43.9%) (24.6%) (36.8%) (3.5%) (26.3%) (3.5%)
16.5 62.5 54.4 16 3 6 2 4 2
⫾ 3.4 ⫾ 12.0 ⫾ 7.7 (84.2%) (15.8%) (31.6%) (10.5%) (21.1%) (10.5%)
o0.001 0.005 o0.001 0.003 0.537 0.786 0.259 0.766 0.259
1 1.58 2.3 3
(1.8%) ⫾ 1.52 ⫾ 0.7 (5.3%)
1 2.74 2.6 2
(5.3%) ⫾ 1.94 ⫾ 0.7 (10.5%)
0.440 0.009 0.130 0.594
60.8 13.5 40.2 1.0 7 113.6 77.2 40 0 0 5 24.7
⫾ 12.0 ⫾ 1.2 ⫾ 3.5 ⫾ 0.2 (12.3%) ⫾ 58.9 ⫾ 46.4 (70.2%) (0.0%) (0.0%) (12.5%) ⫾ 3.1
56.3 12.0 36.5 0.9 13 152.1 114.7 16 2 3 6 21.3
⫾ 11.3 ⫾ 1.5 ⫾ 4.4 ⫾ 0.3 (68.4%) ⫾ 60.8 ⫾ 41.3 (84.2%) (12.5%) (15.8%) (37.5%) ⫾ 2.6
0.157 o0.001 o0.001 0.780 o0.001 0.033 0.007 0.367 0.078 0.014 0.059 o0.001
NOTE: Data are presented as mean ⫾ standard deviation for continuous variables and as number and percentage for categoric variables. Abbreviations: ACC, aortic cross-clamping; ANH, acute normovolemic hemodilution; CPB, cardiopulmonary bypass; EuroSCORE, European System for Cardiac Operative Risk Evaluation; Hct, hematocrit; NYHA, New York Heart Association; TRACK, Transfusion Risk and Clinical Knowledge. *Low-risk group includes patients with a TRACK score of less than 13; high-risk group includes patients with a TRACK score of 13 or more. †Student’s t-test for continuous variables; Fisher’s exact test for categoric variables.
ascending aorta surgery (n ¼ 1), aortic root surgery (n ¼ 2), myxoma removal (n ¼ 3), atrial septal defect closure (n ¼ 5), ventricular septal defect closure (n ¼ 3), and maze procedure (n ¼ 1) in the low-risk group and valve surgery (n ¼ 13), coronary bypass surgery (n ¼ 6), atrial septal defect closure (n ¼ 1), and maze procedure (n ¼ 1) in the high-risk group. Preoperative and operative data in the low-risk and high-risk groups are depicted in Table 1. This study was reviewed and approved by the Institutional Review Board of the authors’ institution. The requirement for individual patient consent was waived. Perioperative and Operative Management Since the early 2000s, the authors have applied a comprehensive multimodality program for performing surgeries without blood transfusion in Jehovah’s Witness patients
undergoing cardiac surgery. This blood conservation strategy without transfusion has been developed and modified in the authors’ institution with reference to other studies.14–16 During the study period, the cases of these patients were managed according to the authors’ blood conservation strategy and clinical protocols as described in the following. Any intake of alcohol, medications, or supplements that might increase the risk of bleeding (eg, celecoxib, vitamin E, ginkgo supplements, garlic) was discontinued 7 days before surgery. In all patients, aspirin (3 to 5 days before surgery) and clopidogrel (7 days before surgery) were withheld. Patients who received warfarin had their prothrombin time/international normalized ratio (PT/INR) normalized for conversion to unfractionated heparin. Heparin infusion was adjusted to maintain an activated partial thromboplastin time of 50 to approximately 70 seconds. Just after a patient was admitted for surgery, erythropoietin (500 U/kg/d every other day) was injected subcutaneously, as indicated, to achieve a goal hemoglobin level of 13 g/dL (male) or 12g/dL (female). Supplements of iron, folate, calcium, and vitamin C also were administered to these patients. Low-volume acute normovolemic hemodilution (5 to 8 mL/kg) was performed if hemoglobin level was greater than 13 g/dL in male and 12 g/dL in female patients.17 After anesthetic induction, venous blood was drained into a collecting bag through a central venous line, and the same volume of colloid solution was replaced through another venous line at the same time. During the surgery, the patient’s blood in the collecting bag was stored at room temperature and was re-transfused after protamine administration. All patients underwent moderate hypothermia (321C) and alpha-stat pH management during surgery. A centrifugal pump with a hollow-fiber oxygenator and polymethylpentene-coated cardiopulmonary bypass (CPB) circuits (CAPIOX; Terumo, Ann Arbor, MI) were used during all the surgeries. An initial dose of heparin (300 U/kg) was given to achieve and maintain an activated clotting time greater than 480 seconds. The activated clotting time was measured every hour during CPB. Heparin and protamine administration were monitored using a dose-response assay. The authors performed the retrograde autologous priming technique, which is the modified protocol from previous studies.18,19 Myocardial protection was achieved using cold antegrade crystalloid cardioplegia (histidine-tryptophan-ketoglutarate solution) or cold retrograde blood cardioplegia (1:4), according to surgeons’ preferences, supplemented by topical cooling with cold saline solution. Blood in an operative field was aspirated to a cardiotomy pump sucker during CPB and to a cell saving device (autoLog Autotransfusion System; Medtronic, Minneapolis, MN) before and after CPB. Field blood was not discarded using suckers. All the sponges were wrung in a bowl, and the drainage was directed to a cellsaving device. Modified ultrahemofiltration during CPB was used to concentrate the blood in all the cases whenever feasible. After separation from CPB, heparin was neutralized with protamine sulfate (1 mg/100 U of heparin) to achieve an activated clotting time within 10% of baseline. After the surgery and during the intensive care unit stay, shed mediastinal and pleural blood
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collected in a reservoir was reinfused into the patients using a cell-saving device. After the surgery, patients were transferred to the intensive care unit and their cases were managed according to the unit protocol. Antifibrinolytic drugs, such as tranexamic acid, were used immediately after surgery in the intensive care unit. On the first postoperative day, anticoagulation was started, as indicated. After cardiac valve surgery using a mechanical valve, warfarin medication was started with a target PT/INR of 2.0 to 3.0, which requires lifelong administration. In patients with a history of atrial fibrillation or thromboembolism, PT/ INR with warfarin was maintained within a range between 2.5 and 3.5. Patients with biologic valves were advised to take warfarin for the first 3 months, which was discontinued during the follow-up period. After the coronary bypass surgery, aspirin and clopidogrel were prescribed for life-long use. Follow-Up The clinical follow-up data were collected retrospectively from the medical records of the authors’ institution or by telephone interviews. The date of the last inquiry was between January and May 2014. The mean duration of follow-up was 73.0 ⫾ 40.0 months and 63.5 ⫾ 48.7 months in the low-risk and the high-risk groups, respectively (p = 0.440); 98.7% (n = 75) of hospital survivors completed the follow-up. Statistical Analysis Descriptive statistics are described as the mean ⫾ standard deviation for continuous variables and as frequency and percentage for categoric variables. Differences between groups for the continuous variables and the categoric variables were tested using Student’s t-test and Fisher’s exact test, respectively. Results with p values o0.05 were considered statistically significant. Long-term survival and event-free survival were analyzed using the Kaplan-Meier survival method. To compare survival curves between the groups, log-rank test was used. To evaluate the predictive performance between the TRACK and EuroSCORE scoring systems, the area under receiver operating characteristic (AUROC) curve was compared between the 2 systems. The SPSS software 20.0 program (IBM Corp, Armonk, NY) was used for statistical analyses, except for the AUROC curve analysis. AUROC curve analysis was performed using MedCalc for Windows, version 15.6 (MedCalc Software, Ostend, Belgium). RESULTS
Postoperative Outcomes The operative mortality was 0% in the low-risk group and 21.1% (n = 4) in the high-risk group (p = 0.003). The main causes of operative death were right ventricle failure (n = 1), arrhythmia (n = 1), renal failure (n = 1), and sepsis (n = 1). Ten patients (17.5%) in the low-risk group and 11 patients (57.9%) in the high-risk group experienced major postoperative complications (p = 0.002). In the low-risk group, major postoperative complications (multiple counting for a patient) included new-onset left ventricular dysfunction (n = 4), newonset supraventricular arrhythmia (n = 2), systemic infection
with positive blood culture results (n = 1), renal insufficiency (n = 2), and gastrointestinal bleeding (n = 1). In the high-risk group, major postoperative complications (multiple counting for a patient) included extracorporeal membrane oxygenation support (n = 1), new-onset left ventricular dysfunction (n = 3), new-onset supraventricular arrhythmia (n = 1), resternotomy for other reasons excluding bleeding control (n = 2), sternal wound infection including mediastinitis (n = 2), systemic infection with positive blood culture results (n = 1), renal insufficiency (n = 2), renal failure requiring dialysis (n = 2), pneumonia (n = 1), operative bleeding control (n = 3), and intracranial hemorrhage (n = 1). The high-risk group (n = 4; 21.1%) experienced more postoperative bleeding-related complications than did the lowrisk group (n = 1; 1.8%) (p = 0.013). The degree of postoperative changes of hemoglobin and hematocrit level was within the acceptable range for both groups (Table 2). Postoperative hemoglobin and hematocrit levels were checked on the first postoperative day. The postoperative creatinine level (highest level for the first 3 postoperative days) as an indicator of renal injury did not demonstrate a significant difference between both groups. Long-Term Outcomes There were 5 late overall deaths during the follow-up period —4 in the low-risk group and 1 in the high-risk group (see Table 2). The main causes of late death in the low-risk group were severe brain damage after reoperation (n ¼ 1), intracranial hemorrhage (n ¼ 2), and gastrointestinal bleeding (n ¼ 1). In the high-risk group, 1 patient died as a result of acute heart failure after reoperation (second-time valve replacement) in another hospital. The late morbidities (multiple counting for a patient) included congestive heart failure (n ¼ 2), supraventricular arrhythmia (n ¼ 3), ischemic heart disease (n ¼ 2), pneumonia (n ¼ 2), reoperation (n ¼ 1), percutaneous coronary intervention (n ¼ 1), intracranial hemorrhage (n ¼ 2), and gastrointestinal bleeding (n ¼ 1) in the low-risk group and reoperation (n ¼ 1) and gastrointestinal bleeding (n ¼ 1) in the high-risk group. There were no significant differences in the actuarial rates of overall survival, late morbidity-free survival, and late bleedingrelated morbidity-free survival between both groups (Table 3). Comparison with EuroSCORE II There were no significant differences of predictive performance in operative mortality, major postoperative complications, and postoperative bleeding-related complications between the TRACK score and EuroSCORE II (Table 4). The AUC in major postoperative complications for the 2 models is represented in Fig 1. DISCUSSION
The major finding of this study was that the TRACK score might predict postoperative clinical outcomes of cardiac surgery for patients who decline blood transfusion. Also, there were no significant differences of predictive performance in operative mortality, major postoperative complications, and
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Table 2. Postoperative Data and Clinical Outcomes Low-Risk Variables
Postoperative data Postoperative Hb (g/dL)‡ Postoperative Hct (%)‡ Postoperative Cr (mg/dL)‡ Postoperative LVEF (%) Postoperative LOS (day) Difference (preop Hb – postop Hb) Difference (preop Hct – postop Hct) Difference (preop Hct – lowest Hct during CPB) Lowest Hct (%) during CPB Postoperative outcomes Operative death Postoperative complications Postoperative bleedingrelated complications Long-term outcomes Late death Late morbidity Bleeding-related morbidity
High-Risk
Group*
Group*
(n ¼ 57)
(n ¼ 19)
12.4 37.1 1.1 58.3 15.8 1.1
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
1.3 3.8 0.3 12.4 8.0 1.1
Table 4. Area Under Receiver Operating Characteristic Curve for the TRACK Score and EuroSCORE II
10.6 31.7 1.2 53.5 21.1 1.4
⫾ ⫾ ⫾ ⫾ ⫾ ⫾
p Value†
1.6 4.4 0.6 9.7 15.8 1.1
o0.001 o0.001 0.411 0.148 0.176 0.220
3.1 ⫾ 3.0
4.8 ⫾ 3.6
0.044
15.6 ⫾ 3.7
15.2 ⫾ 3.9
0.688
24.7 ⫾ 3.1
21.3 ⫾ 2.6
o0.001
0 (0%) 10 (17.5%) 1 (1.8%)
4 (21.1%) 11 (57.9%) 4 (21.1%)
0.003 0.002 0.013
4 (7.0%) 13 (22.8%) 3 (5.3%)
1 (6.7%) 2 (13.3%) 1 (6.7%)
0.893 0.658 0.708
NOTE: Data are presented as mean ⫾ standard deviation for continuous variables and as number and percentage for categoric variables. Abbreviations: CPB, cardiopulmonary bypass; Cr, creatinine; Hb, hemoglobin; Hct, hematocrit; LVEF, left ventricular ejection fraction; LOS, length of stay. *Low-risk group includes patients with a TRACK score of less than 13; high-risk group includes patients with a TRACK score of 13 or more. †Student’s t-test for postoperative data, Fisher’s exact test for postoperative outcomes, and log-rank test for long-term outcomes. ‡Lowest hemoglobin and hematocrit levels at the first postoperative day; highest creatinine levels for the first 3 postoperative days.
postoperative bleeding-related complications between the TRACK score and EuroSCORE II. To predict the rate of transfusion in cardiac surgery, several scoring models have been proposed.7–13 The TRACK scoring model offers a simple method to predict the transfusion rate in cardiac surgery.11 This simple transfusion risk model that is based on 5 preoperative variables had a similar or better accuracy and validation in quantifying the transfusion rate during cardiac surgery than the other models. The 5 predictors
Operative mortality TRACK score EuroSCORE II Major postoperative complications TRACK score EuroSCORE II Postoperative bleeding-related complications TRACK score EuroSCORE II
AUROC
95% CI
0.877 0.774
0.781-0.941 0.664-0.862
0.695 0.700
0.579-0.795 0.584-0.799
p Value
0.4169
0.9547
1.0000 0.728 0.728
0.614-0.824 0.614-0.824
Abbreviations: AUROC, area under receiver operating characteristic; CI, confidence interval; EuroSCORE, European System for Cardiac Operative Risk Evaluation; TRACK, Transfusion Risk and Clinical Knowledge.
of age, weight, sex, complex surgery, and hematocrit level constitute the TRACK score. This score has a distribution range between 0 and 32. The authors’ study population was divided into the following 2 groups according to their TRACK score: patients with a TRACK score of less than 13 (low-risk group) and those with a TRACK score of 13 (high-risk group). A TRACK score of 13 corresponded to a transfusion risk of 60% in the development series.11 In the Transfusion Risk Understanding Scoring Tool model, a total score of 3 was interpreted as a high chance of receiving blood transfusion and corresponded to the predictive rate of transfusion between 0.60 and 0.79.9 Also, the score of 4 to 8 was interpreted as very high risk of exposure to transfusion (0.80-1.00). The Al-Khabori et al13 model showed that the probabilities of transfusion of 42%, 63%, and 91% were equivalent to a score of less than 2, between 2 and 5, and more than 5, respectively. Those authors believed that the value of risk probability of 60% seemed to be a cutoff point for grouping. Of course, the 2 groups in this study had significant differences in 5 preoperative variables: age (p ¼ 0.005), weight (p o 0.001), sex (p ¼ 0.003), hematocrit level (p o 0.001), and complex surgery (p o 0.001) (see Table 1). The grouping of the patients in this study was considered to be appropriate. Interestingly, Ranucci et al11 excluded Jehovah’s Witness patients and surgery without CPB in their study population of the TRACK scoring model. However, the entire population of this study was comprised of Jehovah’s Witnesses, and a quarter of the population underwent cardiac surgeries without
Table 3. Long-Term Clinical Outcomes Low-Risk Group* (n ¼ 57) Variables
Overall survival Morbidity-free survival Bleeding-related morbidity-free survival
1 year
5 years
High-Risk Group* (n ¼ 19) 10 years
1 year
5 years
10 years
98.2% ⫾ 1.8% 98.2% ⫾ 1.8% 91.9% ⫾ 3.9% 92.3% ⫾ 7.4% 92.3% ⫾ 7.4% 92.3% ⫾ 7.4% 90.6% ⫾ 4.0% 79.7% ⫾ 6.3% 64.6% ⫾ 8.6% 92.3% ⫾ 7.4% 84.6% ⫾ 10.0% 84.6% ⫾ 10.0% 98.1% ⫾ 1.9% 93.0% ⫾ 4.0% 93.0% ⫾ 4.0% 100.0% ⫾ 0.0% 91.7% ⫾ 8.0% 91.7% ⫾ 8.0%
p Value†
0.893 0.658 0.708
*Low-risk group includes patients with a TRACK score of less than 13, and high-risk group includes patients with a TRACK score of 13 or more. †Log-rank test for long-term clinical outcomes.
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TRACK SCORE AND CARDIAC SURGERY TRANSFUSION
postoperative hospital stay in this study demonstrated a tendency to be longer in the high-risk group (21.1 days) than in the low-risk group (15.8 days). Unfortunately, intensive care unit length of stay was not included in this study. This variable will be included in the next study with a larger series of patients. In the low-risk group, only 2 patients experienced renal insufficiency (2/57; 3.5%). In the high-risk group, 2 patients experienced renal insufficiency and 2 patients required dialysis for renal failure (4/19; 21.1%). Similarly to use of the EuroSCORE II, practitioners can use the TRACK score to predict the perioperative clinical outcomes after cardiac surgery in patients refusing transfusions. Study Limitations Fig 1. Area under receiver operating characteristic curve in major postoperative complications for the TRACK score and EuroSCORE II.
CPB (see Table 1). Because the TRACK score serves as a predictive value for patients undergoing transfusion, this score may be applied to predict postoperative outcomes for patients who do not undergo transfusion. The lowest hematocrit level during CPB was significantly less in the high-risk group than in the low-risk group (see Table 1). This difference might be due to the lower preoperative hematocrit level in the high-risk group than that in the low-risk group. Loor et al20 recently reported that preoperative anemia is the most significant risk factor for a low nadir hematocrit level during CPB. In this study, the high-risk group with a lower nadir hematocrit level during CPB (21.3%) experienced worse clinical outcomes after cardiac surgeries than did the low-risk group (24.7%; p o 0.001). The lowest hematocrit level during CPB was believed to be strongly associated with adverse postoperative clinical outcomes in other studies.20–25 The lowest hematocrit value less than 22% significantly increased the incidence of stroke, myocardial infarction, low cardiac output, prolonged ventilation, pulmonary edema, reoperation due to bleeding, and multiorgan failure.21 Ranucci et al22 also suggested that the lowest hematocrit value during CPB was an independent risk factor for postoperative renal failure. In their study, the hematocrit cutoff value for renal failure was 23%. Interestingly, these findings were similar to the data presented in this study (21.3% versus 24.7%). The operative mortality was 0% in the low-risk group and 21.1% (n ¼ 4) in the high-risk group (p ¼ 0.003). In addition, 5 late overall deaths occurred during the follow-up period: 4 in the low-risk group and 1 in the high-risk group (p ¼ 0.893). In this study, patients with a higher TRACK score had higher operative mortality but not long-term mortality. The length of
This study had several limitations that are inherent in retrospective reviews in a single medical institution. The long-term clinical outcomes of this study had low statistical power due to the low number of events. However, the authors could obtain meaningful results with respect to postoperative outcomes by performing statistical analysis. Unfortunately, the authors could not determine whether blood transfusion in patients in the high-risk group would have produced better clinical results. However, the authors found evidence of severe anemia in patients with accompanying mortality or morbidity who declined blood transfusion even in adverse situations. Recently, some noteworthy studies about the balance between anemia and blood transfusion have been published.26,27 Although blood transfusion is associated with increased morbidity risk, anemia also is a significant risk factor for adverse outcomes. Loor et al20 mentioned that it is unclear whether tolerating the anemia would be riskier than treating it with a blood transfusion once perioperative anemia has occurred. Indeed, this situation seems to be like 2 sides of the same coin. CONCLUSION
The most noticeable finding of this study was that the TRACK score might predict postoperative clinical outcomes of cardiac surgery in a specific population such as Jehovah’s Witnesses refusing blood transfusion. For the first time, this study identified the TRACK score as a predictor of clinical outcomes in cardiac surgery for patients who do not undergo transfusion. In addition, the TRACK score had predictive performance in operative mortality, major postoperative complications, and postoperative bleeding-related complications compared with EuroSCORE II. However, further investigations with a larger series of patients are required to draw more powerful conclusions on the predictive power of the TRACK score in terms of postoperative outcomes.
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