Although mortality rates for patients undergoing isolated coronary-artery bypass grafting (CABG) continue to decline, postoperative neurologic morbidity remains a concern [
This was a cohort study using data from the ACS NSQIP database. Details of the ACS NSQIP (
Patients under the age of 16 years (data collected after the year 2008 was for patients over 18 years). Cases listed on the CPT Code Exclusion List on the website ( Trauma cases—specifically: a patient who is admitted to the hospital with acute trauma and has surgery(s) for that trauma will be excluded. Any operation performed after the patient has been discharged from the trauma stay will be included. Transplant cases—specifically: a patient who is admitted to the hospital for a transplant and has a transplant procedure and any additional surgical procedure during the transplant hospitalization will be excluded. Any operation performed after the patient has been discharged from the transplant stay will be included. American Society of Anesthesiologists score 6 (brain-death organ donors). Concurrent case—an additional operative procedure performed by a different surgical team under the same anesthetic (e.g., coronary artery bypass graft procedure on a patient who is also undergoing a carotid endarterectomy). An assessment is not required on the concurrent procedure; however, this procedure would be reported as “concurrent” in the operative section for the assessed case.
To ensure a diverse surgical case mix, also excluded (at each center) are the following. More than 3 inguinal herniorrhaphies in an 8-day period. More than 3 breast lumpectomies in an 8-day period. More than 3 laparoscopic cholecystectomies in an 8-day period. If the site is collecting urology cases, more than 3 transurethral resection of the prostate and/or transurethral resection of bladder tumor in an 8-day period.
It is a validated outcomes registry designed to provide feedback to member hospitals on 30-day risk-adjusted surgical mortality and morbidity [
For this study, the available ACS NSQIP participant use files of the years 2008 (271,368 patients from 211 sites) and 2009 (336,190 patients from 237 sites) were retrieved for major surgeries performed within various surgical subspecialties at participating ACS NSQIP medical centers in the US, Canada, Lebanon, and UAE. We identified all isolated primary CABG cases using the Current Procedural Terminology (CPT) codes: 33510–33514, 33516–33519, 33521–33523, 33530, and 33533–33536. A total of 2313 patients were identified and included in this study. In accordance with the American University of Beirut’s guidelines (which follow the US Code of Federal Regulations for the Protection of Human Subjects), institutional review board approval was not needed or sought for our analysis because data were collected as part of a quality assurance activity.
The ACS NSQIP registers data on stroke occurrence within 30-days of the index operation, which is defined as a focal brain dysfunction lasting ≥24 hours from a vascular cause. This definition of stroke encompasses intracranial hemorrhage, but we considered this outcome as a surrogate of ischemic stroke because hemorrhagic strokes make up only 1% of perioperative strokes [
Retrieved preoperative hematocrit concentration reflected the last hematocrit measurement prior to the index operation. Some 99.9% of the hematocrit levels were obtained within eight weeks of the index surgery, 99.1% were obtained within four weeks and 96.6% were obtained within two weeks.
Descriptive statistics are presented as means (standard deviation (SD)), medians (interquartile range (IQR)), or percentages. The primary study outcome measure was stroke within 30 days of surgery. We used multivariate logistic regression analysis to retrieve effect estimates (odds ratios (OR) and 95% confidence intervals (CI)) upon adjusting the association between preoperative hematocrit concentration and the outcome of stroke for potential confounders. Models were built by adjusting (Enter method) the determinant variable (preoperative hematocrit concentration) to a priori defined potential confounders of clinical relevance (risk factors that may cause both preoperative hematocrit concentration alterations as well as stroke). Two levels of adjustment were used, Model 1 (
We carried out the data management and analyses using the SAS software version 9.1 (SAS Institute Inc., Cary, NC, USA).
A total of 2,313 patients undergoing isolated CABG were included in this analysis. The mean age of the study cohort was 65.9 years (SD: 10.7, range: 25–90) with 1,703 (73.6%) patients being men. The mean preoperative hematocrit concentration was 38.8% (SD: 5.1, range: 12.4–54.9). Forty-three patients developed stroke within 30 days following CABG, corresponding to a 30-day cumulative incidence of 1.9% (95% CI: 1.4–2.5). The median time to development of stroke was 4 days (IQR: 1–7 days, min: same day, max: 29 days), with most patients (74.4%, 95% CI: 59.7–85.0) developing stroke within the first 6 days after surgery (Figure
Patients’ characteristics.
Parameter | No stroke |
Stroke |
---|---|---|
Preoperative hematocrit concentration, mean (SD) |
|
|
Age in years, mean (SD) | 65.9 (10.7) | 69.3 (9.2) |
Male, |
1,673 (73.7) | 30 (69.8) |
White race, |
1,866 (82.2) | 37 (86.0) |
Body mass index ≥ 30 kg/m2, |
974 (42.9) | 15 (34.9) |
Diabetes, |
831 (36.6) | 19 (44.2) |
Hypertension, |
1,914 (84.3) | 39 (90.7) |
Congestive heart failure, |
255 (11.2) | 8 (18.6) |
Peripheral vascular disease, |
119 (5.2) | 2 (4.7) |
Currently on dialysis, |
56 (2.5) | 4 (9.3) |
Current Smoker, |
554 (24.2) | 15 (34.9) |
Chronic obstructive pulmonary disease, |
237 (10.4) | 9 (20.9) |
History of transient ischemic attack, |
138 (6.1) | 4 (9.3) |
History of stroke with neurologic deficit, |
100 (4.4) | 4 (9.3) |
History of stroke without neurologic deficit, |
91 (4.0) | 1 (2.3) |
Bleeding disorder, |
366 (16.1) | 8 (18.6) |
Disseminated cancer, |
3 (0.1) | 0 (0.0) |
Tumor involving central nervous system, |
1 (0.0) | 0 (0.0) |
(a) Number of patients developing stroke on each day in the 30-day observation period following surgery. (b) Instantaneous stroke incidence per day in the exposed population.
In an unadjusted analysis, each drop of 1% in preoperative hematocrit concentration (continuous variable) was associated with a 1.09 increased odds of 30-day postoperative stroke (95% CI: 1.04–1.15). The effect was steeper and more certain in men (OR: 1.11, 95% CI: 1.04–1.18) than women (OR: 1.05, 95% CI: 0.93–1.17). After adjustment for potential confounders, the effect estimates dropped minimally (
Effects of preoperative hematocrit concentration on 30-day postoperative stroke.
Variable | Odds of stroke | ||
---|---|---|---|
ORunadj (95% CI) | ORadj-1 (95% CI) | ORadj-2 (95% CI) | |
Preoperative hematocrit concentration |
|||
All patients ( |
1.09 (1.04–1.15) | 1.09 (1.03–1.15) | 1.07 (1.01–1.13) |
Men ( |
1.11 (1.04–1.18) | 1.10 (1.04–1.17) | 1.08 (1.01–1.16) |
Women ( |
1.05 (0.93–1.17) | 1.04 (0.92–1.17) | 1.02 (0.91–1.16) |
Preoperative hematocrit concentration |
|||
All patients <37% versus ≥37% | 1.92 (1.05–3.51) | 1.76 (0.93–3.35) | 1.49 (0.76–2.91) |
Men <37% versus ≥37% | 3.07 (1.49–6.34) | 2.80 (1.34–5.88) | 2.39 (1.08–5.26) |
Women <38% versus ≥38% | 2.88 (0.63–13.10) | 2.71 (0.59–12.42) | 2.52 (0.53–11.98) |
ORunadj: Unadjusted odds ratio.
ORadj-1: Adjusted odds ratio according to Model 1. Adjusted for age, sex, and race.
ORadj-2: Adjusted odds ratio according to Model 2. Adjusted for all variables in Table
The predicted probability of stroke for descending preoperative hematocrit concentration values in a clinically relevant range is illustrated in Figure
Predicted probability of 30-day postoperative stroke as a function of preoperative hematocrit concentration in (a) all patients and (b) men and women.
A total of 1,779 (76.9%, 95% CI: 75.2–78.6) patients received intraoperative transfusions (55.1% received 1 or 2 packed red blood cell (pRBC) units and 21.8% received 3 or more pRBC units). The odds of 30-day stroke were more notably increased in patients receiving 3 or more pRBC units (OR: 2.69, 95% CI: 1.04–7.00) than patients receiving 1 or 2 pRBC units (OR: 1.55, 95% CI: 0.62–3.84) when compared to patients who did not receive intraoperative transfusions. The mean preoperative hematocrit concentration was lower in patients who received 3 or more pRBC units intraoperatively than those who did not (36.1% versus 39.5%, mean difference: 3.4%, 95% CI: 2.9–3.9) (Figure
(a) Bar chart showing mean preoperative hematocrit concentration according to the number of pRBC units transfused intraoperatively, whiskers present standard deviation. (b) Predicted probability of receiving 3 or more pRBC units intraoperatively as a function of preoperative hematocrit concentration. pRBC = packed red blood cell.
The association between preoperative hematocrit concentration (continuous variable) and 30-day postoperative stroke was observed in both patients who received (
The incidence of stroke in our study, relying on data from isolated CABG procedures performed in 2008 and 2009, was 1.9%, which is in close agreement to recent reports [
We identified an association between descending preoperative hematocrit concentration values and an increased risk of stroke in the 30-day period following isolated CABG. The increased risk of stroke exceeded 2% in patients with a preoperative hematocrit concentration <37%. Moreover, the increased postoperative stroke risk attributed to declining preoperative hematocrit concentration values was more notable in men than women and was independent of yet augmented by the excessive use of intraoperative pRBC transfusions.
Although numerous studies identified the effects of perioperative hematocrit alterations and pRBC transfusions on morbidity and mortality in cardiac surgery, very few reports evaluated the outcome of stroke in specific. An association between hemodilutional anemia during cardiopulmonary bypass (nadir intraoperative hematocrit levels) and the incidence of stroke was previously demonstrated [
Previous studies suggest that intraoperative hypotension and subsequent hypoperfusion may be a source of neurologic injury in patients undergoing CABG [
Our study carries several limitations. The ACS NSQIP database does not record intraoperative nadir hematocrit or immediate postoperative hematocrit. Thus, we could not evaluate the association between these variables and a stroke outcome. Moreover, the database does not record data on cardiovascular drug use. The ACS NSQIP database also does not document the means by which stroke was diagnosed. The use of magnetic resonance imaging rather than computed tomography may result in higher rates of radiographic infarct. Although the types of imaging techniques used may have affected the observed incidence of stroke in our study, an association between the use of a certain imaging technique and the evaluated risk factors is less likely. Another potential limitation of this study was that we were unable to control for hospital effects owing to the absence of hospital identifiers in our data. There may have been variability in hospital quality or variability in surgical strategy which may have potentially confounded the association between risk factors and outcome. Finally, the possibility of residual confounding is always present in observational studies.
Current efforts continue to focus on reducing the embolic burden during CABG, being considered as the primary mechanism through which neurologic injury occurs. Our study shows that other mechanisms of injury could be involved. An increasing number of surgical centers now use preoperative screening to identify patients who have an increased risk for stroke, and to modify surgical conditions according to the results of such screening. This approach should ideally become standard of care.
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and the hospitals participating in the ACS NSQIP are the source of data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.
K. M. Musallam received consultancy fees and travel support from Vifor Pharma Ltd. F. R. Jamali received research funding from Vifor Pharma Ltd. TR department received consultancy fees and research funding from Vifor Pharma Ltd. DRS department received grant support from Vifor SA, Villars-sur-Glâne. D. R. Spahn received honoraria or travel support for consulting or lecturing from the following companies: Galenica AG (including Vifor SA, Villars-sur-Glâne), Janssen-Cilag AG, Janssen-Cilag EMEA, ratiopharm Arzneimittel Vertriebs-GmbH, Roche Pharma (Schweiz) AG, Vifor Pharma Deutschland GmbH, Vifor Pharma Österreich GmbH, Vifor (International) AG. F. R. Rosendaal, K. Khavandi, I. Barakat, B. Demoss, L. A. Lotta, F. Peyvandi, P. M. Sfeir have no relevant conflicts of interest to disclose.
Study conception and design: K. M. Musallam, F. R. Jamali, F. R. Rosendaal and P. M. Sfeir. Statistical analysis: K. M. Musallam. Review and interpretation of data: K. M. Musallam, F. R. Jamali, F. R. Rosendaal, T. Richards, D. R. Spahn, K. Khavandi, I. Barakat, B. Demoss, L. A. Lotta, F. Peyvandi, P. M. Sfeir. Drafting of the manuscript: K. M. Musallam, F. R. Jamali and P. M. Sfeir. Critical revision of the manuscript for important intellectual content: F. R. Rosendaal, T. Richards, D. R. Spahn, K. Khavandi, I. Barakat, B. Demoss, L. A. Lotta, F. Peyvandi. All authors gave final approval of the paper for submission.