Preoperative Beta-Blocker in Ventricular Dysfunction Patients: Need a More Granular Quality Metric.
preprint
OA: closed
Abstract
Background: The use of preoperative beta-blockers has been accepted as a quality standard for patients undergoing coronary artery bypass graft (CABG) surgery. However, conflicting results from recent studies have raised questions concerning the effectiveness of this quality metric. We sought to determine the influence of preoperative beta-blocker administration before CABG in patients with left ventricular dysfunction. Methods: The authors analyzed all cases of isolated CABGs in patients with left ventricular ejection fraction less than 50%, performed between 2012 January and 2017 June, at 94 centres recorded in the China Heart Failure Surgery Registry database. In addition to the use of multivariate regression models, a 1 to 1 propensity scores matched analysis was performed. Results: Of 6,116 eligible patients, 61.7% received a preoperative beta-blocker. No difference in operative mortality was found between two cohorts (3.7% for the non-beta-blockers group vs 3.0% for the beta-blocker group; adjusted odds ratio [OR], 0.82 [95% CI, 0.58-1.15]). Few differences in the incidence of other postoperative clinical end points were observed as a function of preoperative beta-blockers except in stroke (0.7% for the non-beta-blocker group vs 0.3 for the beta-blocker group; adjusted OR, 0.39 [95% CI, 0.16-0.96]). Results of propensity-matched analyses were broadly consistent. Conclusions: In this study, the administration of beta-blockers before CABG was not associated with improved operative mortality and complications except the incidence of postoperative stroke in patients with left ventricular dysfunction. A more granular quality metric which would guide the use of beta-blockers should be developed.
Full text
115,725 characters
· extracted from
preprint-html
· click to expand
Preoperative Beta-Blocker in Ventricular Dysfunction Patients: Need a More Granular Quality Metric. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Preoperative Beta-Blocker in Ventricular Dysfunction Patients: Need a More Granular Quality Metric. Hanwei Tang, Kai Chen, Jianfeng Hou, Xiaohong Huang, Sheng Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-147397/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2021 Read the published version in BMC Cardiovascular Disorders → Version 1 posted 9 You are reading this latest preprint version Abstract Background The use of preoperative beta-blockers has been accepted as a quality standard for patients undergoing coronary artery bypass graft (CABG) surgery. However, conflicting results from recent studies have raised questions concerning the effectiveness of this quality metric. We sought to determine the influence of preoperative beta-blocker administration before CABG in patients with left ventricular dysfunction. Methods The authors analyzed all cases of isolated CABGs in patients with left ventricular ejection fraction less than 50%, performed between 2012 January and 2017 June, at 94 centres recorded in the China Heart Failure Surgery Registry database. In addition to the use of multivariate regression models, a 1 to 1 propensity scores matched analysis was performed. Results Of 6,116 eligible patients, 61.7% received a preoperative beta-blocker. No difference in operative mortality was found between two cohorts (3.7% for the non-beta-blockers group vs 3.0% for the beta-blocker group; adjusted odds ratio [OR], 0.82 [95% CI, 0.58-1.15]). Few differences in the incidence of other postoperative clinical end points were observed as a function of preoperative beta-blockers except in stroke (0.7% for the non-beta-blocker group vs 0.3 for the beta-blocker group; adjusted OR, 0.39 [95% CI, 0.16-0.96]). Results of propensity-matched analyses were broadly consistent. Conclusions In this study, the administration of beta-blockers before CABG was not associated with improved operative mortality and complications except the incidence of postoperative stroke in patients with left ventricular dysfunction. A more granular quality metric which would guide the use of beta-blockers should be developed. Cardiac & Cardiovascular Systems Cardiothoracic Surgery Beta-blocker quality metric coronary artery bypass grafting Figures Figure 1 Figure 2 Background Coronary artery bypass grafting is an essential therapeutic approach to reduce mortality and morbidity in patients with complex, multivessel coronary artery disease (CAD).[ 1 , 2 ] The perioperative medical treatment is key in the optimal success of the cardiac surgery. In the late 1990s, a large retrospective analysis demonstrated benefits of preoperative beta-blockers usage.[ 3 ] Our group previously reported that postoperative beta-blocker therapy was associated a lower risk of long-term mortality and adverse cardiovascular events.[ 4 ] Since 2007, the use of preoperative beta-blockers has been used as a quality standard for patients undergoing CABG.[ 5 ] However, controversies still exist in the literature regarding the effectiveness of beta-blockers for patients undergoing CABG.[ 6 – 9 ] These studies failed to show perioperative mortality advantage in patients receiving beta-blockers before surgery. A recently meta-analysis suggests that the use of preoperative beta-blockers did not reduce either operative mortality or the incidence of postoperative complications.[ 10 ] Therefore, the preoperative use of beta-blockers as a quality indicator has been questioned. To date, the efficacy and safety of beta-blocker use during the preoperative period of CABG have not been adequately evaluated in patients with left ventricular dysfunction. Accurately identifying and utilizing measures of performance and quality is essential. Prospective randomized clinical trials to investigate the effect of preoperative beta-blocker use on cardiovascular patients is difficult and there are concerns that the design of such trials would entail an unacceptable risk for the withdrawal of beta-blockers in patients already taking this medication can lead to substantial morbidity and even mortality.[ 7 ] As large-scale registries may overcome these difficulties to support clinical decisions, the currents study aims to review a large national database to assessed whether preoperative administration of beta-blockers was associated with improved early clinical outcomes after CABG in patients with left ventricular dysfunction. Methods Study design The China Heart Failure Surgery Registry (China-HFSR) was led by Fuwai Hospital and other representative cardiac centres in different regions around China. In total, 94 centres with annual surgery volumes > 100 were included as participants in the study. We included patients ≥ 17 years old who underwent CABG from January 2012 to June 2017 with documented LVEF < 50%. Patients were excluded if they underwent concomitant valve or other surgeries or non-elective surgeries. We also excluded patients who have preoperative intra-aortic balloon pump insertion, cardiogenic shock and third degree heart block. (Fig. 1 ) These patients were then stratified according to preoperative beta-blocker administration. All CABG procedures represented standard surgical approaches to surgical myocardial revascularization with and without the use of cardiopulmonary bypass support. This study was approved by the institutional review board at Fuwai Hospital (approval number 887, April 25th, 2017) and carried out in accordance with relevant guidelines and regulations. The informed consent was provided by participants. Data collection All data were collected at the local sites from the medical records. The requirements for data collection and the definitions of variables were clearly identified. Standardized electronic case report forms were completed at the local sites and then submitted online to the data processing centre. All data were into the database separately by two trained technicians. Two separate reviewers from the data processing centre randomly selected and assessed 5–10% of each of the participating centres’ medical records during annual on-site audits. We compared the data in the database and the original medical records. A committee composed of physicians and surgeons determined the correct final value when there was a disagreement. In all patients included in China-HFSR database, 90 (1.5%) patients were without listed height, 74 (1.2%) without listed weight and 1 without data regarding smoking history. Considering the fact that they only accounted for a very small proportion of our patients, we imputed missing continuous variables (height and weight) with different mean values for the sexes. The missing categorical variable (smoking history) was imputed with negative values. So that patients who might have experienced the end point (in-hospital death) would not be excluded from analysis simply for 1 or 2 missing variables among the many examined. Clinical data The preoperative variables included age, gender, body mass index, smoking history, New York Heart Association (NYNH) classification, Canadian Cardiovascular Society (CCS) classification, diabetes mellitus (DM), hypertension, hyperlipidemia, renal failure, chronic obstructive pulmonary disease (COPD), cerebrovascular accident, carotid disease and other peripheral arterial disease, preoperative atrial fibrillation, previous myocardial infarction (MI), percutaneous transluminal coronary angioplasty (PTCA) history, No. of diseased vessels, Left main CAD, LVEF, preoperative creatinine and prior cardiovascular surgeries. The major postoperative complications included re-intubation, MI, mediastinal infection, stroke, renal failure, multiple organ dysfunction syndrome, postoperative atrial fibrillation and reoperation for bleeding. MI was counted as a complication if it newly occurred postoperatively and was defined as any one of the following: MI documented in the medical record with an elevation of cardiac troponin values with at least one value above the 10 times 99th percentile upper reference limit or electrocardiograph documented ST-segment elevation in evolution, Q waves 0.03 seconds in width and/or one-third or greater of the total QRS complex in 2 or more contiguous leads, or new left bundle branch block.[ 11 ] Mediastinal infection was defined according to the expert consensus.[ 12 ] Stroke was defined as a central neurological deficit persisting > 24 hours (i.e., extremity weakness or loss of motion, loss of consciousness, loss of speech, visual field cuts). Renal failure was defined as an increase in serum creatinine level to > 4 mg/dL, 3× the most recent preoperative creatinine level, or a new postoperative need for dialysis. Reoperation for bleeding was defined as chest tube drainage ≥ 200 mL/h for at least 3 hours requiring surgical intervention. Statistical analysis Continuous variables are expressed as either mean ± standard deviation or medians and quartiles depending upon overall variable distribution. Categorical variables are presented as frequencies and percentages. We performed a t-test for normally distributed continuous variables; otherwise, the Mann-Whitney U test or Kruskal-Wallis H test was used. Chi square tests or Fisher’s exact tests were used for categorical variables. Cochran-Armitage trend test were used to examine the trend of beta-blocker use during the study period. We used the following 2 techniques to adjust for selection bias when comparing outcomes of the beta-blocker vs non-beta-blocker groups: multiple logistic regression modelling and propensity matching. For the regression-based analyses, the association between preoperative beta-blocker use and each clinical end point were adjusted for baseline patient risk by inclusion of the following validated and widely accepted measures of patient-level covariates: age, body mass index, sex, smoking history, diabetes mellitus, hypertension, hyperlipidemia, chronic obstructive pulmonary disease, cerebrovascular accident, previous MI, PTCA history, LVEF, preoperative creatinine, CCS classification, NYHA classification, No. of diseased vessels, Left main CAD, preoperative atrial fibrillation and prior cardiovascular surgery history. Each logistic model also included year of surgery and a set of fixed-effect hospital-specific intercept variables.[ 13 ] Model results are reported as odds ratios (OR) with a 95% confidence interval. The second method of adjusting for selection bias involved matching patients with similar estimated probability of receiving beta-blockers (propensity score). The propensity score was calculated by a multivariable logistic regression model which was developed using the same covariates listed above for the regression-based analyses. Then we matched patients in a 1:1 fashion without replacement.[ 14 ] ORs with 95% CIs comparing the frequency of each end point for patients receiving vs not receiving beta-blockers were estimated using univariable logistic regression. Additional analysis were performed to examine whether the association between beta-blockers and mortality differed across prespecified subgroups based on age, sex, ejection fraction, diabetes mellitus, hypertension and chronic lung disease. Subgroup-specific ORs were estimated and displayed with 95% CIs. All reported P values are 2 sided, and values of P < 0.05 were considered to indicate statistical significance. All statistical analysis was performed using SPSS version 22.0 (IBM Corp., Armonk, NY). Results Patients Characteristics Of 6,116 patients who met study inclusion criteria, 61.7% of patients received a preoperative beta-blocker. During the study period, no significant trend was found in the beta-blocker use (Figure S1, P = 0.163). According to the preoperative profiles, women accounted for 16.2% of the patients, and 34.0% of the overall patient population had diabetes mellitus; the mean patient age was 61.3 ± 9.2 years. Small differences in baseline characteristics existed between study groups. Patients receiving beta-blockers were more likely to have DM, hypertension prior PTCA history and left main CAD while hyperlipidemia, COPD, Carotid disease and triple vessel disease were more common in these patients (Table 1 ). Table 1 Baseline Demographic and Clinical Characteristics in Overall Cohort Beta-blocker Use Groups Variable All Patients (n = 6116) No (n = 2343) Yes (n = 3773) P Age, mean (SD), y 61.3 (9.2) 61.4 (9.3) 61.3 (9.1) 0.921 Female, n (%) 988 (16.2) 402 (17.2) 586 (15.5) 0.093 BMI, mean (SD) 24.7 (3.2) 24.7 (3.1) 24.8 (3.2) 0.445 Smoking history, n (%) 3388 (55.4) 1304 (55.7) 2084 (55.2) 0.748 Diabetes mellitus, n (%) 2079 (34.0) 757 (32.3) 1322 (35.0) 0.028 Hypertension, n (%) 3353 (54.8) 1237 (52.8) 2116 (56.1) 0.012 Hyperlipemia, n (%) 1970 (32.2) 816 (34.8) 1154 (30.6) 0.001 Chronic renal failure, n (%) 113 (1.8) 37 (1.6) 76 (2.0) 0.219 COPD, n (%) 94 (1.5) 46 (2.0) 48 (1.3) 0.033 Peripheral artery disease, n (%) 260 (4.3) 103 (4.4) 157 (4.2) 0.658 Carotid disease, n (%) 1000 (16.4) 441 (18.8) 559 (14.8) < 0.001 Cerebrovascular accident, n (%) 527 (8.6) 191 (8.2) 336 (8.9) 0.307 Creatinine, median (quartile), umol/dL 82.0 (70.0,96.6) 81.7 (69.0,95.9) 44.0 (40,46) 0.132 Left main CAD, n (%) 1625 (26.6) 589 (25.1) 1036 (27.5) 0.046 Triple vessel disease, n (%) 4218 (69.0) 2275 (73.5) 1443 (61.6) < 0.001 Previous MI, n (%) 2561 (41.9) 952 (40.6) 1609 (42.6) 0.121 PTCA history, n (%) 760 (12.4) 255 (10.9) 505 (13.4) 0.004 CCS class < 0.001 NA, n (%) 1181 (19.3) 508 (21.7) 673 (17.8) I, n (%) 886 (14.5) 348 (14.9) 216 (5.7) II, n (%) 2086 (34.1) 666 (28.4) 926 (24.5) III, n (%) 1606 (26.3) 680 (29.0) 1420 (37.5) IV, n (%) 357 (5.8) 141 (6.0) 538 (14.3) LVEF, Mean (SD), % 42.3 (5.2) 42.3 (5.1) 42.3 (5.3) 0.484 NYHA class < 0.001 I, n (%) 865 (14.1) 257 (11.0) 608 (16.1) II, n (%) 2252 (36.8) 864 (36.9) 1388 (36.8) III, n (%) 2694 (44.0) 1091 (46.6) 1603 (42.5) IV, n (%) 305 (5.0) 131 (5.6) 174 (4.6) Atrial fibrillation, n (%) 123 (2.0) 44 (1.9) 79 (2.1) 0.559 Prior cardiovascular surgery, n (%) 69 (1.1) 23 (1.0) 46 (1.2) 0.393 STS PROM, Median [25th, 75th percentile] (%) 3.0 [2.1, 4.4] 2.9 [2.0, 4.3] 3.1 [2.2, 4.6] < 0.001 BMI indicate body mass index, CAD, coronary vascular disease; CCS, Canadian Cardiovascular Society; COPD, chronic obstructive pulmonary disease; LFEF, left ventricular ejection fraction; MI, myocardial infarction; NA, not available; NYHA, New York Heart Association; PROM, predicted risk of mortality; PTCA, percutaneous transluminal coronary angioplasty; SD, standard deviation; STS, Society of Thoracic Surgeons. Operative Outcomes Table 2 summarizes the outcomes from the unmatched groups. No difference in mortality was found between two cohorts (3.7% for the non-beta-blockers group vs 3.0% for the beta-blocker group; adjusted OR, 0.82 [95% CI, 0.58–1.15]). Few differences in the incidence of other postoperative clinical end points were observed as a function of preoperative beta-blockers except in the incidence of stroke (0.7% for the non-beta-blocker group vs 0.3 for the beta-blocker group; adjusted OR, 0.39 [95% CI, 0.16–0.96]). Table 2 Number of End Point Events and Covariate-Adjusted ORs in Overall Cohort End Point No. (%) of Events by Group No beta-blocker (n = 2343) Beta-blocker (n = 3773) OR (95% CI) P Mortality 87 (3.7) 113 (3.0) 0.82 (0.58–1.15) 0.256 Re-intubation 60 (2.6) 91 (2.4) 1.03 (0.69–1.54) 0.869 Postoperative MI 24 (1.0) 24 (0.6) 0.95 (0.44–2.07) 0.894 Mediastinal infection 19 (0.8) 28 (0.7) 0.92 (0.45–1.89) 0.825 Postoperative AF 634 (27.1) 1089 (28.9) 1.07 (0.94–1.21) 0.135 Postoperative stroke 17 (0.7) 12 (0.3) 0.37 (0.16–0.96) 0.040 Postoperative renal failure 43 (1.8) 62 (1.6) 0.85 (0.53–1.36) 0.494 MODS 43 (1.8) 62 (1.6) 0.99 (0.56–1.75) 0.975 Re-operation 37 (1.6) 90 (2.4) 1.31 (0.85–2.02) 0.228 AF indicates atrial fibrillation; CI, confidence interval; MI, myocardial infarction; MODS, multiple organ dysfunction syndrome; OR, odds ratio. After propensity matching, comparable groups of 2,430 each were created (Table S1. FigureS2). Outcomes for propensity-matched patients receiving vs not receiving beta-blockers are displayed in Table 3 . Operative mortality was similar for the 2 groups (3.7% vs 3.0% for the beta-blocker vs non-beta-blocker groups; OR, 0.85 [95% CI, 0.62–1.16]). Less frequency of stroke was found in patients receiving preoperative beta-blockers (0.3%) compared with non-beta-blockers (0.7%; OR, 0.41 [95% CI, 0.17–0.99]). Of other clinical end points, no significant differences were found. Table 3 Number of End Point Events and ORs in Propensity-Matched Cohort End Point No. (%) of Events by Group No beta-blocker (n = 2340) Beta-blocker (n = 2340) OR (95% CI) P Mortality 87 (3.7) 74 (3.2) 0.85 (0.62–1.16) 0.298 Re-intubation 60 (2.6) 58 (2.5) 0.97 (0.67–1.39) 0.852 Postoperative MI 24 (1.0) 16 (0.7) 0.66 (0.35–1.25) 0.207 Mediastinal infection 19 (0.8) 20 (0.9) 1.05 (0.56–1.98) 0.872 Postoperative AF 634 (27.1) 628 (26.8) 0.987 (0.87–1.12) 0.843 Postoperative stroke 17 (0.7) 7 (0.3) 0.41 (0.17–0.99) 0.048 Postoperative renal failure 43 (1.8) 41 (1.8) 1.17 (0.75–1.81) 0.499 MODS 31 (1.3) 32 (1.4) 1.03 (0.63–1.70) 0.899 Re-operation 37 (1.6) 53 (2.3) 1.44 (0.94–2.20) 0.090 AF indicates atrial fibrillation; CI, confidence interval; MI, myocardial infarction; MODS, multiple organ dysfunction syndrome; OR, odds ratio. Prespecified Subgroup Analysis Figure 2 illustrates the effects of beta-blocker therapy among prespecified patient subgroups in the propensity matched cohort. For each subgroups, all the calculations include 1.0 in the 95% CI for the OR and the interaction P value was not significant ( P ≥ 0.05). Disccussion The present study reports upon the effect of preoperative beta-blocker use on the operative outcomes of CABG. We performed analyses on the unmatched and propensity-matched cohorts, controlling for the preoperative risk factors. No statistical mortality benefit was associated with the use of preoperative beta-blockers. This finding was consistent among the various subgroups. Other end points were equal between groups except for postoperative stroke, which incidence was higher in the non-beta-blocker group. These results re-examined the appropriateness of preoperative beta-blocker use as a useful quality measure for isolated CABG in patients with left ventricular dysfunction. As beta-blockers have been proved to be effective in correcting the imbalance between oxygen demand and supply, this medication has been used routinely as a main therapy for patients with cardiovascular disease over the past 2 decades. The basis for preoperative beta-blocker use was extrapolated from studies in noncardiac surgical patient populations and a single nationwide retrospective analysis from the late 1990s.[ 3 , 15 ] At present, clinical guidelines for CABG surgery recommend preoperative beta-blockers for patients without contraindications.[ 1 , 16 , 17 ] However, there always has been controversy regarding whether preoperative beta-blocker use should be used as an quality metric, on account of it simply identifies whether a patient either received or did not received a preoperative beta-blocker. The large observational analysis reported by Ferguson and colleagues revealed a slightly lower mortality for patients undergoing CABG.[ 3 ] However, this benefit was limited in this analysis as patients with LVEF less than 30% were associated with a trend toward an increased mortality rate. In 2003, a retrospective review of propensity-matched CABG patients reported by Srinivasan et al revealed that preoperative beta-blocker therapy was not associated with differences in operative outcomes.[ 18 ] Brinkman and colleagues similarly failed to show in their series propensity-matched studies that mortality or major complications benefits for preoperative beta-blocker use.[ 8 , 9 ] In2013, Lapar et al reported potential negative impact of preoperative beta-blocker therapy.[ 6 ] They found association between perioperative myocardial infarction and preoperative beta-blocker therapy and observed patients treated with preoperative beta-blockers more commonly underwent intraoperative blood product transfusions. A recent meta-analysis including 6 observational studies with a total of 1,231,850 patients showed that preoperative beta-blocker use did not significantly reduce operative mortality and postoperative complications but significantly increased the incidence of atrial fibrillation.[ 10 ] In the present study, preoperative beta-blocker use in isolated CABG patients with left ventricular dysfunction was not associated with lower operative mortality in the whole study cohort (3.0% in beta-blockers group vs 3.7% in non-beta-blockers groups; adjusted OR, 0.82 [95% CI, 0.58–1.15]) or in the propensity-matched cohort (3.2% in beta-blockers group vs 3.7% in non-beta-blockers groups; OR, 0.85 [95% CI, 0.62–1.16]). We analyzed the association of beta-blocker use with operative outcomes in various subgroups but the results were similar in all cases. In regard to postoperative complications, we were unable to demonstrate any benefit of preoperative beta-blocker use except postoperative stroke. The 30-day results of the PeriOperative ischemic Evaluation (POISE) trial showed a significant reduction in cardiac events at the cost of a significant increase in the incidence of total mortality and stroke.[ 19 ] Concerns were raised as postoperative stroke might be associated with perioperative hypotension related with beta-blocker therapy. However, to our knowledge, there is lack of evidence linking beta-blocker use to hypotension after CABG. The chronic use of beta-blockers may improve baroreflex sensitivity and lower heart rate variability.[ 20 ] Therefore, beta-blockers may prevent severe hemodynamic fluctuations after CABG thus reducing the incidence of stroke. Moreover, long-term beta-blocker use has been shown to slow artery plague development and improve plague stabilization.[ 21 , 22 ] This in turn could result in less microembolizations during and after CABG and therefore less post operative stroke. Our report has important clinical and health policy related meanings. At present, the STS has identified preoperative beta-blocker use, which simply identifies whether a patient either received or did not received a preoperative beta-blocker, as a quality metric. Further details related to beta-blocker type, dose, timing of administration, goal heart rate, or duration of preoperative therapy is not involved in the assessment. Without more granular metric, the true efficacy of preoperative beta-blocker therapy will remain uncertain. As the existing binary metric is unlikely to show any difference, then it should not be a quality metric. A quality metric should be one that makes a difference in outcomes. In order to really help guide health policy makers and guide surgeons in the future, we believe we need to look at preoperative beta-blocker use in greater depth. More granular in definitions of whether a goal preoperative beta-blocker effect was achieved is needed. We suggest that the appropriate use of beta-blockers is where we need to take effort in the future investigation. For patients who are on beta-blockers, we advocate that these patients continue their preoperative beta-blockers therapy. Giving a patient a preoperative beta-blocker right before they go into the operation room to meet a predefined measure of cardiac surgical quality should be questioned. We assumed that a balance between the beta-blocker does to achieve a target heart rate in relation to the drug side effects should be optimized. There is a demand for further studies. Limitations Our study has several limitations. First, selection bias regarding the use of beta-blockers is unavoidable in observational studies. The propensity score used to adjust for baseline beta-blocker use can only account for measured covariates; thus we could not exclude the influence of unmeasured confounders on clinical outcomes. Second, salient details related to the type of beta-blockers, dosage, timing and duration of beta-blocker therapy, heart rate, blood pressure and postoperative vasopressor cannot be determined from this data set. Finally, all analyses were limited to short-term outcomes. Any long-term benefit related to preoperative beta-blockers therapy would not be demonstrated. Conclusion In this study, the administration of beta-blockers before CABG in patients with left ventricular dysfunction was not associated with improved operative mortality and complications except the incidence of postoperative stroke. Simply identifying whether or not beta-blockers are used before surgery should not be used as a measure of surgical quality. Beta-blockers are an important and effective tool in the care of specific patients undergoing cardiac surgery in specific clinical scenarios. However, a more granular quality metric should be developed. Abbreviations CABG, coronary artery bypass grafting CAD, coronary artery disease CCS, Canadian Cardiovascular Society CI, confidence interval COPD, chronic obstructive pulmonary disease DM, diabetes mellitus LVEF, left ventricular ejection fraction MI, myocardial infarction NYHA, New York Heart Association OR, odds ratio PTCA, percutaneous transluminal coronary angioplasty Declarations Ethics approval and consent to participate: This study was approved by the institutional review board at Fuwai Hospital (approval number 887, April 25th, 2017) and carried out in accordance with relevant guidelines and regulations. The informed consent was signed by participants. Consent for publication: Nota applicable Availability of data and materials: The datasets generated during and analyzed during the current study are not publicly available due to the datasets also forms part of other ongoing studies but are available from the corresponding author on reasonable request. Competing interest: The authors declare that they have no competing interests. Funding: The China-HFSR was supported by the 13th Five-year National Science and Technology Major Project of China (2016YFC1300900). They had no role in designing the study, data collection or analysis, interpretation of data, or writing the manuscript. Author’s contributions: S.H conceived of the China-HFSR study and take responsibility for all aspects of it. S.H, H.T and X.H designed the study. H.T wrote the first draft of the article and did the statistical analysis, with further contributions from K.C, J.H and S.L. All authors read and approved the final manuscript. Acknowledgements: The authors thank all China-HFSR investigators and participants for their contributions: Xin Chen, Yingbin Xiao, Fei Li, Feng Wan, Tao Han, Liangwan Chen, Hongyu Liu, Su Liu, Zhaoyun Cheng, Guimin Zhang, Zhongmin Liu, Chunsheng Wang, Huishan Wang, Zhenya Shen, Zhigang Liu, Chengchao Sun, Xinmin Zhou, Yiming Ni. References Windecker S, Kolh P, Alfonso F, Collet JP, Cremer J, Falk V, Filippatos G, Hamm C, Head SJ, Juni P et al : 2014 ESC/EACTS Guidelines on myocardial revascularization: The Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS)Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI) . European heart journal 2014, 35 (37):2541-2619. Sabik JF, 3rd: Why coronary artery bypass grafting remains the standard of care for patients with complex, multivessel coronary artery disease . The Journal of thoracic and cardiovascular surgery 2016, 152 (5):1227-1228. Ferguson TB, Jr., Coombs LP, Peterson ED, Society of Thoracic Surgeons National Adult Cardiac Surgery D: Preoperative beta-blocker use and mortality and morbidity following CABG surgery in North America . Jama 2002, 287 (17):2221-2227. Zhang H, Yuan X, Zhang H, Chen S, Zhao Y, Hua K, Rao C, Wang W, Sun H, Hu S et al : Efficacy of Long-Term beta-Blocker Therapy for Secondary Prevention of Long-Term Outcomes After Coronary Artery Bypass Grafting Surgery . Circulation 2015, 131 (25):2194-2201. O'Brien SM, Shahian DM, DeLong ER, Normand SLT, Edwards FH, Ferraris VA, Haan CK, Rich JB, Shewan CM, Dokholyan RS et al : Quality Measurement in Adult Cardiac Surgery: Part 2-Statistical Considerations in Composite Measure Scoring and Provider Rating . Annals of Thoracic Surgery 2007, 83 (4 SUPPL.):S13-S26. LaPar DJ, Crosby IK, Kron IL, Kern JA, Fonner E, Jr., Rich JB, Speir AM, Ailawadi G: Preoperative beta-blocker use should not be a quality metric for coronary artery bypass grafting . The Annals of thoracic surgery 2013, 96 (5):1539-1544; discussion 1544-1535. Kohsaka S, Miyata H, Motomura N, Imanaka K, Fukuda K, Kyo S, Takamoto S: Effects of Preoperative beta-Blocker Use on Clinical Outcomes after Coronary Artery Bypass Grafting: A Report from the Japanese Cardiovascular Surgery Database . Anesthesiology 2016, 124 (1):45-55. Brinkman W, Herbert MA, O'Brien S, Filardo G, Prince S, Dewey T, Magee M, Ryan W, Mack M: Preoperative beta-blocker use in coronary artery bypass grafting surgery: national database analysis . JAMA Intern Med 2014, 174 (8):1320-1327. Brinkman WT, Herbert MA, Prince SL, Magee MJ, Dewey TM, Smith RL, Edgerton JR, Head SJ, Ryan WH, Mack MJ: Preoperative beta-blocker usage: is it really worthy of being a quality indicator? The Annals of thoracic surgery 2011, 92 (3):788-795; discussion 795-786. Wang L, Wang H, Hou X: Short-term effects of preoperative beta-blocker use for isolated coronary artery bypass grafting: A systematic review and meta-analysis . The Journal of thoracic and cardiovascular surgery 2018, 155 (2):620-629 e621. Ibanez B, James S, Agewall S, Antunes MJ, Bucciarelli-Ducci C, Bueno H, Caforio ALP, Crea F, Goudevenos JA, Halvorsen S et al : 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC) . European heart journal 2018, 39 (2):119-177. Lazar HL, Salm TV, Engelman R, Orgill D, Gordon S: Prevention and management of sternal wound infections . The Journal of thoracic and cardiovascular surgery 2016, 152 (4):962-972. Griswold ME, Localio AR, Mulrow C: Propensity score adjustment with multilevel data: setting your sites on decreasing selection bias . Annals of internal medicine 2010, 152 (6):393-395. Li F, Zaslavsky AM, Landrum MB: Propensity score weighting with multilevel data . Stat Med 2013, 32 (19):3373-3387. Mangano DT, Layug EL, Wallace A, Tateo I: Effect of atenolol on mortality and cardiovascular morbidity after noncardiac surgery . New England Journal of Medicine 1996, 335 (23):1713-1720. Sousa-Uva M, Head SJ, Milojevic M, Collet JP, Landoni G, Castella M, Dunning J, Gudbjartsson T, Linker NJ, Sandoval E et al : 2017 EACTS Guidelines on perioperative medication in adult cardiac surgery . European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery 2018, 53 (1):5-33. Hillis LD, Smith PK, Anderson JL, Bittl JA, Bridges CR, Byrne JG, Cigarroa JE, Disesa VJ, Hiratzka LF, Hutter AM, Jr. et al : 2011 ACCF/AHA Guideline for Coronary Artery Bypass Graft Surgery: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines . Circulation 2011, 124 (23):e652-735. Srinivasan AK, Shackcloth MJ, Grayson AD, Fabri BM: Preoperative beta-blocker therapy in coronary artery bypass surgery: a propensity score analysis of outcomes . Interactive cardiovascular and thoracic surgery 2003, 2 (4):495-500. Group PS, Devereaux PJ, Yang H, Yusuf S, Guyatt G, Leslie K, Villar JC, Xavier D, Chrolavicius S, Greenspan L et al : Effects of extended-release metoprolol succinate in patients undergoing non-cardiac surgery (POISE trial): a randomised controlled trial . Lancet (London, England) 2008, 371 (9627):1839-1847. Airaksinen KE, Niemela MJ, Huikuri HV: Effect of beta-blockade on baroreflex sensitivity and cardiovascular autonomic function tests in patients with coronary artery disease . European heart journal 1994, 15 (11):1482-1485. Hedblad B, Wikstrand J, Janzon L, Wedel H, Berglund G: Low-dose metoprolol CR/XL and fluvastatin slow progression of carotid intima-media thickness: Main results from the Beta-Blocker Cholesterol-Lowering Asymptomatic Plaque Study (BCAPS) . Circulation 2001, 103 (13):1721-1726. Heidland UE, Strauer BE: Left ventricular muscle mass and elevated heart rate are associated with coronary plaque disruption . Circulation 2001, 104 (13):1477-1482. Supplementary Files FigureS1.tif FigureS2.tif Supplementlematerials.docx Cite Share Download PDF Status: Published Journal Publication published 19 Nov, 2021 Read the published version in BMC Cardiovascular Disorders → Version 1 posted Editorial decision: Major revision 10 May, 2021 Reviews received at journal 28 Mar, 2021 Reviewers agreed at journal 28 Mar, 2021 Reviewers agreed at journal 25 Jan, 2021 Reviewers invited by journal 20 Jan, 2021 Editor assigned by journal 20 Jan, 2021 Editor invited by journal 15 Jan, 2021 Submission checks completed at journal 15 Jan, 2021 First submitted to journal 14 Jan, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-147397","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":8270386,"identity":"29f11f48-cf51-4c33-839d-7915b3216ae5","order_by":0,"name":"Hanwei Tang","email":"","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hanwei","middleName":"","lastName":"Tang","suffix":""},{"id":8270387,"identity":"a14161e4-2149-43a6-9d24-6b07983f575a","order_by":1,"name":"Kai Chen","email":"","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Chen","suffix":""},{"id":8270388,"identity":"bfcee2bd-9bca-4a2c-9418-8ae5ea225a8f","order_by":2,"name":"Jianfeng Hou","email":"","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jianfeng","middleName":"","lastName":"Hou","suffix":""},{"id":8270389,"identity":"9e01b8cc-e93e-4659-956a-4354427becae","order_by":3,"name":"Xiaohong Huang","email":"","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaohong","middleName":"","lastName":"Huang","suffix":""},{"id":8270391,"identity":"00f3f1fc-91cc-4536-a66a-d46caf4ebf69","order_by":4,"name":"Sheng Liu","email":"","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Liu","suffix":""},{"id":8270393,"identity":"63055939-1b0d-4b77-a8b8-5303ed6da509","order_by":5,"name":"Shengshou Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYBACAxDxwQZIMPOAmBIMDOxEaGGckYbQIsHATIQWZh6QFgawFgbCWswl0h9/tkk4nNjfznvw4c8dFnX8zQyMjyt+4dZiOSPHTDoHqGXGYb5kY94zEhIShxmYDc/24XHYjRw25twfh3MbDvOYSTO2Af1ymIFNsrEHnxagwywSDufOB2qR/AnUIk9YS4KBNANQywagFgleoBYDkJaGH3i0nHljJtmTkF6/8TCPMcgvkhsPMzYbNjbg0XI8/fGHHwnWxnLnzxgCQ6yOX+5488GHDX9wa0EFjA1QkrGNNC0gQLQto2AUjIJRMAIAAHFxUAPul2NbAAAAAElFTkSuQmCC","orcid":"","institution":"Fu Wai Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Shengshou","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2021-01-14 09:36:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-147397/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-147397/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12872-021-02371-1","type":"published","date":"2021-11-19T12:59:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":5065710,"identity":"ac34f972-5208-4791-9263-d946078df36d","added_by":"auto","created_at":"2021-01-18 22:25:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":246044,"visible":true,"origin":"","legend":"Patient Flowchart\nCABG indicates, coronary artery bypass grafting; IABP, intra-aortic balloon pump.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/66109be164c76f1cd667bf54.png"},{"id":5065793,"identity":"a660e872-b2ea-421d-bfb5-407605ecdf15","added_by":"auto","created_at":"2021-01-18 22:28:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":664974,"visible":true,"origin":"","legend":"Relative risk/benefit for Prespecified Subgroups in Propensity-Matched Cohort\nCOPD indicates chronic obstructive pulmonary disease.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/432181ba0d8b5a50786e5ea3.png"},{"id":15709749,"identity":"1d1686a1-8e5f-47d9-80d8-e8892138332a","added_by":"auto","created_at":"2021-11-19 12:59:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1070216,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/c4d6b2c7-a7a2-4e71-ac66-ab72fac94fa8.pdf"},{"id":5065791,"identity":"f4035280-4fd0-4cd3-9735-b83270dd50db","added_by":"auto","created_at":"2021-01-18 22:28:46","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1884808,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/f5c580be97ff9123f38cd839.tif"},{"id":5065714,"identity":"ad5b480e-8608-4e25-9cce-c84297dc20da","added_by":"auto","created_at":"2021-01-18 22:25:46","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":668516,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/bc91d9478fe2a38f39f767ef.tif"},{"id":5065864,"identity":"93bba000-3063-4e43-b912-adc382665b6a","added_by":"auto","created_at":"2021-01-18 22:31:46","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":19694,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementlematerials.docx","url":"https://assets-eu.researchsquare.com/files/rs-147397/v1/2b4a88807a9cf1f3f98b3f86.docx"}],"financialInterests":"","formattedTitle":"Preoperative Beta-Blocker in Ventricular Dysfunction Patients: Need a More Granular Quality Metric.","fulltext":[{"header":"Background","content":" \u003cp\u003eCoronary artery bypass grafting is an essential therapeutic approach to reduce mortality and morbidity in patients with complex, multivessel coronary artery disease (CAD).[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] The perioperative medical treatment is key in the optimal success of the cardiac surgery. In the late 1990s, a large retrospective analysis demonstrated benefits of preoperative beta-blockers usage.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Our group previously reported that postoperative beta-blocker therapy was associated a lower risk of long-term mortality and adverse cardiovascular events.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Since 2007, the use of preoperative beta-blockers has been used as a quality standard for patients undergoing CABG.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHowever, controversies still exist in the literature regarding the effectiveness of beta-blockers for patients undergoing CABG.[\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] These studies failed to show perioperative mortality advantage in patients receiving beta-blockers before surgery. A recently meta-analysis suggests that the use of preoperative beta-blockers did not reduce either operative mortality or the incidence of postoperative complications.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Therefore, the preoperative use of beta-blockers as a quality indicator has been questioned.\u003c/p\u003e \u003cp\u003eTo date, the efficacy and safety of beta-blocker use during the preoperative period of CABG have not been adequately evaluated in patients with left ventricular dysfunction. Accurately identifying and utilizing measures of performance and quality is essential. Prospective randomized clinical trials to investigate the effect of preoperative beta-blocker use on cardiovascular patients is difficult and there are concerns that the design of such trials would entail an unacceptable risk for the withdrawal of beta-blockers in patients already taking this medication can lead to substantial morbidity and even mortality.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAs large-scale registries may overcome these difficulties to support clinical decisions, the currents study aims to review a large national database to assessed whether preoperative administration of beta-blockers was associated with improved early clinical outcomes after CABG in patients with left ventricular dysfunction.\u003c/p\u003e "},{"header":"Methods","content":" \u003cp\u003eStudy design\u003c/p\u003e \u003cp\u003eThe China Heart Failure Surgery Registry (China-HFSR) was led by Fuwai Hospital and other representative cardiac centres in different regions around China. In total, 94 centres with annual surgery volumes\u0026thinsp;\u0026gt;\u0026thinsp;100 were included as participants in the study. We included patients\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;17\u0026nbsp;years old who underwent CABG from January 2012 to June 2017 with documented LVEF\u0026thinsp;\u0026lt;\u0026thinsp;50%. Patients were excluded if they underwent concomitant valve or other surgeries or non-elective surgeries. We also excluded patients who have preoperative intra-aortic balloon pump insertion, cardiogenic shock and third degree heart block. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) These patients were then stratified according to preoperative beta-blocker administration. All CABG procedures represented standard surgical approaches to surgical myocardial revascularization with and without the use of cardiopulmonary bypass support. This study was approved by the institutional review board at Fuwai Hospital (approval number 887, April 25th, 2017) and carried out in accordance with relevant guidelines and regulations. The informed consent was provided by participants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eData collection\u003c/p\u003e \u003cp\u003eAll data were collected at the local sites from the medical records. The requirements for data collection and the definitions of variables were clearly identified. Standardized electronic case report forms were completed at the local sites and then submitted online to the data processing centre. All data were into the database separately by two trained technicians. Two separate reviewers from the data processing centre randomly selected and assessed 5\u0026ndash;10% of each of the participating centres\u0026rsquo; medical records during annual on-site audits. We compared the data in the database and the original medical records. A committee composed of physicians and surgeons determined the correct final value when there was a disagreement. In all patients included in China-HFSR database, 90 (1.5%) patients were without listed height, 74 (1.2%) without listed weight and 1 without data regarding smoking history. Considering the fact that they only accounted for a very small proportion of our patients, we imputed missing continuous variables (height and weight) with different mean values for the sexes. The missing categorical variable (smoking history) was imputed with negative values. So that patients who might have experienced the end point (in-hospital death) would not be excluded from analysis simply for 1 or 2 missing variables among the many examined.\u003c/p\u003e \u003cp\u003eClinical data\u003c/p\u003e \u003cp\u003eThe preoperative variables included age, gender, body mass index, smoking history, New York Heart Association (NYNH) classification, Canadian Cardiovascular Society (CCS) classification, diabetes mellitus (DM), hypertension, hyperlipidemia, renal failure, chronic obstructive pulmonary disease (COPD), cerebrovascular accident, carotid disease and other peripheral arterial disease, preoperative atrial fibrillation, previous myocardial infarction (MI), percutaneous transluminal coronary angioplasty (PTCA) history, No. of diseased vessels, Left main CAD, LVEF, preoperative creatinine and prior cardiovascular surgeries.\u003c/p\u003e \u003cp\u003eThe major postoperative complications included re-intubation, MI, mediastinal infection, stroke, renal failure, multiple organ dysfunction syndrome, postoperative atrial fibrillation and reoperation for bleeding. MI was counted as a complication if it newly occurred postoperatively and was defined as any one of the following: MI documented in the medical record with an elevation of cardiac troponin values with at least one value above the 10 times 99th percentile upper reference limit or electrocardiograph documented ST-segment elevation in evolution, Q waves 0.03 seconds in width and/or one-third or greater of the total QRS complex in 2 or more contiguous leads, or new left bundle branch block.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] Mediastinal infection was defined according to the expert consensus.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Stroke was defined as a central neurological deficit persisting\u0026thinsp;\u0026gt;\u0026thinsp;24 hours (i.e., extremity weakness or loss of motion, loss of consciousness, loss of speech, visual field cuts). Renal failure was defined as an increase in serum creatinine level to \u0026gt;\u0026thinsp;4\u0026nbsp;mg/dL, 3\u0026times; the most recent preoperative creatinine level, or a new postoperative need for dialysis. Reoperation for bleeding was defined as chest tube drainage\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;200\u0026nbsp;mL/h for at least 3 hours requiring surgical intervention.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are expressed as either mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;standard deviation or medians and quartiles depending upon overall variable distribution. Categorical variables are presented as frequencies and percentages. We performed a t-test for normally distributed continuous variables; otherwise, the Mann-Whitney U test or Kruskal-Wallis H test was used. Chi square tests or Fisher\u0026rsquo;s exact tests were used for categorical variables. Cochran-Armitage trend test were used to examine the trend of beta-blocker use during the study period.\u003c/p\u003e \u003cp\u003eWe used the following 2 techniques to adjust for selection bias when comparing outcomes of the beta-blocker vs non-beta-blocker groups: multiple logistic regression modelling and propensity matching. For the regression-based analyses, the association between preoperative beta-blocker use and each clinical end point were adjusted for baseline patient risk by inclusion of the following validated and widely accepted measures of patient-level covariates: age, body mass index, sex, smoking history, diabetes mellitus, hypertension, hyperlipidemia, chronic obstructive pulmonary disease, cerebrovascular accident, previous MI, PTCA history, LVEF, preoperative creatinine, CCS classification, NYHA classification, No. of diseased vessels, Left main CAD, preoperative atrial fibrillation and prior cardiovascular surgery history. Each logistic model also included year of surgery and a set of fixed-effect hospital-specific intercept variables.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Model results are reported as odds ratios (OR) with a 95% confidence interval.\u003c/p\u003e \u003cp\u003eThe second method of adjusting for selection bias involved matching patients with similar estimated probability of receiving beta-blockers (propensity score). The propensity score was calculated by a multivariable logistic regression model which was developed using the same covariates listed above for the regression-based analyses. Then we matched patients in a 1:1 fashion without replacement.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] ORs with 95% CIs comparing the frequency of each end point for patients receiving vs not receiving beta-blockers were estimated using univariable logistic regression.\u003c/p\u003e \u003cp\u003eAdditional analysis were performed to examine whether the association between beta-blockers and mortality differed across prespecified subgroups based on age, sex, ejection fraction, diabetes mellitus, hypertension and chronic lung disease. Subgroup-specific ORs were estimated and displayed with 95% CIs.\u003c/p\u003e \u003cp\u003eAll reported \u003cem\u003eP\u003c/em\u003e values are 2 sided, and values of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to indicate statistical significance. All statistical analysis was performed using SPSS version 22.0 (IBM Corp., Armonk, NY).\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003ePatients Characteristics\u003c/p\u003e \u003cp\u003eOf 6,116 patients who met study inclusion criteria, 61.7% of patients received a preoperative beta-blocker. During the study period, no significant trend was found in the beta-blocker use (Figure S1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.163). According to the preoperative profiles, women accounted for 16.2% of the patients, and 34.0% of the overall patient population had diabetes mellitus; the mean patient age was 61.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u0026nbsp;years. Small differences in baseline characteristics existed between study groups. Patients receiving beta-blockers were more likely to have DM, hypertension prior PTCA history and left main CAD while hyperlipidemia, COPD, Carotid disease and triple vessel disease were more common in these patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Demographic and Clinical Characteristics in Overall Cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBeta-blocker Use Groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll Patients\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6116)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2343)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3773)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean (SD), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.3 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.3 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e988 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e402 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e586 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.7 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.7 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.8 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3388 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1304 (55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2084 (55.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2079 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e757 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1322 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3353 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1237 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2116 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipemia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1970 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e816 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1154 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic renal failure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral artery disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e260 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarotid disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1000 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e441 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e559 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular accident, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e527 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e336 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, median (quartile), umol/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003cp\u003e(70.0,96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.7\u003c/p\u003e \u003cp\u003e(69.0,95.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003cp\u003e(40,46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft main CAD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1625 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e589 (25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1036 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriple vessel disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4218 (69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2275 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1443 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious MI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2561 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e952 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1609 (42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTCA history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e760 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e505 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCS class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1181 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e508 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e673 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e886 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e348 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e216 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2086 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e666 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e926 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1606 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e680 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1420 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e357 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e538 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF, Mean (SD), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.3 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.3 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.3 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e865 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e608 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2252 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e864 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1388 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2694 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1091 (46.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1603 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e174 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.559\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior cardiovascular surgery, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTS PROM, Median [25th, 75th percentile] (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.0 [2.1, 4.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9 [2.0, 4.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1 [2.2, 4.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI indicate body mass index, CAD, coronary vascular disease; CCS, Canadian Cardiovascular Society; COPD, chronic obstructive pulmonary disease; LFEF, left ventricular ejection fraction; MI, myocardial infarction; NA, not available; NYHA, New York Heart Association; PROM, predicted risk of mortality; PTCA, percutaneous transluminal coronary angioplasty; SD, standard deviation; STS, Society of Thoracic Surgeons.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOperative Outcomes\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the outcomes from the unmatched groups. No difference in mortality was found between two cohorts (3.7% for the non-beta-blockers group vs 3.0% for the beta-blocker group; adjusted OR, 0.82 [95% CI, 0.58\u0026ndash;1.15]). Few differences in the incidence of other postoperative clinical end points were observed as a function of preoperative beta-blockers except in the incidence of stroke (0.7% for the non-beta-blocker group vs 0.3 for the beta-blocker group; adjusted OR, 0.39 [95% CI, 0.16\u0026ndash;0.96]).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of End Point Events and Covariate-Adjusted ORs in Overall Cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnd Point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo. (%) of Events by Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo beta-blocker\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2343)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeta-blocker\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3773)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82 (0.58\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-intubation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.69\u0026ndash;1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.44\u0026ndash;2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMediastinal infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.45\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative AF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e634 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1089 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.94\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37 (0.16\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative renal failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.53\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMODS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.56\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-operation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.31 (0.85\u0026ndash;2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAF indicates atrial fibrillation; CI, confidence interval; MI, myocardial infarction; MODS, multiple organ dysfunction syndrome; OR, odds ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter propensity matching, comparable groups of 2,430 each were created (Table S1. FigureS2). Outcomes for propensity-matched patients receiving vs not receiving beta-blockers are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Operative mortality was similar for the 2 groups (3.7% vs 3.0% for the beta-blocker vs non-beta-blocker groups; OR, 0.85 [95% CI, 0.62\u0026ndash;1.16]). Less frequency of stroke was found in patients receiving preoperative beta-blockers (0.3%) compared with non-beta-blockers (0.7%; OR, 0.41 [95% CI, 0.17\u0026ndash;0.99]). Of other clinical end points, no significant differences were found.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of End Point Events and ORs in Propensity-Matched Cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnd Point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo. (%) of Events by Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo beta-blocker\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2340)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeta-blocker\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2340)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.62\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-intubation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.67\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66 (0.35\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMediastinal infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.56\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative AF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e634 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e628 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.987 (0.87\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41 (0.17\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative renal failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.17 (0.75\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMODS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.63\u0026ndash;1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-operation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.44 (0.94\u0026ndash;2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAF indicates atrial fibrillation; CI, confidence interval; MI, myocardial infarction; MODS, multiple organ dysfunction syndrome; OR, odds ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePrespecified Subgroup Analysis\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the effects of beta-blocker therapy among prespecified patient subgroups in the propensity matched cohort. For each subgroups, all the calculations include 1.0 in the 95% CI for the OR and the interaction \u003cem\u003eP\u003c/em\u003e value was not significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Disccussion","content":" \u003cp\u003eThe present study reports upon the effect of preoperative beta-blocker use on the operative outcomes of CABG. We performed analyses on the unmatched and propensity-matched cohorts, controlling for the preoperative risk factors. No statistical mortality benefit was associated with the use of preoperative beta-blockers. This finding was consistent among the various subgroups. Other end points were equal between groups except for postoperative stroke, which incidence was higher in the non-beta-blocker group. These results re-examined the appropriateness of preoperative beta-blocker use as a useful quality measure for isolated CABG in patients with left ventricular dysfunction.\u003c/p\u003e \u003cp\u003eAs beta-blockers have been proved to be effective in correcting the imbalance between oxygen demand and supply, this medication has been used routinely as a main therapy for patients with cardiovascular disease over the past 2 decades. The basis for preoperative beta-blocker use was extrapolated from studies in noncardiac surgical patient populations and a single nationwide retrospective analysis from the late 1990s.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] At present, clinical guidelines for CABG surgery recommend preoperative beta-blockers for patients without contraindications.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] However, there always has been controversy regarding whether preoperative beta-blocker use should be used as an quality metric, on account of it simply identifies whether a patient either received or did not received a preoperative beta-blocker.\u003c/p\u003e \u003cp\u003eThe large observational analysis reported by Ferguson and colleagues revealed a slightly lower mortality for patients undergoing CABG.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] However, this benefit was limited in this analysis as patients with LVEF less than 30% were associated with a trend toward an increased mortality rate. In 2003, a retrospective review of propensity-matched CABG patients reported by Srinivasan et al revealed that preoperative beta-blocker therapy was not associated with differences in operative outcomes.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Brinkman and colleagues similarly failed to show in their series propensity-matched studies that mortality or major complications benefits for preoperative beta-blocker use.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] In2013, Lapar et al reported potential negative impact of preoperative beta-blocker therapy.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] They found association between perioperative myocardial infarction and preoperative beta-blocker therapy and observed patients treated with preoperative beta-blockers more commonly underwent intraoperative blood product transfusions. A recent meta-analysis including 6 observational studies with a total of 1,231,850 patients showed that preoperative beta-blocker use did not significantly reduce operative mortality and postoperative complications but significantly increased the incidence of atrial fibrillation.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn the present study, preoperative beta-blocker use in isolated CABG patients with left ventricular dysfunction was not associated with lower operative mortality in the whole study cohort (3.0% in beta-blockers group vs 3.7% in non-beta-blockers groups; adjusted OR, 0.82 [95% CI, 0.58\u0026ndash;1.15]) or in the propensity-matched cohort (3.2% in beta-blockers group vs 3.7% in non-beta-blockers groups; OR, 0.85 [95% CI, 0.62\u0026ndash;1.16]). We analyzed the association of beta-blocker use with operative outcomes in various subgroups but the results were similar in all cases.\u003c/p\u003e \u003cp\u003eIn regard to postoperative complications, we were unable to demonstrate any benefit of preoperative beta-blocker use except postoperative stroke. The 30-day results of the PeriOperative ischemic Evaluation (POISE) trial showed a significant reduction in cardiac events at the cost of a significant increase in the incidence of total mortality and stroke.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Concerns were raised as postoperative stroke might be associated with perioperative hypotension related with beta-blocker therapy. However, to our knowledge, there is lack of evidence linking beta-blocker use to hypotension after CABG. The chronic use of beta-blockers may improve baroreflex sensitivity and lower heart rate variability.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Therefore, beta-blockers may prevent severe hemodynamic fluctuations after CABG thus reducing the incidence of stroke. Moreover, long-term beta-blocker use has been shown to slow artery plague development and improve plague stabilization.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] This in turn could result in less microembolizations during and after CABG and therefore less post operative stroke.\u003c/p\u003e \u003cp\u003eOur report has important clinical and health policy related meanings. At present, the STS has identified preoperative beta-blocker use, which simply identifies whether a patient either received or did not received a preoperative beta-blocker, as a quality metric. Further details related to beta-blocker type, dose, timing of administration, goal heart rate, or duration of preoperative therapy is not involved in the assessment. Without more granular metric, the true efficacy of preoperative beta-blocker therapy will remain uncertain. As the existing binary metric is unlikely to show any difference, then it should not be a quality metric. A quality metric should be one that makes a difference in outcomes. In order to really help guide health policy makers and guide surgeons in the future, we believe we need to look at preoperative beta-blocker use in greater depth. More granular in definitions of whether a goal preoperative beta-blocker effect was achieved is needed.\u003c/p\u003e \u003cp\u003eWe suggest that the appropriate use of beta-blockers is where we need to take effort in the future investigation. For patients who are on beta-blockers, we advocate that these patients continue their preoperative beta-blockers therapy. Giving a patient a preoperative beta-blocker right before they go into the operation room to meet a predefined measure of cardiac surgical quality should be questioned. We assumed that a balance between the beta-blocker does to achieve a target heart rate in relation to the drug side effects should be optimized. There is a demand for further studies.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eOur study has several limitations. First, selection bias regarding the use of beta-blockers is unavoidable in observational studies. The propensity score used to adjust for baseline beta-blocker use can only account for measured covariates; thus we could not exclude the influence of unmeasured confounders on clinical outcomes. Second, salient details related to the type of beta-blockers, dosage, timing and duration of beta-blocker therapy, heart rate, blood pressure and postoperative vasopressor cannot be determined from this data set. Finally, all analyses were limited to short-term outcomes. Any long-term benefit related to preoperative beta-blockers therapy would not be demonstrated.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eIn this study, the administration of beta-blockers before CABG in patients with left ventricular dysfunction was not associated with improved operative mortality and complications except the incidence of postoperative stroke. Simply identifying whether or not beta-blockers are used before surgery should not be used as a measure of surgical quality. Beta-blockers are an important and effective tool in the care of specific patients undergoing cardiac surgery in specific clinical scenarios. However, a more granular quality metric should be developed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCABG, coronary artery bypass grafting\u003c/p\u003e\n\u003cp\u003eCAD, coronary artery disease\u003c/p\u003e\n\u003cp\u003eCCS, Canadian Cardiovascular Society\u003c/p\u003e\n\u003cp\u003eCI, confidence interval\u003c/p\u003e\n\u003cp\u003eCOPD, chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eDM, diabetes mellitus\u003c/p\u003e\n\u003cp\u003eLVEF, left ventricular ejection fraction\u003c/p\u003e\n\u003cp\u003eMI, myocardial infarction\u003c/p\u003e\n\u003cp\u003eNYHA, New York Heart Association\u003c/p\u003e\n\u003cp\u003eOR, odds ratio\u003c/p\u003e\n\u003cp\u003ePTCA, percutaneous transluminal coronary angioplasty\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate:\u003c/p\u003e\n\u003cp\u003eThis study was approved by the institutional review board at Fuwai Hospital (approval number 887, April 25th, 2017) and carried out in accordance with relevant guidelines and regulations. The informed consent was signed by participants.\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u003c/p\u003e\n\u003cp\u003eNota applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analyzed during the current study are not publicly available due to the datasets also forms part of other ongoing studies but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interest:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThe China-HFSR was supported by the 13th Five-year National Science and Technology Major Project of China (2016YFC1300900). They had no role in designing the study, data collection or analysis, interpretation of data, or writing the manuscript.\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s contributions:\u003c/p\u003e\n\u003cp\u003eS.H conceived of the China-HFSR study and take responsibility for all aspects of it. S.H, H.T and X.H designed the study. H.T wrote the first draft of the article and did the statistical analysis, with further contributions from K.C, J.H and S.L. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u003c/p\u003e\n\u003cp\u003eThe authors thank all China-HFSR investigators and participants for their contributions: Xin Chen, Yingbin Xiao, Fei Li, Feng Wan, Tao Han, Liangwan Chen, Hongyu Liu, Su Liu, Zhaoyun Cheng, Guimin Zhang, Zhongmin Liu, Chunsheng Wang, Huishan Wang, Zhenya Shen, Zhigang Liu, Chengchao Sun, Xinmin Zhou, Yiming Ni.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWindecker S, Kolh P, Alfonso F, Collet JP, Cremer J, Falk V, Filippatos G, Hamm C, Head SJ, Juni P\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003e2014 ESC/EACTS Guidelines on myocardial revascularization: The Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS)Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI)\u003c/strong\u003e. \u003cem\u003eEuropean heart journal \u003c/em\u003e2014, \u003cstrong\u003e35\u003c/strong\u003e(37):2541-2619.\u003c/li\u003e\n\u003cli\u003eSabik JF, 3rd: \u003cstrong\u003eWhy coronary artery bypass grafting remains the standard of care for patients with complex, multivessel coronary artery disease\u003c/strong\u003e. \u003cem\u003eThe Journal of thoracic and cardiovascular surgery \u003c/em\u003e2016, \u003cstrong\u003e152\u003c/strong\u003e(5):1227-1228.\u003c/li\u003e\n\u003cli\u003eFerguson TB, Jr., Coombs LP, Peterson ED, Society of Thoracic Surgeons National Adult Cardiac Surgery D: \u003cstrong\u003ePreoperative beta-blocker use and mortality and morbidity following CABG surgery in North America\u003c/strong\u003e. \u003cem\u003eJama \u003c/em\u003e2002, \u003cstrong\u003e287\u003c/strong\u003e(17):2221-2227.\u003c/li\u003e\n\u003cli\u003eZhang H, Yuan X, Zhang H, Chen S, Zhao Y, Hua K, Rao C, Wang W, Sun H, Hu S\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEfficacy of Long-Term beta-Blocker Therapy for Secondary Prevention of Long-Term Outcomes After Coronary Artery Bypass Grafting Surgery\u003c/strong\u003e. \u003cem\u003eCirculation \u003c/em\u003e2015, \u003cstrong\u003e131\u003c/strong\u003e(25):2194-2201.\u003c/li\u003e\n\u003cli\u003eO'Brien SM, Shahian DM, DeLong ER, Normand SLT, Edwards FH, Ferraris VA, Haan CK, Rich JB, Shewan CM, Dokholyan RS\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eQuality Measurement in Adult Cardiac Surgery: Part 2-Statistical Considerations in Composite Measure Scoring and Provider Rating\u003c/strong\u003e. \u003cem\u003eAnnals of Thoracic Surgery \u003c/em\u003e2007, \u003cstrong\u003e83\u003c/strong\u003e(4 SUPPL.):S13-S26.\u003c/li\u003e\n\u003cli\u003eLaPar DJ, Crosby IK, Kron IL, Kern JA, Fonner E, Jr., Rich JB, Speir AM, Ailawadi G: \u003cstrong\u003ePreoperative beta-blocker use should not be a quality metric for coronary artery bypass grafting\u003c/strong\u003e. \u003cem\u003eThe Annals of thoracic surgery \u003c/em\u003e2013, \u003cstrong\u003e96\u003c/strong\u003e(5):1539-1544; discussion 1544-1535.\u003c/li\u003e\n\u003cli\u003eKohsaka S, Miyata H, Motomura N, Imanaka K, Fukuda K, Kyo S, Takamoto S: \u003cstrong\u003eEffects of Preoperative beta-Blocker Use on Clinical Outcomes after Coronary Artery Bypass Grafting: A Report from the Japanese Cardiovascular Surgery Database\u003c/strong\u003e. \u003cem\u003eAnesthesiology \u003c/em\u003e2016, \u003cstrong\u003e124\u003c/strong\u003e(1):45-55.\u003c/li\u003e\n\u003cli\u003eBrinkman W, Herbert MA, O'Brien S, Filardo G, Prince S, Dewey T, Magee M, Ryan W, Mack M: \u003cstrong\u003ePreoperative beta-blocker use in coronary artery bypass grafting surgery: national database analysis\u003c/strong\u003e. \u003cem\u003eJAMA Intern Med \u003c/em\u003e2014, \u003cstrong\u003e174\u003c/strong\u003e(8):1320-1327.\u003c/li\u003e\n\u003cli\u003eBrinkman WT, Herbert MA, Prince SL, Magee MJ, Dewey TM, Smith RL, Edgerton JR, Head SJ, Ryan WH, Mack MJ: \u003cstrong\u003ePreoperative beta-blocker usage: is it really worthy of being a quality indicator?\u003c/strong\u003e \u003cem\u003eThe Annals of thoracic surgery \u003c/em\u003e2011, \u003cstrong\u003e92\u003c/strong\u003e(3):788-795; discussion 795-786.\u003c/li\u003e\n\u003cli\u003eWang L, Wang H, Hou X: \u003cstrong\u003eShort-term effects of preoperative beta-blocker use for isolated coronary artery bypass grafting: A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eThe Journal of thoracic and cardiovascular surgery \u003c/em\u003e2018, \u003cstrong\u003e155\u003c/strong\u003e(2):620-629 e621.\u003c/li\u003e\n\u003cli\u003eIbanez B, James S, Agewall S, Antunes MJ, Bucciarelli-Ducci C, Bueno H, Caforio ALP, Crea F, Goudevenos JA, Halvorsen S\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003e2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC)\u003c/strong\u003e. \u003cem\u003eEuropean heart journal \u003c/em\u003e2018, \u003cstrong\u003e39\u003c/strong\u003e(2):119-177.\u003c/li\u003e\n\u003cli\u003eLazar HL, Salm TV, Engelman R, Orgill D, Gordon S: \u003cstrong\u003ePrevention and management of sternal wound infections\u003c/strong\u003e. \u003cem\u003eThe Journal of thoracic and cardiovascular surgery \u003c/em\u003e2016, \u003cstrong\u003e152\u003c/strong\u003e(4):962-972.\u003c/li\u003e\n\u003cli\u003eGriswold ME, Localio AR, Mulrow C: \u003cstrong\u003ePropensity score adjustment with multilevel data: setting your sites on decreasing selection bias\u003c/strong\u003e. \u003cem\u003eAnnals of internal medicine \u003c/em\u003e2010, \u003cstrong\u003e152\u003c/strong\u003e(6):393-395.\u003c/li\u003e\n\u003cli\u003eLi F, Zaslavsky AM, Landrum MB: \u003cstrong\u003ePropensity score weighting with multilevel data\u003c/strong\u003e. \u003cem\u003eStat Med \u003c/em\u003e2013, \u003cstrong\u003e32\u003c/strong\u003e(19):3373-3387.\u003c/li\u003e\n\u003cli\u003eMangano DT, Layug EL, Wallace A, Tateo I: \u003cstrong\u003eEffect of atenolol on mortality and cardiovascular morbidity after noncardiac surgery\u003c/strong\u003e. \u003cem\u003eNew England Journal of Medicine \u003c/em\u003e1996, \u003cstrong\u003e335\u003c/strong\u003e(23):1713-1720.\u003c/li\u003e\n\u003cli\u003eSousa-Uva M, Head SJ, Milojevic M, Collet JP, Landoni G, Castella M, Dunning J, Gudbjartsson T, Linker NJ, Sandoval E\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003e2017 EACTS Guidelines on perioperative medication in adult cardiac surgery\u003c/strong\u003e. \u003cem\u003eEuropean journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery \u003c/em\u003e2018, \u003cstrong\u003e53\u003c/strong\u003e(1):5-33.\u003c/li\u003e\n\u003cli\u003eHillis LD, Smith PK, Anderson JL, Bittl JA, Bridges CR, Byrne JG, Cigarroa JE, Disesa VJ, Hiratzka LF, Hutter AM, Jr.\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003e2011 ACCF/AHA Guideline for Coronary Artery Bypass Graft Surgery: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines\u003c/strong\u003e. \u003cem\u003eCirculation \u003c/em\u003e2011, \u003cstrong\u003e124\u003c/strong\u003e(23):e652-735.\u003c/li\u003e\n\u003cli\u003eSrinivasan AK, Shackcloth MJ, Grayson AD, Fabri BM: \u003cstrong\u003ePreoperative beta-blocker therapy in coronary artery bypass surgery: a propensity score analysis of outcomes\u003c/strong\u003e. \u003cem\u003eInteractive cardiovascular and thoracic surgery \u003c/em\u003e2003, \u003cstrong\u003e2\u003c/strong\u003e(4):495-500.\u003c/li\u003e\n\u003cli\u003eGroup PS, Devereaux PJ, Yang H, Yusuf S, Guyatt G, Leslie K, Villar JC, Xavier D, Chrolavicius S, Greenspan L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEffects of extended-release metoprolol succinate in patients undergoing non-cardiac surgery (POISE trial): a randomised controlled trial\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2008, \u003cstrong\u003e371\u003c/strong\u003e(9627):1839-1847.\u003c/li\u003e\n\u003cli\u003eAiraksinen KE, Niemela MJ, Huikuri HV: \u003cstrong\u003eEffect of beta-blockade on baroreflex sensitivity and cardiovascular autonomic function tests in patients with coronary artery disease\u003c/strong\u003e. \u003cem\u003eEuropean heart journal \u003c/em\u003e1994, \u003cstrong\u003e15\u003c/strong\u003e(11):1482-1485.\u003c/li\u003e\n\u003cli\u003eHedblad B, Wikstrand J, Janzon L, Wedel H, Berglund G: \u003cstrong\u003eLow-dose metoprolol CR/XL and fluvastatin slow progression of carotid intima-media thickness: Main results from the Beta-Blocker Cholesterol-Lowering Asymptomatic Plaque Study (BCAPS)\u003c/strong\u003e. \u003cem\u003eCirculation \u003c/em\u003e2001, \u003cstrong\u003e103\u003c/strong\u003e(13):1721-1726.\u003c/li\u003e\n\u003cli\u003eHeidland UE, Strauer BE: \u003cstrong\u003eLeft ventricular muscle mass and elevated heart rate are associated with coronary plaque disruption\u003c/strong\u003e. \u003cem\u003eCirculation \u003c/em\u003e2001, \u003cstrong\u003e104\u003c/strong\u003e(13):1477-1482.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Beta-blocker, quality metric, coronary artery bypass grafting","lastPublishedDoi":"10.21203/rs.3.rs-147397/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-147397/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe use of preoperative beta-blockers has been accepted as a quality standard for patients undergoing coronary artery bypass graft (CABG) surgery. However, conflicting results from recent studies have raised questions concerning the effectiveness of this quality metric. We sought to determine the influence of preoperative beta-blocker administration before CABG in patients with left ventricular dysfunction.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe authors analyzed all cases of isolated CABGs in patients with left ventricular ejection fraction less than 50%, performed between 2012 January and 2017 June, at 94 centres recorded in the China Heart Failure Surgery Registry database. In addition to the use of multivariate regression models, a 1 to 1 propensity scores matched analysis was performed.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eOf 6,116 eligible patients, 61.7% received a preoperative beta-blocker. No difference in operative mortality was found between two cohorts (3.7% for the non-beta-blockers group vs 3.0% for the beta-blocker group; adjusted odds ratio [OR], 0.82 [95% CI, 0.58-1.15]). Few differences in the incidence of other postoperative clinical end points were observed as a function of preoperative beta-blockers except in stroke (0.7% for the non-beta-blocker group vs 0.3 for the beta-blocker group; adjusted OR, 0.39 [95% CI, 0.16-0.96]). Results of propensity-matched analyses were broadly consistent.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eIn this study, the administration of beta-blockers before CABG was not associated with improved operative mortality and complications except the incidence of postoperative stroke in patients with left ventricular dysfunction. A more granular quality metric which would guide the use of beta-blockers should be developed.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Preoperative Beta-Blocker in Ventricular Dysfunction Patients: Need a More Granular Quality Metric.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-01-18 22:25:44","doi":"10.21203/rs.3.rs-147397/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-05-10T09:13:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-03-29T01:44:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4a663f25-299e-47fe-aa63-b50763a33d08","date":"2021-03-28T22:22:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"09a0b24b-95a1-4602-beba-1007c94d50ea","date":"2021-01-25T08:42:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-01-20T05:53:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-01-20T05:50:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-01-15T05:35:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-01-15T05:24:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2021-01-14T09:17:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fbec6b03-963d-422c-b658-5f98380563ae","owner":[],"postedDate":"January 18th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":1944719,"name":"Cardiac \u0026 Cardiovascular Systems"},{"id":1944720,"name":"Cardiothoracic Surgery"}],"tags":[],"updatedAt":"2021-11-19T12:59:44+00:00","versionOfRecord":{"articleIdentity":"rs-147397","link":"https://doi.org/10.1186/s12872-021-02371-1","journal":{"identity":"bmc-cardiovascular-disorders","isVorOnly":false,"title":"BMC Cardiovascular Disorders"},"publishedOn":"2021-11-19 12:59:44","publishedOnDateReadable":"November 19th, 2021"},"versionCreatedAt":"2021-01-18 22:25:44","video":"","vorDoi":"10.1186/s12872-021-02371-1","vorDoiUrl":"https://doi.org/10.1186/s12872-021-02371-1","workflowStages":[]},"version":"v1","identity":"rs-147397","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-147397","identity":"rs-147397","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.
My notes (saved in your browser only)
Ask this paper
Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00