Abstract
Background
Novel cardiac biomarkers including sST2, Galectin-3 and NT-proBNP may be associated with long-term adverse outcomes following cardiac surgery. We sought to measure the association between cardiac biomarker levels and 1-year hospital readmission or mortality.
Methods
Plasma biomarkers from 1,047 patients discharged alive after isolated CABG surgery from eight medical centers were measured in a cohort from the NNE Cardiovascular Disease Study Group between 2004 and 2007. We evaluated the association between preoperative and postoperative biomarkers and 1-year readmission or mortality using Kaplan-Meier estimates and Cox’s Proportional Hazards modeling, adjusting for covariates used in the STS 30-day readmission model.
Results
The median follow-up time was 365 days. After adjustment for established risk factors, above median levels of postoperative Galectin-3 and NT-proBNP were each significantly associated with 1-year readmission or mortality: Galectin-3 (median = 10.35 ng/mL, HR: 1.40, 95% CI: 1.08–1.80, p=0.010); NT-proBNP (median = 15.21 ng/mL, HR: 1.42, 95% CI: 1.07–1.87, p=0.014).
Conclusions
In patients undergoing cardiac surgery, novel cardiac biomarkers were associated with readmission or mortality independent of established risk factors. Measurement of these biomarkers may improve our ability to identify patients at highest risk for readmission or mortality prior to discharge. This will also allow resource allocation accordingly, while implementing strategies for personalized medicine based on the biomarker profile of the patient.
Hospital readmission after coronary artery bypass graft surgery (CABG) is common and unfortunately often associated with increased mortality. The 30-day all-cause readmission rate among CABG patients exceeds 17.0% [1]. Readmitted patients have a 3 to 11-fold higher rate of in-hospital mortality compared to those not readmitted [2]. Recognized risk factors for short term readmission after CABG include diabetes, mediastinitis, surgical site infections, heart failure (HF), chronic lung disease, female sex, and kidney injury [1,3]. In addition to these clinical and demographic variables, theoretical and empirical evidence suggests that biomarker measures offer additional utility in predicting readmission events [4–6]. However, few studies have evaluated the relationship between cardiac biomarkers and hospital readmission in CABG patients. Biomarkers have significant predictive value in HF and may also be used to identify patients at the highest risk of readmission and subsequent death after CABG [7–12].
A number of novel cardiac biomarkers, including soluble ST 2 (sST2), Galectin-3 (Gal-3), and N-terminal prohormone of BNP (NT-proBNP), may also have predictive utility [13–15]. sST2, a member of the interleukin (IL)-1 family, is a protein up-regulated by cardiac myocytes in response to mechanical strain [16]. Similarly, Gal-3 is a beta-galactoside-binding lectin and a key mediator of cardiac fibrosis and remodeling [17]. Both sST2 and Gal-3 are representative of the ventricular remodeling process and have the potential to be surrogate markers for patients readmitted for HF, infection and inflammation [13,18,19]. NT-proBNP is up-regulated by cardiac myocytes during states of pressure and volume overload and is found in higher circulating concentrations compared to active BNP [20]. Research has demonstrated that sST2, Gal-3 and NT-proBNP are associated with worsening HF severity, and that they are independent predictors of mortality in HF patients [14,16,17,20].
Identifying CABG patients who may benefit from additional intervention is of interest to both cardiothoracic surgeons and hospitals. Novel cardiac biomarkers have been shown to significantly predict mortality in HF patients and may also have a predictive role in cardiac surgery. Therefore, the aim of this study was to evaluate the relationship between sST2, Gal-3 and NT-proBNP levels and 1-year hospital readmission or death among patients undergoing isolated CABG.
PATIENTS AND METHODS
Study Population
The Northern New England (NNE) Cardiovascular Disease Study Group directs a prospective registry of patients undergoing cardiac surgery at 8 hospitals located in New Hampshire, Maine and Vermont. Data from this registry is used to inform improvements in care for patients undergoing coronary revascularization and open-heart surgery both locally and across the United States. NNE data is also used continually to update and refine risk prediction models for cardiac surgery patients as new clinically relevant factors are identified. The NNE registry contains data on patient and clinical characteristics, procedural indications, and outcomes, and procedural and survival data is verified every two years. The institutional review boards at all hospitals approved the collection of NNE registry data as well as the conduct of this study.
The NNE Biomarker Study was carried out from 2004 to 2007 to identify biomarkers predictive of death in cardiac surgical patients (n = 1,690) [21]. Our current study population was comprised of a subset of patients who 1) underwent isolated CABG, 2) were discharged alive, and 3) had blood banked preoperatively (n=1393) and postoperatively (n=1047) on day one to measure levels of sST2, Gal-3, and NT-proBNP.
Biomarker Data Collection
Cardiac biomarkers sST2, Gal3, and NT-proBNP were the main exposures of interest in this study. We collected biomarker samples preoperatively prior to incision at each participating site and the postoperative samples (10mL) were collected approximately 24 hours after patient surgery. Biomarker levels were measured using custom made multiplex ELISA assays (Meso Scale Discovery, Rockville, MD). Blood samples were stored at room temperature for 20 minutes to allow clotting and separation. Tubes were centrifuged at 3500 rpm for 20 minutes. Resulting sera samples were stored at the respective medical centers below −80°C until transportation on dry ice to the University of Vermont Laboratory for Clinical and Biochemical Research in Colchester, Vermont. Samples were then stored at −80°C until measurement where they were analyzed for cytokine measurement.
Patient Follow Up
The primary endpoint of this study was 1-year readmission or mortality after isolated CABG. A composite readmission/mortality outcome was used because it has been shown that CABG patients with elevated postoperative biomarker levels who are readmitted to the hospital are also at significantly increased risk of death [5,22]. Readmission status and all-cause mortality data were obtained for each patient by linking NNE registry data with Medicare claims, state all-payers claims, and the National Death Index using Social Security numbers and date of birth.
Statistical Analysis
Patient, clinical and procedural characteristics were compared by readmission/mortality status using descriptive statistics. Event rates and time-to-event analyses were conducted for 1-year readmission or mortality. Time zero was defined as the date of discharge after CABG and the follow-up period was predefined as 1 year. Kaplan-Meier and log-rank techniques were used to conduct a time-to-event analysis for each biomarker. Patients were stratified by biomarker levels above and below the population median. We elected to treat the biomarker levels as categorical rather than continuous variables due to the graded relationship of median categories and the incidence of readmission or mortality.
Multivariate Cox proportional hazards models were constructed to assess the relationship of biomarker levels and 1-year readmission or mortality, using biomarker median cut points. Adjustment was carried out using the Society of Thoracic Surgeons (STS) 30-day readmission model. The STS 30-day readmission model accounts for 21 different preoperative factors (Supplemental Table S1 in the Appendix) [23]. A competing risks regression analysis was performed for all biomarkers to account for patients experiencing death prior to readmission. Lastly, a multiple imputation regression sensitivity analysis was conducted to assess estimates after accounting for missing covariate values.
RESULTS
Patient, clinical, and procedural characteristics by 1-year readmission or mortality status can be viewed in Table 1. Out of the 1,047 patients included in the study, 39% (n = 405) experienced 1-year readmission or mortality. CABG patients who experienced 1-year readmission or mortality were significantly older (67.9 vs. 63.9 years; p < 0.001) and were more likely to have a history of atrial fibrillation, congestive HF, chronic obstructive pulmonary disease (COPD), and any vascular disease, compared to patients without an event. A significantly higher percentage of females comprised the event group (28.9 vs. 20.1%; p < 0.001).
Table 1.
Patient Characteristics by Readmission or Death Within 1 Year of Discharge
| Patient Characteristics | Readmitted or Dead | p Value | |
|---|---|---|---|
| No (n = 642) | Yes (n = 405) | ||
| Age, years | 63.91 ± 9.92 | 67.8 ± 9.98 | <0.001 |
| Female | 20.14 | 28.89 | <0.001 |
| Body mass index, kg/m2 | 29.66 ± 5.39 | 29.81 ± 5.75 | 0.636 |
| Body surface area, m2 | 2.04 ± 0.23 | 2.03 ± 0.26 | 0.534 |
| Smoker | 22.62 | 22.96 | 0.889 |
| Atrial fibrillation | 3.65 | 9.14 | <0.001 |
| CHF | 7.69 | 13.86 | <0.001 |
| Last preoperative serum creatinine | 1.13 ± 1.13 | 1.22 ± 0.84 | 0.115 |
| Diabetes | 36.23 | 40.49 | 0.136 |
| Ejection fraction <40% | 9.75 | 12.01 | 0.221 |
| Hypertension | 80.16 | 82.88 | 0.242 |
| IABP preoperative | 3.85 | 3.70 | 0.900 |
| Prior MI | |||
| No | 57.89 | 51.36 | 0.132 |
| <24 hours preoperative | 1.52 | 1.73 | |
| >24 hours and <7 days preoperative | 19.13 | 19.26 | |
| >7 days and <365 days preoperative | 9.31 | 12.35 | |
| >365 days preoperative | 12.15 | 15.31 | |
| Vascular disease | 22.57 | 35.80 | <0.001 |
| Unstable angina | 55.41 | 55.50 | 0.975 |
| COPD | 10.43 | 16.79 | 0.001 |
| Left main, ≥50% stenosis | 32.39 | 36.05 | 0.189 |
| Prior CABG surgery | 1.74 | 2.75 | 0.227 |
| Prior PCI | 18.93 | 21.48 | 0.276 |
| Priority | |||
| Emergent | 2.33 | 1.23 | 0.385 |
| Urgent | 66.30 | 68.15 | |
| Nonurgent | 31.38 | 30.62 | |
| Received pRBC units | 31.91 | 45.93 | <0.001 |
| pRBC units given preoperative | |||
| 0 | 98.99 | 95.80 | 0.001 |
| 1 | 0.30 | 0.99 | |
| 2 | 0.51 | 2.22 | |
| ≥3 | 0.20 | 0.99 | |
Values are mean ± SD or %.
CABG = coronary artery bypass graft; CHF = congestive heart failure; COPD = chronic obstructive pulmonary disease; IABP = intraaortic balloon pump; MI = myocardial infarction; PCI = percutaneous coronary intervention; pRBC = packed red blood cell.
Preoperative and Postoperative sST2 & 1-year Readmission or Mortality
The median preoperative sST2 level among CABG patients was 3.80 ng/mL with an interquartile range of 2.87 ng/mL to 5.17 ng/mL. The median postoperative sST2 level was 43.61 ng/mL with an interquartile range of 24.44 ng/mL to 72.69 ng/mL. Biomarker summary statistics can be viewed in Supplemental Table S4 in the appendix. Postoperative sST2 levels above the median were significantly associated with a greater hazard of 1-year readmission or mortality in unadjusted models (HR: 1.34; 95% CI: 1.06 – 1.69; Table 2). After adjustment, the relationship was not significant (HR: 1.15; 95% CI: 0.89 – 1.47; Table 2).
Table 2.
Cox Proportional Hazards Regression Model Analysis: Looking at Biomarkers with 1-year outcomes
| Univariate | Multivariate1 | |||||
|---|---|---|---|---|---|---|
| HR | 95% CI | P-value | HR | 95% CI | P-value | |
| sST2 | ||||||
| (preop) log transformed | 1.28 | 1.09 – 1.49 | 0.002 | 1.16 | 0.98 – 1.38 | 0.089 |
| (preop) above median | 1.15 | 0.95 – 1.40 | 0.154 | 1.03 | 0.84 – 1.27 | 0.783 |
| (postop) log transformed | 1.32 | 1.15 – 1.52 | <0.001 | 1.19 | 1.02 – 1.38 | 0.026 |
| (postop) above median | 1.34 | 1.06 – 1.69 | 0.014 | 1.15 | 0.89 – 1.47 | 0.293 |
| Galectin-3 | ||||||
| (preop) log transformed | 1.35 | 1.13 – 1.61 | 0.001 | 1.12 | 0.91 – 1.35 | 0.240 |
| (preop) above median | 1.36 | 1.12 – 1.66 | 0.002 | 1.16 | 0.94 – 1.43 | 0.165 |
| (postop) log transformed | 1.46 | 1.22 – 1.74 | <0.001 | 1.26 | 1.03 – 1.56 | 0.027 |
| (postop) above median | 1.57 | 1.24 – 1.99 | <0.001 | 1.40 | 1.08 – 1.80 | 0.010 |
| NT-proBNP | ||||||
| (preop) log transformed | 1.28 | 1.20 – 1.37 | <0.001 | 1.19 | 1.07 – 1.32 | 0.001 |
| (preop) above median | 1.67 | 1.36 – 2.04 | <0.001 | 1.18 | 0.91 – 1.52 | 0.214 |
| (postop) log transformed | 1.54 | 1.36 – 1.74 | <0.001 | 1.32 | 1.10 – 1.58 | 0.003 |
| (postop) above median | 1.85 | 1.45 – 2.34 | <0.001 | 1.42 | 1.07 – 1.87 | 0.014 |
Adjusted for the STS 30-day readmission model
Postoperative Gal-3 & 1-year Readmission or Mortality
The median preoperative Gal-3 level among CABG patients was 10.34 ng/mL with an interquartile range of 6.93 ng/mL to 14.79. The median postoperative Gal-3 level was 10.35 ng/mL with an interquartile range of 7.13 ng/mL to 15.23 ng/mL. Biomarker summary statistics can be viewed in Supplemental Table S4 in the appendix. Patients with Gal-3 levels above the median were significantly associated with a greater hazard of 1-year readmission or mortality in unadjusted models (HR: 1.57; 95% CI: 1.24 – 1.99; Table 2). After adjustment, the relationship was still significant. (HR: 1.40; 95% CI: 1.08 – 1.80).
Postoperative NT-proBNP & 1-year Readmission or Mortality
The median preoperative NT-proBNP level among CABG patients was 2.44 ng/mL with an interquartile range of 1.12 ng/mL to 5.95 ng/mL. The median postoperative NT-proBNP level was 13.2 ng/mL with an interquartile range of 7.8 ng/mL to 23.5 ng/mL. Biomarker summary statistics can be viewed in Supplemental Table S4 in the appendix. NT-proBNP levels above the median were associated with 1-year readmission or mortality in unadjusted (HR: 1.85; 95% CI: 1.45 – 2.34; Table 2) and adjusted models (HR: 1.42; 95% CI: 1.07 – 1.87; Table 2).
The Kaplan-Meier 1-year readmission or mortality curves for sST2, Gal-3 and NT-proBNP median cut points are presented in Figure 1A–C, respectfully. The multiple imputations regression analysis for missing covariates revealed similar results for sST2, Gal-3 and NT-proBNP (Supplemental Table 2).
Figure 1.
Probability of 1-year readmission or mortality after coronary artery bypass graft surgery at biomarker median cut points of (A) soluble suppression of tumorigenicity 2 (sST2), (B) galectin-3, and (C) N-terminal prohormone of brain natriuretic peptide (NT-proBNP).
COMMENT
In patients undergoing isolated CABG, we found that postoperative Gal-3 and NT-proBNP levels are associated with readmission or mortality at 1-year, independent of established risk factors. Our findings demonstrate the utility of postoperative Gal-3 and NT-proBNP as biomarkers to identify CABG patients at increased risk of readmission or mortality at 1-year after discharge.
sST2 exhibits pro-cardiac remodeling effects by binding to and reducing levels of circulating IL-33, a cytokine that normally inhibits signaling pathways involved in inflammation and hypertrophic changes to the myocardium [24]. Attenuating this inhibition is believed to enhance cardiac remodeling and scarring resulting in increased cardiovascular risk in patients [25]. Multiple studies have shown that sST2 is an independent predictor of mortality in HF, myocardial infarction, and in healthy, asymptomatic adults [19,26]. To-date, only one published study, Lindman et al. found that preoperative sST2 levels above the median were significantly associated with a higher hazard of mortality in patients undergoing valve replacement surgery [27]. We examined both preoperative and postoperative sST2 levels and utilized a composite readmission/mortality outcome measure.
While much is still unknown regarding Gal-3 cardiac physiology, expression of this protein is up regulated by cardiac fibroblasts and macrophages during states of acute and chronic HF [10]. Meijers and colleagues found that Gal-3 concentrations above 17.8 (ng/mL) were significantly associated with HF re-hospitalization at 30, 60, 90 and 120 days [28]. Yu and colleagues also demonstrated that Gal-3 was an independent predictor of all-cause mortality or re-hospitalization in patients with coronary artery disease and chronic HF at one year follow up [29]. Not all studies have shown this relationship, and the utility of Gal-3 as a prognostic biomarker in HF is still being debated [30].
In our study, we examined the relationship between Gal-3 levels and patient outcomes after CABG. We found that postoperative Gal-3 levels above the median were significantly associated with readmission or mortality at one-year. Our median Gal-3 level was substantially lower than levels found to be predictive of poorer outcomes in HF patients. This finding may suggest that Gal-3 is a more specific biomarker for adverse outcomes in the cardiac surgery population.
NT-proBNP levels have been found to predict readmission and mortality among hospitalized HF patients at 6 months [31]. In a 2010 study by Schachner and colleagues, preoperative NT-proBNP levels were found to be an independent predictor of mortality at 18 months follow-up and were associated with numerous perioperative complications in patients undergoing isolated CABG [32]. Similar findings were observed among acute coronary syndrome patients undergoing CABG and in patients enduring CABG and/or valve surgery in both the immediate in-hospital setting and in long-term follow-up [33,34]. Vikholm et al found that cardiac surgery patients with preoperative BNP levels in the fourth quartile had significantly increased mortality compared to the first quartile, with an adjusted hazard ratio of 2.9 (95% CI: 1.6–5.1), however NT-proBNP did not predict hospital readmission (p = 0.11) [35].
We examined the relationship between NT-proBNP levels and patient outcomes after isolated CABG. Contrary to Vikholm et al, we observed that patients with postoperative NT-proBNP levels above the median had a significantly increased hazard of readmission or mortality at 1-year follow up in adjusted analyses (HR: 1.5; 95% CI: 1.1–1.9).
The NNE Biomarker Study was a multicenter, regional investigation that prospectively enrolled patients across multiple hospitals, ensuring the generalizability of its subsequent findings. We conducted sensitivity analyses to account for competing risks and missing values to judge the accuracy of our main findings. We did not focus on preoperative biomarker measurements in our study. Biomarkers sST2 and NT-proBNP present at very low concentrations preoperatively, and their levels increase by several fold in patients who experience adverse cardiac events after surgery. It is possible that some of these patients have underlying pathology and chronically elevated biomarker levels. Elevated biomarkers may therefore be reflective of chronic illness rather than the operation itself; nevertheless, this finding is still important as the elevated biomarker still allows for the identification of patients at increased risk.
In our study, risk adjustment was performed using the STS 30-day readmission model [3], which likely reflects perioperative problems and complications. In contrast, readmissions at one year are more likely a reflection of underlying chronic disease processes. Given our composite endpoint, we performed additional analyses using a harmonized dataset of the STS 30-day readmission model and the STS ASCERT long-term mortality model (Table 3) [36]. This model is less parsimonious than the STS 30-day readmission model, but it does consider all potential cofounders. We did not observe a meaningful difference between the models. We repeated the analyses with left censoring at 30 days, therefore restricting the analyses to 30 to 365 days. We did not observe any significant changes in the association of readmission or mortality with postoperative biomarkers (Supplemental Table 3 and Supplemental Figure 1).
Table 3.
Multivariate1 Cox Proportional Hazards Regression Model Analysis: Looking at Biomarkers with 1-year outcomes
| HR | 95% CI | P-value | |
|---|---|---|---|
| ST2 | |||
| (preop) log transformed | 1.14 | 0.95 – 1.36 | 0.166 |
| (preop) above median | 1.03 | 0.84 – 1.27 | 0.776 |
| (postop) log transformed | 1.20 | 1.03 – 1.40 | 0.018 |
| (postop) above median | 1.16 | 0.90 – 1.49 | 0.263 |
| Galectin-3 | |||
| (preop) log transformed | 1.10 | 0.91 – 1.34 | 0.310 |
| (preop) above median | 1.15 | 0.93 – 1.42 | 0.205 |
| (postop) log transformed | 1.25 | 1.02 – 1.54 | 0.033 |
| (postop) above median | 1.38 | 1.07 – 1.78 | 0.014 |
| NT-proBNP | |||
| (preop) log transformed | 1.17 | 1.05 – 1.31 | 0.004 |
| (preop) above median | 1.16 | 0.89 – 1.51 | 0.269 |
| (postop) log transformed | 1.34 | 1.12 – 1.60 | 0.002 |
| (postop) above median | 1.45 | 1.09 – 1.93 | 0.010 |
Adjusted for the STS 30-day readmission model and the STS ASCERT long-term mortality risk model
A one-year follow up period may not be adequate to assess the relationship between these biomarkers and long-term patient outcomes. Further research should be conducted to examine these relationships beyond one year. We believe that it would be worthwhile to evaluate multiple time points and with additional funding, a prospective study could be conducted to evaluate multiple time points and validate on our current time points. We propose several strategies that could be used to take corrective action if cardiac biomarkers are elevated: 1) elevated preoperative levels could be reviewed by the surgeon to determine readiness for surgery; 2) responding to postoperative elevations in these biomarkers may signify undiagnosed low cardiac output or on-going ischemia indicating a need for the clinical care team to conduct postoperative testing, to modify medications, to address additional risk factors and to adapt a transitional care plan.
Supplementary Material
Acknowledgments
To the best of our knowledge, we are the first to report that postoperative Gal-3 and NT-proBNP levels are significantly associated with readmission and/or mortality in CABG patients. Our findings indicate that these novel biomarkers can be used to identify patients at increased risk of readmission and death after CABG; and therefore, these biomarkers may facilitate strategies of personalized medicine in patients undergoing cardiac surgery.
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