- Email: [email protected]
Plasma Monocyte Chemotactic Protein-1 Is Associated With Acute Kidney Injury and Death After Cardiac Operations
Dennis G. Moledina, MBBS, Selin Isguven, BS, Eric McArthur, MS, Heather Thiessen-Philbrook, MMath, Amit X. Garg, MD, PhD, Michael Shlipak, MD, Richard Whitlock, MD, Peter A. Kavsak, PhD, Steven G. Coca, MD, MS, and Chirag R. Parikh, MD, PhD, for the Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury (TRIBE-AKI) Consortium Program of Applied Translational Research, Department of Medicine, Yale School of Medicine, New Haven, Connecticut; Institute for Clinical Evaluative Sciences Western, London, Ontario, Canada; Division of Nephrology, Department of Medicine, and Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada; Kidney Health Research Collaborative, San Francisco Veterans Affairs Medical Center, University of California, San Francisco, San Francisco, California; Division of Cardiac Surgery, Population Health Research Institute and Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada; Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Internal Medicine, Veterans Affairs Medical Center, West Haven, Connecticut
Background. Monocyte chemotactic protein-1 (MCP-1; chemokine C-C ligand-2 [CCL-2]) is upregulated in ischemia-reperfusion injury and is a promising biomarker of inflammation in cardiac operations. Methods. We measured preoperative and postoperative plasma MCP-1 levels in adults undergoing cardiac operations to evaluate the association of perioperative MCP-1 levels with acute kidney injury (AKI) and death in Translational Research Investigating Biomarker Endpoints in AKI (TRIBE-AKI), a prospective, multicenter, observational cohort. Results. Of the 972 participants in the study, AKI developed in 329 (34%), and severe AKI developed in 45 (5%). During a median follow-up of 2.9 years (interquartile range, 2.2 to 3.5 years), 119 participants (12%) died. MCP-1 levels were significantly higher in those who developed AKI and died than in those without AKI and death. Participants with a preoperative MCP-1 level in the highest tertile (>196 pg/mL) had an increased AKI risk
than those in the lowest tertile (<147 pg/mL; odds ratio [OR], 1.43l; 95% confidence interval [CI], 1.00 to 2.05). The association appeared similar but was not significant for the severe AKI outcome (OR, 1.48; 95% CI, 0.62 to 3.54). Compared with participants with preoperative MCP-1 level in the lowest tertile, those in the highest tertile had higher adjusted risk of death (hazard ratio, 1.82; 95% CI, 1.40 to 2.38). Similarly, participants in the highest tertile had a higher adjusted risk of death (hazard ratio, 1.95; 95% CI, 1.09–3.49) than those with a postoperative MCP-1 level in the lowest tertile. Conclusions. Higher plasma MCP-1 is associated with increased AKI and risk of death after cardiac operations. MCP-1 could be used as a biomarker to identify high-risk patients for potential AKI prevention strategies in the setting of cardiac operations.
A
improve patient outcomes and health care costs by targeted interventions. Preoperative and intraoperative inflammation is recognized as an important predictor of postoperative
pproximately 2 million cardiac operations are performed each year around the world. The postoperative complication of acute kidney injury (AKI) occurs in about 280,000 (14%) of these patients, which leads to increased hospital length of stay and health care expenditure [1–3]. Identification of patients who are most susceptible to postoperative complications could
(Ann Thorac Surg 2017;104:613–20) Ó 2017 by The Society of Thoracic Surgeons
Dr Kavsak discloses being named an inventor in acute heart failure patent #458491871B2 filed by McMaster University; Dr Parikh discloses a financial relationship with AbbVie and Genfit.
Accepted for publication Nov 7, 2016. Presented at The American Society of Nephrology Kidney Week 2016, Chicago, IL, Nov 15–20, 2016. Address correspondence to Dr Parikh, Yale Program of Applied Translational Research, 60 Temple St, Ste 6C, New Haven, CT 06510; email: [email protected].
Ó 2017 by The Society of Thoracic Surgeons Published by Elsevier Inc.
The Supplemental Material can be viewed in the online version of this article [http://dx.doi.org/10.1016/j. athoracsur.2016.11.036] on http://www.annalsthoracic surgery.org.
0003-4975/$36.00 http://dx.doi.org/10.1016/j.athoracsur.2016.11.036
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Plasma Monocyte Chemotactic Protein-1 Is Associated With Acute Kidney Injury and Death After Cardiac Operations
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complications after cardiac operations [4, 5]. Preoperative inflammation primes the kidney and other organs for intraoperative injury, and elevations of preoperative inflammatory markers are associated with adverse postoperative outcomes. Cardiac operations are associated with periods of hypoperfusion, tissue ischemia, contact of blood components with the bypass circuit, nonpulsatile blood flow, and operative trauma that all contribute to a proinflammatory state [6]. Given the important role of inflammation in cardiac operations, trials of antiinflammatory interventions have been conducted in hopes of improving postsurgical outcomes [7–9]. Studies are also attempting to discover biomarkers that can identify patients with subclinical inflammation who might be candidates for antiinflammatory therapy to mitigate the risk of cardiac operations. Monocyte chemotactic protein-1 (MCP-1; chemokine C-C ligand-2 [CCR-2]) is a member of the chemokine family. Monocytes express CCR-2, the receptor for MCP-1, and MCP-1 regulates trafficking of monocytes from the bone marrow to inflamed tissue in response to inflammatory signals. In preclinical studies, MCP-1 expression was upregulated immediately after ischemia-reperfusion injury [10], and MCP-1 inhibition was associated with lower cardiac fibrosis [11]. Small studies in humans have shown MCP-1 expression increased immediately after cardiac operations [12, 13], and MCP-1 elevation was associated with AKI [14]. Studies have also used MCP-1 as a surrogate marker to quantify intraoperative inflammation after various interventions [13, 15]; however, the association of MCP-1 with outcomes after cardiac operations has not been examined in a large, prospective cohort. We hypothesized that elevated perioperative plasma MCP-1 would be a marker of unrecognized inflammation and would be associated with a higher risk of adverse outcomes in patients undergoing cardiac operations. In this study, we measured MCP-1 levels before and after cardiac operations in participants of the Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury (TRIBE-AKI) cohort, and tested its association with AKI and death.
Patients and Methods Participants The TRIBE-AKI study is a prospective, multicenter, observational cohort of adults at high risk for developing AKI who underwent cardiac operations (coronary artery bypass grafting [CABG] valve operations, or both). Full study details have been previously published [16–18]. In brief, we enrolled participants with at least one risk factor for AKI at 5 academic medical centers in North America (details in the Supplemental Material). Written informed consent was obtained from all patients or their proxy decision makers. The TRIBE-AKI study was approved by the institutional review boards at each participating institution. We collected preoperative characteristics, operative details, and postoperative complications using definitions of the Society of Thoracic Surgeons [16].
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Exposures The exposures for this study were (1) the preoperative concentration of plasma MCP-1 levels and (2) the peak postoperative concentration in days 1 to 3 postoperatively. Blood specimens were collected preoperatively and daily for up to 5 days postoperatively. After a single freeze-thaw cycle of stored plasma samples, we measured MCP-1 on the Randox Evidence Investigator using a Randox-developed custom cytokine array (Randox Laboratories Ltd, Crumlin, United Kingdom) with a detection range of 12 to 1,580 pg/mL and an intraassay coefficient of variation of 10% to 16% using the manufacturer’s specifications. The personnel measuring the biomarkers were blinded to clinical outcomes.
Outcomes The main outcomes for this study were occurrence of in-hospital AKI and all-cause death at complete cohort follow-up. AKI was defined as serum creatinine of 0.3 mg/dL, a rise in serum creatinine from baseline exceeding 50%, or requiring dialysis during hospitalization. Severe AKI was defined as a more than 100% rise in serum creatinine from baseline or requiring dialysis during hospitalization. Of the 329 AKI events, 327 (99%) occurred within 7 days of the operation. The magnitude of changes in serum creatinine for AKI and severe AKI in our study correspond to Kidney Disease: Improving Global Outcomes AKI stage 1 and AKI stage 2 or higher, respectively. All preoperative creatinine values were measured within 2 months before the operation. We used the Chronic Kidney Disease Epidemiology Collaboration equation to determine the preoperative estimated glomerular filtration rate (eGFR). We obtained death data after discharge through various mechanisms and cross-referenced, when possible. For United States participants, we telephoned patients’ homes, searched the National Death Index, and received hospital records. For participants from Canada, we used telephone calls and data held at the Institute for Clinical Evaluative Sciences to acquire vital status. These data sets were linked using unique, encoded identifiers and analyzed at the Institute for Clinical Evaluative Sciences. The death status and date of death were recorded through December 31, 2012. Vital status ascertainment on the cohort was 100%.
Statistical Analysis We performed descriptive statistics and report continuous variables as mean SD or median (interquartile range [IQR]) and categoric variables as frequency (percentage). Small cell counts are only presented for data collected by TRIBE-AKI (not from Institute for Clinical Evaluative Sciences data). Continuous variables were compared using the Wilcoxon rank sum test or the Fisher exact test, as appropriate. Categoric variables were compared using the c2 test. We performed preoperative and postoperative MCP-1 correlation with each other and with the eGFR from corresponding time points using Spearman correlations. We divided the population into
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Table 1. Patient Characteristics by Preoperative Monocyte Chemotactic Protein-1 Tertiles MCP-1 Tertileb
Demographics Age at operation, mean (SD), y Men, No. (%) White race, No. (%) Medical history Diabetes, No. (%) Hypertension, No. (%) Heart failure, No. (%) LVEF <0.40, No. (%) Previous myocardial infarction, No. (%) eGFR mean (SD), mL/min/1.73m2 eGFR <60 mL/min/1.73m2, No. (%) Serum creatinine, median (IQR), mg/dL Urine albumin-to-creatinine, No. (%) 30–300 >300 Surgical characteristics Elective operation, No. (%) Operation type, No. (%) CABG or valve Off-pump Perfusion time, mean (SD), min Cross-clamp time, mean (SD), min
Overall (N ¼ 957)
Lowest (T1) (n ¼ 319)
Middle (T2) (n ¼ 320)
Highest (T3) (n ¼ 318)
71.7 (9.9) 652 (68.1) 894 (93.4)
70.9 (10.4) 227 (71.2) 307 (96.2)
72.6 (8.9) 210 (65.6) 298 (93.1)
71.6 (10.2) 215 (67.6) 289 (90.9)
379 758 232 98 247 67.5 331 1.0
104 240 73 35 77 72.8 69 1.0
123 249 67 30 83 66.2 124 1.0
152 269 92 33 87 63.3 138 1.1
(39.6) (79.2) (24.2) (10.2) (25.8) (19.5) (35) (0.9–1.2)
(32.6) (75.2) (22.9) (11.0) (24.1) (17.9) (22) (0.8–1.1)
(38.4) (77.8) (20.9) (9.4) (25.9) (18.1) (39) (0.9–1.2)
(47.8) (84.6) (28.9) (10.4) (27.4) (21.2) (43) (0.9–1.4)
265 (27.7) 59 (6.2)
85 (26.6) 13 (4.1)
83 (25.9) 27 (8.4)
97 (30.5) 19 (6.0)
766 (80.0)
262 (82.1)
261 (81.6)
243 (76.4)
748 86 112.3 76.7
(78.2) (9.0) (56.9) (43.4)
259 38 106.9 73.6
(81.2) (11.9) (58.6) (44.7)
247 24 109.4 75.4
(77.2) (7.5) (53.2) (39.2)
242 24 120.7 81.2
(76.1) (7.5) (58.0) (45.8)
p Valuec 0.08 0.32 0.02 <0.001 0.01 0.05 0.80 0.02 <0.001 <0.001 <0.001 0.08
0.14 0.33 0.20 0.005 0.08
a Small cell counts are only presented for data collected by Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury (TRIBE-AKI) b Preoperative MCP-1 tertile (T) cutoffs (pg/mL): T1, 12 to 147; T2, 147 to and not from Institute for Clinical Evaluative Sciences (ICES) data holdings. c 196; T3, 196 to 1,581. Continuous variables are compared using Wilcoxon rank sum test or the Fisher exact test, and categoric variables are compared using c2 test.
CABG ¼ coronary artery bypass grafting; eGFR ¼ estimated glomerular filtration rate; ejection fraction; MCP-1 ¼ monocyte chemotactic protein-1.
MCP-1 concentration tertiles at preoperative and postoperative time points. We used logistic regression to determine the association of MCP-1 tertiles with the AKI outcomes, with the lowest tertile as the reference group. For the death outcome, we used Cox proportional hazards regression to estimate the hazard ratio of death, with the lowest tertile of MCP-1 as the reference group. For the preoperative MCP-1 models, we adjusted the analyses for the following covariates: demographics (age, sex, race), comorbidities (diabetes, hypertension, heart failure, myocardial infarction), type of operation (CABG or valve vs all others), and evidence of kidney disease (preoperative albumin-to-creatinine ratio, preoperative eGFR). For the postoperative MCP-1 models, we additionally adjusted for surgical characteristics (cardiopulmonary bypass time >120 minutes, nonelective operation), change in renal function (using change in serum creatinine), and baseline MCP-1 level. We performed two supplementary analyses: (1) evaluation of association of each log increase in MCP-1 level with AKI and death, and (2) evaluation of association of MCP-1 tertiles with death after excluding patients who died in-hospital. We used
IQR ¼ interquartile range;
LVEF ¼ left ventricular
SAS 9.3 (SAS Institute, Cary, NC) and R 2.10.1 (R Foundation for Statistical Computing, Vienna, Austria) software to perform the analysis.
Results We enrolled 1,219 patients to the TRIBE-AKI study from July 2007 through December 2009 (Supplemental Fig 1). Of these, 972 participants (68% men) with an adequate plasma sample for MCP-1 level measurement were included in the analysis. The mean age was 71 years. There were baseline participant differences across the preoperative plasma MCP-1 tertiles (Table 1). Patients in the highest tertile of MCP-1 were less likely to be white, had a lower mean preoperative eGFR, and were more likely to have diabetes and hypertension. Differences in baseline characteristics by postoperative MCP-1 tertiles were similar to the preoperative tertiles. Patients with a longer cross-clamp time and who underwent on-pump operations were more likely to be in the highest tertile of postoperative MCP-1 (Supplemental Table 1).
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Fig 1. (A) Monocyte chemotactic protein-1 (MCP-1) levels are significantly higher in patients with acute kidney injury (AKI). *p < 0.001 at all timepoints. (B) MCP-1 levels are significantly higher in those who died. *p ¼ 0.001 on the preoperative time point, p ¼ 0.02 on the first postoperative day, and p < 0.001 at all other time points. The top and bottom of the box represent the interquartile range, and the horizontal line represents the median. Day 1 refers to 0 to 6 hours after the operation, day 2 corresponds to 48 hours after the operation, and day 3 corresponds to 72 hours after the operation.
Perioperative Plasma MCP-1 Levels
Perioperative MCP-1 Levels and AKI Duration
MCP-1 increased from a median level of 171 pg/mL (IQR, 135 to 212 pg/mL) preoperatively to a peak of 450 pg/mL (IQR, 307 to 735 pg/mL) 0 to 6 hours after the operation (Fig 1). MCP-1 levels were higher in participants who developed AKI and died than in participants without AKI who survived (Supplemental Table 2). Preoperative MCP-1 positively correlated with postoperative MCP-1 (R2 ¼ 0.31) and negatively correlated with eGFR (R2 ¼ –0.22).
Of the 329 participants with AKI, the duration of AKI was 1 to 2 days in 206 (63%), 3 to 6 days in 98 (29%), and 7 days or longer in 25 (8%). The highest preoperative MCP-1 tertile was associated with longer AKI duration compared with the lowest tertile (OR, 1.45; 95% CI, 1.03 to 2.05; Supplemental Table 3). The highest postoperative MCP-1 tertile showed a trend toward longer AKI duration compared with the lowest tertile (OR, 1.36; 95% CI, 0.89 to 2.08).
Perioperative MCP-1 Levels and AKI Risk
Perioperative MCP-1 Levels and Risk of Death
Of the 972 participants, AKI developed in 329 (34%), severe AKI developed in 45 (5%), and 13 (1%) received acute dialysis. After adjusting for baseline characteristics and preoperative eGFR, the highest tertile of preoperative MCP-1 was associated with a higher odds ratio (OR) of AKI (OR, 1.43; 95% confidence interval [CI], 1.00 to 2.05; Table 2). The association appeared similar but was not significant for severe AKI (OR, 1.48; 95% CI, 0.62 to 3.54). The postoperative MCP-1 level showed similar trends of association as the preoperative MCP-1 level, but was no longer statistically significant after covariate adjustment.
During median follow-up of 2.9 years (IQR, 2.2 to 3.5 years), 119 participants (12%) died. Of the 119 deaths, 15 occurred during the index hospitalization. Median time from the operation to death for these in-hospital deaths was 10 days (IQR, 4 to 23 days). Participants in the highest preoperative and postoperative MCP-1 tertile had higher death rates than those in the lowest tertile (Table 3). After adjustment for baseline covariates, surgical characteristics, and eGFR, participants in the highest preoperative and postoperative MCP-1 tertiles had a higher risk of death than participants in the lowest preoperative and postoperative MCP-1 tertile (preoperative: HR, 1.82 [95%
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Table 2. Association of Monocyte Chemotactic Protein-1 With Acute Kidney Injurya
Time point
Tertile (MCP-1 level in pg/mL)
Odds Ratio (95% CI)b AKI events, No. (%)
Model 1
Model 2
AKI Pre-op
Post-op
Severe AKId Pre-op
Post-op
Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
95 (30) 93 (29) 133 (42)
1.76 (1.29–2.42) Referent 1.01 (0.72–1.42) 1.78 (1.28–2.47) 1.50 (1.21–1.85) Referent 1.41 (1.01–1.96) 1.65 (1.18–2.30)
1.36 (0.97–1.90) Referent 1.10 (0.76–1.59) 1.48 (1.04–2.11) 1.25 (0.98–1.58) Referent 1.27 (0.88–1.82) 1.29 (0.89–1.87)
1.27 (0.90–1.79) Referent 1.16 (0.80–1.68) 1.43 (1.00–2.05) 1.62 (1.03–2.56) Referent 0.87 (0.45–1.69) 1.63 (0.83–3.19)
91 (28) 114 (35) 124 (38)
Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
9 (3) 12 (4) 20 (6)
1.68 (0.86–3.27) Referent 1.34 (0.56–3.23) 2.31 (1.04–5.16) 1.88 (1.18–2.99) Referent 2.46 (1.06–5.70) 2.32 (1.00–5.42)
1.27 (0.59–2.72) Referent 1.21 (0.49–2.99) 1.62 (0.69–3.77) 1.57 (0.96–2.56) Referent 2.40 (1.02–5.69) 1.88 (0.78–4.53)
1.19 (0.55–2.60) Referent 1.15 (0.46–2.89) 1.48 (0.62–3.54) 2.07 (0.85–5.04) Referent 1.05 (0.23–4.84) 2.36 (0.55–10.03)
8 (3) 19 (6) 18 (6)
a For preoperative biomarkers: model 1 was adjusted for age, sex, race, nonelective operation, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and model 2 was model 1 plus the preoperative estimated glomerular filtration rate. For postoperative biomarkers: model 1 was adjusted for age, sex, race, cardiopulmonary bypass >120 minutes, nonelective operation, preoperative estimated glomerular filtration rate, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and b c Logistic regression. Defined as 0.3 mg/dL model 2 was model 1 þ change in serum creatinine from preoperative to peak þ baseline MCP-1 level. d or >50% rise in serum creatinine, or requiring dialysis. Defined as >100% rise in serum creatinine or requiring dialysis.
AKI ¼ acute kidney injury; preoperative; T ¼ tertile.
CI ¼ confidence interval;
MCP-1 ¼ monocyte chemotactic protein-1;
CI, 1.40 to 2.38]; postoperative: HR, 1.95 [95% CI, 1.09 to 3.49]; Fig 2). We noted similar results when the association of death was analyzed using the per-log increase in MCP-1 level (Table 3). We noted a similar association of MCP-1 level with long-term death after excluding participants with in-hospital deaths, except that the association of postoperative MCP-1 level with death was no
Post-op ¼ postoperative;
Pre-op ¼
longer statistically significant (Supplemental Table 4 and Supplemental Fig 2).
Comment Inflammation is associated with adverse outcomes after cardiac operations, and biomarkers are being evaluated
Table 3. Association of Monocyte Chemotactic Protein-1 With Deatha
Time point Pre-op
Post-op
Tertile (MCP-1 level in pg/mL) Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
Hazard Ratio (95% CI)c Death ratesb
33.4 44.3 72.9 37.3 45.9 67.5
Unadjusted
Model 1
Model 2
1.54 (1.18–2.01) Referent 1.33 (0.99–1.78) 2.14 (1.62–2.83) 1.56 (1.07–2.27) Referent 1.21 (0.87–1.70) 1.79 (0.96–3.33)
1.43 (1.08–1.90) Referent 1.34 (1.05–1.70) 1.86 (1.40–2.48) 1.54 (1.12–2.10) Referent 1.28 (1.03–1.59) 1.85 (1.11–3.08)
1.40 (1.09–1.81) Referent 1.32 (1.02–1.71) 1.82 (1.40–2.38) 1.59 (1.13–2.25) Referent 1.20 (0.93–1.55) 1.95 (1.09–3.49)
a
For preoperative biomarkers: model 1 was adjusted for age, sex, race, nonelective operation, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs. all others), and model 2 was model 1 þ preoperative estimated glomerular filtration rate. For postoperative biomarkers: model 1 was adjusted for age, sex, race, cardiopulmonary bypass >120 minutes, nonelective operation, preoperative estimated glomerular filtration rate, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and model 2 was model 1 þ b c Per 1,000 person-years. Cox proportional hazards model. change in serum creatinine from preoperative to peak þ baseline MCP-1 level.
CI ¼ confidence interval;
MCP-1 ¼ monocyte chemotactic protein-1;
Post-op ¼ postoperative;
Pre-op ¼ preoperative;
T ¼ tertile.
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c
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Fig 2. (A) Probability of death after a cardiac operation by preoperative monocyte chemotactic protein-1 (MCP-1) tertiles (T). (B) Probability of death after a cardiac operation by postoperative MCP-1 tertiles. MCP-1 tertile cutoffs (pg/mL): Preoperative: T1, 12 to 147; T2, 147 to 196; T3, 196 to 1,581. Postoperative: T1, 40 to 359; T2, 359 to 600; T3, 600 to 1,581. Median length of follow-up was 2.9 years (interquartile range, 2.2 to 3.5 years).
to detect patients with subclinical inflammation. Several trials of antiinflammatory interventions have been conducted in hopes of improving outcomes after cardiac operations [7, 9]. MCP-1 is a promising inflammatory biomarker that has been shown to increase in cardiac operations and is associated with adverse postoperative outcomes in small clinical studies. In our large, multicenter, prospective cohort, we hypothesized that perioperative plasma MCP-1 would be associated with adverse outcomes. Our study found that a higher plasma MCP-1 level was associated with increased in-hospital AKI and risk of death. Our findings suggest that in a subset of patients undergoing cardiac operations, unrecognized perioperative inflammation may contribute to higher postoperative death and that this inflammation can be detected by elevated plasma MCP-1 levels. MCP-1 (CCL-2) is upregulated in the setting of inflammation. MCP-1 is the ligand for CCR-2, and CCR-2 is present almost exclusively on monocytes. Thus, in the setting of inflammation, MCP-1 attracts monocytes out of the bone marrow and recruits them to inflammatory sites [19]. Although MCP-1 is elevated in various renal diseases, such as lupus nephritis, diabetic nephropathy, and
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transplant rejection, its role is not limited to the kidneys [19]. MCP-1 is elevated in various other conditions, including infection, allergic reactions, bone remodeling, atherosclerosis, and inflammatory bowel disease [20]. Given the pathogenic role of MCP-1 in various disorders, MCP-1 receptor blocker has been developed and is now in early-phase clinical trials [21]. There is preclinical and clinical evidence to suggest the role of MCP-1 as an inflammatory biomarker in cardiac operations. Preclinical and clinical studies show that MCP-1 is increased immediately after ischemiareperfusion injury and cardiac operations [10, 13]. Studies have used a decrease in the MCP-1 level as a surrogate marker for reduced postoperative inflammation from various interventions [13, 15]. MCP-1 level has also been associated with death in small studies. A study of 32 patients found a higher serum MCP-1 level was associated with 10-fold higher risk of death in acute respiratory distress syndrome [22]. Similarly, in a study of 2,270 patients with unstable coronary syndromes with 10 months’ follow-up, a higher MCP-1 level was associated with a 54% higher risk of death [23]. However, no study has examined the association of preoperative MCP-1 levels with death after cardiac operations. Similar to preclinical studies, we noted a 2.5-fold rise in MCP-1 after operations and that patients with a longer cardiopulmonary bypass time were more likely to have a higher postoperative MCP-1 level. Patients in the highest tertile of MCP-1 before and after the cardiac operation were at increased risk of dying postoperatively. Our results remained significant after adjustment for various confounders, including diabetes, hypertension, surgical characteristics, and eGFR. This association of a higher MCP-1 level with death has been shown in the setting of coronary artery disease [24, 25]. We believe that this increase in death in patients with a higher baseline and postoperative MCP-1 level may be due to unrecognized inflammation and resulting fibrosis in various tissues. Thus, although a major trial of untargeted antiinflammatory therapy showed null results in cardiac operations [9], MCP-1 may be able to select individuals who might benefit from targeted antiinflammatory therapy. Prior studies showed an association of elevated MCP-1 level with AKI in various settings [22, 26]. One small study of 100 individuals and 27% AKI events found a nonsignificant fourfold AKI risk for patients in the highest MCP1 tertile after the operation compared with the lowest tertile [14]. Our study of more than 900 patients sought to definitively establish this connection between MCP-1 and AKI. We found that the preoperative plasma MCP-1 level was associated with AKI and showed a similar, but statistically nonsignificant, association of the preoperative plasma MCP-1 level with severe AKI. The postoperative MCP-1 level showed similar associations as preoperative MCP-1 but was no longer statistically significant after we adjusted for demographics and surgical characteristics. Our study has several important strengths. This is the largest study examining the association of MCP-1 with important postcardiac surgical outcomes of AKI and death. Our sample size was adequate to detect clinically
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Dennis G. Moledina is a Yale Investigative Medicine PhD Program graduate student supported by Clinical and Translational Science Awards Grant UL1-TR-000142 from the National Center for Advancing Translational Sciences, a component of the National Institutes of Health (NIH). NIH (R01-HL-085757 to Chirag R. Parikh) funded the TRIBE-AKI Consortium. Chirag R. Parikh is supported by NIH grant K24-DK-090203 and by the P30-DK-079310-07 O’Brien Kidney Center Grant. Steven G. Coca is supported by NIH grant R01-DK-096549. Steven G Coca, Amit X Garg, and Chirag Parikh are members of the NIH-sponsored Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Consortium (U01-DK082185). The Institute for Clinical Evaluative Sciences (ICES), which is funded by the Ontario Ministry of Health and LongTerm Care (MOHLTC), supported this study. The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by NIH, ICES, or the Ontario MOHLTC is intended or should be inferred. Peter A. Kavsak received a reagent grant from Randox to perform this testing. The manufacturers did not have any role in the analysis samples, interpretation of results, or writing of this manuscript.
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predicts cardiovascular events after coronary artery bypass grafting surgery: a prospective observational study. Ann Card Anaesth 2009;12:127–32. Franke A, Lante W, Fackeldey V, et al. Pro-inflammatory cytokines after different kinds of cardio-thoracic surgical procedures: is what we see what we know? Eur J Cardiothorac Surg 2005;28:569–75. Rosner MH, Okusa MD. Acute kidney injury associated with cardiac surgery. Clin J Am Soc Nephrol 2006;1:19–32. Garg AX, Vincent J, Cuerden M, et al. Steroids in Cardiac Surgery (SIRS) trial: acute kidney injury substudy protocol of an international randomised controlled trial. BMJ Open 2014;4:e004842. Inoue T, Abe C, Sung SS, et al. Vagus nerve stimulation mediates protection from kidney ischemia-reperfusion injury through a7nAChRþ splenocytes. J Clin Invest 2016;126:1939–52. Whitlock RP, Devereaux PJ, Teoh KH, et al. Methylprednisolone in patients undergoing cardiopulmonary bypass (SIRS): a randomised, double-blind, placebo-controlled trial. Lancet 2015;386:1243–53. Shimamoto A, Chong AJ, Yada M, et al. Inhibition of Toll-like receptor 4 with eritoran attenuates myocardial ischemiareperfusion injury. Circulation 2006;114(1 Suppl):I270–4. Frangogiannis NG, Dewald O, Xia Y, et al. Critical role of monocyte chemoattractant protein-1/CC chemokine ligand 2 in the pathogenesis of ischemic cardiomyopathy. Circulation 2007;115:584–92. de Mendonca-Filho HT, Pereira KC, Fontes M, et al. Circulating inflammatory mediators and organ dysfunction after cardiovascular surgery with cardiopulmonary bypass: a prospective observational study. Crit Care 2006;10:R46. Lindholm EE, Aune E, Seljeflot I, Otterstad JE, Kirkeboen KA. Biomarkers of inflammation in major vascular surgery: a prospective randomised trial. Acta Anaesthesiol Scand 2015;59:773–87. Ejaz AA, Kambhampati G, Ejaz NI, et al. Post-operative serum uric acid and acute kidney injury. J Nephrol 2012;25: 497–505. Drapalova J, Kopecky P, Bartlova M, et al. The influence of deep hypothermia on inflammatory status, tissue hypoxia and endocrine function of adipose tissue during cardiac surgery. Cryobiology 2014;68:269–75. Parikh CR, Coca SG, Thiessen-Philbrook H, et al. Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. J Am Soc Nephrol 2011;22:1748–57. Coca SG, Garg AX, Thiessen-Philbrook H, et al. Urinary biomarkers of AKI and mortality 3 years after cardiac surgery. J Am Soc Nephrol 2014;25:1063–71. Moledina DG, Parikh CR, Garg AX, et al. Association of perioperative plasma neutrophil gelatinase-associated lipocalin levels with 3-year mortality after cardiac surgery: a prospective observational cohort study. PLoS One 2015;10: e0129619. Haller H, Bertram A, Nadrowitz F, Menne J. Monocyte chemoattractant protein-1 and the kidney. Curr Opin Nephrol Hypertens 2016;25:42–9. Yadav A, Saini V, Arora S. MCP-1: chemoattractant with a role beyond immunity: a review. Clin Chim Acta 2010;411: 1570–9. Kashyap S, Warner GM, Hartono SP, et al. Blockade of CCR2 reduces macrophage influx and development of chronic renal damage in murine renovascular hypertension. Am J Physiol Renal Physiol 2016;310:F372–84. Bautista E, Arcos M, Jimenez-Alvarez L, et al. Angiogenic and inflammatory markers in acute respiratory distress syndrome and renal injury associated to A/H1N1 virus infection. Exp Mol Pathol 2013;94:486–92. de Lemos JA, Morrow DA, Sabatine MS, et al. Association between plasma levels of monocyte chemoattractant protein-1
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meaningful difference in outcomes. We were also able to reach 100% ascertainment of vital status. We adjusted our analysis for important covariates. Finally, the personnel who performed the biomarker measurement were blinded to clinical data. Our study also has several limitations. We do not have data on cause of death. However, all-cause death is an important and clinically meaningful outcome. We did not have other traditional inflammatory markers, such as erythrocyte sedimentation rate or C-reactive protein, to compare with MCP-1. However, one study of patients with acute coronary syndrome demonstrated the ability of MCP-1 to predict long-term death in addition to Creactive protein, interleukin 6, troponin I, and N-terminal pro-brain natriuretic peptide [25]. In conclusion, our study shows that elevated perioperative plasma MCP-1 is associated with a higher AKI and risk of death after cardiac operations. MCP-1 may be a useful inflammatory biomarker that can be used to identify high-risk individuals for antiinflammatory interventions in cardiac operations.
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and long-term clinical outcomes in patients with acute coronary syndromes. Circulation 2003;107:690–5. 24. Tunon J, Blanco-Colio L, Cristobal C, et al. Usefulness of a combination of monocyte chemoattractant protein-1, galectin-3, and N-terminal probrain natriuretic peptide to predict cardiovascular events in patients with coronary artery disease. Am J Cardiol 2014;113:434–40.
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25. Kavsak PA, Ko DT, Newman AM, et al. Risk stratification for heart failure and death in an acute coronary syndrome population using inflammatory cytokines and N-terminal pro-brain natriuretic peptide. Clin Chem 2007;53:2112–8. 26. Bihorac A, Baslanti TO, Cuenca AG, et al. Acute kidney injury is associated with early cytokine changes after trauma. J Trauma Acute Care Surg 2013;74:1005–13.
INVITED COMMENTARY Dennis G. Moledina and the TRIBE-AKI Consortium [1] present a prospective observational multicenter study of patients undergoing cardiac surgery. They evaluated preoperative and postoperative levels of the novel inflammatory biomarker monocyte chemotactic protein-1 (MCP-1) and found that higher plasma levels preoperatively and postoperatively were associated with increased risk of acute kidney injury (AKI) and risk of death. The data were generated from the Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury (TRIBE-AKI) cohort comprising a large number of patients with at least one risk factor for AKI. This database has helped to gain important insights into the problem of AKI following cardiac surgery [2]. AKI is a typical and frequent complication of both onand off-pump cardiac surgery increasing postoperative morbidity and mortality. Inflammatory response has been shown to cause systemic tissue and organ damage. Renal impairment reflects such effects, especially in high-risk patients. This important study focusing on a biomarker associated with inflammation supports our understanding of the pathophysiology of AKI. The key message is that measuring MCP-1 preoperatively might help with early identification of patients with an increased risk of AKI and death due to inflammation. Therefore, MCP-1 seems to be a valuable tool in preoperative risk evaluation, helping to inform the patients and plan the perioperative management. Unfortunately, significant efforts to mitigate inflammation in cardiac surgery have failed. Researchers
Ó 2017 by The Society of Thoracic Surgeons Published by Elsevier Inc.
discuss a delay of diagnosis of AKI using creatinine and other parameters as one possible attributing factor. Reliable biomarkers might help clinicians to detect upcoming AKI earlier and act accordingly. MCP-1 obviously could be useful in this respect. However, the question remains how to manage patients to reduce the risk of AKI. Further research should try to find answers possibly using a multimodal approach focusing on perfusion and controlling inflammatory response. MCP-1 is an important marker to evaluate the effect of therapeutic interventions in the fight against post–cardiac surgery inflammatory damage and AKI. Stefan P. Wirtz, MD Department of Intensive Care Medicine HELIOS Hospital Bad Saarow Pieskower Straße 33 D-15526 Bad Saarow, Germany email: [email protected]
References 1. Moledina DG, Isguven S, McArthur E, et al. Plasma monocyte chemotactic protein-1 is associated with acute kidney injury and death after cardiac operations. Ann Thorac Surg 2017;104: 613–20. 2. Parikh CR, Coca SG, Thiessen-Philbrook H, et al. Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. J Am Soc Nephrol 2011;22:1748–57.
0003-4975/$36.00 http://dx.doi.org/10.1016/j.athoracsur.2016.12.016
Background. Monocyte chemotactic protein-1 (MCP-1; chemokine C-C ligand-2 [CCL-2]) is upregulated in ischemia-reperfusion injury and is a promising biomarker of inflammation in cardiac operations. Methods. We measured preoperative and postoperative plasma MCP-1 levels in adults undergoing cardiac operations to evaluate the association of perioperative MCP-1 levels with acute kidney injury (AKI) and death in Translational Research Investigating Biomarker Endpoints in AKI (TRIBE-AKI), a prospective, multicenter, observational cohort. Results. Of the 972 participants in the study, AKI developed in 329 (34%), and severe AKI developed in 45 (5%). During a median follow-up of 2.9 years (interquartile range, 2.2 to 3.5 years), 119 participants (12%) died. MCP-1 levels were significantly higher in those who developed AKI and died than in those without AKI and death. Participants with a preoperative MCP-1 level in the highest tertile (>196 pg/mL) had an increased AKI risk
than those in the lowest tertile (<147 pg/mL; odds ratio [OR], 1.43l; 95% confidence interval [CI], 1.00 to 2.05). The association appeared similar but was not significant for the severe AKI outcome (OR, 1.48; 95% CI, 0.62 to 3.54). Compared with participants with preoperative MCP-1 level in the lowest tertile, those in the highest tertile had higher adjusted risk of death (hazard ratio, 1.82; 95% CI, 1.40 to 2.38). Similarly, participants in the highest tertile had a higher adjusted risk of death (hazard ratio, 1.95; 95% CI, 1.09–3.49) than those with a postoperative MCP-1 level in the lowest tertile. Conclusions. Higher plasma MCP-1 is associated with increased AKI and risk of death after cardiac operations. MCP-1 could be used as a biomarker to identify high-risk patients for potential AKI prevention strategies in the setting of cardiac operations.
A
improve patient outcomes and health care costs by targeted interventions. Preoperative and intraoperative inflammation is recognized as an important predictor of postoperative
pproximately 2 million cardiac operations are performed each year around the world. The postoperative complication of acute kidney injury (AKI) occurs in about 280,000 (14%) of these patients, which leads to increased hospital length of stay and health care expenditure [1–3]. Identification of patients who are most susceptible to postoperative complications could
(Ann Thorac Surg 2017;104:613–20) Ó 2017 by The Society of Thoracic Surgeons
Dr Kavsak discloses being named an inventor in acute heart failure patent #458491871B2 filed by McMaster University; Dr Parikh discloses a financial relationship with AbbVie and Genfit.
Accepted for publication Nov 7, 2016. Presented at The American Society of Nephrology Kidney Week 2016, Chicago, IL, Nov 15–20, 2016. Address correspondence to Dr Parikh, Yale Program of Applied Translational Research, 60 Temple St, Ste 6C, New Haven, CT 06510; email: [email protected].
Ó 2017 by The Society of Thoracic Surgeons Published by Elsevier Inc.
The Supplemental Material can be viewed in the online version of this article [http://dx.doi.org/10.1016/j. athoracsur.2016.11.036] on http://www.annalsthoracic surgery.org.
0003-4975/$36.00 http://dx.doi.org/10.1016/j.athoracsur.2016.11.036
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Plasma Monocyte Chemotactic Protein-1 Is Associated With Acute Kidney Injury and Death After Cardiac Operations
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complications after cardiac operations [4, 5]. Preoperative inflammation primes the kidney and other organs for intraoperative injury, and elevations of preoperative inflammatory markers are associated with adverse postoperative outcomes. Cardiac operations are associated with periods of hypoperfusion, tissue ischemia, contact of blood components with the bypass circuit, nonpulsatile blood flow, and operative trauma that all contribute to a proinflammatory state [6]. Given the important role of inflammation in cardiac operations, trials of antiinflammatory interventions have been conducted in hopes of improving postsurgical outcomes [7–9]. Studies are also attempting to discover biomarkers that can identify patients with subclinical inflammation who might be candidates for antiinflammatory therapy to mitigate the risk of cardiac operations. Monocyte chemotactic protein-1 (MCP-1; chemokine C-C ligand-2 [CCR-2]) is a member of the chemokine family. Monocytes express CCR-2, the receptor for MCP-1, and MCP-1 regulates trafficking of monocytes from the bone marrow to inflamed tissue in response to inflammatory signals. In preclinical studies, MCP-1 expression was upregulated immediately after ischemia-reperfusion injury [10], and MCP-1 inhibition was associated with lower cardiac fibrosis [11]. Small studies in humans have shown MCP-1 expression increased immediately after cardiac operations [12, 13], and MCP-1 elevation was associated with AKI [14]. Studies have also used MCP-1 as a surrogate marker to quantify intraoperative inflammation after various interventions [13, 15]; however, the association of MCP-1 with outcomes after cardiac operations has not been examined in a large, prospective cohort. We hypothesized that elevated perioperative plasma MCP-1 would be a marker of unrecognized inflammation and would be associated with a higher risk of adverse outcomes in patients undergoing cardiac operations. In this study, we measured MCP-1 levels before and after cardiac operations in participants of the Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury (TRIBE-AKI) cohort, and tested its association with AKI and death.
Patients and Methods Participants The TRIBE-AKI study is a prospective, multicenter, observational cohort of adults at high risk for developing AKI who underwent cardiac operations (coronary artery bypass grafting [CABG] valve operations, or both). Full study details have been previously published [16–18]. In brief, we enrolled participants with at least one risk factor for AKI at 5 academic medical centers in North America (details in the Supplemental Material). Written informed consent was obtained from all patients or their proxy decision makers. The TRIBE-AKI study was approved by the institutional review boards at each participating institution. We collected preoperative characteristics, operative details, and postoperative complications using definitions of the Society of Thoracic Surgeons [16].
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Exposures The exposures for this study were (1) the preoperative concentration of plasma MCP-1 levels and (2) the peak postoperative concentration in days 1 to 3 postoperatively. Blood specimens were collected preoperatively and daily for up to 5 days postoperatively. After a single freeze-thaw cycle of stored plasma samples, we measured MCP-1 on the Randox Evidence Investigator using a Randox-developed custom cytokine array (Randox Laboratories Ltd, Crumlin, United Kingdom) with a detection range of 12 to 1,580 pg/mL and an intraassay coefficient of variation of 10% to 16% using the manufacturer’s specifications. The personnel measuring the biomarkers were blinded to clinical outcomes.
Outcomes The main outcomes for this study were occurrence of in-hospital AKI and all-cause death at complete cohort follow-up. AKI was defined as serum creatinine of 0.3 mg/dL, a rise in serum creatinine from baseline exceeding 50%, or requiring dialysis during hospitalization. Severe AKI was defined as a more than 100% rise in serum creatinine from baseline or requiring dialysis during hospitalization. Of the 329 AKI events, 327 (99%) occurred within 7 days of the operation. The magnitude of changes in serum creatinine for AKI and severe AKI in our study correspond to Kidney Disease: Improving Global Outcomes AKI stage 1 and AKI stage 2 or higher, respectively. All preoperative creatinine values were measured within 2 months before the operation. We used the Chronic Kidney Disease Epidemiology Collaboration equation to determine the preoperative estimated glomerular filtration rate (eGFR). We obtained death data after discharge through various mechanisms and cross-referenced, when possible. For United States participants, we telephoned patients’ homes, searched the National Death Index, and received hospital records. For participants from Canada, we used telephone calls and data held at the Institute for Clinical Evaluative Sciences to acquire vital status. These data sets were linked using unique, encoded identifiers and analyzed at the Institute for Clinical Evaluative Sciences. The death status and date of death were recorded through December 31, 2012. Vital status ascertainment on the cohort was 100%.
Statistical Analysis We performed descriptive statistics and report continuous variables as mean SD or median (interquartile range [IQR]) and categoric variables as frequency (percentage). Small cell counts are only presented for data collected by TRIBE-AKI (not from Institute for Clinical Evaluative Sciences data). Continuous variables were compared using the Wilcoxon rank sum test or the Fisher exact test, as appropriate. Categoric variables were compared using the c2 test. We performed preoperative and postoperative MCP-1 correlation with each other and with the eGFR from corresponding time points using Spearman correlations. We divided the population into
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Table 1. Patient Characteristics by Preoperative Monocyte Chemotactic Protein-1 Tertiles MCP-1 Tertileb
Demographics Age at operation, mean (SD), y Men, No. (%) White race, No. (%) Medical history Diabetes, No. (%) Hypertension, No. (%) Heart failure, No. (%) LVEF <0.40, No. (%) Previous myocardial infarction, No. (%) eGFR mean (SD), mL/min/1.73m2 eGFR <60 mL/min/1.73m2, No. (%) Serum creatinine, median (IQR), mg/dL Urine albumin-to-creatinine, No. (%) 30–300 >300 Surgical characteristics Elective operation, No. (%) Operation type, No. (%) CABG or valve Off-pump Perfusion time, mean (SD), min Cross-clamp time, mean (SD), min
Overall (N ¼ 957)
Lowest (T1) (n ¼ 319)
Middle (T2) (n ¼ 320)
Highest (T3) (n ¼ 318)
71.7 (9.9) 652 (68.1) 894 (93.4)
70.9 (10.4) 227 (71.2) 307 (96.2)
72.6 (8.9) 210 (65.6) 298 (93.1)
71.6 (10.2) 215 (67.6) 289 (90.9)
379 758 232 98 247 67.5 331 1.0
104 240 73 35 77 72.8 69 1.0
123 249 67 30 83 66.2 124 1.0
152 269 92 33 87 63.3 138 1.1
(39.6) (79.2) (24.2) (10.2) (25.8) (19.5) (35) (0.9–1.2)
(32.6) (75.2) (22.9) (11.0) (24.1) (17.9) (22) (0.8–1.1)
(38.4) (77.8) (20.9) (9.4) (25.9) (18.1) (39) (0.9–1.2)
(47.8) (84.6) (28.9) (10.4) (27.4) (21.2) (43) (0.9–1.4)
265 (27.7) 59 (6.2)
85 (26.6) 13 (4.1)
83 (25.9) 27 (8.4)
97 (30.5) 19 (6.0)
766 (80.0)
262 (82.1)
261 (81.6)
243 (76.4)
748 86 112.3 76.7
(78.2) (9.0) (56.9) (43.4)
259 38 106.9 73.6
(81.2) (11.9) (58.6) (44.7)
247 24 109.4 75.4
(77.2) (7.5) (53.2) (39.2)
242 24 120.7 81.2
(76.1) (7.5) (58.0) (45.8)
p Valuec 0.08 0.32 0.02 <0.001 0.01 0.05 0.80 0.02 <0.001 <0.001 <0.001 0.08
0.14 0.33 0.20 0.005 0.08
a Small cell counts are only presented for data collected by Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury (TRIBE-AKI) b Preoperative MCP-1 tertile (T) cutoffs (pg/mL): T1, 12 to 147; T2, 147 to and not from Institute for Clinical Evaluative Sciences (ICES) data holdings. c 196; T3, 196 to 1,581. Continuous variables are compared using Wilcoxon rank sum test or the Fisher exact test, and categoric variables are compared using c2 test.
CABG ¼ coronary artery bypass grafting; eGFR ¼ estimated glomerular filtration rate; ejection fraction; MCP-1 ¼ monocyte chemotactic protein-1.
MCP-1 concentration tertiles at preoperative and postoperative time points. We used logistic regression to determine the association of MCP-1 tertiles with the AKI outcomes, with the lowest tertile as the reference group. For the death outcome, we used Cox proportional hazards regression to estimate the hazard ratio of death, with the lowest tertile of MCP-1 as the reference group. For the preoperative MCP-1 models, we adjusted the analyses for the following covariates: demographics (age, sex, race), comorbidities (diabetes, hypertension, heart failure, myocardial infarction), type of operation (CABG or valve vs all others), and evidence of kidney disease (preoperative albumin-to-creatinine ratio, preoperative eGFR). For the postoperative MCP-1 models, we additionally adjusted for surgical characteristics (cardiopulmonary bypass time >120 minutes, nonelective operation), change in renal function (using change in serum creatinine), and baseline MCP-1 level. We performed two supplementary analyses: (1) evaluation of association of each log increase in MCP-1 level with AKI and death, and (2) evaluation of association of MCP-1 tertiles with death after excluding patients who died in-hospital. We used
IQR ¼ interquartile range;
LVEF ¼ left ventricular
SAS 9.3 (SAS Institute, Cary, NC) and R 2.10.1 (R Foundation for Statistical Computing, Vienna, Austria) software to perform the analysis.
Results We enrolled 1,219 patients to the TRIBE-AKI study from July 2007 through December 2009 (Supplemental Fig 1). Of these, 972 participants (68% men) with an adequate plasma sample for MCP-1 level measurement were included in the analysis. The mean age was 71 years. There were baseline participant differences across the preoperative plasma MCP-1 tertiles (Table 1). Patients in the highest tertile of MCP-1 were less likely to be white, had a lower mean preoperative eGFR, and were more likely to have diabetes and hypertension. Differences in baseline characteristics by postoperative MCP-1 tertiles were similar to the preoperative tertiles. Patients with a longer cross-clamp time and who underwent on-pump operations were more likely to be in the highest tertile of postoperative MCP-1 (Supplemental Table 1).
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Characteristica
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Fig 1. (A) Monocyte chemotactic protein-1 (MCP-1) levels are significantly higher in patients with acute kidney injury (AKI). *p < 0.001 at all timepoints. (B) MCP-1 levels are significantly higher in those who died. *p ¼ 0.001 on the preoperative time point, p ¼ 0.02 on the first postoperative day, and p < 0.001 at all other time points. The top and bottom of the box represent the interquartile range, and the horizontal line represents the median. Day 1 refers to 0 to 6 hours after the operation, day 2 corresponds to 48 hours after the operation, and day 3 corresponds to 72 hours after the operation.
Perioperative Plasma MCP-1 Levels
Perioperative MCP-1 Levels and AKI Duration
MCP-1 increased from a median level of 171 pg/mL (IQR, 135 to 212 pg/mL) preoperatively to a peak of 450 pg/mL (IQR, 307 to 735 pg/mL) 0 to 6 hours after the operation (Fig 1). MCP-1 levels were higher in participants who developed AKI and died than in participants without AKI who survived (Supplemental Table 2). Preoperative MCP-1 positively correlated with postoperative MCP-1 (R2 ¼ 0.31) and negatively correlated with eGFR (R2 ¼ –0.22).
Of the 329 participants with AKI, the duration of AKI was 1 to 2 days in 206 (63%), 3 to 6 days in 98 (29%), and 7 days or longer in 25 (8%). The highest preoperative MCP-1 tertile was associated with longer AKI duration compared with the lowest tertile (OR, 1.45; 95% CI, 1.03 to 2.05; Supplemental Table 3). The highest postoperative MCP-1 tertile showed a trend toward longer AKI duration compared with the lowest tertile (OR, 1.36; 95% CI, 0.89 to 2.08).
Perioperative MCP-1 Levels and AKI Risk
Perioperative MCP-1 Levels and Risk of Death
Of the 972 participants, AKI developed in 329 (34%), severe AKI developed in 45 (5%), and 13 (1%) received acute dialysis. After adjusting for baseline characteristics and preoperative eGFR, the highest tertile of preoperative MCP-1 was associated with a higher odds ratio (OR) of AKI (OR, 1.43; 95% confidence interval [CI], 1.00 to 2.05; Table 2). The association appeared similar but was not significant for severe AKI (OR, 1.48; 95% CI, 0.62 to 3.54). The postoperative MCP-1 level showed similar trends of association as the preoperative MCP-1 level, but was no longer statistically significant after covariate adjustment.
During median follow-up of 2.9 years (IQR, 2.2 to 3.5 years), 119 participants (12%) died. Of the 119 deaths, 15 occurred during the index hospitalization. Median time from the operation to death for these in-hospital deaths was 10 days (IQR, 4 to 23 days). Participants in the highest preoperative and postoperative MCP-1 tertile had higher death rates than those in the lowest tertile (Table 3). After adjustment for baseline covariates, surgical characteristics, and eGFR, participants in the highest preoperative and postoperative MCP-1 tertiles had a higher risk of death than participants in the lowest preoperative and postoperative MCP-1 tertile (preoperative: HR, 1.82 [95%
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Table 2. Association of Monocyte Chemotactic Protein-1 With Acute Kidney Injurya
Time point
Tertile (MCP-1 level in pg/mL)
Odds Ratio (95% CI)b AKI events, No. (%)
Model 1
Model 2
AKI Pre-op
Post-op
Severe AKId Pre-op
Post-op
Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
95 (30) 93 (29) 133 (42)
1.76 (1.29–2.42) Referent 1.01 (0.72–1.42) 1.78 (1.28–2.47) 1.50 (1.21–1.85) Referent 1.41 (1.01–1.96) 1.65 (1.18–2.30)
1.36 (0.97–1.90) Referent 1.10 (0.76–1.59) 1.48 (1.04–2.11) 1.25 (0.98–1.58) Referent 1.27 (0.88–1.82) 1.29 (0.89–1.87)
1.27 (0.90–1.79) Referent 1.16 (0.80–1.68) 1.43 (1.00–2.05) 1.62 (1.03–2.56) Referent 0.87 (0.45–1.69) 1.63 (0.83–3.19)
91 (28) 114 (35) 124 (38)
Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
9 (3) 12 (4) 20 (6)
1.68 (0.86–3.27) Referent 1.34 (0.56–3.23) 2.31 (1.04–5.16) 1.88 (1.18–2.99) Referent 2.46 (1.06–5.70) 2.32 (1.00–5.42)
1.27 (0.59–2.72) Referent 1.21 (0.49–2.99) 1.62 (0.69–3.77) 1.57 (0.96–2.56) Referent 2.40 (1.02–5.69) 1.88 (0.78–4.53)
1.19 (0.55–2.60) Referent 1.15 (0.46–2.89) 1.48 (0.62–3.54) 2.07 (0.85–5.04) Referent 1.05 (0.23–4.84) 2.36 (0.55–10.03)
8 (3) 19 (6) 18 (6)
a For preoperative biomarkers: model 1 was adjusted for age, sex, race, nonelective operation, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and model 2 was model 1 plus the preoperative estimated glomerular filtration rate. For postoperative biomarkers: model 1 was adjusted for age, sex, race, cardiopulmonary bypass >120 minutes, nonelective operation, preoperative estimated glomerular filtration rate, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and b c Logistic regression. Defined as 0.3 mg/dL model 2 was model 1 þ change in serum creatinine from preoperative to peak þ baseline MCP-1 level. d or >50% rise in serum creatinine, or requiring dialysis. Defined as >100% rise in serum creatinine or requiring dialysis.
AKI ¼ acute kidney injury; preoperative; T ¼ tertile.
CI ¼ confidence interval;
MCP-1 ¼ monocyte chemotactic protein-1;
CI, 1.40 to 2.38]; postoperative: HR, 1.95 [95% CI, 1.09 to 3.49]; Fig 2). We noted similar results when the association of death was analyzed using the per-log increase in MCP-1 level (Table 3). We noted a similar association of MCP-1 level with long-term death after excluding participants with in-hospital deaths, except that the association of postoperative MCP-1 level with death was no
Post-op ¼ postoperative;
Pre-op ¼
longer statistically significant (Supplemental Table 4 and Supplemental Fig 2).
Comment Inflammation is associated with adverse outcomes after cardiac operations, and biomarkers are being evaluated
Table 3. Association of Monocyte Chemotactic Protein-1 With Deatha
Time point Pre-op
Post-op
Tertile (MCP-1 level in pg/mL) Log T1 (12–147) T2 (147–196) T3 (196–1,581) Log T1 (40–359) T2 (359–600) T3 (600–1,581)
Hazard Ratio (95% CI)c Death ratesb
33.4 44.3 72.9 37.3 45.9 67.5
Unadjusted
Model 1
Model 2
1.54 (1.18–2.01) Referent 1.33 (0.99–1.78) 2.14 (1.62–2.83) 1.56 (1.07–2.27) Referent 1.21 (0.87–1.70) 1.79 (0.96–3.33)
1.43 (1.08–1.90) Referent 1.34 (1.05–1.70) 1.86 (1.40–2.48) 1.54 (1.12–2.10) Referent 1.28 (1.03–1.59) 1.85 (1.11–3.08)
1.40 (1.09–1.81) Referent 1.32 (1.02–1.71) 1.82 (1.40–2.38) 1.59 (1.13–2.25) Referent 1.20 (0.93–1.55) 1.95 (1.09–3.49)
a
For preoperative biomarkers: model 1 was adjusted for age, sex, race, nonelective operation, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs. all others), and model 2 was model 1 þ preoperative estimated glomerular filtration rate. For postoperative biomarkers: model 1 was adjusted for age, sex, race, cardiopulmonary bypass >120 minutes, nonelective operation, preoperative estimated glomerular filtration rate, diabetes, hypertension, center, heart failure, myocardial infarction, preoperative urine albumin-to-creatinine ratio, and type of operation (coronary artery bypass grafting or valve vs all others), and model 2 was model 1 þ b c Per 1,000 person-years. Cox proportional hazards model. change in serum creatinine from preoperative to peak þ baseline MCP-1 level.
CI ¼ confidence interval;
MCP-1 ¼ monocyte chemotactic protein-1;
Post-op ¼ postoperative;
Pre-op ¼ preoperative;
T ¼ tertile.
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c
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Fig 2. (A) Probability of death after a cardiac operation by preoperative monocyte chemotactic protein-1 (MCP-1) tertiles (T). (B) Probability of death after a cardiac operation by postoperative MCP-1 tertiles. MCP-1 tertile cutoffs (pg/mL): Preoperative: T1, 12 to 147; T2, 147 to 196; T3, 196 to 1,581. Postoperative: T1, 40 to 359; T2, 359 to 600; T3, 600 to 1,581. Median length of follow-up was 2.9 years (interquartile range, 2.2 to 3.5 years).
to detect patients with subclinical inflammation. Several trials of antiinflammatory interventions have been conducted in hopes of improving outcomes after cardiac operations [7, 9]. MCP-1 is a promising inflammatory biomarker that has been shown to increase in cardiac operations and is associated with adverse postoperative outcomes in small clinical studies. In our large, multicenter, prospective cohort, we hypothesized that perioperative plasma MCP-1 would be associated with adverse outcomes. Our study found that a higher plasma MCP-1 level was associated with increased in-hospital AKI and risk of death. Our findings suggest that in a subset of patients undergoing cardiac operations, unrecognized perioperative inflammation may contribute to higher postoperative death and that this inflammation can be detected by elevated plasma MCP-1 levels. MCP-1 (CCL-2) is upregulated in the setting of inflammation. MCP-1 is the ligand for CCR-2, and CCR-2 is present almost exclusively on monocytes. Thus, in the setting of inflammation, MCP-1 attracts monocytes out of the bone marrow and recruits them to inflammatory sites [19]. Although MCP-1 is elevated in various renal diseases, such as lupus nephritis, diabetic nephropathy, and
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transplant rejection, its role is not limited to the kidneys [19]. MCP-1 is elevated in various other conditions, including infection, allergic reactions, bone remodeling, atherosclerosis, and inflammatory bowel disease [20]. Given the pathogenic role of MCP-1 in various disorders, MCP-1 receptor blocker has been developed and is now in early-phase clinical trials [21]. There is preclinical and clinical evidence to suggest the role of MCP-1 as an inflammatory biomarker in cardiac operations. Preclinical and clinical studies show that MCP-1 is increased immediately after ischemiareperfusion injury and cardiac operations [10, 13]. Studies have used a decrease in the MCP-1 level as a surrogate marker for reduced postoperative inflammation from various interventions [13, 15]. MCP-1 level has also been associated with death in small studies. A study of 32 patients found a higher serum MCP-1 level was associated with 10-fold higher risk of death in acute respiratory distress syndrome [22]. Similarly, in a study of 2,270 patients with unstable coronary syndromes with 10 months’ follow-up, a higher MCP-1 level was associated with a 54% higher risk of death [23]. However, no study has examined the association of preoperative MCP-1 levels with death after cardiac operations. Similar to preclinical studies, we noted a 2.5-fold rise in MCP-1 after operations and that patients with a longer cardiopulmonary bypass time were more likely to have a higher postoperative MCP-1 level. Patients in the highest tertile of MCP-1 before and after the cardiac operation were at increased risk of dying postoperatively. Our results remained significant after adjustment for various confounders, including diabetes, hypertension, surgical characteristics, and eGFR. This association of a higher MCP-1 level with death has been shown in the setting of coronary artery disease [24, 25]. We believe that this increase in death in patients with a higher baseline and postoperative MCP-1 level may be due to unrecognized inflammation and resulting fibrosis in various tissues. Thus, although a major trial of untargeted antiinflammatory therapy showed null results in cardiac operations [9], MCP-1 may be able to select individuals who might benefit from targeted antiinflammatory therapy. Prior studies showed an association of elevated MCP-1 level with AKI in various settings [22, 26]. One small study of 100 individuals and 27% AKI events found a nonsignificant fourfold AKI risk for patients in the highest MCP1 tertile after the operation compared with the lowest tertile [14]. Our study of more than 900 patients sought to definitively establish this connection between MCP-1 and AKI. We found that the preoperative plasma MCP-1 level was associated with AKI and showed a similar, but statistically nonsignificant, association of the preoperative plasma MCP-1 level with severe AKI. The postoperative MCP-1 level showed similar associations as preoperative MCP-1 but was no longer statistically significant after we adjusted for demographics and surgical characteristics. Our study has several important strengths. This is the largest study examining the association of MCP-1 with important postcardiac surgical outcomes of AKI and death. Our sample size was adequate to detect clinically
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Dennis G. Moledina is a Yale Investigative Medicine PhD Program graduate student supported by Clinical and Translational Science Awards Grant UL1-TR-000142 from the National Center for Advancing Translational Sciences, a component of the National Institutes of Health (NIH). NIH (R01-HL-085757 to Chirag R. Parikh) funded the TRIBE-AKI Consortium. Chirag R. Parikh is supported by NIH grant K24-DK-090203 and by the P30-DK-079310-07 O’Brien Kidney Center Grant. Steven G. Coca is supported by NIH grant R01-DK-096549. Steven G Coca, Amit X Garg, and Chirag Parikh are members of the NIH-sponsored Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Consortium (U01-DK082185). The Institute for Clinical Evaluative Sciences (ICES), which is funded by the Ontario Ministry of Health and LongTerm Care (MOHLTC), supported this study. The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by NIH, ICES, or the Ontario MOHLTC is intended or should be inferred. Peter A. Kavsak received a reagent grant from Randox to perform this testing. The manufacturers did not have any role in the analysis samples, interpretation of results, or writing of this manuscript.
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meaningful difference in outcomes. We were also able to reach 100% ascertainment of vital status. We adjusted our analysis for important covariates. Finally, the personnel who performed the biomarker measurement were blinded to clinical data. Our study also has several limitations. We do not have data on cause of death. However, all-cause death is an important and clinically meaningful outcome. We did not have other traditional inflammatory markers, such as erythrocyte sedimentation rate or C-reactive protein, to compare with MCP-1. However, one study of patients with acute coronary syndrome demonstrated the ability of MCP-1 to predict long-term death in addition to Creactive protein, interleukin 6, troponin I, and N-terminal pro-brain natriuretic peptide [25]. In conclusion, our study shows that elevated perioperative plasma MCP-1 is associated with a higher AKI and risk of death after cardiac operations. MCP-1 may be a useful inflammatory biomarker that can be used to identify high-risk individuals for antiinflammatory interventions in cardiac operations.
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25. Kavsak PA, Ko DT, Newman AM, et al. Risk stratification for heart failure and death in an acute coronary syndrome population using inflammatory cytokines and N-terminal pro-brain natriuretic peptide. Clin Chem 2007;53:2112–8. 26. Bihorac A, Baslanti TO, Cuenca AG, et al. Acute kidney injury is associated with early cytokine changes after trauma. J Trauma Acute Care Surg 2013;74:1005–13.
INVITED COMMENTARY Dennis G. Moledina and the TRIBE-AKI Consortium [1] present a prospective observational multicenter study of patients undergoing cardiac surgery. They evaluated preoperative and postoperative levels of the novel inflammatory biomarker monocyte chemotactic protein-1 (MCP-1) and found that higher plasma levels preoperatively and postoperatively were associated with increased risk of acute kidney injury (AKI) and risk of death. The data were generated from the Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury (TRIBE-AKI) cohort comprising a large number of patients with at least one risk factor for AKI. This database has helped to gain important insights into the problem of AKI following cardiac surgery [2]. AKI is a typical and frequent complication of both onand off-pump cardiac surgery increasing postoperative morbidity and mortality. Inflammatory response has been shown to cause systemic tissue and organ damage. Renal impairment reflects such effects, especially in high-risk patients. This important study focusing on a biomarker associated with inflammation supports our understanding of the pathophysiology of AKI. The key message is that measuring MCP-1 preoperatively might help with early identification of patients with an increased risk of AKI and death due to inflammation. Therefore, MCP-1 seems to be a valuable tool in preoperative risk evaluation, helping to inform the patients and plan the perioperative management. Unfortunately, significant efforts to mitigate inflammation in cardiac surgery have failed. Researchers
Ó 2017 by The Society of Thoracic Surgeons Published by Elsevier Inc.
discuss a delay of diagnosis of AKI using creatinine and other parameters as one possible attributing factor. Reliable biomarkers might help clinicians to detect upcoming AKI earlier and act accordingly. MCP-1 obviously could be useful in this respect. However, the question remains how to manage patients to reduce the risk of AKI. Further research should try to find answers possibly using a multimodal approach focusing on perfusion and controlling inflammatory response. MCP-1 is an important marker to evaluate the effect of therapeutic interventions in the fight against post–cardiac surgery inflammatory damage and AKI. Stefan P. Wirtz, MD Department of Intensive Care Medicine HELIOS Hospital Bad Saarow Pieskower Straße 33 D-15526 Bad Saarow, Germany email: [email protected]
References 1. Moledina DG, Isguven S, McArthur E, et al. Plasma monocyte chemotactic protein-1 is associated with acute kidney injury and death after cardiac operations. Ann Thorac Surg 2017;104: 613–20. 2. Parikh CR, Coca SG, Thiessen-Philbrook H, et al. Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. J Am Soc Nephrol 2011;22:1748–57.
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