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. 2015 Apr 13;10(4):e0123093.
doi: 10.1371/journal.pone.0123093. eCollection 2015.

Renal function interferes with copeptin in prediction of major adverse cardiac events in patients undergoing vascular surgery

Claudia Schrimpf  1 , Hans-Joerg Gillmann  2 , Bianca Sahlmann  2 , Antje Meinders  2 , Jan Larmann  2 , Mathias Wilhelmi  1 , Thomas Aper  1 , Saad Rustum  1 , Ralf Lichtinghagen  3 , Gregor Theilmeier  2 , Omke E Teebken  1
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Renal function interferes with copeptin in prediction of major adverse cardiac events in patients undergoing vascular surgery

Claudia Schrimpf et al. PLoS One. .

Abstract

Objective: Precise perioperative risk stratification is important in vascular surgery patients who are at high risk for major adverse cardiovascular events (MACE) peri- and postoperatively. In clinical practice, the patient's perioperative risk is predicted by various indicators, e.g. revised cardiac index (RCRI) or modifications thereof. Patients suffering from chronic kidney disease (CKD) are stratified into a higher risk category. We hypothesized that Copeptin as a novel biomarker for hemodynamic stress could help to improve the prediction of perioperative cardiovascular events in patients undergoing vascular surgery including patients with chronic kidney disease.

Methods: 477 consecutive patients undergoing abdominal aortic, peripheral arterial or carotid surgery from June 2007 to October 2012 were prospectively enrolled. Primary endpoint was 30-day postoperative major adverse cardiovascular events (MACE).

Results: 41 patients reached the primary endpoint, including 63.4% aortic, 26.8% carotid, and 9.8% peripheral surgeries. Linear regression analysis showed that RCRI (P< .001), pre- (P< .001), postoperative Copeptin (P< .001) and Copeptin level change (P= .001) were associated with perioperative MACE, but CKD remained independently associated with MACE and Copeptin levels. Multivariate regression showed that increased Copeptin levels added risk predictive information to the RCRI (P= .003). Especially in the intermediate RCRI categories was Copeptin significantly associated with the occurrence of MACE. (P< .05 Kruskal Wallis test). Subdivision of the study cohort into CKD stages revealed that preoperative Copeptin was significantly associated with CKD stages (P< .0001) and preoperative Copeptin measurements could not predict MACE in patients with more severe CKD stages.

Conclusion: Preoperative Copeptin loses its risk predictive potential for perioperative MACE in patients with chronic kidney disease undergoing vascular surgery.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Copeptin is elevated in patients sustaining Major Adverse Cardiovascular Events (MACE) throughout the perioperative phase.
Boxplots of pre- (A) and postoperative (B) Copeptin levels as well as perioperative Copeptin change (C) (pmol/L). Groups were analyzed by Mann-Whitney U test (A) P = .0001, (B) P = .0002, (C) P = .014.
Fig 2
Fig 2. ROC analysis comparing the RCRI alone or combined with Copeptin-derived parameters.
Only preoperative Copeptin (blue dotted line) improved risk predictive accuracy of the RCRI (P = .0371, AUC .752). The RCRI-ROC Curve (black line) (AUC .714) indicates prediction of the occurrence of major adverse cardiovascular events (MACE). The combination of RCRI and postoperative Copeptin (red dashed line) (P = .0620, AUC .751) and RCRI and Copeptin changes (P = .1525, AUC .710) during the perioperative course (green dashed and dotted line) do not reach significantly larger AUCs. * marks significant values.
Fig 3
Fig 3. Copeptin interferes with kidney injury in prediction of MACE.
Preoperative Copeptin levels (pmol/L) are significantly (P<.0001) elevated in patients with chronic kidney disease increasing with severity of kidney injury (A). Preoperative Copeptin is not associated with MACE in patients with CKD 1&2 (B) (P = .3787) or CKD 4&5 (D) (P = .2264) but shows significant association with MACE in CKD 3 (C) (P = .0163). Data were analyzed using Mann Whitney U test for comparing two groups and Kruskal Wallis test followed by Dunns test for multiple comparisons. Blots are depicted as 5–95 percentile.
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