Growth differentiation factor-15 levels and the risk of contrast induced acute kidney injury in acute myocardial infarction patients treated invasively: A propensity-score match analysis

<div><p>Background</p><p>Growth differentiation factor-15 (GDF-15) is an emerging biomarker for risk stratification in cardiovascular disease. Contrast-induced acute kidney injury (AKI) is an important complication in patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). In this retrospectively observational study, we aimed to determine the role of GDF-15 and the risk of AKI in acute myocardial infarction (AMI) patients.</p><p>Methods</p><p>The medical records of 1195 patients with AMI were reviewed. After exclusion criteria, a total of 751 eligible patients who underwent CAG or PCI were studied. Preoperative clinical parameters including GDF-15 levels were recorded. Multivariate logistic regression analysis was used to identify the risk factors of AKI. Subsequently, to reduce a potential selection bias and to balance differences between the two groups, a propensity score-matched analysis was performed. We recorded the 30-day all-cause mortality of the total study population. Kaplan-Meier analysis was performed to identify the association between short term survival in AMI patients and GDF-15 level.</p><p>Results</p><p>Among 751 enrolled patients, 106 patients (14.1%) developed AKI. Patients were divided into two groups: AKI group (n = 106) and non-AKI group (n = 645). GDF-15 levels were significantly higher in AKI group compared to non-AKI group (1328.2 ± 349.7 ng/L vs. 1113.0 ± 371.3 ng/L, P <0.001). Multivariate logistic regression analyses showed GDF-15 was an independent risk factor of AKI (per 1000 ng/L increase of GDF-15, OR: 3.740, 95% CI: 1.940–7.207, P < 0.001). According to GDF-15 tertiles, patients were divided into three groups. Patients in middle (OR 2.93, 95% CI: 1.46–5.89, P = 0.003) and highest GDF-15 tertile (OR 3.72, 95% CI: 1.87–7.39, P <0.001) had higher risk of AKI compared to patients in the lowest GDF-15 tertile. The propensity score-matched group set comprised of 212 patients. Multivariate logistic regression revealed that GDF-15 is still an independent risk factor for AKI after matching (per 1000 ng/L increase of GDF-15, OR: 2.395, 95% CI: 1.020–5.626, P = 0.045). Based on the Kaplan-Meier analysis, the risk of 30-day all-cause mortality increased in higher GDF-15 tertiles log rank chi-square: 29.895, P <0.001).</p><p>Conclusion</p><p>This suggests that preoperative plasma GDF-15 is an independent risk factor of AKI in AMI patients underwent CAG or PCI. GDF-15 and AKI are associated with poor short term survival of AMI patients.</p></div

Growth differentiation factor-15 levels and the risk of contrast induced nephropathy in patients with acute myocardial infarction undergoing percutaneous coronary intervention: A retrospective observation study

<div><p>Aims</p><p>To investigate the association between growth differentiation factor-15 (GDF-15) and contrast-induced nephropathy (CIN) in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI).</p><p>Methods</p><p>A total of 311 patients with AMI were studied retrospectively. All patients were divided into two groups according to the occurrence of CIN after PCI. Baseline clinical data were compared between two groups. Multivariate logistic regression analysis was used to identify the risk factors for CIN. Cox regression analysis was used to identify the association between GDF-15, CIN and short-term outcome.</p><p>Results</p><p>There were 80 patients in CIN group (average age was 71.60 ± 13.00 years; 67.5% male) and 231 patients in non-CIN group (average age was 63.80 ± 11.70 years; 71.9%male). The concentration of GDF-15 in CIN group was higher than that of non-CIN group (1232 ± 366.6 ng/L vs. 939.20 ± 309.6 ng/L, P <0.001). According to GDF-15 quartiles, patients were divided into four groups. Multivariate logistic model indicated that the highest quartile(Q4) was significantly associated with an increased risk of CIN compared with lower level of GDF-15 (Q1, Q2 and Q3) (OR : 3.572, 1.803–7.078, P < 0.001). Of 243 patients who could calculate the ACEF risk score, area under the curve (AUC) of GDF-15 was 0.793, 95%CI: 0.729–0.856, P < 0.001, while AUC of ACEF was 0.708, 95%CI: 0.630–0.786, P < 0.001. Using 10% and 30% as arbitrary thresholds to define patients at low, intermediate, and high risk, GDF-15 achieved a net reclassification improvement (NRI) of 0.32 (95%CI: 0.123–0.518, P = 0.001) compared with the ACEF risk score. Cox regression model showed that high concentration of GDF-15 (Q4) was significantly associated with an increased risk of all-cause mortality and major adverse clinical events (MACE) (HR: 8.434, 95%CI: 2.650–26.837, P <0.001; HR: 3.562, 95%CI: 1.658–7.652, P = 0.001) compared with low level of GDF-15 (Q1, Q2 and Q3). CIN was an independent predictor of all-cause mortality and MACE in AMI patients (HR: 3.535, 95%CI: 1.135–11.005, P = 0.029; HR: 5.154, 95%CI: 2.228–11.925, P <0.001).</p><p>Conclusion</p><p>GDF-15 levels increased in CIN group in AMI patients underwent PCI. GDF-15 was an independent risk factor for CIN in AMI patients underwent PCI. GDF-15 level and CIN are independent risk factors for all-cause mortality and MACE in short-term follow-ups.</p></div

Basic clinical and procedural characteristics between AKI group and non-AKI group.

<p>Basic clinical and procedural characteristics between AKI group and non-AKI group.</p

C-statistics of Cox models with or without GDF-15.

<p>There were incremental trends in C-statistics incorporating GDF-15 in Cox model. Model 1 (Cox model predicting mortality in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197609#pone.0197609.g006" target="_blank">Fig 6</a>, but without GDF-15): CIN, Age>70 years, Male, Hydration therapy, Primary PCI, Anemia; Model 2 (Cox model for mortality in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197609#pone.0197609.g006" target="_blank">Fig 6</a>): Q4 vs.(Q1+Q2+Q3), CIN, Age>70 years, Male, Hydration therapy, Primary PCI, Anemia; Model 3 (Cox model for MACE in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197609#pone.0197609.g006" target="_blank">Fig 6</a>, but without GDF-15): CIN, Age>70 years, Male, Hydration therapy, Primary PCI, Anemia; Model 4 (Cox model for MACE in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197609#pone.0197609.g006" target="_blank">Fig 6</a>): Q4 vs.(Q1+Q2+Q3), CIN, Age>70 years, Male, Hydration therapy, Primary PCI, Anemia.</p

Reclassification across pre-defined risk thresholds in a cohort of 243 patients using GDF-15 and the ACEF risk score.

<p>Reclassification across pre-defined risk thresholds in a cohort of 243 patients using GDF-15 and the ACEF risk score.</p

Kaplan-Meier survival curves according to GDF-15 quartiles and the prevalence of CIN.

<p>Q1 (GDF-15 ≤ 800.27 ng/L), n = 78, Q2 (800.27ng/L< GDF-15 ≤900.49 ng/L), n = 78, Q3 (900.49ng/L Fig 3B). 30-days survival rate between CIN group and non-CIN group (Fig 5C). 30-days 1-MACE event rate between CIN group and non-CIN group (Fig 5D).</p

Multivariate Cox analysis: Independent predictors of all-cause mortality and MACE event.

<p>Presented are Cox proportional hazard model to estimate the associations between risk factors and short-term outcomes.</p

Basic clinical characteristics of CIN group and non-CIN group.

<p>Basic clinical characteristics of CIN group and non-CIN group.</p

AUC of variables for predicting mortality.

<p>AUC of variables for predicting mortality.</p

Baseline patient characteristics according to GDF-15 quartiles.

<p>Baseline patient characteristics according to GDF-15 quartiles.</p