Impact of contrast-induced acute kidney injury on long-term major adverse cardiovascular events and kidney function after percutaneous coronary intervention: insights from a territory-wide cohort study in Hong Kong

The impact of the stress hyperglycemia ratio on the risk of contrast-associated acute kidney injury in patients undergoing coronary angiography: a large real-world cohort study

BACKGROUND

Contrast-associated acute kidney injury (CA-AKI) is an important complication in the perioperative period of coronary angiography (CAG). Dysglycemia is closely associated with the occurrence of CA-AKI. However, the association between stress hyperglycemia and CA-AKI in patients undergoing CAG remains unclear. The study aims to investigate the association of the stress hyperglycemia ratio (SHR) and CA-AKI under CAG in a large real-world cohort.

METHODS

This was a retrospective observational study, and patients undergoing CAG were enrolled. SHR is calculated by dividing the random blood glucose with the estimated average glucose derived from the glycosylated hemoglobin (HbA1c), and subjects were divided into five groups according to SHR. The outcome was CA-AKI defined as an increase in serum creatinine of ≥ 0.3 mg/dL (26.5 μmol/L) or 1.5-fold higher than normal levels in 48 h. The association was assessed with logistic regression and restricted cubic spline analysis.

RESULTS

In 19,965 participants (men: 73.3%, mean age: 63.1 ± 10.8 years) undergoing CAG, a total of 1,621 CA-AKI cases occurred. There were reverse J-shaped associations between the SHR and CA-AKI after adjustment for other confounding factors. Moreover, SHR improved the predictive effectiveness of the traditional Mehran score (AUC 0.65 vs 0.63, P < 0.001), a predictive model of CA-AKI in patients undergoing percutaneous coronary intervention.

CONCLUSIONS

There were reverse J-shaped associations of SHR with CA-AKI risk among patients undergoing CAG, and the assessment of SHR before CAG may assist clinicians in identifying patients at higher risk of CA-AKI.

Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach

BACKGROUND

Acute kidney injury (AKI) is one of the preventable complications of percutaneous coronary intervention (PCI). This study aimed to develop machine learning (ML) models to predict AKI after PCI in patients with acute coronary syndrome (ACS).

METHODS

This study was conducted at Tehran Heart Center from 2015 to 2020. Several variables were used to design five ML models: Naïve Bayes (NB), Logistic Regression (LR), CatBoost (CB), Multi-layer Perception (MLP), and Random Forest (RF). Feature importance was evaluated with the RF model, CB model, and LR coefficients while SHAP beeswarm plots based on the CB model were also used for deriving the importance of variables in the population using pre-procedural variables and all variables. Sensitivity, specificity, and the area under the receiver operating characteristics curve (ROC-AUC) were used as the evaluation measures.

RESULTS

A total of 4592 patients were included, and 646 (14.1%) experienced AKI. The train data consisted of 3672 and the test data included 920 cases. The patient population had a mean age of 65.6 ± 11.2 years and 73.1% male predominance. Notably, left ventricular ejection fraction (LVEF) and fasting plasma glucose (FPG) had the highest feature importance when training the RF model on only pre-procedural features. SHAP plots for all features demonstrated LVEF and age as the top features. With pre-procedural variables only, CB had the highest AUC for the prediction of AKI (AUC 0.755, 95% CI 0.713 to 0.797), while RF had the highest sensitivity (75.9%) and MLP had the highest specificity (64.35%). However, when considering pre-procedural, procedural, and post-procedural features, RF outperformed other models (AUC: 0.775). In this analysis, CB achieved the highest sensitivity (82.95%) and NB had the highest specificity (82.93%).

CONCLUSION

Our analyses showed that ML models can predict AKI with acceptable performance. This has potential clinical utility for assessing the individualized risk of AKI in ACS patients undergoing PCI. Additionally, the identified features in the models may aid in mitigating these risk factors.

Contrast-associated acute kidney injury and cardiovascular events: a secondary analysis of the PRESERVE cohort

Background

Contrast-associated acute kidney injury (CA-AKI) has been associated with a higher risk of cardiovascular (CV) events. We studied the risk of CV events in chronic kidney disease (CKD) patients undergoing angiography and whether biomarkers can predict such events. We also explored whether CA-AKI mediates the association of pre-angiography estimated glomerular filtration rate (eGFR) on CV events.

Methods

We analysed participants from the Prevention of Serious Adverse Events following the Angiography (PRESERVE) trial. Urinary tissue inhibitor of matrix metalloproteinase [TIMP]-2 and insulin growth factor binding protein [IGFBP]-7, plasma brain-type natriuretic peptide (BNP), high sensitivity C-reactive protein (hs-CRP), and serum cardiac troponin-I (Tn-I) were assayed before and after angiography. We assessed the composite risk of CV events by day 90.

Results

Of the 922 participants, 119 (12.9%) developed CV events, and 73 (7.9%) developed CA-AKI. Most cases of CA-AKI (90%) were stage 1. There were no differences in urinary [TIMP-2]•[IGFBP7] concentrations or the proportion of patients with CA-AKI among those with and without CV events. Higher BNP, Tn-I, and hs-CRP were associated with CV events, but their discriminatory capacity was modest (AUROC <0.7). CA-AKI did not mediate the association of the pre-angiography eGFR on CV events.

Conclusions

Most episodes of CA-AKI are stage 1 AKI and are not associated with CV events. Less severe CA-AKI episodes also did not mediate the risk of pre-angiography eGFR on CV events. Our findings suggest that most CV events after contrast procedures are due to underlying CKD and CV risk factors rather than less severe CA-AKI episodes and should help enhance the utilization of clinically indicated contrast procedures among high-risk patients with CKD. Further research is required to examine whether moderate-to-severe CA-AKI episodes are associated with CV events.

Prognostic Nutritional Index Combined with Triglyceride-Glucose Index to Contrast a Nomogram for Predicting Contrast-Induced Kidney Injury in Type 2 Diabetes Mellitus Patients with Acute Coronary Syndrome After Percutaneous Coronary Intervention

Objective

Our objective was to develop and validate a nomogram model aiming at predicting the risk of contrast-induced acute kidney injury (CI-AKI) following percutaneous coronary intervention (PCI) in patients suffering from type 2 diabetes mellitus (T2DM) and also diagnosed with acute coronary syndrome (ACS).

Methods

The study gathered data from 722 T2DM patients with ACS who received PCI treatment at the Affiliated Hospital of Xuzhou Medical University between February 2019 and December 2022, serving as the training set. Considering the validation set, the study included 217 patients who received PCI at the East Affiliated Hospital of Xuzhou Medical University. The patients were classified into CI-AKI and non-CI-AKI groups. The study employed univariate and multivariate logistic analysis for identifying independent risk factors for CI-AKI, followed by developing a predictive nomogram model for CI-AKI risk using R software. The predictive performance and clinical utility of the nomogram were assessed through internal and external validation, utilizing the areas under the receiver operating characteristic curve (AUC-ROC), the Hosmer-Lemeshow test and calibration correction curve, and decision curve analysis (DCA).

Results

The nomogram comprised four variables: age, estimated glomerular filtration rate (eGFR), triglyceride-glucose (TyG) index, and prognostic nutritional index (PNI). The AUC-ROC were 0.785 (95% confidence interval (CI) 0.729-0.841) and 0.802 (95% CI 0.699-0.905) for the training and validation cohorts, respectively, indicating a high discriminative ability of the nomogram. The calibration assessment and decision curve analysis have substantiated the strong concordance and clinical usefulness of the aforementioned.

Conclusion

The nomogram exhibits favorable discrimination and accuracy, enabling it to visually and individually identify pre-procedure high-risk patients, and possesses a predictive capacity regarding CI-AKI incidence after PCI in patients diagnosed with both T2DM and ACS.

Brain natriuretic peptide as a biomarker for predicting contrast-induced nephropathy in patients undergoing coronary angiography/intervention: A systematic review and meta-analysis

BACKGROUND

Contrast-induced nephropathy (CIN) is associated with adverse events. As there are no effective treatments, the early identification of high-risk patients is required. Individual studies have suggested the utility of brain natriuretic peptide in predicting CIN. Therefore, this meta-analysis aimed to systematically investigate the value of brain natriuretic peptide in predicting CIN in patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI).

METHODS

We searched PubMed, Embase, Cochrane Central Register of Controlled Trials Library, and Web of Science from inception date to March 9, 2022. Studies that evaluated the predictive value of brain natriuretic peptide for CIN outcomes in patients after CAG or PCI were included. The quality of the included studies was assessed using the QUADAS-2 tool. Diagnostic accuracy estimates were calculated using a random-effects model. Subgroup and meta-regression analyses were performed to identify the potential sources of heterogeneity.

RESULTS

Twelve studies with 7789 patients were included in the meta-analysis. The pooled sensitivity and specificity of brain natriuretic peptide for the prediction of CIN were 0.73 (95% CI: 0.67-0.78) and 0.77 (95% CI: 0.71-0.82), respectively. The area under the summary receiver operating characteristic curve was 0.80 (95% CI: 0.77-0.84). Meta-regression analysis indicated that the sources of sensitivity heterogeneity may be the country, mean age, and study population. Additionally, country, study population, study design, and index text contributed to the specificity heterogeneity.

CONCLUSION

This study demonstrated that brain natriuretic peptide could function as a novel potential marker for the early detection of CIN in patients undergoing CAG or PCI.

Predictive and Prognostic Value of Serum Neutrophil Gelatinase-Associated Lipocalin for Contrast-Induced Acute Kidney Injury and Long-Term Clinical Outcomes after Percutaneous Coronary Intervention

Neutrophil gelatinase-associated lipocalin (NGAL) has been proposed as an early marker for estimating the risk of contrast-induced acute kidney injury (CI-AKI). However, the predictive value of baseline serum NGAL levels for CI-AKI remains unclear. Serum NGAL was measured before percutaneous coronary intervention in 633 patients with coronary artery disease. The primary clinical endpoints were a composite of major adverse cardiac and cerebrovascular events (MACCEs; cardiac death, myocardial infarction, stroke, and any revascularization). The mean follow-up duration was 29.4 months. Ninety-eight (15.5%) patients developed CI-AKI. Compared with patients without CI-AKI, baseline serum NGAL was higher in patients with CI-AKI (149.6 ± 88.8 ng/mL vs. 138.0 ± 98.6 ng/mL, p = 0.0279), although serum creatinine and estimated glomerular filtration rate were not different between groups. Patients in the highest tertile of baseline serum NGAL showed a significantly higher rate of MACCEs (10.5% vs. 3.8%, p = 0.02). Using the first tertile as a reference, the adjusted hazard ratios for MACCEs in patients in the second and third tertiles of NGAL were 2.151 (confidence interval (CI) 0.82 to 5.59, p = 0.116) and 2.725 (CI 1.05 to 7.05, p = 0.039), respectively. Baseline serum NGAL is a reliable marker for predicting CI-AKI, and high serum NGAL levels are associated with a higher incidence rate of long term MACCEs.