Gamma glutamyl transferase as a biomarker to predict contrast-induced nephropathy among patients with acute coronary syndrome undergoing coronary interventions: a meta-analysis

Mechanism and clinical role of TIMP-2 and IGFBP-7 in cardiac surgery-associated acute kidney injury: A review

Acute kidney injury (AKI) is a common postoperative complication, but there is still a lack of accurate biomarkers. Cardiac surgery-associated AKI is the most common cause of major-surgery-related AKI, and patients requiring renal replacement therapy have high mortality rates. Early diagnosis, intervention, and management are crucial for improving patient prognosis. However, diagnosing AKI based solely on changes in serum creatinine level and urine output is insufficient, as these changes often lag behind actual kidney damage, making early detection challenging. Biomarkers such as tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein-7 (IGFBP-7) have been found to be significant predictors of moderate-to-severe AKI when combined with urine content analysis. This article reviews the mechanism of biomarkers TIMP-2 and IGFBP-7 in AKI and provides a comprehensive overview of the clinical effects of TIMP-2 and IGFBP-7 in cardiac surgery-associated AKI, including prediction, diagnosis, and progression.

Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study

BACKGROUND

Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms. The authors also evaluated the predictive performance of models that included only preoperative variables or only important predictors.

MATERIALS AND METHODS

Adult patients undergoing noncardiac surgery were retrospectively included in the study (76 457 patients in the discovery cohort and 11 910 patients in the validation cohort). AKI was determined using the KDIGO criteria. The prediction model was developed using 87 variables (56 preoperative variables and 31 intraoperative variables). A variety of machine learning algorithms were employed to develop the model, including logistic regression, random forest, extreme gradient boosting, and gradient boosting decision trees. The performance of different models was compared using the area under the receiver operating characteristic curve (AUROC). Shapley Additive Explanations (SHAP) analysis was employed for model interpretation.

RESULTS

The patients in the discovery cohort had a median age of 52 years (IQR: 42-61 years), and 1179 patients (1.5%) developed AKI after surgery. The gradient boosting decision trees algorithm showed the best predictive performance using all available variables, or only preoperative variables. The AUROCs were 0.849 (95% CI: 0.835-0.863) and 0.828 (95% CI: 0.813-0.843), respectively. The SHAP analysis showed that age, surgical duration, preoperative serum creatinine, and gamma-glutamyltransferase, as well as American Society of Anesthesiologists physical status III were the most important five features. When gradually reducing the features, the AUROCs decreased from 0.852 (including the top 40 features) to 0.839 (including the top 10 features). In the validation cohort, the authors observed a similar pattern regarding the models' predictive performance.

CONCLUSIONS

The machine learning models the authors developed had satisfactory predictive performance for identifying high-risk postoperative AKI patients. Furthermore, the authors found that model performance was only slightly affected when only preoperative variables or only the most important predictive features were included.

Evaluating biomarkers for contrast-induced nephropathy following coronary interventions: an umbrella review on meta-analyses

BACKGROUND

Contrast-induced nephropathy (CIN) is a form of acute kidney injury (AKI) occurring in patients undergoing cardiac catheterization, such as coronary angiography (CAG) or percutaneous coronary intervention (PCI). Although the conventional criterion for CIN detection involves a rise in creatinine levels within 72 h after contrast media injection, several limitations exist in this definition. Up to now, various meta-analyses have been undertaken to assess the accuracy of different biomarkers of CIN prediction. However, the existing body of research lacks a cohesive overview. To address this gap, a comprehensive umbrella review was necessary to consolidate and summarize the outcomes of prior meta-analyses. This umbrella study aimed to offer a current, evidence-based understanding of the prognostic value of biomarkers in predicting CIN.

METHODS

A systematic search of international databases, including PubMed, Scopus, and Web of Science, from inception to December 12, 2023, was conducted to identify meta-analyses assessing biomarkers for CIN prediction. Our own meta-analysis was performed by extracting data from the included studies. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were assessed using Meta-Disc and CMA softwares.

RESULTS

Twelve studies were ultimately included in the umbrella review. The results revealed that neutrophil gelatinase-associated lipocalin (NGAL) exhibited the highest area under the curve (AUC), followed by cystatin-C, urinary kidney injury molecule-1 (uKIM-1), and brain natriuretic peptide (BNP) with AUCs of 0.91, 0.89, 0.85, and 0.80, respectively. NGAL also demonstrated the highest positive likelihood ratio [effect size (ES): 6.02, 95% CI 3.86-9.40], followed by cystatin-C, uKIM-1, and BNP [ES: 4.35 (95% CI 2.85-6.65), 3.58 (95% CI 2.75-4.66), and 2.85 (95% CI 2.13-3.82), respectively]. uKIM-1 and cystatin-C had the lowest negative likelihood ratio, followed by NGAL and BNP [ES: 0.25 (95% CI 0.17-0.37), ES: 0.25 (95% CI 0.13-0.50), ES: 0.26 (95% CI 0.17-0.41), and ES: 0.39 (0.28-0.53) respectively]. NGAL emerged as the biomarker with the highest diagnostic odds ratio for CIN, followed by cystatin-C, uKIM-1, BNP, gamma-glutamyl transferase, hypoalbuminemia, contrast media volume to creatinine clearance ratio, preprocedural hyperglycemia, red cell distribution width (RDW), hyperuricemia, neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), high-sensitivity CRP, and low hematocrit (P < 0.05).

CONCLUSION

NGAL demonstrated superior diagnostic performance, exhibiting the highest AUC, positive likelihood ratio, and diagnostic odds ratio among biomarkers for CIN, followed by cystatin-C, and uKIM-1. These findings underscore the potential clinical utility of NGAL, cystatin-C and uKIM-1 in predicting and assessing CIN.

An Investigation of Contrast-Induced Acute Kidney Injury in Patients Undergoing Percutaneous Coronary Intervention: A Cross-Sectional Study From Pakistan

Background and objective Contrast-induced acute kidney injury (CIAKI) is a complication observed among individuals undergoing primary percutaneous coronary intervention (PCI) and is associated with high morbidity and mortality rates. It is characterized by an elevation in serum creatinine (SCr) levels >0.5 mg/dl or a 50% relative increase in SCr from the baseline value following exposure to contrast within a 48- to 72-hour timeframe, in the absence of any alternative causes for acute kidney injury (AKI). This study aimed to assess the incidence of CIAKI in patients following PCI. Methods This prospective study was conducted from July to December 2022, after obtaining ethical approval from the institutional ethics committee (reference no: 147/LRH/MTI). A total of 159 consecutive patients who met the selection criteria were enrolled. A detailed patient and family history was obtained, and a thorough physical examination was conducted. Baseline tests, including SCr, were performed, with SCr repeated 72 hours post-PCI. All investigations were performed in the affiliated hospital's main laboratory and conducted by the same biochemist. Results The study included 159 patients presenting with myocardial infarction, angina pectoris, or ischemic features on EKG, exercise tolerance test (ETT), or echocardiogram and underwent PCI. The patients had a mean age of 51 ± 9 years, baseline SCr of 0.77 ± 0.41 mg/dl, SCr 72 hours post-procedure of 0.83 ± 0.41 mg/dl, and an average contrast volume of 128.6 ± 63 ml; 87 (55%) patients were male, and 72 (45%) were female. CIAKI was observed in 15 (9.4%) patients. Hypertension and diabetes mellitus were the most prevalent comorbidities. Male gender, diabetes mellitus, and hypertension had a clinically significant association with the development of CIAKI (p<0.05). ST-elevation myocardial infarction (STEMI) was the predominant clinical presentation in 81 (50.9%) cases. Conclusions This study examines the frequency, risk factors, and associations of CIAKI following PCI at a tertiary care hospital in a low-middle-income country. We believe our findings provide future directions for identifying and minimizing the risk of CIAKI in this patient population.

Diagnostic efficacy of the triglyceride-glucose index in the prediction of contrast-induced nephropathy following percutaneous coronary intervention

Introduction

Contrast-induced nephropathy (CIN) is a common complication of percutaneous coronary intervention (PCI). Identifying patients at high CIN risk remains challenging. The triglyceride-glucose (TyG) index may help predict CIN but evidence is limited. We conducted a meta-analysis to evaluate the diagnostic value of TyG index for CIN after PCI.

Methods

A systematic literature search was performed in MEDLINE, Cochrane, and EMBASE until August 2023 (PROSPERO registration: CRD42023452257). Observational studies examining TyG index for predicting CIN risk in PCI patients were included. This diagnostic meta-analysis aimed to evaluate the accuracy of the TyG index in predicting the likelihood of CIN. Secondary outcomes aimed to assess the pooled incidence of CIN and the association between an elevated TyG index and the risk of CIN.

Results

Five studies (Turkey, n=2; China, n=3) with 3518 patients (age range: 57.6 to 68.22 years) were included. The pooled incidence of CIN was 15.3% [95% confidence interval (CI) 11-20.8%]. A high TyG index associated with increased CIN risk (odds ratio: 2.25, 95% CI 1.82-2.77). Pooled sensitivity and specificity were 0.77 (95% CI 0.59-0.88) and 0.55 (95% CI 0.43-0.68) respectively. Analysis of the summary receiver operating characteristic (sROC) curve revealed an area under the curve of 0.69 (95% CI 0.65-0.73). There was a low risk of publication bias (p = 0.81).

Conclusion

The TyG index displayed a noteworthy correlation with the risk of CIN subsequent to PCI. However, its overall diagnostic accuracy was found to be moderate in nature. While promising, the TyG index should not be used in isolation for CIN screening given the heterogeneity between studies. In addition, the findings cannot be considered conclusive given the scarcity of data. Further large-scale studies are warranted to validate TyG cutoffs and determine how to optimally incorporate it into current risk prediction models.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023452257, identifier CRD42023452257.