The association between neutrophil-to-lymphocyte ratio and contrast-induced acute kidney injury in patients with carotid artery stenting

Early Identification of Sepsis-Induced Acute Kidney Injury by Using Monocyte Distribution Width, Red-Blood-Cell Distribution, and Neutrophil-to-Lymphocyte Ratio

Sepsis-induced acute kidney injury (AKI) is a common complication in patients with severe illness and leads to increased risks of mortality and chronic kidney disease. We investigated the association between monocyte distribution width (MDW), red-blood-cell volume distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), sepsis-related organ-failure assessment (SOFA) score, mean arterial pressure (MAP), and other risk factors and sepsis-induced AKI in patients presenting to the emergency department (ED). This retrospective study, spanning 1 January 2020, to 30 November 2020, was conducted at a university-affiliated teaching hospital. Patients meeting the Sepsis-2 consensus criteria upon presentation to our ED were categorized into sepsis-induced AKI and non-AKI groups. Clinical parameters (i.e., initial SOFA score and MAP) and laboratory markers (i.e., MDW, RDW, and NLR) were measured upon ED admission. A logistic regression model was developed, with sepsis-induced AKI as the dependent variable and laboratory parameters as independent variables. Three multivariable logistic regression models were constructed. In Model 1, MDW, initial SOFA score, and MAP exhibited significant associations with sepsis-induced AKI (area under the curve [AUC]: 0.728, 95% confidence interval [CI]: 0.668-0.789). In Model 2, RDW, initial SOFA score, and MAP were significantly correlated with sepsis-induced AKI (AUC: 0.712, 95% CI: 0.651-0.774). In Model 3, NLR, initial SOFA score, and MAP were significantly correlated with sepsis-induced AKI (AUC: 0.719, 95% CI: 0.658-0.780). Our novel models, integrating MDW, RDW, and NLR with initial SOFA score and MAP, can assist with the identification of sepsis-induced AKI among patients with sepsis presenting to the ED.

Association of preoperative neutrophil-lymphocyte ratio with acute kidney injury in patients with non-cardiac surgery: difference among surgical types

PURPOSE

To examine the relationship between Neutrophil-Lymphocyte Ratio (NLR) and Acute Kidney Injury (AKI) in patients undergoing noncardiac surgery, and subgroup analysis was performed for different types of non-cardiac surgery.

METHODS

The present retrospective cohort study included 10,159 adult patients who underwent major noncardiac surgery at Nanfang Hospital, Southern Medical University, between 2008 and 2018. Postoperative AKI was defined as an increase in serum creatinine level of at least 0.3 mg/dl within 48 h, or 1.5 times higher than baseline within 7 days postoperatively according to the Kidney Disease Improving Global Outcome. The correlation between preoperative NLR and postoperative AKI was determined by stepwise multivariate logistic regression analysis, and the predictive value of NLR was evaluated by the receiver operating characteristics curve (ROC) analysis.

RESULTS

Four hundred and eighty-five (4.77%) patients developed AKI postoperatively. Preoperative NLR was independently associated with postoperative AKI in all patients undergoing non-cardiac surgery (Odds ratio [OR], 1.03; 95% confidence interval [CI], 1.00-1.06). The optimal cut-off value of NLR was 2.12 according ROC analysis. The OR and 95% CI of AKI for NLR > 2.12 was 1.48 (1.21-1.81) compared with NLR ≤ 2.12. In addition, the positive association was mainly shown in patients undergone digestive system surgery with a cut-off value of 2.12 but not in neurological and musculoskeletal system surgeries.

CONCLUSION

The present study confirmed the association of preoperative NLR with postoperative AKI in digestive system surgical patients. A NLR value of 2.12 may be a useful cut-off to evaluate the risk of AKI.

Correlation between neutrophil-to-lymphocyte ratio and contrast-induced acute kidney injury and the establishment of machine-learning-based predictive models

OBJECTIVE

To explore the correlation between neutrophil-to-lymphocyte ratio (NLR) and contrast-induced acute kidney injury (CI-AKI). To develop machine-learning (ML) methods based on NLR and other relevant high-risk factors to establish new and effective predictive models of CI-AKI. Methods: The data of 2230 patients, who underwent elective vascular intervention, coronary angiography and percutaneous coronary intervention were retrospectively collected. The patients were divided into a CI-AKI group and a non-CI-AKI group. Logistic regression was used to analyze the correlation of NLR with CI-AKI and high-risk factors for CI-AKI, and logistic regression (LR), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and naïve Bayes (NB) models based on NLR and the high-risk factors were established.

RESULTS

A high NLR(>2.844) was an independent risk factor for CI-AKI (odds ratio = 2.304, p < 0.001). The area under the ROC curve (AUC) of the NB model was the largest (0.774), indicating that it had the best performance. NLR, serum creatinine concentration, fasting plasma glucose concentration, and use of β-blocker all accounted for a large proportion of the predictive performance of each model and were the four most important factors affecting the occurrence of CI-AKI.

CONCLUSIONS

There was a significant correlation between NLR and CI-AKI The NB model exhibited the best predictive performance out of the five ML models based on NLR exhibited the best predictive performance out of the five ML models.

A Predictive Model for Contrast-Induced Acute Kidney Injury After Percutaneous Coronary Intervention in Elderly Patients with ST-Segment Elevation Myocardial Infarction

Purpose

Development and validation of a nomogram model to predict the risk of Contrast-Induced Acute Kidney Injury (CI-AKI) after emergency percutaneous coronary intervention (PCI) in elderly patients with acute ST-segment elevation myocardial infarction (STEMI).

Patients and Methods

Retrospective analysis of 542 elderly (≥65 years) STEMI patients undergoing emergency PCI in our hospital from January 2019 to June 2022, with all patients randomized to the training cohort (70%; n=380) and the validation cohort (30%; n=162). Univariate analysis, LASSO regression, and multivariate logistic regression analysis were used to determine independent risk factors for developing CI-AKI in elderly STEMI patients. R software is used to generate a nomogram model. The predictive power of the nomogram model was compared with the Mehran score 2. The area under the ROC curve (AUC), calibration curves, and decision curve analysis (DCA) was used to evaluate the prediction model's discrimination, calibration, and clinical validity, respectively.

Results

The nomogram model consisted of five variables: diabetes mellitus (DM), left ventricular ejection fraction (LVEF), Systemic immune-inflammatory index (SII), N-terminal pro-brain natriuretic peptide (NT-proBNP), and highly sensitive C-reactive protein(hsCRP). In the training cohort, the AUC is 0.84 (95% CI: 0.790-0.890), and in the validation cohort, it is 0.844 (95% CI: 0.762-0.926). The nomogram model has better predictive ability than Mehran score 2. Based on the calibration curves, the predicted and observed values of the nomogram model were in good agreement between the training and validation cohort. Decision curve analysis (DCA) and clinical impact curve showed that the nomogram prediction model has good clinical utility.

Conclusion

The established nomogram model can intuitively and specifically screen high-risk groups with a high degree of discrimination and accuracy and has a specific predictive value for CI-AKI occurrence in elderly STEMI patients after PCI.

Elevated Serum Uric Acid/Albumin Ratio as a Predictor of Post-Contrast Acute Kidney Injury After Percutaneous Coronary Intervention in Patients with ST-Segment Elevation Myocardial Infarction

Background

The serum uric acid/albumin ratio (sUAR), a novel inflammatory marker, effectively predicts acute kidney injury (AKI) and cardiovascular outcomes. However, whether the sUAR predicts post-contrast acute kidney injury (PC-AKI) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) remains uncertain. In this study, we evaluated the association between the sUAR and PC-AKI in patients with STEMI undergoing PCI.

Methods

We consecutively recruited patients with STEMI who underwent PCI and stratified them into three groups according to the terciles of the sUAR. The primary outcome was the incidence of PC-AKI. The association between the sUAR and PC-AKI was assessed by multivariate logistic regression analysis.

Results

A total of 2861 patients with STEMI were included in this study. The incidence of PC-AKI increased stepwise with increasing sUAR tercile (2.6% vs 4.0% vs 11.6%, p < 0.001), and the incidence of in-hospital major adverse clinical events (MACEs) was highest among patients in the Q3 group. Multivariate logistic regression analysis revealed that the sUAR was also an independent predictor of PC-AKI (continuous sUAR, per 1-unit increase, odds ratio [OR] [95% confidence interval (CI)]: 1.06 [1.02–1.10], p = 0.005; tercile of sUAR, OR [95% CI] for Q2 and Q3: 1.18 [0.69–2.01] and 1.85 [1.12–3.06], respectively, with Q1 as a reference) but not in-hospital MACEs. In the receiver operating characteristic (ROC) analysis, the area under the curve (AUC) of the sUAR for predicting PC-AKI was 0.708 (95% CI: 0.666–0.751), and ROC analysis also showed that the sUAR was superior to uric acid and albumin alone in predicting PC-AKI.

Conclusion

Increasing sUAR was significantly associated with a higher risk of PC-AKI but not in-hospital MACEs in patients with STEMI who underwent PCI, suggesting that sUAR had a predictive value for PC-AKI after PCI in patients with STEMI. Further studies are required to confirm this finding.

Comparative analysis of four established risk scores for predicting contrast induced acute kidney injury after primary percutaneous coronary interventions

Objectives

 This study aimed to compare Mehran Risk Score (MRS) with three well -known scoring systems namely CHA₂DS₂-VASc score, Canada Acute Coronary Syndrome Risk Score (C-ACS), and Thrombolysis in Myocardial Infarction risk index (TRI) to predict the contrast-induced acute kidney injury (CI-AKI) after primary percutaneous coronary intervention (PCI).

Background

CI-AKI is a common complication after primary PCI associated with an adverse prognosis.

Methods

In this study consecutive patients of primary PCI were included. Patients with chronic kidney diseases, exposure to the contrast medium within the past 7 days, and Killip class IV at presentation were excluded. MRS along with three risk scores namely CHA₂DS₂-VASc, C-ACS, and TRI were calculated for all patients and CI-AKI was defined as either 0.5 mg/dL or 25% relative increase in post-procedure serum creatinine. The area under the curve (AUC) curve was reported.

Results

Post primary PCI CI-AKI was observed in 63 (9.1%) patients out of 691 patients. The AUC was 0.745 [0.679-0.810] for MRS, 0.725 [0.662-0.788] for CHA₂DS₂-VASc, 0.671 [0.593-0.749] for C-ACS, and 0.734 [0.674-0.795] for TRI. Sensitivity and specificity were 61.9% [48.8-73.8%] and 76.0% [72.4-79.3%] for MRS ≥ 6.5, 66.7% [53.7-78.0%] and 66.7% [62.9-70.4%] for CHA₂DS₂-VASc ≥ 2, 52.4% [39.4-65.1%] and 79.9% [76.6-83.0%] for C-ACS ≥ 1, and 87.3% [76.5-94.4%] and 49.2% [45.2-53.2%] for TRI ≥ 16 respectively.

Conclusions

The MRS has shown higher discriminating power than CHA₂DS₂-VASc, C-ACS, and TRI. However, the TRI can be of good value in clinical practice due to its simplicity and high sensitivity in detecting patients at higher risk of CI-AKI after primary PCI.