Effects of hyperglycaemia and elevated glycosylated haemoglobin on contrast-induced nephropathy after coronary angiography

Prevalence of contrast-induced nephropathy after primary percutaneous coronary intervention at a tertiary referral hospital

Objective

This study aimed to quantify the incidence of Contrast-induced nephropathy (CIN) in patients undergoing primary percutaneous coronary intervention (PPCI) due to acute ST-elevation myocardial infarction (STEMI).

Methods

From April 2019 to March 2022, a prospective, observational study enrolled 213 consecutive STEMI patients referred to a tertiary hospital for PPCI. Participants were divided into tow groups based on the presence or absence of contrast-induced nephropathy. The chi-square test (χ2) and Student's t-test evaluated the data, with logistic regression identifying CIN's independent predictors.

Results

Results: In this study, the incidence of contrast-induced nephropathy was observed at 13.1% (N = 28). Several factors were more prevalent among patients exhibiting contrast-induced nephropathy. These factors encompassed: radial access for coronary angiography over the femoral method (P = 0.021), elevated contrast volume (P = 0.003), smoking (P = 0.009), diabetes (P = 0.04), heart failure (P = 0.049), a history of coronary artery bypass graft (P = 0.006), diminished left ventricular ejection fraction indicating systolic dysfunction (P = 0.012), cardiogenic shock (P = 0.046), increased BUN at the time of admission (P = 0.043), decreased initial GFR (P = 0.004), and prior consumption of medications such as aspirin (P = 0.002), diuretics (P = 0.046), beta blockers (P = 0.04), angiotensin-converting enzyme inhibitors (P = 0.033), angiotensin receptor blockers (P = 0.02). Other relevant conditions included anemia (P = 0.012), leukocytosis (P = 0.011), hypercholesterolemia (P = 0.034), and reduced HDL levels (P = 0.004).Through logistic regression, key predictors for the onset of contrast-induced nephropathy were determined, which included heart failure (OR: 5.52; 95% CI: 1.08-28.24), radial access (OR: 12.71; 95% CI: 1.45-110.9), hypercholesterolemia (OR: 1.02; 95% CI: 1.004-1.04), increased BUN upon admission (OR: 1.11; 95% CI: 1.006-1.24), and leukocytosis (OR: 2.03; 95% CI: 1.18-3.49).

Conclusions

While heart failure, radial access, hypercholesterolemia, elevated BUN at admission, and leukocytosis significantly influenced renal filtration deterioration post-PPCI, it's evident that CIN is multifactorial. Further studies are crucial to elucidate the underlying factors.

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.

Comparison of Four Machine Learning Techniques for Prediction of Intensive Care Unit Length of Stay in Heart Transplantation Patients

Background

Post-operative heart transplantation patients often require admission to an intensive care unit (ICU). Early prediction of the ICU length of stay (ICU-LOS) of these patients is of great significance and can guide treatment while reducing the mortality rate among patients. However, conventional linear models have tended to perform worse than non-linear models.

Materials and Methods

We collected the clinical data of 365 patients from Wuhan Union Hospital who underwent heart transplantation surgery between April 2017 and August 2020. The patients were randomly divided into training data (N = 256) and test data (N = 109) groups. 84 clinical features were collected for each patient. Features were validated using the Least Absolute Shrinkage and Selection Operator (LASSO) regression’s fivefold cross-validation method. We obtained Shapley Additive explanations (SHAP) values by executing package “shap” to interpret model predictions. Four machine learning models and logistic regression algorithms were developed. The area under the receiver operating characteristic curve (AUC-ROC) was used to compare the prediction performance of different models. Finally, for the convenience of clinicians, an online web-server was established and can be freely accessed via the website https://wuhanunion.shinyapps.io/PredictICUStay/.

Results

In this study, 365 consecutive patients undergoing heart transplantation surgery for moderate (NYHA grade 3) or severe (NYHA grade 4) heart failure were collected in Wuhan Union Hospital from 2017 to 2020. The median age of the recipient patients was 47.2 years, while the median age of the donors was 35.58 years. 330 (90.4%) of the donor patients were men, and the average surgery duration was 260.06 min. Among this cohort, 47 (12.9%) had renal complications, 25 (6.8%) had hepatic complications, 11 (3%) had undergone chest re-exploration and 19 (5.2%) had undergone extracorporeal membrane oxygenation (ECMO). The following six important clinical features were selected using LASSO regression, and according to the result of SHAP, the rank of importance was (1) the use of extracorporeal membrane oxygenation (ECMO); (2) donor age; (3) the use of an intra-aortic balloon pump (IABP); (4) length of surgery; (5) high creatinine (Cr); and (6) the use of continuous renal replacement therapy (CRRT). The eXtreme Gradient Boosting (XGBoost) algorithm presented significantly better predictive performance (AUC-ROC = 0.88) than other models [Accuracy: 0.87; sensitivity: 0.98; specificity: 0.51; positive predictive value (PPV): 0.86; negative predictive value (NPV): 0.93].

Conclusion

Using the XGBoost classifier with heart transplantation patients can provide an accurate prediction of ICU-LOS, which will not only improve the accuracy of clinical decision-making but also contribute to the allocation and management of medical resources; it is also a real-world example of precision medicine in hospitals.

Implications of Malnutrition on Contrast-Associated Acute Kidney Injury in Young and Old Patients Undergoing Percutaneous Coronary Intervention: A Multicenter Prospective Cohort

Background

The relationship between malnutrition and the risk of contrast-associated acute kidney injury (CA-AKI) and the resulting prognosis in patients undergoing percutaneous coronary intervention (PCI) is still not well known.

Methods

Patients undergoing PCI were consecutively enrolled in a multicenter study in China (NCT01402232), categorized by nutritional status (non-malnutrition, malnutrition) based on two different cut-off values (i.e., traditional threshold and the best cut-off value based on the receiver operating characteristic (ROC) curve) for the controlling nutritional status (CONUT) score. The primary endpoint was CA-AKI, diagnosed as a rise in serum creatinine >0.3 mg/dl or >50% than the baseline level occurring within 48 h after the intervention. The secondary endpoint was all-cause mortality. The relationships of malnutrition, CA-AKI, and all-cause mortality were examined using multivariate-adjusted logistic and Cox regression analyses, respectively.

Results

Among 2,083 patients undergoing PCI (age: 62.8 ± 11.1 years; 79.0% men), 1,258 (60.4%) were malnourished. During hospitalization, 80 (3.8%) patients developed CA-AKI events. The incidence of CA-AKI in patients who did not have malnutrition (the non-malnutrition group) and those who did have malnutrition (the malnutrition group) was 1.7% and 5.25%, respectively. Patients with malnutrition had a 2-fold increased adjusted risk of CA-AKI compared to those with no malnutrition [adjusted odds ratio (aOR) (95% confidence interval CI): 2.41 (1.22 to 5.22)]. Malnutrition was associated with a 3-fold increased adjusted risk of CA-AKI in patients aged ≤ 75 years [N = 1,791, aOR (95% CI): 3.39 (1.46–9.25)]. Malnourished patients with CA-AKI had a higher risk of all-cause mortality than the others. Similar results were observed in the grouping of Supplemental Analyses based on the optimal cut-off value of the CONUT score identified by the ROC curve.

Conclusions

Malnutrition is strongly associated with an increased risk of CA-AKI in both young and old patients undergoing PCI. Malnourished patients with CA-AKI had a significantly higher risk of all-cause mortality. Further studies are needed to prospectively assess the efficacy of nutritional interventions on outcomes in patients undergoing PCI.

Development and Validation of a Risk Nomogram Model for Predicting Contrast-Induced Acute Kidney Injury in Patients with Non-ST-Elevation Acute Coronary Syndrome Undergoing Primary Percutaneous Coronary Intervention

Objective

To establish a nomogram model to predict the risk of contrast-induced acute kidney injury (CI-AKI) by analyzing the risk factors of CI-AKI and to evaluate its effectiveness.

Methods

Retrospectively analyze the clinical data of non-ST-elevation acute coronary syndrome (NSTE-ACS) patients who underwent percutaneous coronary intervention (PCI) in our cardiology department from September 2018 to June 2021. Of these, patients who underwent PCI in an earlier period formed the training cohort (70%; n = 809) for nomogram development, and those who underwent PCI thereafter formed the validation cohort (30%; n = 347) to confirm the model’s performance. The independent risk factors of CI-AKI were determined by LASSO regression and multivariable logistic regression analysis. By using R software from which nomogram models were subsequently generated. The nomogram was developed and evaluated based on discrimination, calibration, and clinical efficacy using the concordance statistic (C-statistic), calibration plot, and decision curve analysis (DCA), respectively.

Results

The nomogram consisted of six variables: age >75, left ventricular ejection fraction, diabetes mellitus, fibrinogen-to-albumin ratio, high-sensitive C-reactive protein, and lymphocyte count. The C-index of the nomogram is 0.835 (95% CI: 0.800–0.871) in the training cohort and 0.767 (95% CI: 0.711–0.824) in the validation cohort, respectively. The calibration plots exhibited that the nomogram was in good agreement between prediction and observation in the training and validation cohorts. Decision curve analysis and clinical impact curve suggested that the predictive nomogram had clinical utility.

Conclusion

The nomogram model established has a good degree of differentiation and accuracy, which is intuitively and individually to screen high-risk groups and has a certain predictive value for the occurrence of CI-AKI in NSTE-ACS patients after PCI.

Malnutrition and the risk for contrast-induced acute kidney injury in patients with coronary artery disease

PURPOSE

Malnutrition is a common comorbidity of coronary artery disease (CAD) and is often associated with adverse events. The malnutrition often means lower cholesterol, albumin and high lymphocyte, as risk factors of Contrast-Induced Acute Kidney Injury (CI-AKI). We aim to evaluate the association between malnutrition and CI-AKI following coronary angiography (CAG) in CAD patients.

METHODS

We analyzed 3170 CAD patients with variables of nutritional status (Controlling Nutritional Status score (CONUT)) from the prospective multicenter study, REICIN (NCT01402232) including 4,271 consecutive patients undergoing CAG from January 2013 to February 2016. Patients were divided into the normal group (CONUT score 0-1) and malnutrition group (CONUT score > 1). The association of malnutrition and the risk of CI-AKI was examined in all CAD patients using multivariable logistics regression analysis.

RESULTS

Among the 3170 patients (mean age: 63.1 ± 10.7 years), 1865 (58.8%) suffered from malnutrition, 111 (3.5%) developed CI-AKI, including 23 (1.76%) in normal group and 88 (4.72%) in malnutrition group (p < 0.01). The malnourished patients were older, and likely had anemia and worse cardiorenal function. After adjustment for confounders, the risk of CI-AKI was 1.04 times higher in the malnutrition group than in the normal group (adjusted OR: 2.04, 95% CI 1.28-3.38, p < 0.01).

CONCLUSIONS

Among CAD patients undergoing CAG, malnutrition is extremely common and associated with a double risk of CI-AKI. Further studies are needed to investigate the potential renal protection of intervening malnutrition in CAD patients.

Glycosylated hemoglobin levels and the risk for contrast-induced nephropathy in diabetic patients undergoing coronary arteriography/percutaneous coronary intervention

Backgrounds

Diabetes mellitus is an independent risk factor for Contrast-induced nephropathy (CIN) in patients undergoing Coronary arteriography (CAG)/percutaneous coronary intervention (PCI). Glycosylated hemoglobin (HbA1c) is the gold standard to measure blood glucose control, which has important clinical significance for evaluating blood glucose control in diabetic patients in the past 3 months. This study aimed to assess whether preoperative HbA1c levels in diabetic patients who received CAG/PCI impacted the occurrence of postoperative CIN.

Methods

We reviewed the incidence of preoperative HbA1c and postoperative CIN in 670 patients with CAG/PCI from January 1, 2020 to October 30, 2020 and divided the preoperative HbA1c levels into 5 groups. Blood samples were collected at admission, 48 h and 72 h after operation to measure the Scr value of patients. Categorical variables were compared using a chi-square test, and continuous variables were compared using an analysis of variance. Fisher’s exact test was used to compare the percentages when the expected frequency was less than 5. Univariable and multivariable logistic regression analysis was used to exclude the influence of confounding factors, and P for trend was used to analyze the trend between HbA1c levels and the increased risk of CIN.

Results

Patients with elevated HbA1c had higher BMI, FBG, and LDL-C, and they were more often on therapy with hypoglycemic agents, Insulin and PCI. They also had higher basal, 48 h and 72 h Scr. The incidence of CIN in the 5 groups of patients were: 9.8, 11.9, 15.2, 25.3, 48.1%. (p < 0.0001) The multivariate analysis confirmed that in the main high-risk subgroup, patients with elevated HbA1C levels (≥8.8%) had a higher risk of CIN disease. Trend test showed the change of OR (1.000,1.248,1.553,2.625,5.829).

Conclusions

Studies have shown that in diabetic patients undergoing CAG/PCI, elevated HbA1c is independently associated with the risk of CIN, and when HbA1c > 9.5%, the incidence of CIN trends increase. Therefore, we should attach great importance to patients with elevated HbA1c at admission and take more active measures to prevent CIN.

Glycemic variability as predictor of contrast-induced nephropathy in diabetic patients with acute myocardial infarction undergoing percutaneous coronary intervention

Background

Contrast-induced nephropathy (CIN) is a frequent complication in patients undergoing percutaneous coronary intervention (PCI). Diabetes mellitus (DM) and acute myocardial infarction (AMI) are associated with an increased risk of CIN. However, it remains unclear whether glycemic variability (GV) has the important prognostic significance of CIN in diabetic patients with AMI undergoing PCI. We conducted this study to investigate the independent prognostic value of the in-hospital GV in diabetic patients who presented with AMI and were treated with PCI.

Methods

The study group comprised 252 diabetic patients with AMI who underwent PCI and were assigned to CINand non-CIN groups. A continuous glucose monitoring system (CGMS) was used to determine the mean amplitude of glycemic excursion (MAGE), a representative index of GV. Independent risk factors for CIN were determined by multivariate logistic regression analysis (MLRA), and receiver-operating characteristic (ROC) analysis was used to measure the prognostic potential of GV.

Results

A total of 55 patients had CIN and they showed markedly elevated MAGE compared with the non-CIN group. MLRA revealed that MAGE had potential to independently predict CIN. The area under the ROC curve, optimal cut-point value, sensitivity and specificity for MAGE were 0.739, 2.95, 70.91% and 61.42%, respectively.

Conclusions

In diabetic AMI patients undergoing PCI, high GV is associated with increased risk of CIN.