Nomogram for contrast-induced acute kidney injury in patients with chronic kidney disease undergoing coronary angiography in China: a cohort study

Comparison of cardiac biomarkers on risk assessment of contrast-associated acute kidney injury in patients undergoing cardiac catheterization: A multicenter retrospective study

AIM

Cardiac biomarkers' predictive value of contrast-associated acute kidney injury (CA-AKI) remains unclear. We analysed whether creatine kinase isoenzyme-MB (CKMB), cardiac troponin I (cTnI) and preoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) are tied to CA-AKI patients undergoing cardiac catheterization.

METHODS

In the multi-center study, we included 3553 people underwent cardiac catheterization for analysis. CA-AKI was defined as the absolute increase of over 0.3 mg/dL or an increase of more than 50% compared with the baseline serum creatinine within 48 hours following cardiac catheterization. Logistic regression model and receiver operating characteristic (ROC) curves were used to examine the association between cardiac biomarkers and CA-AKI and the efficacy of Mehran risk score (MRS) model on CA-AKI prediction with and without cardiac biomarkers.

RESULTS

Among 3553 people, 200 people eventually developed CA-AKI. The logistic regression model showed that log10 CKMB (odds ratio (OR): 1.97, 95%CI:1.51-2.57, p < .001), cTnI (OR: 1.03, 95%CI: 1.02-1.04, p < .001) and log10 NT-proBNP (OR: 3.19, 95%CI: 2.46-4.17, p < .001) were independent predictors of CA-AKI. The ROC curve demonstrated that area under the curve (AUC) of MRS was 0.733. CKMB, cTnI and NT-proBNP all significantly improved the AUC value in combination with MRS model. (NT-proBNP: 0.798, p < .001; CKMB: 0.758, p = .003; cTnI: 0.755, p = .002), among which the NT-proBNP had the best predictive efficacy improvement.

CONCLUSION

Cardiac biomarkers of CKMB, cTnI and NT-proBNP are all independently associated with CA-AKI among patients undergoing cardiac catheterization while NT-proBNP remains the best indicator. Adding CKMB, cTnI and NT-proBNP to MRS improved the prognostic efficacy and may be considered effective tools to predict the risk of CA-AKI in clinical practice.

Circulating mitochondrial dysfunction as an early biomarker for contrast media-induced acute kidney injury in chronic kidney disease patients

Contrast-induced acute kidney injury (CI-AKI) is the common hospitalized acute kidney injury (AKI). However, the diagnosis by serum creatinine might not be early enough. Currently, the roles of circulating mitochondria in CI-AKI are still unclear. Since early detection is crucial for treatment, the association between circulating mitochondrial function and CI-AKI was tested as a potential biomarker for detection of CI-AKI. Twenty patients with chronic kidney disease (CKD) undergoing percutaneous coronary intervention (PCI) were enrolled. Blood and urine samples were obtained at the time of PCI, and 6, 24, 48 and 72 h after PCI. Plasma and urine neutrophil gelatinase-associated lipocalin (NGAL) were measured. Oxidative stress, inflammation, mitochondrial function, mitochondrial dynamics and cell death were determined from peripheral blood mononuclear cells. Forty percent of patients developed AKI. Plasma NGAL levels increased after 24 h after receiving contrast media. Cellular and mitochondrial oxidative stress, mitochondrial dysfunction and decreased mitochondrial fusion occurred at 6 h following contrast media exposure. Subgroup of AKI had higher %necroptosis cells and TNF-α mRNA expression than subgroup without AKI. Collectively, circulating mitochondrial dysfunction could be an early predictive biomarker for CI-AKI in CKD patients receiving contrast media. These findings provide novel strategies to prevent CI-AKI according to its pathophysiology.

Endorsement of the TRIPOD statement and the reporting of studies developing contrast-induced nephropathy prediction models for the coronary angiography/percutaneous coronary intervention population: a cross-sectional study

OBJECTIVE

Clear and specific reporting of a research paper is essential for its validity and applicability. Some studies have revealed that the reporting of studies based on the clinical prediction models was generally insufficient based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist. However, the reporting of studies on contrast-induced nephropathy (CIN) prediction models in the coronary angiography (CAG)/percutaneous coronary intervention (PCI) population has not been thoroughly assessed. Thus, the aim is to evaluate the reporting of the studies on CIN prediction models for the CAG/PCI population using the TRIPOD checklist.

DESIGN

A cross-sectional study.

METHODS

PubMed and Embase were systematically searched from inception to 30 September 2021. Only the studies on the development of CIN prediction models for the CAG/PCI population were included. The data were extracted into a standardised spreadsheet designed in accordance with the 'TRIPOD Adherence Assessment Form'. The overall completeness of reporting of each model and each TRIPOD item were evaluated, and the reporting before and after the publication of the TRIPOD statement was compared. The linear relationship between model performance and TRIPOD adherence was also assessed.

RESULTS

We identified 36 studies that developed CIN prediction models for the CAG/PCI population. Median TRIPOD checklist adherence was 60% (34%-77%), and no significant improvement was found since the publication of the TRIPOD checklist (p=0.770). There was a significant difference in adherence to individual TRIPOD items, ranging from 0% to 100%. Moreover, most studies did not specify critical information within the Methods section. Only 5 studies (14%) explained how they arrived at the study size, and only 13 studies (36%) described how to handle missing data. In the Statistical analysis section, how the continuous predictors were modelled, the cut-points of categorical or categorised predictors, and the methods to choose the cut-points were only reported in 7 (19%), 6 (17%) and 1 (3%) of the studies, respectively. Nevertheless, no relationship was found between model performance and TRIPOD adherence in both the development and validation datasets (r=-0.260 and r=-0.069, respectively).

CONCLUSIONS

The reporting of CIN prediction models for the CAG/PCI population still needs to be improved based on the TRIPOD checklist. In order to promote further external validation and clinical application of the prediction models, more information should be provided in future studies.

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.

Homocysteine, hypertension, and risks of cardiovascular events and all-cause death in the Chinese elderly population: a prospective study

BACKGROUND

Increased homocysteine levels are associated with the risk of cardiovascular disease (CVD) and death. However, their prevention has not been effective in decreasing CVD risk. This study investigated the individual and combined associations of hyperhomocysteinemia and hypertension with incident CVD events and all-cause death in the Chinese elderly population without a history of CVD.

METHODS

This prospective study was conducted among 1,257 elderly participants (mean age: 69 years). A questionnaire survey, physical examinations, and laboratory tests were conducted to collect baseline data. Hyperhomocysteinemia was defined as homocysteine level ≥ 15 µmol/L. H-type hypertension was defined as concomitant hypertension and hyperhomocysteinemia. Multivariate Cox regression analysis was used to evaluate individual and combined associations of hyperhomocysteinemia and hypertension with the risks of incident CVD events and all-cause death.

RESULTS

Over a median of 4.84-year follow-up, hyperhomocysteinemia was independently associated with incident CVD events and all-cause death. The hazard ratios (HRs) were 1.45 (95% CI: 1.01−2.08) for incident CVD events and 1.55 (95% CI: 1.04−2.30) for all-cause death. After adjustment for confounding factors, H-type hypertension had the highest HRs for incident CVD events and all-cause death. The fully adjusted HRs were 2.44 for incident CVD events (95% CI: 1.28−4.65), 2.07 for stroke events (95% CI: 1.01−4.29), 8.33 for coronary events (95% CI: 1.10−63.11), and 2.31 for all-cause death (95% CI: 1.15−4.62).

CONCLUSIONS

Hyperhomocysteinemia was an independent risk factor, and when accompanied by hypertension, it contributed to incident CVD events and all-cause death in the Chinese elderly population without a history of CVD.

A Simple Nomogram to Predict Contrast-Induced Acute Kidney Injury in Patients with Congestive Heart Failure Undergoing Coronary Angiography

Background

Patients with congestive heart failure (CHF) are vulnerable to contrast-induced kidney injury (CI-AKI), but few prediction models are currently available. Therefore, we aimed to establish a simple nomogram for CI-AKI risk assessment for patients with CHF undergoing coronary angiography.

Methods

A total of 1876 consecutive patients with CHF (defined as New York Heart Association functional class II-IV or Killip class II-IV) were enrolled and randomly (2:1) assigned to a development cohort and a validation cohort. The endpoint was CI-AKI defined as serum creatinine elevation of ≥0.3 mg/dL or 50% from baseline within the first 48–72 hours following the procedure. Predictors for the simple nomogram were selected by multivariable logistic regression with a stepwise approach. The discriminative power was assessed using the area under the receiver operating characteristic (ROC) curve and was compared with the classic Mehran score in the validation cohort. Calibration was assessed using the Hosmer–Lemeshow test and 1000 bootstrap samples.

Results

The incidence of CI-AKI was 9.06% (170) in the total sample, 8.64% (n = 109) in the development cohort, and 9.92% (n = 61) in the validation cohort (P=0.367). The simple nomogram including four predictors (age, intra-aortic balloon pump, acute myocardial infarction, and chronic kidney disease) demonstrated a similar predictive power as the Mehran score (area under the curve: 0.80 vs. 0.75, P=0.061), as well as a well-fitted calibration curve.

Conclusions

The present simple nomogram including four predictors is a simple and reliable tool to identify CHF patients at risk of CI-AKI, whereas further external validations are needed.

Nomogram to predict the risk of acute kidney injury in patients with diabetic ketoacidosis: an analysis of the MIMIC-III database

BACKGROUND

This study aimed to develop and validate a nomogram for predicting acute kidney injury (AKI) during the Intensive Care Unit (ICU) stay of patients with diabetic ketoacidosis (DKA).

METHODS

A total of 760 patients diagnosed with DKA from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included and randomly divided into a training set (70%, n = 532) and a validation set (30%, n = 228). Clinical characteristics of the data set were utilized to establish a nomogram for the prediction of AKI during ICU stay. The least absolute shrinkage and selection operator (LASSO) regression was utilized to identified candidate predictors. Meanwhile, a multivariate logistic regression analysis was performed based on variables derived from LASSO regression, in which variables with P < 0.1 were included in the final model. Then, a nomogram was constructed applying these significant risk predictors based on a multivariate logistic regression model. The discriminatory ability of the model was determined by illustrating a receiver operating curve (ROC) and calculating the area under the curve (AUC). Moreover, the calibration plot and Hosmer-Lemeshow goodness-of-fit test (HL test) were conducted to evaluate the performance of our newly bullied nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit.

RESULTS

A multivariable model that included type 2 diabetes mellitus (T2DM), microangiopathy, history of congestive heart failure (CHF), history of hypertension, diastolic blood pressure (DBP), urine output, Glasgow coma scale (GCS), and respiratory rate (RR) was represented as the nomogram. The predictive model demonstrated satisfied discrimination with an AUC of 0.747 (95% CI, 0.706-0.789) in the training dataset, and 0.712 (95% CI, 0.642-0.782) in the validation set. The nomogram showed well-calibrated according to the calibration plot and HL test (P > 0.05). DCA showed that our model was clinically useful.

CONCLUSION

The nomogram predicted model for predicting AKI in patients with DKA was constructed. This predicted model can help clinical physicians to identify the patients with high risk earlier and prevent the occurrence of AKI and intervene timely to improve prognosis.

A prediction model of contrast-associated acute kidney injury in patients with hypoalbuminemia undergoing coronary angiography

BACKGROUND

Risk stratification is recommended as the key step to prevent contrast-associated acute kidney injury (CA-AKI) among at-risk patients following coronary angiography (CAG) and/or percutaneous coronary intervention (PCI). Patients with hypoalbuminemia are prone to CA-AKI and do not have their own risk stratification tool. Therefore, this study developed and validated a new model for predicting CA-AKI among hypoalbuminemia patients CAG/PCI.

METHODS

1272 patients with hypoalbuminemia receiving CAG/PCI were enrolled and randomly allocated (2:1 ratio) into the development cohort (n = 848) and the validation cohort (n = 424). CA-AKI was defined as an increase of ≥0.3 mg/dL or 50% in serum creatinine (SCr) compared to baseline in the 48 to 72 h after CAG/PCI. A prediction model was established with independent predictors according to stepwise logistic regression, showing as a nomogram. The discrimination of the new model was evaluated by the area under the curve (AUC) and was compared to the classic Mehran CA-AKI model. The Hosmer-Lemeshow test was conducted to assess the calibration of our model.

RESULTS

Overall, 8.4% (71/848) patients of the development group and 11.2% (48/424) patients of the validation group experienced CA-AKI. A new nomogram included estimated glomerular filtration rate (eGFR), serum albumin (ALB), age and the use of intra-aortic balloon pump (IABP); showed better predictive ability than the Mehran score (C-index 0.756 vs. 0.693, p = 0.02); and had good calibration (Hosmer-Lemeshow test p = 0.187).

CONCLUSIONS

We developed a simple model for predicting CA-AKI among patients with hypoalbuminemia undergoing CAG/PCI, but our findings need validating externally.

TRIAL REGISTRATION

http://www.ClinicalTrials.gov NCT01400295 , retrospectively registered 21 July 2011.