An Online Pre-procedural Nomogram for the Prediction of Contrast-Associated Acute Kidney Injury in Patients Undergoing Coronary Angiography

Abstract

BackgroundIdentifying high-risk patients for contrast-associated acute kidney injury (CA-AKI) helps to take early preventive interventions. The current study aimed to establish and validate an online pre-procedural nomogram for CA-AKI in patients undergoing coronary angiography (CAG).MethodsIn this retrospective dataset, 4,295 patients undergoing CAG were enrolled and randomized into the training or testing dataset with a split ratio of 8:2. Optimal predictors for CA-AKI were determined by Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) algorithm. Nomogram was developed and deployed online. The discrimination and accuracy of the nomogram were evaluated by receiver operating characteristic (ROC) and calibration analysis, respectively. Clinical usefulness was estimated by decision curve analysis (DCA) and clinical impact curve (CIC).ResultsA total of 755 patients (17.1%) was diagnosed with CA-AKI. 7 pre-procedural predictors were identified and integrated into the nomogram, including age, gender, hemoglobin, N-terminal of the prohormone brain natriuretic peptide, neutrophil-to-lymphocyte ratio, cardiac troponin I, and loop diuretics use. The ROC analyses showed that the nomogram had a good discrimination performance for CA-AKI in the training dataset (area under the curve, AUC = 0.766, 95%CI [0.737 to 0.794]) and testing dataset (AUC = 0.737, 95%CI [0.693 to 0.780]). The nomogram was also well-calibrated in both the training dataset (P = 0.965) and the testing dataset (P = 0.789). Good clinical usefulness was identified by DCA and CIC. Finally, this model was deployed in a web server for public use (https://duanbin-li.shinyapps.io/DynNomapp/).ConclusionAn easy-to-use pre-procedural nomogram for predicting CA-AKI was established and validated in patients undergoing CAG, which was also deployed online.

Mehran 2 Contrast-Associated Acute Kidney Injury Risk Score: Is it Applicable to the Asian Percutaneous Coronary Intervention Population?

“… 24 There are many risk warning systems for CA-AKI, and different models have a variety of predictors and risk thresholds for the same predictor. 25 , 26 The Mehran score is a classic and the most commonly used scoring system; it has long been used as the “gold standard” to measure the discriminative ability of other novel pre-glance models. 27 The system was developed by Mehran et al in 2004, 5 but it still has some flaws.…”

Construction and validation of a risk prediction model for acute kidney injury in patients after cardiac arrest

“…MAP and heart rate were assessed by calculating the median value from multiple measurements obtained within a 30-min timeframe following admission to ICU. The formula for calculating MAP: MAP (mmHg) = (SBP + 2 × DBP)/3 [ 16 ]. The shock was defined as persistent hypotension, indicated by an SBP < 90 mmHg, despite adequate fluid resuscitation or administration of vasopressor agents (e.g., dopamine/dobutamine, adrenaline) for a duration exceeding 6 hours [ 17 ].…”

Development and validation of a nomogram for predicting the risk of pressure injury in adult patients undergoing abdominal surgery

“…In this study, patients with PI occurring from postoperative to pre-discharge periods were included in the PI group, and patients without PI occurring were included in the non-PI group. And all datasets were randomly divided into training and validation cohorts according to a ratio of 8:2 through the R software [ 23 ]. The training cohort was adopted for correlation analysis through univariate analysis and multivariable Logistic regression analysis.…”