A concise predictive nomogram for renal artery stenosis in selective patients undergoing coronary angiography

Area of Science:

• Cardiology
• Nephrology
• Medical Imaging

Background:

• Existing scoring systems for renal artery stenosis (RAS) screening lack easy validation.
• A simple predictive method for RAS is needed, especially for patients undergoing coronary angiography (CAG).

Purpose of the Study:

• To develop and validate a simple nomogram for predicting or ruling out RAS in patients undergoing CAG.
• To identify independent predictors of significant RAS.

Main Methods:

• A multivariable logistic regression model was used to derive a nomogram.
• The nomogram's accuracy was assessed using the area under the receiver operating characteristic curve (AUC).
• Two cohorts (development: 503 patients, validation: 158 patients) were enrolled between 2012-2017.

Main Results:

• Hypertension (OR 17.92), estimated glomerular filtration rate ≤72.66 mL/min·1.73 m² (OR 2.75), early to late transmitral flow velocity ratio ≤1.02 (OR 2.58), and low-density lipoprotein cholesterol ≤3.17 mmol/L (OR 1.85) were independent predictors of RAS.
• The nomogram achieved AUCs of 0.754 in the development cohort and 0.772 in the validation cohort.
• Hypertension demonstrated a high negative predictive value (88.9%) for RAS.

Conclusions:

• A concise predictive nomogram can effectively estimate the probability of significant RAS during CAG.
• The nomogram, combined with clinical data like normotension, aids in evaluating the necessity of RAS screening.