Usefulness of Adding Pre-procedural Glycemia to the Mehran Score to Enhance Its Ability to Predict Contrast-induced Kidney Injury in Patients Undergoing Percutaneous Coronary Intervention Development and Validation of a Predictive Model

• Published in: The American journal of cardiology Vol. 155; pp. 16 - 22
• Main Authors: Nusca, Annunziata, Mangiacapra, Fabio, Sticchi, Alessandro, Polizzi, Giovanni, D'Acunto, Giulia, Ricottini, Elisabetta, Melfi, Rosetta, Gallo, Paolo, Miglionico, Marco, Giannone, Sara, Ussia, Gian Paolo, Grigioni, Francesco
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 15-09-2021; Elsevier Limited
• Subjects: Anemia; Angioplasty; Blood glucose; Calibration; Derivation; Diabetes; Diabetes mellitus; Discrimination; Ejection fraction; Females; Heart failure; Hyperglycemia; Hypotension; Kidney diseases; Kidneys; Patients; Prediction models; Risk analysis; Risk factors; Variables
• ISSN: 0002-9149; 1879-1913
• DOI: 10.1016/j.amjcard.2021.06.014

The Mehran score is the most widely accepted tool for predicting contrast-induced acute kidney injury (CI-AKI), a major complication of percutaneous coronary intervention (PCI). Similarly, abnormal fasting pre-procedural glycemia (FPG) represents a modifiable risk factor for CI-AKI, but it is not included in current risk models for CI-AKI prediction. We sought to analyze whether adding FPG to the Mehran score improves its ability to predict CI-AKI following PCI. We analyzed 671 consecutive patients undergoing PCI (age 69 [63,75] years, 23% females), regardless of their diabetic status, to derive a revised Mehran score obtained by including FPG in the original Mehran score (Derivation Cohort). The new risk model (GlyMehr) was externally validated in 673 consecutive patients (Validation Cohort) (age 69 [62,76] years, 21% females). In the Derivation Cohort, both FPG and the original Mehran score predicted CI-AKI (AUC 0.703 and 0.673, respectively). The GlyMehr score showed a better predictive ability when compared with the Mehran score both in the Derivation Cohort (AUC 0.749, 95%CI 0.662 to 0.836; p = 0.0016) and the Validation Cohort (AUC 0.848, 95%CI, 0.792 to 0.903; p = 0.0008). In the overall population (n = 1344), the GlyMehr score confirmed its independent and incremental predictive ability regardless of diabetic status (p ≤0.0034) or unstable/stable coronary syndromes (p ≤0.0272). In conclusion, adding FPG to the Mehran score significantly enhances our ability to predict CI-AKI. The GlyMehr score may contribute to improve the clinical management of patients undergoing PCI by identifying those at high risk of CI-AKI and potentially detecting modifiable risk factors.