Mount Sinai Prediction Model Scores Acute Kidney Injury Risk

A new prediction model created by Mount Sinai researchers can score risks and determine potential contrast-associated acute kidney injury (CA-AKI) among patients undergoing percutaneous coronary intervention (PCI).

According to the researchers, the tool can enhance the management of patients at high risk of CA-AKI during and after PCI to improve their prognosis following the procedure.

The risk score, named “The Mehran-2 CA-AKI Risk Score,” was created by Roxana Mehran, MD, Professor of Medicine (Cardiology), and Population Health Science and Policy, and other Mount Sinai cardiologists.

Patients with coronary artery disease often undergo PCI, a non-surgical procedure in which cardiologists use a catheter to place stents in the blocked coronary arteries to restore blood flow.

Cardiologists use X-ray imaging, known as angiography, to identify which arteries have the most severe blockages. The cardiologists then inject iodinated contrast into the bloodstream to make the blockages visible on X-ray. However, iodinated contrast is toxic, and high-risk groups can have kidney problems as a result.

“Although the incidence of CA-AKI has decreased over the past few years, it remains a significant complication of PCI and is associated with mortality, prolonged hospital stay, and increased medical costs. As the number of high-risk patients undergoing PCI increases every year, it is really crucial to risk-stratify these patients to optimize outcomes and minimize cardiorenal complications,” Mehran said in a press release.

“Simple measures can be taken around the time of procedure when a patient is identified to be at high risk of CA-AKI, and we hope this new score is widely adopted to enhance the care of patients and improve outcomes.”

The risk model expands upon Mehran’s original model developed in 2004 that was widely implemented in cardiac catheterization labs around the globe. The new updates consider how practices have progressed around PCI, including advancing imaging techniques and improved stents.

To update the risk score model, researchers examined data from 30,000 patients who underwent PCI at Mount Sinai Hospital from 2012 to 2020. Each patient had documented creatinine tests before, 48 hours after, and one year after the procedure.

The research team then developed a predictive model to determine which patients are at the highest risk of acute kidney injury based on risk factors such as diabetes, anemia, congestive heart failure, advanced kidney disease, acute heart attack, and ST-segment elevation myocardial infarction (STEMI), or complete blockage of a major heart artery.

Additionally, being over the age of 75 was also considered a risk factor. The team then assigned individual scores to each risk factor and calculated patients’ overall risk scores. Those between 0-4 points were “low risk,” 5-9 was “moderate risk,” 10-13 was “high risk,” and anything above 14 was “extremely high risk.”

By calculating risk scores and determining which category patients fit into, doctors can modify their periprocedural management approach to improve outcomes. According to researchers, the risk scores could also help doctors increase monitoring before and after PCI.

“Acute kidney injury after invasive procedures remains a mystery since it has such a robust adverse prognosis, yet we still don’t know of a clear responsible mechanism. Therefore, it remains a very challenging and interesting research field,” explains senior author George Dangas, MD, PhD, Professor of Medicine (Cardiology).

“The fact that periprocedural events have only minor contribution to the overall predictive power makes this model even more important, as its risk assessment is accurately available before the start, and plans can be made very early on.”

Mehran added, “We plan to design clinical trials and incorporate this score to evaluate both external validation in predicting acute kidney injury but also clinical outcomes.”