**Authors and Affiliations**
David M Harmon MD, Kan Liu PhD, Jennifer Dugan BA, Jacob C Jentzer MD, Zachi I Attia, Paul A Friedman, John J Dillon 
Department of Internal Medicine, Mayo Clinic, Rochester MN 
Department of Cardiovascular Disease, Mayo Clinic, Rochester MN 
Division of Nephrology and Hypertension, Mayo Clinic, Rochester MN

**Background**
We have previously trained a convolutional neural network to detect hyperkalemia from a surface ECG. In this validation study, we assessed the network's performance among ED and ICU patients.

**Methods**
We included research-authorized, adult patients presenting to the ED at all Mayo Clinic sites between February and August 2021 (ED cohort) and patients admitted to the ICU at Mayo Clinic St. Mary's Hospital, Rochester, MN between August 2017 and February 2018 (ICU cohort) who had a standard 12-lead supine ECG and a blood potassium value within 4 hours of the ECG. The network analyzed leads I and II of the 12-lead ECG to calculate the probability of hyperkalemia, defined as K>6 mEq/L. The ED and ICU cohorts were analyzed separately. Exploratory subgroup analyses were performed for patients with low eGFR(<45 ml/min).

**Results**
40,128 ED patients and 2636 ICU patients were included. The prevalence of hyperkalemia was 0.9% in the ED cohort and 3.3% in the ICU cohort. The AI-ECG had AUCs of 0.88 in both cohorts with sensitivities and specificities ≥ 80%. Negative predictive values (NPVs) were >99% in both cohorts. Although positive AI-ECGs quadrupled the probability of hyperkalemia, positive predictive values (PPVs) were relatively low: 3.5% in the ED and 14% in the ICU in part due to low hyperkalemia prevalences. Low eGFR subgroups had higher hyperkalemia prevalences and higher PPVs.

**Conclusion**
The AI-ECG demonstrated excellent discrimination in both cohorts. It was highly effective at ruling out hyperkalemia with NPVs>99% with much lower PPVs, suggesting that it is most useful as a screening test to exclude hyperkalemia. One method by which PPVs can be increased is by limiting testing to high-risk populations, such as those with reduced eGFR.



Non-Invasive AI-Enhanced Electrocardiographic Detection of Hyperkalemia in the ED and ICU