Novel bloodless potassium determination using a signal-processed single-lead ECG

Zachi I. Attia, Christopher V. DeSimone, John J. Dillon, Yehu Sapir, Virend K. Somers, Jennifer L. Dugan, Charles J. Bruce, Michael J. Ackerman, Samuel J. Asirvatham, Bryan L. Striemer, Jan Bukartyk, Christopher G. Scott, Kevin E. Bennet, Dorothy J. Ladewig, Emily J. Gilles, Dan Sadot, Amir B. Geva, Paul A. Friedman

Research output: Contribution to journalArticlepeer-review


Background-Hyper- and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood-free method for tracking potassium would be an important clinical advance. Methods and Results-Two groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent highresolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassiumvalues during the second and third dialysis sessions using only the processed single-channel ECG. In addition, by analyzing the entire development group's first-visit data,we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). Conclusions-The signal-processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost-effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

Original languageAmerican English
Article numbere002746
JournalJournal of the American Heart Association
Issue number1
StatePublished - 1 Jan 2016


  • Electrophysiology
  • Potassium
  • Waves

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine


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