A sequential method for real-time detection of life-threatening signals in serum potassium level after myocardial infarction. Issue 2 (3rd April 2017)

• Record Type: Journal Article
• Authors: Shauly-Aharonov, Michal; Pollak, Moshe; Plakht, Ygal
• Is Part Of: Sequential analysis. Volume 36:Issue 2(2017)
• Page Start: 179
• Page End: 193
• Publication Date: 2017-04-03
• Subjects: ARMA model -- arrhythmia -- change-point detection -- myocardial infarction -- potassium -- Shiryaev-Roberts procedure; 62L05 -- 62L10 -- 92C50; Sequential analysis -- Periodicals; 519.54
• DOI: 10.1080/07474946.2017.1319679
• Languages: English
• ISSNs: 0747-4946

Abstract

ABSTRACT: Clinical guidelines recommend maintaining potassium levels between 4.0 and 5.0 mEq/L in patients with acute myocardial infarction (MI). These guidelines are based on studies that found associations between crossing of absolute potassium limits and mortality. This article investigates a different approach: we hypothesized that a change in the potassium level may be a harbinger of short survivability, rather than crossing of absolute boundaries. Our objectives were to (1) examine whether a change in the mean potassium level can predict in-hospital death in complicated MI hospitalizations (30 days or more) and (2) formulate a framework for on-line detection of such changes in patients hospitalized with MI. The study included 195 patients who were hospitalized from 2002 to 2014. We found evidence that a change in the mean has the ability to distinguish between survivors and nonsurvivors. A threshold for raising an alarm was specified by plotting a receiver operating characteristic (ROC) curve and choosing the best combination of sensitivity and specificity. The method detected 64% of the patients who eventually died, while wrongly alerting for 25% of the survivors. Almost all of the true alarms were given in a time that would have been reasonable enough to address the cause of the disorder.