The prediction of the in-hospital mortality of acutely ill medical patients by electrocardiogram (ECG) dispersion mapping compared with established risk factors and predictive scores--a pilot study.

OBJECTIVE: ECG dispersion mapping (ECG-DM) is a novel technique that analyzes low amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI). This study compared the ability of ECG-DM to predict in-hospital mortality with traditional risk factors such as age, vital signs and co-morbid diagnoses, as well as three predictive scores: the Simple Clinical Score (SCS)--based on clinical and ECG findings, and two Medical Admission Risk System scores--one based on vital signs and laboratory data (MARS), and one only on laboratory data (LD).
METHODS: A convenient sample of 455 acutely ill medical patients (mean age 69.7±14.0 years) had their vital signs, mental and functional status recorded and a 12 lead ECG, routine laboratory investigations and ECG-DM performed immediately after admission to hospital. Each patient's in-hospital course and diagnoses at death or discharge were reviewed.
RESULTS: Of the vital signs only oxygen saturation and respiratory rate were statistically significant predictors of death. The continuous variables that predicted death the best were: MARS, SCS, LD, white cell count and MMI. The categorical variables that predicted in-hospital mortality with highest Chi-square were: a diagnosis of stroke, SCS>=12, LD>0.10, MARS>0.09 and MMI>36%.
CONCLUSION: ECG-DM may be a clinically useful predictor of in-hospital mortality. ECG-DM is inexpensive, only takes a few seconds to perform and requires no skill to interpret.