The Romhilt-Estes left ventricular hypertrophy score and its components predict all-cause mortality in the general

E Harvey Estes1, Zhu-Ming Zhang2, Yabing Li2

  • 1Department of Community and Family Medicine, Duke University Medical Center, Durham, NC.

Insights

The Romhilt-Estes (R-E) score, used for left ventricular hypertrophy (LVH), effectively predicts mortality risk. This electrocardiogram (ECG) tool and its components offer valuable insights into adverse clinical outcomes.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Public Health

Background:

  • Electrocardiogram (ECG) criteria for left ventricular hypertrophy (LVH) are increasingly recognized as predictors of adverse clinical outcomes.
  • The predictive ability of these ECG criteria for clinical outcomes requires further exploration.

Purpose of the Study:

  • To investigate the association between the Romhilt-Estes (R-E) score for LVH and all-cause mortality.
  • To examine the predictive value of individual components of the R-E score for mortality.
  • To assess the association between changes in the R-E score and mortality risk.

Main Methods:

  • Analysis of 14,984 participants from the ARIC study with baseline ECG data (1987-1989).
  • Calculation of the Romhilt-Estes (R-E) LVH score and its components.
  • Ascertainment of all-cause mortality up to December 2010.
  • Use of Cox proportional hazard models to analyze associations between R-E score (baseline and change) and mortality.

Main Results:

  • A median follow-up of 21.7 years revealed 4,549 all-cause mortality events.
  • Increasing baseline R-E scores and increases in R-E score over time were associated with higher mortality risk.
  • Four of the six R-E score components (P-terminal force, QRS amplitude, LV strain, intrinsicoid deflection) were predictive of mortality.

Conclusions:

  • The Romhilt-Estes (R-E) score, beyond its use for LVH detection, serves as a valuable tool for predicting adverse clinical outcomes.
  • Specific ECG components within the R-E score demonstrate differential predictive power for mortality.
Abstract

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