Septal q waves as an indicator of risk of mortality in elderly patients with chronic heart failure

Am Heart J. 2002 Oct;144(4):740-4. doi: 10.1067/mhj.2002.123838.

Abstract

Background: The absence of electrocardiographic septal q wave is a recognized marker of left ventricular disease. We aimed to investigate the prognostic significance of absent septal q waves in elderly (age >65 years) patients with chronic heart failure.

Methods: A total of 110 patients (mean age 73 +/- 4 years) with New York Heart Association functional class II to IV and left ventricular ejection fraction of <45% were enrolled in the study. Standard 12-lead electrocardiograms were critically analyzed for the presence or absence of septal q waves in leads I, aVL, V5, and V6. Patient survival was determined from hospital and general practitioner records and National Statistics Registry at a mean follow-up of 4 years.

Results: Septal q waves were absent in 71 and present in 39 patients. The overall mortality rate was 47% (43 patients). The incidence of death was 49% (36 patients) in the group with no septal q waves and 18% (7 patients) in those who demonstrated septal q waves. On univariate analysis by Cox proportional hazard method, absence of septal q waves was found to be a strong marker of poor prognosis in CHF (P =.003, hazard ratio 1.40, 95% CI 1.10-1.67). Kaplan-Meier survival curves showed a significant difference in survival independent of age, New York Heart Association functional class, peak VO2, and QRS duration between these 2 groups.

Conclusions: Absence of the normal septal q wave on 12-lead electrocardiography, which may indicate structural heart disease and myocardial fibrosis, is an independent predictor of poor prognosis in elderly patients with CHF.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Chronic Disease
  • Electrocardiography*
  • Follow-Up Studies
  • Heart Failure / mortality
  • Heart Failure / physiopathology*
  • Heart Septum / physiology
  • Humans
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Stroke Volume
  • Survival Analysis