» Articles » PMID: 12912813

Natural History of Asymptomatic Left Ventricular Systolic Dysfunction in the Community

Overview
Journal Circulation
Date 2003 Aug 13
PMID 12912813
Citations 181
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Information is limited regarding the rates of progression to congestive heart failure (CHF) and death in individuals with asymptomatic left ventricular systolic dysfunction (ALVD). We sought to characterize the natural history of ALVD, by studying unselected individuals with this condition in the community.

Methods And Results: We studied 4257 participants (1860 men) from the Framingham Study who underwent routine echocardiography. The prevalence of ALVD (visually estimated ejection fraction [EF]<or=50% without a history of CHF) was 6.0% in men and 0.8% in women. During up to 12 years of follow-up, rates of CHF among subjects with normal left ventricular systolic function (EF >50%, n=4128) and ALVD (n=129) were 0.7 and 5.8 per 100 person-years, respectively. After adjustment for cardiovascular disease risk factors, ALVD was associated with a hazards ratio (HR) for CHF of 4.7 (95% CI 2.7 to 8.1), compared with individuals without ALVD. An elevated risk of CHF after ALVD was observed even in individuals without prior myocardial infarction or valvular disease, with an adjusted HR of 6.5 (CI 3.1 to 13.5). Mild ALVD (EF 40% to 50%, n=78) and moderate-to-severe ALVD (EF <40%, n=51) were associated with adjusted HRs for CHF of 3.3 (CI 1.7 to 6.6) and 7.8 (CI 3.9 to 15.6), respectively. ALVD was also associated with an increased mortality risk (adjusted HR 1.6, CI 1.1 to 2.4). The median survival of ALVD subjects was 7.1 years.

Conclusions: Individuals with ALVD in the community are at high risk of CHF and death, even when only mild impairment of EF is present. Additional studies are needed to define optimal therapy for mild ALVD.

Citing Articles

Deep Learning-Based Identification of Echocardiographic Abnormalities From Electrocardiograms.

Fujiki G, Kodera S, Setoguchi N, Tanabe K, Miyaji K, Kushida S JACC Asia. 2025; 5(1):88-98.

PMID: 39886205 PMC: 11775793. DOI: 10.1016/j.jacasi.2024.10.012.


Haemoglobin levels are associated with echocardiographic measures in a Finnish midlife population.

Tapio J, Gronlund T, Kaikkonen K, Junttila M, Tulppo M, Koivunen P Ann Med. 2024; 56(1):2425061.

PMID: 39624964 PMC: 11616746. DOI: 10.1080/07853890.2024.2425061.


Comparison of Outcomes Between ST-Segment Elevation and Non-ST-Segment Elevation Myocardial Infarctions Based on Left Ventricular Ejection Fraction.

Kim Y, Her A, Rha S, Choi C, Choi B, Park S J Clin Med. 2024; 13(22).

PMID: 39597888 PMC: 11595183. DOI: 10.3390/jcm13226744.


Development and Multinational Validation of an Ensemble Deep Learning Algorithm for Detecting and Predicting Structural Heart Disease Using Noisy Single-lead Electrocardiograms.

Aminorroaya A, Dhingra L, Pedroso Camargos A, Vasisht Shankar S, Coppi A, Khunte A medRxiv. 2024; .

PMID: 39417103 PMC: 11482986. DOI: 10.1101/2024.10.07.24314974.


Machine learning in the prevention of heart failure.

Hamid A, Segar M, Bozkurt B, Santos-Gallego C, Nambi V, Butler J Heart Fail Rev. 2024; 30(1):117-129.

PMID: 39373822 DOI: 10.1007/s10741-024-10448-0.