Literature DB >> 26742587

Prognostic Significance of ST-Segment Elevation in Leads V₁-₂ in Patients With Severe Aortic Stenosis.

Tomohiko Taniguchi1, Hiroki Shiomi, Masami Kosuge, Takeshi Morimoto, Kenji Nakatsuma, Masataka Nishiga, Tomoki Sasa, Naritatsu Saito, Takeshi Kimura.   

Abstract

BACKGROUND: ST-segment elevation (STE) in leads V1-2 is often observed in patients with severe aortic stenosis (AS), but its significance remains unknown. METHODS AND 
RESULTS: We retrospectively evaluated baseline ECGs and 5-year clinical outcomes in 211 consecutive patients with severe AS, defined as peak aortic jet velocity (Aortic Vmax) >4.0 m/s, or mean aortic pressure gradient >40 mmHg, or aortic valve area (AVA) <1.0 cm(2). The primary outcome measure was a composite of death or surgical aortic valve replacement (AVR). Patients with STE in leads V1-2(≥0.15 mV) had greater Aortic Vmax and smaller AVA than patients without. With a median follow-up of 4.9 years, the cumulative 5-year incidence of death or AVR was significantly higher in patients with STE in leads V1-2 than in patients without (91.4% vs. 77.1%; P=0.003). After adjusting for confounders, STE in leads V1-2 was independently associated with higher risk for death or AVR (hazard ratio, 1.53; 95% confidence interval, 1.06-2.22; P=0.02). In 64 asymptomatic patients without any indication for AVR at initial diagnosis of severe AS, the cumulative incidence of AVR was significantly higher in patients with STE in leads V1-2 than in patients without (57.6% vs. 30.5%; P<0.001).
CONCLUSIONS: STE in leads V1-2 independently predicted poorer prognosis and more frequent need for AVR in patients with severe AS.

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Year:  2016        PMID: 26742587     DOI: 10.1253/circj.CJ-15-0641

Source DB:  PubMed          Journal:  Circ J        ISSN: 1346-9843            Impact factor:   2.993


  2 in total

1.  Electrocardiographic appearance of aortic stenosis before and after aortic valve replacement.

Authors:  Ivana I Vranic
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-04-21       Impact factor: 1.468

2.  Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.

Authors:  Joon-Myoung Kwon; Soo Youn Lee; Ki-Hyun Jeon; Yeha Lee; Kyung-Hee Kim; Jinsik Park; Byung-Hee Oh; Myong-Mook Lee
Journal:  J Am Heart Assoc       Date:  2020-03-21       Impact factor: 5.501

  2 in total

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