2017
DOI: 10.1111/anec.12495
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Total cosine R‐to‐T for predicting ventricular arrhythmic and mortality outcomes: A systematic review and meta‐analysis

Abstract: TCRT is lower in MI patients at high risk of adverse events when compared to those free from such events. It can provide additional risk stratification beyond the use of clinical parameters and traditional electrocardiogram markers. Its value in other diseases such as heart failure requires further studies.

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Cited by 12 publications
(9 citation statements)
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“…The normal range in the general population based on the study was 72.2 ± 9.8 ms, and predictor value for the risk of ventricular arrhythmia was 99.8 ± 27.6. Meanwhile, the range in HFrEF population was 107 ± 22 ms, and predictor value for the risk of ventricular arrhythmia was 106.3 ± 8.4 [11,12]. The Tpe interval in our subjects was considered high compared to the general population but lower than HFrEF population.…”
Section: Discussionmentioning
confidence: 67%
“…The normal range in the general population based on the study was 72.2 ± 9.8 ms, and predictor value for the risk of ventricular arrhythmia was 99.8 ± 27.6. Meanwhile, the range in HFrEF population was 107 ± 22 ms, and predictor value for the risk of ventricular arrhythmia was 106.3 ± 8.4 [11,12]. The Tpe interval in our subjects was considered high compared to the general population but lower than HFrEF population.…”
Section: Discussionmentioning
confidence: 67%
“…Уже 20 лет назад было показано, что у пациентов после инфаркта миокарда (ИМ) большое расхождение в пространстве векторов де-и реполяризации желудочков имело независимую прогностическую ценность в отношении внезапной сердечной смерти (ВСС) [2,3].…”
Section: автор для перепискиunclassified
“…Dear Editor, My colleagues and I have read the review and meta-analysis of TCRT by Tse et al (2017) with substantial interest. Indeed, our team was the first to note the predictive value of increased spatial QRS-T angle (Zabel et al, 2000) and in this seminal clinical study, we used the TCRT technology that we previously developed (Acar, Yi, Hnatkova, & Malik, 1999).…”
Section: Shallow Meta Analysismentioning
confidence: 99%