Predictive Power of f99 Repolarization Index for the Occurrence of Ventricular Arrhythmias

Giuliani, Corrado; Swenne, Cees A.; Man, Sumche; Agostinelli, Angela; Fioretti, Sandro; Nardo, Francesco Di; Burattini, Laura

doi:10.1111/anec.12274

Cited by 5 publications

(10 citation statements)

References 29 publications

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“…Therefore, to light of results, the use of HRS_BH3 is appropriate for sport applications relying on MHR estimations, but not to clinical evaluations based on HRV measurements. Instead, ECG_BH3, although sampled at a frequency (200 Hz) that is lower than that characterizing modern ECG machine (typically over 1000 Hz), can provide useful clinical information, allowing computation of both HR and repolarization parameters such as QT interval [20] Twave alternans [21,22] and f99 [23]. Still, there are several important differences between BH3 and traditional clinical ECG devices.…”

Section: Discussionmentioning

confidence: 99%

Validation of the Heart:Rate Signal Provided by the Zephyr BioHarness 3.0

Nepi

Sbrollini

Agostinelli

et al. 2016

2016 Computing in Cardiology Conference (CinC)

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Section: Discussionmentioning

confidence: 99%

Validation of the Heart:Rate Signal Provided by the Zephyr BioHarness 3.0

Nepi

Sbrollini

Agostinelli

et al. 2016

2016 Computing in Cardiology Conference (CinC)

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“…Development of a CaRiSMA 1.0 app providing alarms in real time is in progress. Future versions of CaRiSMA using other innovative ECG risk indexes such as T-wave alternans and f99 [20,42,43], besides QTc, are also under evaluation.…”

Section: Carisma 10 Softwarementioning

confidence: 99%

CaRiSMA 1.0: Cardiac Risk Self-Monitoring Assessment

Agostinelli¹,

Morettini²,

Sbrollini³

et al. 2017

TOSSJ

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Background: Sport-related sudden cardiac death (SRSCD) can only be fought through prevention. Objective: The aim of this study is to propose an innovative software application, CaRiSMA 1.0 (Cardiac Risk Self-Monitoring Assessment), as a potential tool to help contrasting SRSCD and educating to a correct training. Methods: CaRiSMA 1.0 analyzes the electrocardiographic and heart-rate (HR) signals acquired during a training session through wearable sensors and provides intuitive graphical outputs consisting of two traffic lights, one related to cardiac health, based on resting QTc (a parameter quantifying the duration of ventricular contraction and subsequent relaxation), and one related to training, based on exercise HR. Safe and worthwhile training sessions have green traffic lights. A red QTc traffic light indicates the need of a medical consultation, whereas a red HR traffic light indicate the need of a reduction of training intensity. By way of example, CaRiSMA 1.0 was applied to sample data acquired in 10 volunteers (age= 27±11 years; males/females 3/7). Results: Two acquisitions (20.0%) were rejected because too noisy, indicating that wearable sensors may record poor quality signals. The QTc traffic light was red in 1 case, indicating that people practicing sport may not be aware of being at risk. The HR traffic light was red in 0 cases. Conclusion: CaRiSMA 1.0 is a software application that, for the first time in the sport context, uses QTc, the most important index of cardiac risk in clinics. Thus, it has the potential for giving a contribution in the fight against SRSCD.

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“…Nevertheless, neither LVEF [16] nor the aforementioned indexes have proven sufficiently reliable for SCD prevention [4,5,[16][17][18]. Thus, we recently introduced a new frequency-based repolarization index termed f99, which is defined as the frequency at which the repolarization normalized cumulative energy reaches or overcomes 99% [19][20][21]. Notwithstanding, although f99 was found able to discriminate ventricular arrhythmias [21], still its predictive power is not sufficient to justify preventive diagnostic and therapeutic procedures in previously asymptomatic patients [21].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, we recently introduced a new frequency-based repolarization index termed f99, which is defined as the frequency at which the repolarization normalized cumulative energy reaches or overcomes 99% [19][20][21]. Notwithstanding, although f99 was found able to discriminate ventricular arrhythmias [21], still its predictive power is not sufficient to justify preventive diagnostic and therapeutic procedures in previously asymptomatic patients [21]. To overcome this issue, some authors have reported an increase in the predictive power when combining different indexes through various techniques [22,23], such as multiple linear regression or logistic regression (LR) [24].…”

Section: Introductionmentioning

confidence: 99%

“…Among these, the latter is the best fit in a case-control study since it uses a binary logistic model to predict a binary or dichotomous response variable from on one or more independent predictor variables [25], opposite to the former, which would be more suitable when the outcome variable is continuous [26]. Thus, being LVEF and f99 uncorrelated [21], the aim of the present study was to evaluate if combination of both LVEF and f99 by LR could enhance their predictive value. To this aim, the Leiden University Medical Center database of exercise ECGs in heart failure patients with implanted cardiac defibrillator (ICD) was used.…”

Section: Introductionmentioning

confidence: 99%

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Logistic regression to enhance risk assessment by left ventricular ejection fraction and f99

Giuliani

Swenne

Man

et al. 2015

2015 Computing in Cardiology Conference (CinC)

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Sudden cardiac death remains one of the leading causes of death in developed countries. Left ventricular ejection fraction (LVEF) and f99 are two noninvasive indexes of cardiovascular risk (traditional the former and innovative the latter) which, taken singularly, have not shown sufficiently high SCD predictive power to justify preventive actions. Thus, the aim of the present study was to investigate if their combination improves predictability of ventricular arrhythmias. To this aim, ECG recordings from 266 ICD patients, of which 76 developed ventricular tachycardia or fibrillation during the 4-year follow-up (ICD_Cases), and 190 did not (ICD_Controls). The ECGs of each patient was used to compute the f99, a repolarization index defined as the frequency at which the cumulative power energy reaches 99%. Eventually, a logistic regression between LVEF and f99 was performed in order to derive a combined predictor (CP) of ventricular arrhythmia. Goodness of each index was evaluated in terms of the area under the receiver operator curve (AUC). When used singularly, LVEF and f99 respectively provided an AUC of 0.67 and 0.64. When combined to get CP=-0.15-0.05•LVEF+0.03•f99, this provided an AUC of 0.71. In conclusion, use of logistic regression improves LVEF and f99 predictability of ventricular arrhythmias.

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Predictive Power of f99 Repolarization Index for the Occurrence of Ventricular Arrhythmias

Abstract: The f99 represents a promising risk index for the occurrence of ventricular arrhythmias, especially when maximized over the three orthogonal leads.

Cited by 5 publications

References 29 publications

Validation of the Heart:Rate Signal Provided by the Zephyr BioHarness 3.0

Validation of the Heart:Rate Signal Provided by the Zephyr BioHarness 3.0

CaRiSMA 1.0: Cardiac Risk Self-Monitoring Assessment

Logistic regression to enhance risk assessment by left ventricular ejection fraction and f99

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