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Table 5 Multivariable analysis of variables associated with arrhythmia

From: Association of cardiovascular magnetic resonance diastolic indices with arrhythmia in repaired Tetralogy of Fallot

Atrial arrhythmia

Model 1: Classic Predictors (area under ROC curve = 0.72)

 

OR

p-value

95% CI

QRS Duration

1.03

0.001

1.01–1.04

RVEDVI (per 10 ml/m2)

1.25

0.330

0.80–1.95

RVESVI (per 10 ml/m2)

0.72

0.398

0.33–1.55

RVEF (%)

0.95

0.306

0.86–1.05

Model 2: Including Diastolic Predictors (area under ROC curve = 0.79)

QRS duration

1.02

0.010

1.00–1.03

Indexed LAMin Vol. (per 10 ml/m2)

3.20

0.004

1.46–7.04

tPFR

1.01

0.065

1.00–1.02

Ventricular arrhythmia

Model 1: Classic Predictors (area under ROC curve = 0.70)

 

OR

p-value

95% CI

QRS Duration

1.01

0.060

1.00–1.03

RVEDVI (per 10 ml/m2)

1.42

0.156

0.88–2.30

RVESVI (per 10 ml/m2)

0.59

0.210

0.26–1.35

RVEF (%)

0.91

0.098

0.81–1.02

Model 2: Including Diastolic Predictors (area under ROC curve = 0.72)

QRS duration

1.01

0.160

1.00–1.03

Indexed LAmin Vol. (per 10 ml/m2)

2.19

0.035

1.05–4.53

PFR/EDV

0.61

0.127

0.32–1.15

Total arrhythmia

Model 1: Classic Predictors (area under ROC curve = 0.68)

 

OR

p-value

95% CI

QRS Duration

1.02

0.003

1.01–1.03

RVEDVI (per 10 ml/m2)

1.16

0.467

0.78–1.74

RVESVI (per 10 ml/m2)

0.80

0.535

0.40–1.62

RVEF (%)

0.96

0.362

0.88–1.05

Model 2: Including Diastolic Predictors (area under ROC curve = 0.75)

QRS duration

1.02

0.004

1.01–1.03

Indexed LAmin Vol. (per 10 ml/m2)

2.35

0.010

1.22–4.51

tPFR

1.01

0.146

1.00–1.01

  1. RVEDVI- right ventricular end-diastolic volume index; RVESVI- right ventricular end-systolic volume index; RVEF- right ventricular ejection fraction; LA- left atrium; PER- peak ejection rate; tPER- time to peak ejection rate; PER/EDV- peak ejection rate to end diastolic volume; PFR- peak filling rate; tPFR- time to peak filling rate; PFR/EDV- peak filling rate to end diastolic volume
  2. *Data presented as odds ratios (OR) with 95% CI for multivariable logistic regression