Explanatory variable

LV mass

LVEF

GLS

E/é


Univariable

Multivariable model R^{2} = 0.19

Univariable

Multivariable model R^{2} = 0.09

Univariable

Multivariable model R^{2} = 0.16

Univariable

Multivariable model R^{2} = 0.22


β_{1}, R^{2}

B

β_{1}, R^{2}

B

β_{1}, R^{2}

B

β_{1}, R^{2}

B


Demographic data

Age, years

0.4, 0.01
 
− 0.03, 0.00
 
0.02, 0.00
 
0.21***, 0.12

0.2***

Gender = female

− 15.0***, 0.11

− 10.9**

1.9, 0.02
 
− 1.5**, 0.05

− 1.0

0.5, 0.00

1.5**

Smoker/former smoker

2.1, 0.00
 
− 0.03, 0.00
 
0.38, 0.01
 
0.20, 0.00
 
BMI, kg/m^{2}

0.8, 0.21
 
− 0.56***, 0.08

− 0.6***

0.27***, 0.01

0.2***

0.26***, 0.08
 
Medical history

Angina pectoris

2.9, 0.00
 
− 1.0, 0.00
 
− 0.85, 0.00
 
3.2, 0.02
 
Myocardial infarction

11.4, 0.01
 
− 2.0, 0.00
 
1.2, 0.00
 
− 0.46, 0.00
 
Coronary revascularization

10.1, 0.00
 
0.8, 0.00
 
− 0.49, 0.00
 
− 3.3*, 0.02
 
Hypertension

10.4*, 0.04
 
− 1.9, 0.01
 
0.86, 0.01
 
0.50, 0.00
 
Medication

Statins

12.6*, 0.03

12.9*

− 3.3, 0.02
 
1.1, 0.01
 
− 0.02, 0.00
 
ACEI and/or ARB

8.3, 0.02
 
− 2.2, 0.01
 
1.2, 0.01
 
− 0.44, 0.00
 
Calcium channel blocker

15.6*, 0.03
 
0.5, 0.00
 
− 0.81, 0.00
 
0.53, 0.00
 
βBlocker

5.6, 0.01
 
− 1.0, 0.00
 
0.55, 0.00
 
0.13, 0.00
 
Laboratory analyses

Triglycerides, mmol/L

0.9, 0.00
 
0.06, 0.00
 
0.01*, 0.00
 
− 13, 0.00
 
LDLC, mmol/L

− 1.9, 0.00
 
0.34, 0.00
 
0.36, 0.01
 
0.40, 0.01
 
Microalbuminuria

10.5, 0.01
 
− 14.8, 0.00
 
11.3, 0.00
 
3.5*, 0.04
 
Creatinine, µmol/L

0.3*, 0.03
 
− 0.08, 0.00
 
0.09, 0.02
 
0.05, 0.01
 
GFR, mL/min/1.73 m^{2}

0.1, 0.00
 
0.04, 0.01
 
0.00, 0.00
 
− 0.03, 0.02
 
Blood pressure (mmHg)

Systolic blood pressure

0.4***, 0.09

0.3**

− 0.03, 0.01
 
0.02, 0.01
 
0.06***, 0.09
 
Diastolic blood pressure

0.6**, 0.08
 
− 0.1, 0.02
 
0.08***, 0.07

0.2**

0.10***, 0.08

0.1***

 Results from univariable regression Y = β_{0} + β_{1} *X + ε. Results are presented as estimated regression parameters β_{1} and pvalues (* p < 0.05, ** p < 0.01 and *** p < 0.001) for parameters and R^{2}. Hypothesis tested H_{0}: β_{0} and β_{1} = 0 against H_{1}: β_{0} and β_{1} ≠ 0. Note that the β_{0} term is not presented in the table. Final results of multivariable linear regression analysis Y = Β X + ε of LV mass, LVEF and E/é. B is the estimated vector of regression parameters in the multivariable model. ε represents the errorterm in the model. Results are presented as estimated regression parameters, pvalues for the parameters, and R^{2}, the explained proportion of variation in the outcome variable by the explanatory variables. LV mass are indexed by body surface area. See abbreviations as in Table 1 and 2