Open Access

The effects of smoking and drinking on all-cause mortality in patients with dilated cardiomyopathy: a single-center cohort study

Contributed equally
European Journal of Medical Research201520:78

https://doi.org/10.1186/s40001-015-0171-z

Received: 30 March 2015

Accepted: 4 September 2015

Published: 17 September 2015

Abstract

Subject

Recent studies have shown that smoking and drinking are associated with poorer outcomes in patients with cardiomyopathy. The purpose of this study was to determine all-cause mortality in dilated cardiomyopathy (DCM) associated with smoking and drinking.

Methods

An observational cohort study was undertaken in DCM patients from November 2003 to September 2011. A total of 1118 patients were enrolled, with a mean follow-up of 3.5 ± 2.3 years. Standard demographics were obtained, and transthoracic echocardiography and routine blood testing were performed shortly after admission. Outcome assessment was based on the all-cause death after admission.

Results

The patients were divided into three groups: non-smokers (n = 593), mild-to-moderate smokers (n = 159) and heavy smokers (n = 366). The all-cause mortality rates showed no differences between the three groups (23.8, 20.8 and 24 %, respectively; log-rank χ 2 = 1.281, P = 0.527). There was also no significant difference in mortality between non-drinkers (n = 747), mild drinkers (n = 142) and moderate drinkers (n = 229) (23.7, 23.2 and 22.3 %, respectively; log-rank χ 2 = 2.343, P = 0.310). In the Cox analysis, neither the smoking (HR 0.971, P = 0.663) nor the drinking status (HR 0.891, P = 0.140) was a significant independent predictor of all-cause mortality in patients with DCM.

Conclusion

In conclusion, there were no significant differences in mortality between the smoking- and drinking-related patient groups, indicating no effect of smoking and drinking on all-cause mortality in patients with DCM in the present large-scale study.

Keywords

Smoking Drinking Dilated cardiomyopathy All-cause mortality Survival

Background

Dilated cardiomyopathy (DCM), a disease of the heart muscle characterized by ventricular dilatation and impaired systolic function, is the third most common cause of heart failure [1, 2]. The prognosis of patients with DCM is poor, with approximately half of the patients dying within 5 years of diagnosis, and it is necessary for the physician to predict which clinical course an individual patient may follow [1, 2].

Studies in mice and humans have shown that alcohol is a direct myocardial toxin that causes ultrastructural damage. Heavy drinking has been associated with left ventricular dysfunction and DCM, referred to as alcoholic cardiomyopathy [3, 4]. According to most studies, heavy drinking is associated with increased cardiovascular morbidity and mortality [57]. The US National Health and Nutrition Examination has stated that alcohol consumption has a linear relationship with mortality, with a slightly higher mortality risk for even light drinking [6, 7]. However, some studies have shown that moderate alcohol consumption has cardioprotective effects; reduces the risk of chronic heart failure, coronary artery disease and stroke; and decreases cardiovascular and all-cause mortality [812].

Cigarette smoking is a major modifiable risk factor for cardiovascular diseases, including coronary artery disease, stroke, peripheral vascular disease and congestive heart failure [13, 14]. Both smoking and exposure to passive smoke are major preventable causes of cardiovascular morbidity and mortality [15, 16]. Previous studies have indicated that smoking is related to cardiomyopathy [17] and is an important risk factor for idiopathic congestive cardiomyopathy [18]. However, recent studies have suggested that patients with DCM who smoke have a better prognosis than that of nonsmokers [1921], although data from New Zealand show that smoking is associated with poorer survival in patients with DCM [22].

Although heavy drinking and smoking are known risk factors for cardiovascular mortality, their roles in DCM patients remain unclear [5, 1922]. Therefore, in the present study, we aimed to evaluate the association of drinking and smoking with all-cause mortality in hospitalized patients with DCM in China.

Subjects and methods

Patients and follow-up

A retrospective, observational cohort study of DCM patients was conducted from November 2003 to September 2011. The patients were admitted with symptoms of decompensation and physical signs of heart failure, and DCM was defined as systolic dysfunction (LVEF ≤50 %) with LV dilation in the absence of an apparent secondary cause of cardiomyopathy [23]. Of the 1317 enrolled patients, 175 patients were excluded from the study owing to the presence of various secondary cardiomyopathies, and data on smoking and drinking were lacking for 24 and 25 patients, respectively (Fig. 1). Thus, the final analysis included 1118 patients, with data on drinking lacking for 1 patient. The end point of the study was the all-cause mortality, which was assessed for all patients based on medical records and medical follow-up calls. Mortality data were obtained for all study patients from hospitalization to death. Data from patients who underwent cardiac transplantation were censored at the time of transplantation, if alive, to the date of the most recent clinical evaluation. The mean follow-up was 3.5 ± 2.3 years. The institutional review board approval was obtained.
Fig. 1

Flowchart for participants involved in the present study

Smoking and drinking habits

The three categories of drinkers were: non-drinkers; mild drinkers, who reported drinking an average of one drink a day on the days on which they consumed alcohol during the previous year; and moderate drinkers, who reported drinking an average of two drinks a day on the days on which they consumed alcohol during the previous year (1 drink = 12 g alcohol) [24]. Three categories of smokers were considered: non-smokers, mild-to-moderate smokers, who had smoked less than 40-pack years (PY); and heavy smokers, who had smoked ≥40 PY [25]. PY are calculated as the number of cigarettes smoked per day multiplied by the years of smoking, divided by 20 [26].

Echocardiography

Patients were imaged in the left lateral decubitus position using a commercially available system equipped with a 3.5 MHz transducer. Two-dimensional grayscale, pulsed, continuous and color Doppler data were acquired from the parasternal and apical views. For tissue Doppler imaging, the sector width was adjusted to obtain a frame rate of at least 115 frames/s. Left ventricular ejection fraction (LVEF) was calculated using Simpson’s biplane technique [27].

Statistical analysis

The continuous variables are expressed as mean ± SD or as medians and interquartile ranges. The categorical variables between groups were compared using Chi-square tests. Hazard ratios with 95 % confidence intervals (95 % CIs) were used to estimate the adjusted relative risk for the various groups. Kaplan–Meier survival curves were compared using the log-rank test. Multivariate Cox proportional hazards regression models were applied to adjust for any confounding variables among groups. The analyses were conducted using SPSS (version 16.0, SPSS Inc., Chicago, IL, USA), and all tests were two sided. A p value <0.05 was used to determine statistical significance.

Results

Characteristics of the study population

The cohort consisted of 1118 patients with DCM: 300 (26.8 %) women and 818 (73.2 %) men, with a mean age of 51.2 ± 14.6 years. Among the 1118 patients, those of Han nationality were 1074 (96.1 %), while minor nationality were 44 (3.9 %); patients who lived in the north of the Yazi River were 970 (86.8 %) and those who lived in the south of the Yazi River were 148 (13.2 %). Of these subjects, 53.1 % (n = 593) were non-smokers, 14.2 % (n = 159) were mild-to-moderate smokers and 32.7 % (n = 366) were heavy smokers. In terms of drinking, 66.9 % (n = 747) of the cohort were non-drinkers; 12.7 % (n = 142) were mild drinkers and 20.5 % (n = 229) were moderate drinkers. Table 1 summarizes the baseline clinical characteristics of the cohort. Among the patients in the smoker and non-smoker groups, fewer women were smokers; a history of atrial fibrillation was more common among the heavy smokers; higher blood pressure and circulating creatinine levels and a greater P duration and left ventricle diameter were observed in the mild-to-moderate smokers and heavy smokers; and a larger right ventricle and left atrium diameter were observed in the heavy smokers. Among the patients in the non-drinker, mild-drinker and moderate-drinker categories, the number of women who were drinkers was lower, and a more frequent history of arterial hypertension, higher blood pressure levels and a larger left ventricle and left atrium diameter were observed in the moderate drinkers. There was no significant difference in terms of drug treatment at admission among the smokers or drinkers.
Table 1

Patient characteristics categorized by ventricular conduction blockage patterns

 

All patients (n = 1118)

Non-smokers (n = 593)

Moderate smokers (n = 159)

Heavy smokers (n = 366)

P value

Non-drinkers (n = 747)

Mild drinkers (n = 142)

Moderate drinkers (n = 229)

P value

Age (years)

51.2 ± 14.6

51.0 ± 16.4

49.6 ± 13.9

52.1 ± 11.5

0.184

51.4 ± 15.8

50.4 ± 13.0

50.7 ± 11.2

0.650

Female gender, n (%)

300 (26.8)

280 (47.2)

13 (8.2)

7 (1.9)

<0.001

293 (39.2)

4 (2.8)

3 (1.3)

<0.001

History

 Disease duration (years)

2 (0.5–6)

3 (0.65–7)

2 (0.25–6)

3 (0.5–6)

0.167

2 (0.5–6)

2 (0.325–5)

3 (0.93–7)

0.224

  Arterial hypertension, n (%)

300 (26.8)

142 (23.9)

48 (30.2)

110 (30.1)

0.068

178 (23.8)

41 (28.9)

81 (35.4)

0.002

  Diabetes mellitus, n (%)

161 (14.4)

84 (14.2)

23 (14.5)

54 (14.8)

0.968

108 (14.5)

18 (12.7)

35 (15.3)

0.783

 Stroke, n (%)

51 (4.6)

27 (4.6)

6 (3.8)

18 (4.9)

0.846

38 (5.1)

5 (3.5)

8 (3.5)

0.490

 Atrial fibrillation, n (%)

260 (23.3)

125 (21.1)

32 (20.1)

103 (28.1)

0.025

165 (22.1)

32 (22.5)

63 (27.5)

0.231

 Ventricular premature beat, n (%)

377 (33.7)

199 (33.6)

54 (34.0)

124 (33.9)

0.992

253 (33.9)

51 (35.9)

73 (31.9)

0.718

 Ventricular tachycardia, n (%)

216 (19.3)

120 (20.2)

24 (15.1)

72 (19.7)

0.338

152 (20.3)

26 (18.3)

38 (16.6)

0.429

 NYHA class III and IV, n (%)

821 (73.4)

439 (74.0)

106 (66.7)

276 (75.4)

0.102

558 (74.7)

99 (69.7)

164 (71.6)

0.367

Admission vital signs

 SBP (mm Hg)

113.1 ± 17.8

111.3 ± 17.4

115.0 ± 16.2

115.4 ± 18.7

0.001

112.0 ± 17.7

115.8 ± 17.4

115.1 ± 17.8

0.012

 DBP (mm Hg)

72.5 ± 12.6

71.0 ± 12.3

75.2 ± 12.2

73.6 ± 13.0

<0.001

71.3 ± 12.6

74.2 ± 12.9

75.1 ± 12.2

<0.001

 Heart rate, beats/min

80.8 ± 17.4

81.3 ± 17.8

79.9 ± 16.8

80.8 ± 17.4

0.611

81.1 ± 17.4

79.3 ± 17.4

80.9 ± 16.5

0.546

Laboratory values at admission

 AST (IU/L)

26 (20–35)

25 (19–34.75)

28 (20.75–36)

25 (20–35)

0.969

26 (19–35)

25 (20–34)

27 (21–37)

0.422

 ALT (IU/L)

28 (19–45)

26 (18–43)

33 (22–58.5)

30 (20–45.5)

0.826

27 (19–44)

28 (20–45)

32 (22–47.75)

0.656

 TB (mmol/L)

20.3 (15.1–30.625)

20.5 (15.1–31.5)

19 (15.175–28.525)

20.3 (15.1–29.5)

0.738

20.2 (15–30.775)

19.9 (16.2–29.35)

21 (14.85–30.3)

0.834

 DB (mmol/L)

3.7 (2.5–6.575)

3.6 (2.4–6.9)

3.5 (2.5–5.775)

3.8 (2.6–6.25)

0.653

3.7 (2.4–6.8)

3.6 (2.5–6.2)

3.85 (2.5–6.575)

0.869

 Glucose (mmol/L)

5.61 ± 1.83

5.61 ± 1.90

5.71 ± 2.04

5.58 ± 1.58

0.763

5.61 ± 1.83

5.48 ± 2.04

5.67 ± 1.56

0.614

 TG (mmol/L)

1.56 ± 1.02

1.57 ± 1.06

1.60 ± 0.94

1.53 ± 0.98

0.736

1.54 ± 1.04

1.50 ± 0.81

1.67 ± 1.05

0.237

 CHO (mmol/L)

4.60 ± 1.11

4.56 ± 1.12

4.61 ± 1.14

4.66 ± 1.10

0.458

4.58 ± 1.12

4.62 ± 1.05

4.67 ± 1.20

0.545

 Creatinine (µmol/L)

92.8 ± 35.3

88.2 ± 34.7

98.2 ± 44.4

97.8 ± 30.6

<0.001

91.2 ± 38.2

94.7 ± 25.7

96.9 ± 29.9

0.082

 BUN (µmol/L)

7.98 ± 3.99

7.79 ± 3.71

8.15 ± 5.62

8.20 ± 3.56

0.264

7.96 ± 4.06

7.63 ± 2.63

8.24 ± 4.45

0.366

 Pro-NT BNP (fmol/ml)

1534.85 (790.725–2795.15)

1543.4 (828.85–2827.05)

1475.55 (701.05–2661.425)

1547.2 (790.35–2826.55)

0.353

1583 (825.3–2907.2)

1420 (721.8–2898.3)

1399.6 (737.3–2559.75)

0.149

Electrograph data

 QRS duration (ms)

119.7 ± 30.9

119.9 ± 32.4

119.7 ± 27.9

119.2 ± 29.9

0.941

119.6 ± 30.9

119.1 ± 31.0

120.0 ± 30.8

0.963

 QT (ms)

405.8 ± 54.5

406.7 ± 55.7

406.9 ± 57.5

403.9 ± 51.1

0.727

406.4 ± 54.1

403.0 ± 47.9

404.8 ± 58.7

0.768

 P (ms)

107.5 ± 21.7

105.0 ± 21.1

110.0 ± 20.6

110.7 ± 22.8

0.002

106.3 ± 21.8

108.2 ± 20.3

111.4 ± 21.8

0.036

 PR (ms)

183.0 ± 33.0

183.0 ± 33.4

178.2 ± 32.6

185.2 ± 32.4

0.148

183.0 ± 33.8

182.5 ± 32.8

183.5 ± 30.6

0.965

Echocardiography data

 LVd (mm)

68.1 ± 9.4

67.3 ± 9.15

69.2 ± 9.10

69.1 ± 9.76

0.004

67.6 ± 9.27

69.6 ± 9.80

69.0 ± 9.40

0.020

 LVEF (mm)

31.9 ± 8.4

31.5 ± 8.0

32.1 ± 8.9

32.3 ± 8.7

0.341

31.6 ± 8.2

32.1 ± 8.6

32.7 ± 9.0

0.232

 RV (mm)

23.6 ± 5.4

23.3 ± 5.2

23.0 ± 4.7

24.5 ± 5.8

0.004

23.5 ± 5.4

23.9 ± 4.9

23.8 ± 5.7

0.583

 LA (mm)

44.0 ± 7.7

43.2 ± 7.6

43.9 ± 7.9

45.4 ± 7.6

<0.001

43.6 ± 7.5

44.7 ± 8.6

45.1 ± 7.5

0.020

Medications at admission

 Diuretics, n (%)

1085 (94.6)

562 (94.8)

151 (95.0)

345 (94.3)

0.925

706 (94.5)

130 (91.5)

222 (96.9)

0.079

 ACEI/ARB, n (%)

947 (84.7)

500 (84.3)

137 (86.2)

310 (84.7)

0.848

623 (83.4)

125 (88.0)

199 (86.9)

0.218

 Beta-blockers, n (%)

1015 (90.8)

537 (90.6)

151 (95.0)

327 (89.3)

0.118

677 (90.6)

129 (90.8)

209 (91.3)

0.958

 Digoxin, n (%)

898 (80.3)

486 (82.0)

124 (78.0)

288 (78.7)

0.593

587 (78.6)

118 (83.1)

193 (84.3)

0.111

 Spironolactone, n (%)

1016 (90.9)

544 (91.7)

142 (89.3)

330 (90.2)

0.542

680 (91.0)

125 (88.0)

211 (92.1)

0.396

Data are expressed as mean ± SD, medians (interquartile range) or percentages; P values from independent-sample t tests are shown

Italics indicate P < 0.05

1 patient lacked drinking status data; 22 lacked electrocardiogram data; 43 lacked echocardiography data; 334 lacked NT-pro-BNP levels; 47 lacked fasting blood glucose levels; 29 lacked creatinine data; 40 lacked BUN levels; 83 lacked triglyceride data and total cholesterol levels; 71 lacked AST data; 72 lacked ALT data; 72 lacked TB data; 74 lacked DB data; and 17 lacked data on the medications at admission

NYHA New York Heart Association, SBP systolic blood pressure, DBP diastolic blood pressure, AST aspartate aminotransferase, ALT alanine aminotransferase, BUN blood urea nitrogen, TG triglyceride, TC total cholesterol, BUN blood urea nitrogen, TB total bilirubin, DB direct bilirubin, BUN blood urea nitrogen, NT-pro-BNP N-terminal fragment pro-brain natriuretic peptide, LV left ventricle, LA left atrium, LVEF left ventricular ejection fraction, ACEI angiotensin-converting enzyme inhibitor, ARB angiotensin receptor blocker

Relationship between age, gender and all-cause mortality

Of the 1118 patients studied, 262 (23.4 %) died and 3 (0.26 %) underwent heart transplantation during the mean follow-up of 3.5 ± 2.3 years. The all-cause mortality rates showed no difference between the non-smoker, mild-to-moderate-smoker and heavy-smoker groups (23.8, 20.8 and 24 %, respectively; log-rank χ 2 = 1.281, P = 0.527). There was also no significant difference in mortality between the non-drinker, mild-drinker and moderate-drinker groups (23.7, 23.2 and 22.3 %, respectively; log-rank χ 2 = 2.343, P = 0.310) (Fig. 2).
Fig. 2

Kaplan–Meier survival curves for the smoking- and drinking-related groups of patients with dilated cardiomyopathy. The upper panel shows the survival curves among the non-smoker, mild-to-moderate-smoker and heavy-smoker groups (23.8, 20.8 and 24 %; log-rank χ 2 = 1.281, P = 0.527). The lower panel shows the survival curves among the non-drinker, mild-drinker and moderate-drinker groups (23.7, 23.2 and 22.3 %; log-rank χ 2 = 2.343, P = 0.310)

To determine whether smoking confers different degrees of risk between the different levels of drinkers with DCM, the entire cohort was divided into three subgroups and then further stratified according to the patients’ status as non-smokers, mild-to-moderate smokers and heavy smokers. In the non-drinking patients, the all-cause mortality rates for non-smokers, mild-to-moderate smokers and heavy smokers were 24.3, 22.1 and 22.5 %, respectively; among the mild drinkers, the all-cause mortality rates for non-smokers, mild-to-moderate smokers and heavy smokers were 18.2, 17.9 and 28.6 %, respectively; and in the moderate drinkers, the all-cause mortality rates for non-smokers, mild-to-moderate smokers and heavy smokers were 18.9, 20.6 and 23.4 %, respectively. There was no significant difference in all-cause mortality between the subgroups of patients with different drinking statuses according their different smoking statuses (log-rank χ 2 = 1.286, P = 0.526) (Fig. 3).
Fig. 3

Kaplan–Meier survival curves for patients with DCM who were drinkers, stratified by their status as non-smokers, mild-to-moderate smokers and heavy smokers (log-rank χ 2 = 1.286, P = 0.526)

Cox proportional hazard models

When the clinical, laboratory, electrograph and electrocardiographic data were considered, univariate analysis revealed that age, history of hypertension, ventricular premature beat, New York Heart Association (NYHA) functional class, systolic blood pressure, diastolic blood pressure, P duration, QRS duration, left ventricle diameter, LVEF, right ventricle diameter, left atrium diameter, NT-pro-BNP, serum bilirubin, blood urea nitrogen, creatinine and fasting blood glucose were significant predictors of all-cause mortality in patients with DCM. Neither the smoking (HR 0.971, P = 0.663) nor the drinking status (HR 0.891, P = 0.140) was included in the Cox analysis. After adjustment for age, gender, smoking and drinking status, disease course, right ventricle and left atrium diameter, LVEF and serum creatinine, Cox multivariate analysis showed that ventricular premature beats, systolic blood pressure at admission, QRS duration, left atrium diameter and fasting blood glucose were powerful independent predictors of all-cause mortality in patients with DCM. Neither smoking nor drinking was found to be a predictor of all-cause mortality in the present study (Table 2).
Table 2

Cox regression of all-cause mortality in patients with DCM

Variable

Univariate analysis

Multivariate analysis

HR

95 % CI

P value I

HR

95 % CI

P value

Age

1.010

1.001–1.019

0.024

1.004

0.991–1.016

0.558

Sex

1.121

0.855–1.469

0.408

1.275

0.871–1.867

0.212

Ventricular premature beat

1.462

1.145–1.868

0.002

1.358

1.020–1.807

0.036

NYHA functional class

1.592

1.350–1.877

<0.001

1.223

0.990–1.511

0.062

Disease duration

1.028

1.011–1.044

0.001

1.012

0.990–1.035

0.291

Smoker

0.908

0.712–1.158

0.436

0.911

0.649–1.279

0.591

Drinker

0.817

0.630–1.060

0.129

0.951

0.669–1.352

0.779

Systolic blood pressure

0.982

0.975–0.989

<0.001

0.984

0.975–0.994

0.001

QRS duration

1.009

1.006–1.013

<0.001

1.010

1.005–1.014

<0.001

Left ventricle

1.037

1.025–1.050

<0.001

1.003

0.983–1.022

0.796

Right ventricle

1.061

1.037–1.086

<0.001

1.015

0.986–1.045

0.328

Left atrium

1.055

1.040–1.071

<0.001

1.047

1.025–1.069

<0.001

LVEF

0.963

0.948–0.978

<0.001

0.980

0.961–1.001

0.059

NT-pro-BNP

1.045

1.024–1.067

<0.001

   

FBG

1.097

1.041–1.156

<0.001

1.097

1.026–1.173

0.006

Creatinine

1.004

1.002–1.007

0.001

1.003

1.000–1.006

0.053

The variables analyzed in the multivariate Cox mode included age, gender, ventricular premature beat, drinking and smoke status, disease duration, NYHA functional classes, systolic blood pressure, QRS duration, left ventricular, right ventriclular and left atrium diameter, LVEF, FBG and creatinine

Italics indicate P < 0.05

Discussion

In this large-scale sample cohort study, we investigated the associations between smoking, drinking and all-cause mortality in patients with DCM. Our findings suggested that there was no predictive value of smoking and drinking for all-cause mortality in DCM patients; neither smoking nor drinking was an independent predictor of the all-cause mortality in patients with DCM.

Previous studies have found that that heavy drinkers exhibit a lower ejection fraction, greater end-diastolic volume, increased left atrial dimensions and increased left ventricular wall thickness, which occur in a dose-dependent fashion and precede the onset of clinical symptoms or physical findings [28, 29]. The mechanisms underlying alcohol-induced myocardial damage include cardiac myocyte apoptosis [30], alterations in the excitation–contraction coupling in cardiac myocytes [31], and increased oxidative stress [32] and activation of the renin–angiotensin system and the sympathetic nervous system [33]. However, moderate alcohol consumption has been proposed to confer protection against cardiovascular events while also increasing high-density lipoprotein cholesterol, decreasing platelet aggregation and coagulation, enhancing endothelial function, reducing inflammation, promoting antioxidant effects and decreasing the activity of angiotensin II (Ang II) [3436]. In the present large-sample cohort study, although heavy drinkers were excluded owing to alcoholic cardiomyopathy, no significant differences were found between patients who were non-drinkers, mild drinkers and moderate drinkers. In a study in patients with a previous myocardial infarction, those who consumed small-to-moderate amounts of alcohol exhibited a lower total mortality [10]. However, the present study found no favorable effect of mild-to-moderate drinking on the all-cause mortality in the DCM patients.

Tobacco smoking has been solidly implicated in the etiology of cardiovascular diseases such as coronary artery disease, aortic aneurysm, stroke and peripheral vascular diseases [37], as cigarette smoking has been associated with higher serum levels of cholesterol, coronary vasomotor reactivity, platelet aggregation, and a prothrombotic state [3841]. Additionally, an association between smoking and cardiomyopathy has been suggested by the results of several animal studies [4244]. Possible mechanisms underlying the association between smoking and cardiomyopathy include direct damage to cardiac muscles (following damage to the myocardial mitochondria) and an increase in cardiac susceptibility to viral infections [43, 45]. Although it is well known that smoking increases cardiovascular morbidity and mortality [15, 16], the effect of smoking on the mortality of DCM patients cannot be conclusively determined based on the available data [1922]. In the present study, there was no detectable influence of mild-to-moderate smoking and heavy smoking on the all-cause mortality in DCM patients. Although the all-cause mortality rate was lower among mild-to-moderate smokers than among non-smokers, this association did not achieve statistical significance.

Conclusion

In conclusion, there were no significant differences in mortality between the smoking- and drinking-related patient groups, indicating no effect of smoking and drinking on all-cause mortality in patients with DCM in the present large-scale study.

Limitations

The present study has several limitations. Like all hospital-based cohorts, the examined study population was a selected population of patients who had been referred for treatment. Because the NT-pro-BNP test was not commonly used until the later years of this study and its results were missing in 334 patients, we excluded NT-pro-BNP data from the multivariate Cox analysis to avoid the inclusion of potential confounding variables in the statistical analyses. Additionally, 14.1 % of the patients (n = 158) were lost to follow-up because of factors such as a lack of communication in rural areas; however, the main outcomes were not changed when we detected the losers in the Kaplan–Meier survival and Cox analyses. Ideally, all patients with DCM should be confirmed to be free of coronary artery disease. In practice, however, coronary arteriography is not routinely performed in all patients with congestive heart failure. Because retrospective studies cannot control the conditions under which patients are recruited or investigated, there was a very small subgroup of ischemic heart disease patients in the present study compared with the expected rates based on the numbers of patients who were subjected to coronary artery angiography, coronary CT scans or cardiac radionuclide imaging at other hospitals, as only 334 patients underwent coronary artery angiography and only 80 showed positive results at our hospital.

Notes

Abbreviations

DCM: 

dilated cardiomyopathy

NYHA: 

New York Heart Association

SBP: 

systolic blood pressure

DBP: 

diastolic blood pressure

AST: 

aspartate aminotransferase

ALT: 

alanine aminotransferase

BUN: 

blood urea nitrogen

TG: 

triglyceride

TC: 

total cholesterol

BUN: 

blood urea nitrogen

TB: 

total bilirubin

DB: 

direct bilirubin

BUN: 

blood urea nitrogen

NT-pro-BNP: 

N-terminal fragment pro-brain natriuretic peptide

LV: 

left ventricle

LA: 

left atrium

LVEF: 

left ventricular ejection fraction

ACEI: 

angiotensin-converting enzyme inhibitor

ARB: 

angiotensin receptor blocker

CI: 

confidence interval

Declarations

Authors’ contributions

XL, GL and ML conducted the patients’ enrollment, data collection and follow-up work. YL, RL and PL participated in the data collection and performed the statistical analysis. WH and TH conceived the study and participated in its design and coordination; they also helped to draft the manuscript. All authors read and approved the final manuscript.

Acknowledgements

This study was supported by grants from the National Natural Science Foundation of China (nos. 81000104, 81160141, and 81470521).

Compliance with ethical guidelines

Competing interests The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Cardiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital
(2)
School of Medicine, University of Electronic Science and Technology of China
(3)
State Key Laboratory of Cardiovascular Disease, Cardiac Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College
(4)
Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University
(5)
Key Laboratory of Thermoregulation and Inflammation of Sichuan Higher Education Institutes, Chengdu Medical College
(6)
Cardiovascular Institute and Fuwai Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College
(7)
Hospital of the University of Electronic Science and Technology of China and Sichuan Provincial People’s Hospital

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© Li et al. 2015

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