European Heart Journal Advance Access published online on May 15, 2008
European Heart Journal, doi:10.1093/eurheartj/ehn210
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A smoker's paradox in patients hospitalized for heart failure: findings from OPTIMIZE-HF
1 Department of Medicine, UCLA Medical Center, Los Angeles, CA, USA
2 Division of Cardiology, The Ohio State University, Columbus, OH, USA
3 George M. and Linda H. Kaufman Center for Heart Failure, Cleveland Clinic Foundation, Cleveland, OH, USA
4 Department of Medicine, Duke University Medical Center, Durham, NC, USA
5 Department of Clinical Research, Campbell University School of Pharmacy, Research Triangle Park, NC, USA
6 Division of Cardiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
7 Department of Medicine, USCD Medical Center, University of California, San Diego, CA, USA
8 Division of Cardiology, Duke University Medical Center/Duke Clinical Research Institute, Durham, NC, USA
9 GlaxoSmithKline, Philadelphia, PA, USA
10 Baylor University Medical Center, Dallas, TX, USA
11 Department of Cardiovascular Medicine, Heart Failure Section, Cleveland Clinic Foundation, Cleveland, OH, USA
Received 4 February 2008; revised 17 April 2008; accepted 28 April 2008.
* Corresponding author: Ahmanson-UCLA Cardiomyopathy Center, UCLA Medical Center, 10833 LeConte Avenue, Room 47-123 CHS, Los Angeles, CA 90095-1679, USA. Tel: +1 310 206 9112, Fax: +1 310 206 9111, Email: gfonarow{at}mednet.ucla.edu
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Abstract |
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Aims: Cigarette smoking is a well-established risk factor for cardiovascular disease yet several studies have shown lower mortality after acute coronary syndromes in smokers compared with non-smokers, the so called ‘smoker’s paradox’. This study aimed to ascertain the relationship between smoking and clinical outcomes in patients hospitalized with heart failure (HF).
Methods and results: OPTIMIZE-HF (Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure) collected data on 48 612 patients from 259 hospitals. Characteristics, treatments, and outcomes were compared for current/recent smokers vs. those without current/recent smoking, and multivariable regression analyses with adjustment for hospital clustering were performed. There were 7743 (15.9%) smokers, 39 126 (80.5%) non-smokers, and 1743 (3.6%) missing. Smokers were younger, had similar renal function, but lower ejection fraction. The risk of in-hospital mortality was less in smokers (2.3 vs. 3.9%, P < 0.001). After extensive covariate adjustment, smokers still had lower in-hospital mortality risk OR (odds ratio) 0.70, 95% CI (confidence interval) 0.56–0.88, P = 0.002. Post-discharge, smokers (n = 998) had similar mortality risk (6.7 vs. 8.4%, P = 0.29) compared with those without current/recent smoking.
Conclusion: Smokers hospitalized with HF had lower risk adjusted in-hospital mortality and similar early post-discharge mortality compared with non-smokers. The residual association of smoking and better prognosis, the ‘smoker’s paradox’, was not fully explained by measured covariates.
Key Words: Heart failure • Smoking • Registry • Mortality • Hospitalization
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Introduction |
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Cigarette smoking is associated with significantly increased rates of cardiovascular disease and premature death.1 Smoking is also a strong and independent risk factor for the development of heart failure (HF).2,3 Cigarette smoking was associated with a 45% higher risk of HF in men and an 88% higher risk of HF in women after adjustment for coronary heart disease and other known risk factors of HF.3 In the setting of established chronic HF, current smoking has also been demonstrated to be a powerful independent predictor of morbidity and mortality.4,5
Despite the well-established and modifiable risk associated with smoking, a number of prior studies have suggested that despite the increased prevalence of acute coronary syndromes (ACS) in smokers, the short-term mortality rate after ACS is lower compared with non-smokers.6–10 This relationship has been termed the ‘smoker’s paradox’. While this association has been partly explained by younger age and fewer coexisting high-risk features in patients with ACS who are current smokers, many studies have shown that the residual lower mortality risk persists despite comprehensive covariate adjustment.6–8 A paradoxical relationship with short-term outcomes has also been observed in patients presenting with ischaemic stroke.11 It is unknown whether a similar relationship exists in patients hospitalized with HF. This study utilized data from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to explore the relationship between smoking and clinical outcomes among patients hospitalized with HF.
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Methods |
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OPTIMIZE-HF is a comprehensive hospital-based registry and process-of-care improvement program designed to provide optimal medical care and education to patients hospitalized for HF. The OPTIMIZE-HF program has been previously described in detail and will be briefly summarized.12–15 Patients were qualified for enrolment if they were hospitalized for episodes of new or worsening HF as the primary cause of admission or if significant HF symptoms developed during hospitalization for another primary diagnosis, with HF being the primary discharge diagnosis.12–15 Consecutive patients were enrolled irrespective of their ventricular function, including systolic dysfunction documented by a left ventricular ejection fraction (LVEF) < 40%, HF symptoms in the setting of preserved left ventricular systolic function (diastolic dysfunction HF), or HF without left ventricular function measurement.12–15 Hospital teams used HF case-ascertainment methods similar to those of the Joint Commission.16
From March 1, 2003 to December 31, 2004, 48 612 patients hospitalized at 259 centres in the USA were enrolled in the OPTIMIZE-HF registry. All regions of the USA were represented and institutions from community hospitals to large tertiary medical centres participated.12–15 A pre-specified patient subgroup (10%) was followed for 60–90 days after discharge for the collection of outcomes data. The protocol was approved by each participating centre's institutional review board or through use of a central institutional review board. Written informed consent was obtained prior to enrolment from patients who participated in the follow-up data collection. Sites had the option of participating in the follow-up data collection. There were 91 hospitals which provided 60–90-day follow-up data and 35.4% of patients hospitalized at these sites consented to participate in the outpatient follow-up portion of the study. The follow-up cohort was demographically similar to patients in the overall registry.12–15
The registry captured data on important characteristics (demographic, pathophysiologic, and clinical), treatment patterns, and outcomes of patients hospitalized for HF using the web-based case report form. Data on the presence or absence of current or recent smoking using the same definition as the Joint Commission were collected (a smoker is defined as someone who has smoked cigarettes anytime during the year prior to hospital arrival).16 Data on remote smoking history or pack-years were not collected. Admission staff, medical staff, or both recorded race/ethnicity, usually as the patient was registered. Automated electronic data checks were used to prevent out-of-range entry or duplicate patients. Smoking status was available in 96.4% of patient records. Extensive training was provided to sites before activation and a site visit occurred at least once during participation to help to ensure protocol adherence. Outpatient follow-up data were obtained by patient visit and record review in the period between 60 and 90 days post discharge and were complete in 96.4% of patients. A database audit was performed based on predetermined criteria, of a random sample of 5% of the first 10 000 patients verified against source documents.12,13 The audit showed better than 99% concordance on 53% of fields (118/223) and better than 95% concordance on 91% of fields (205/223). Fields with <95% concordance were not used in this analysis. The registry coordinating centre was Outcome Sciences, Inc. (Cambridge, MA, USA).
Statistical analysis
The primary outcome for this study was risk adjusted in-hospital mortality rate. Hospital length of stay (LOS) and 60–90-day post-discharge mortality, death/rehospitalization, and rehospitalization were also analysed. The data were reported as mean and standard deviation or median (interquartile range) when appropriate, for continuous variables and percentages of non-missing values for categorical variables. Patient characteristics and evidence-based treatments at hospital discharge were compared using Pearson 
2 test for categorical variables and parametric methods (unpaired t-test or one-way ANOVA) for continuous variables. For variables with significant departure from normality non-parametric methods were used (Wilcoxon rank-sum test or Kruskal–Wallis test). Transfer patients were excluded from analyses, which assessed LOS. Multivariable models of in-hospital death, LOS, post-discharge mortality, rehospitalization, and death or rehospitalization were developed as previously described.13–15 The types of models were generalized estimating equation (GEE) with family (binomial), link(logit) and correlation structure (exchangeable)—heretofore called GEE-logistic—for in-hospital mortality, Cox proportional hazards for post-discharge mortality, and GEE-logistic for post-discharge mortality and rehospitalization (date of rehospitalization was not available for survival modelling). Clustering within hospital sites were accounted for in all regression models. Because LOS was treated as count instead of continuous, zero-truncated negative binomial regression was used and estimates reported as incident rates ratios.
The GEE- logistic model for in-hospital mortality included the following variables: age, race, smoking status; prior history of: acute renal failure, cerebrovascular accident, dialysis, Hyperlipidaemia, hypertension, chronic obstructive pulmonary disease, pulmonary hypertension, peripheral vascular disease, and liver disease; admission medications: beta blocker, angiotensin converting enzyme (ACE) inhibitor, loop-diuretic, and statins; admission vital signs: weight, heart rate, systolic blood pressure, and diastolic blood pressure; admission lab: elevated troponin I, sodium, haemoglobin, and creatinine; and left ventricular systolic dysfunction (LVSD) status. The GEE-logistic model for post-discharge rehospitalization and for mortality or rehospitalization included the following variables: LOS; prior history of: chronic obstructive pulmonary disease, and diabetes; procedures: coronary angiography, mechanical ventilation, and cardiac resynchronization therapy placement; discharge medications: ACE inhibitor, angiotensin receptor blocker (ARB), hydralazine, and lipid lowering agent; discharge vital signs: heart rate and systolic blood pressure; admission lab: serum sodium and haemoglobin; discharge lab: serum creatinine; no prior history of HF, LVSD, and ischaemic etiology status. The Cox proportional model (with shared frailty on hospital site) for post-discharge mortality included the following variables: LOS, age, race, smoking status; prior history of: depression, hypertension, and diabetes; procedures: revascularization procedures (PCI or CABG); parenteral therapies: dobutamine; discharge medications: ACE inhibitor, aldosterone antagonist, digoxin, diuretic, and lipid lowering agent; discharge vital signs: weight, heart rate, systolic blood pressure, and diastolic blood pressure; discharge lab: serum sodium and serum creatinine; LVSD and ischaemic etiology status. Adjusted odds ratio (OR)/hazard ratios were presented with their respective 95% confidence intervals (CIs). The predictive ability of the multivariable models was assessed by estimating the receiver operator area under the curve (AUC). The AUC for the in-hospital mortality, post-discharge mortality, post-discharge rehospitalization, and post-discharge mortality/rehospitalization models were 0.768, 0.752, 0.623, and 0.651, respectively. Two-tailed P-value was used. To account for inflation of type I error because of multiple testing, we considered only P-values < 0.01 to be statistically significant. Stata, version 10 was used for all statistical analyses (StataCorp, College Station, TX, USA).
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Clinical characteristics of patients hospitalized for heart failure
OPTIMIZE-HF enrolled a total of 48 612 patients hospitalized for HF at 259 academic and community hospitals of varying size from all the regions of USA. The institutional demographics of participating hospitals have been previously published.12,13 Mean patient age was 73.1 years; 52% of patients were female and 74% were White (Table 1). Co-morbidities were frequent including hypertension in 71%, diabetes in 42%, and chronic obstructive pulmonary disease in 28%. HF etiology was ischaemic in 46% of enrolled patients and the mean LVEF was 39%. Of those patients assessed, 48.8% had documented LVSD and 51.2% had HF with preserved systolic function. The follow-up cohort included 5791 patients, whose characteristics were similar to those of the overall registry.
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There were 7743 (15.9%) smokers, 39 126 (80.5%) non-smokers, and 1743 (3.6%) with smoking status not documented. The characteristics of smokers, non-smokers, and those with smoking status not documented are shown in Table 1. Smokers were substantially younger than those without current or recent smoking, presenting 12.8 years younger. Smokers had less diabetes and history of renal insufficiency but substantially more likely to have chronic obstructive pulmonary disease. LVEF was significantly more impaired in patients with current smoking and a greater proportion presented with HF with LVSD. Admission creatinine was similar between smokers and those without current/recent smoking history but admission BNP (B-type natriuretic peptide) levels were higher in smokers.
In-hospital mortality and hospital length of stay
There were 1834 in-hospital deaths reported out of 48 612 enrolled patients (3.8%). The risk of in-hospital mortality was less in smokers (2.3 vs. 3.9%, OR 0.59, 95% CI 0.50–0.69, P < 0.001). The mortality curves by smoking status separated within 2 days of hospitalization and continued to diverge (Figure 1). After extensive covariate adjustment, smokers still had lower in-hospital mortality risk OR 0.69, 95% CI 0.55–0.85, P = 0.002 (Table 2). In a sensitivity analysis, multivariable models without admission medications yielded similar results of in-hospital mortality (adjusted OR 0.70, 95% CI 0.58–0.85, P < 0.0004). Analysing the subgroup of patients <65 years of age, smoking remained an independent predictor of lower mortality risk (OR 0.71, 95% CI 0.50–0.99, P = 0.043). There was no significant heterogeneity in risk adjusted in-hospital mortality by smoking status of patient subgroups with new onset HF compared with decompensation of prior HF and of those with HF and LVSD compared with those with HF with preserved systolic function.
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The median hospital LOS was 4.0 days (25th, 75th interquartile range: 3.0, 7.0). Hospital LOS differed in smokers and on adjusted analyses; smoking was an independent predictor of shorter hospital LOS (Table 2). The quality of care as indexed by HF discharge performance measures provided to smokers and non-smokers are shown in Figure 2. Smokers were more likely to have measurement of LV function and more likely to be treated with ACE inhibitor/ARB therapy among eligible patients with LVSD. The rate of discharge counselling and treatment with beta-blockers among eligible patients with LVSD were similar between smoker and non-smokers. Smoking cessation counselling prior to hospital discharge was provided to 4464 of 7108 eligible smokers (62.8%).
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60–90-day post-discharge outcomes
During the 60–90-day period after hospital discharge, the follow-up cohort experienced 481 deaths (6.7%), occurring a median of 42 days (25th, 75th interquartile range: 24, 66) after discharge. Rehospitalization within the follow-up period occurred in 1715 patients (29.6%). The combined endpoint of mortality/rehospitalization was met in 1909 (34.9% of patients). The post-discharge mortality rates by proportional hazard analysis did not differ by admission smoking status (Table 3). Current/recent smokers on admission (n = 998) had similar post-discharge mortality risk (6.7 vs. 8.4%, HR 0.87, 95% CI 0.66–1.16, P = 0.35). The re-hospitalization event rates (27.5 vs. 30.3%, OR 0.90, 95% CI 0.77–1.04, P = 0.15) did not differ for current/recent smokers compared with non-smokers. On adjusted analyses, smoking status was not predictive of post-discharge mortality or mortality/rehospitalization (Table 3). Current/recent smoking was associated with lower risk adjusted 60–90-day rehospitalization.
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Discussion |
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This analysis of OPTIMIZE-HF has demonstrated that among a large, broad population of patients admitted to the hospital for HF, smokers present at an earlier age, have lower in-hospital mortality, and shorter hospital LOS compared with those without current or recent smoking history. Even after extensive adjustment for measured covariates, smokers still had lower adjusted in-hospital mortality risk. Further the risk of 60–90 days post-discharge death did not differ by smoking status. These findings provide important new insights into the relationship of smoking to clinical outcomes among patients hospitalized with HF and extend the smoker’s paradox, which has been previously described in patients hospitalized with ACS and acute ischaemic stroke, to patients hospitalized with HF.
Cigarette smoking substantially increases the risk of developing HF in men and women.2,3 Smoking at the age of 50 years among men was associated with a 60% higher risk of new onset HF independent of hypertension, body weight, and other HF risk factors.2 In another study, smoking was associated with a 45% higher risk of HF in men and an 88% higher risk of HF in women after adjustment for established HF risk factors, including the presence of coronary heart disease.3 It has been estimated that cigarette smoking might cause 
17% of the incident HF cases in the US general population.3 In an analysis of the Studies of Left Ventricular Dysfunction (SOLVD) database, current smoking was found to be an independent predictor of morbidity and mortality in patients with reduced left ventricular systolic function with and without symptoms of HF.4 In patients enrolled in the Candesartan in Heart Failure Assessment of Reduction in Mortality and Morbidity (CHARM) trials program, which included chronic HF patients with both reduced and preserved systolic dysfunction, current smoking at the time of study entry was associated with a 34% increase in mortality risk during follow-up, independent of other prognostic variables.5
Cigarette smoking would be expected to have multiple adverse effects in patients with HF. The constituents of inhaled tobacco damage the cardiovascular system contributing to endothelial dysfunction, platelet dysfunction, increased coagulation, increased heart rate, blood pressure, increased myocardial oxygen demand and vasoconstriction.17–21 Cigarette smoking in patients with established HF has been shown to result in a variety of deleterious haemodynamic effects. In a study of patients with New York Heart Association class III HF smoking increased heart rate and systemic blood pressure as well as systemic and pulmonary vascular resistance. Stroke volume was adversely impacted and pulmonary capillary pressure rose with smoking.21 Cigarette smoking increased oxygen demand and decreased myocardial oxygen supply, which has important negative consequences for myocardial oxygen balance.21 Cigarette smoking also has been shown to increase carboxyhaemoglobin, which has a negative inotropic effect and increases left ventricular end-diastolic pressure.19
As cigarette smoking is associated with an increased risk of developing HF, an increased risk of mortality in patients with established chronic HF, and may contribute to the pathophysiology of HF through a multitude of mechanisms, worsened outcomes among hospitalized patients who were current/recent smokers may be expected. Prior studies have suggested that smoking status in patients presenting with acute cardiovascular disease may influence outcomes in unexpected ways, a phenomenon referred to as the smoker’s paradox.6–11 Despite the increased prevalence of ACS in active smokers, prior studies have found that the early mortality risk of smokers after ACS was observed to be lower than non-smokers, including patients treated with fibrinolytic therapy or direct percutaneous coronary intervention.6–10 These observations have been partly explained by fewer coexisting high-risk features in patients with ACS who are current smokers, but many studies have continued to show lower risk despite covariate adjustment.6–8 It has been hypothesized that the underlying infarct lesion in smokers may have a greater thrombotic component with relatively less atherosclerotic plaque burden, thereby contributing to the better prognosis in these patients.6–10 The independent effect of smoking on outcome following acute ischaemic stroke has also been studied. After adjusting for covariates, recent smokers who received thrombolysis were found to have a significantly greater drop in 24 h median stroke severity scores from baseline than non-smokers who received thrombolysis as well as lower mortality risk.11 The relationship between smoking and outcome in patients hospitalized with HF has not previously been well studied.
Differences in clinical outcomes of HF patients by smoking status observed in this study could reflect differences in the characteristics of patients hospitalized. Prior studies have suggested that the severity of ACS may vary according to smoking status but comparable studies for HF have not been performed. Compared with non-smokers, smokers may develop HF and experience decompensation of HF much earlier in the course of their cardiovascular disease, at a time when their prognosis tends to be still more favourable. In this study, smoking patients admitted for HF were younger and did have less diabetes, history of renal insufficiency, and history of atrial arrhythmias. For other prognostic variables, smokers did not appear to be less sick than those admitted without current/recent smoking as judged by the severity of symptoms and multiple prognostic variables. Thus, any detected difference in clinical outcomes potentially reflects intrinsic differences in risk, different care provided during or after hospitalization, or different responses to therapy. Alternately, unmeasured covariates, may fully account for the relationships observed and these findings may merely reflect the intrinsic limitations of observational analyses.
These observations may be explained if the abrupt cessation of smoking during the HF hospitalization improves outcomes among smokers. It can be hypothesized that smoking contributes to decompensation of HF as a result of vasoconstriction, increased ventricular filling pressures, and reduced cardiac index. It is then possible that the abrupt cessation of smoking during the acute HF hospitalization allows for the more rapid stabilization and re-achieving a state of compensation among patients who were smoking up until the time of HF hospitalization. These patients as a result would be at lower risk for early mortality. Non-smoking patients hospitalized with HF do not have this specific precipitating variable withdrawn during hospitalization and thus achieving clinical compensation may be more challenging and accompanied by increased risk, as reflected in longer LOS and higher in-hospital mortality. In the analysis of the SOLVD database, quitting smoking was associated with the accomplishment of a rapid decrease in morbidity and mortality in patients with reduced left ventricular systolic function and symptoms of HF.4 It is also possible that exposure to current/recent smoking has a pre-conditioning-like effect on HF patients allowing better survival during an episode of acute decompensated HF. Differential response to one or more acute HF therapies among current/recent smokers is another potential explanation for these observations.
This apparent smoker’s paradox in HF should not be interpreted as a benefit of or justification for cigarette smoking. The deleterious cardiovascular effects of cigarette smoking are manifested as the appearance of HF necessitating hospitalization in patients >10 years earlier than might otherwise have occurred. Intensive efforts to encourage smoking cessation as a primary and secondary preventive measure for HF should remain a very high priority. Effective smoking prevention and cessation methods should be implemented as vigorously as other guideline recommended therapies for the prevention and treatment of HF.22,23
Limitations
This analysis of OPTIMIZE-HF may be influenced by several limitations. As in prior studies examining the relationship between smoking and outcomes in patients with cardiovascular disease, there may be residual measured and unmeasured confounding variables, which influence the findings. Patients reporting of smoking status may not have been reliable in each case. These analyses were of patients hospitalized with HF and cannot account for patients who may have died before reaching the hospital or not admitted from the Emergency Department. Smoking status was incompletely defined, as we did not collect details regarding remote smoking history, packs per day, or duration of smoking which limit this study. Also we did not collect data on current or recent smoking separately. Follow-up data were obtained in a subset of patients and were limited to 60–90 days. Date of rehospitalization was not collected. Smoking status after discharge was not prospectively collected in this study and discontinuation of smoking after HF hospitalization may modulate short- and intermediate-term risk confounding the post-discharge results. Furthermore, smoking status may have significantly influenced outcomes beyond the 60–90-day follow-up collected in this study. No quantitative measurements were done to evaluate the biologic effects of smoking such as endothelial dysfunction, systemic vasoconstriction, and systemic inflammation. Also, these findings may not apply to hospitals that differ in patient characteristics or care patterns from OPTIMIZE-HF hospitals. Given the overall large number of patients observed, some differences, while statistically significant, may not be clinically relevant. Despite these limitations, this analysis provides new insights into the relationship between smoking status and clinical outcomes from a broad dataset of patients hospitalized with HF from all regions of the country and including patients with preserved systolic function and multiple co-morbidities.
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Conclusions |
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Smokers hospitalized with HF had lower-risk adjusted in-hospital mortality, shorter LOS, and similar early post-discharge mortality compared with non-smokers. The residual association of smoking and better prognosis, the ‘smoker’s paradox’, was not fully explained by measured covariates. However residual confounding cannot be excluded and this study may illustrate limitations of observational analyses. This study demonstrates that smoking contributes to decompensation of HF requiring hospitalization at an earlier age. These findings may also suggest that patients with current or recent smoking exposure have different intrinsic risk and/or response to therapy compared with patients without recent exposure to smoking. Further exploration of the relationship of smoking to outcome in HF is indicated.
Conflict of interest: G.C.F., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. W.T.A., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. N.M.A., PhD, RN, reported that she is a consultant for GlaxoSmithKline. W.G.S., PharmD, reported that she has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. M.G., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. B.H.G., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. C.M.O., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. C.W.Y., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. J.B.Y., MD, reported that he has received research grants, honorarium and has served as a consultant for GlaxoSmithKline. E.N., MD, was an employee of GlaxoSmithKline.
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OPTIMIZE-HF and this study were funded by GlaxoSmithKline, Philadelphia, PA, USA. OPTIMIZE-HF is registered: www.clinicaltrials.gov, study number NCT00344513 [ClinicalTrials.gov] .
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  G. C. Fonarow Smoking cessation in heart failure: easier said than done: reply Eur. Heart J., March 1, 2009; 30(5): 625 - 625. [Full Text] [PDF]
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