Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Health-related quality of life after myocardial infarction is associated with level of left ventricular ejection fraction

BMC Cardiovascular Disorders volume 8, Article number: 28 (2008) Cite this article

Abstract

Background

The objective was to explore the relationship between left ventricular ejection fraction (LVEF) assessed during hospitalization for acute myocardial infarction (MI) and later health-related quality of life (HRQoL).

Methods

We used multivariable linear regression to assess the relationship between LVEF and HRQoL in 256 MI patients who responded to the Kansas City Cardiomyopathy Questionnaire (KCCQ), the EQ-5D Index, and the EuroQol Visual Analogue Scale (EQ-VAS) 2.5 years after the index MI.

Results

167 patients had normal LVEF (>50%), 56 intermediate (40%–50%), and 33 reduced (<40%). The mean (SD) KCCQ clinical summary scores were 85 (18), 75 (22), and 68 (21) (p <0.001) in the three groups, respectively. The corresponding EQ-5D Index scores were 0.83 (0.18), 0.72 (0.27), and 0.76 (0.14) (p = 0.005) and EQ-VAS scores were 72 (18), 65 (21), and 57 (20) (p = 0.001). In multivariable linear regression analysis age ≥ 70 years, known chronic obstructive pulmonary disease (COPD), subsequent MI, intermediate LVEF, and reduced LVEF were independent determinants for reduced KCCQ clinical summary score. Female sex, medication for angina pectoris at discharge, and intermediate LVEF were independent determinants for reduced EQ-5D Index score. Age ≥ 70 years, COPD, and reduced LVEF were associated with reduced EQ-VAS score.

Conclusion

LVEF measured during hospitalization for MI was a determinant for HRQoL 2.5 years later.

Peer Review reports

Background

Left ventricular ejection fraction (LVEF) is the single most used non-invasive measure of cardiac function in clinical practice and is an important prognostic factor for survival after myocardial infarction (MI), in stable coronary artery disease (CAD), and in heart failure [1–3]. Health-related quality of life (HRQoL) has also been identified as a predictor of survival in patients with CAD and heart failure [4–7].

However, the relationship between LVEF and HRQoL has not been settled and whether LVEF can predict HRQoL is still controversial. Some studies have observed an association [8–11] while others have not [12–17]. Most of these studies reported on highly selected heart patients enrolled in clinical trials [9, 13, 14], patients with known reduced LVEF [13, 14], and patients with chronic heart failure [11, 17]. Only two previous studies included unselected MI patients, of which one observed an association between LVEF measured at the time of the MI and later HRQoL [10, 16]. Better understanding of the relationship between cardiac function and quality of life might contribute to tailor treatment that would maintain or improve the patients' daily functioning. Evidently, more research on this subject is needed.

Accordingly, our aim was to assess the relationship between LVEF measured during hospitalization for acute MI and HRQoL 2.5 years later in an unselected MI patient population, using both a generic and a disease-specific HRQoL measure.

Methods

Study design and sample

We established a cohort of hospitalized patients with a discharge diagnosis of acute MI, defined as codes I21 and I22 in ICD-10 (The International Statistical Classification of Diseases and Related Health Problems, tenth revision) [18]. We wanted our cohort to be representative of Norwegian patients with MI, and hence recruited them from teaching and non-teaching hospitals in different regions of Norway. We included a total of 754 consecutive patients who were discharged alive from 15 hospitals during a 3-month period between August 1, 1999, and January 31, 2000. Before discharge, LVEF was measured in 406 (54%) patients. The patient population is described in Figure 1.

Figure 1
figure 1

Flow chart of study population. Study population stratified on patients with and without their left ventricular ejection fraction measured

Full size image

In 2002, we mailed a questionnaire to patients who were still alive according to hospital information systems and the National Population Register of Statistics Norway. The questionnaires were mailed from the hospital of discharge, along with a cover letter signed by the head of the hospital's cardiology unit. After 4 weeks, we sent a reminder to non-respondents.

At the time of the survey, 191 of the 754 patients had died, 8 had an unknown address, and 7 were excluded for miscellaneous reasons. Hence, we mailed the questionnaire to the remaining 548 patients of whom 408 (74%) returned completed questionnaires. A total of 256 of the 408 respondents (63%) had data on LVEF (Figure 1). The mean time from the index MI to questionnaire response was 2.5 (SD = 0.2) years, range 2.1–3.1 years.

Review of medical records

Baseline characteristics were abstracted from the patients' medical records and included previous medical history, presenting features, in-hospital treatment, and medication at discharge. Cardiovascular morbidities from before the index MI were categorized as previous MI, hypertension, angina pectoris, heart failure, peripheral vascular disease, or stroke. The diagnoses were based on either previous ICD-codes or explicit statements in the medical record. The major indications for each cardiovascular drug prescribed at discharge were classified as secondary prevention, hypertension, angina pectoris, heart failure, or other. More details about sampling and collection of data from the patients' medical records are available elsewhere [18].

Measurement of left ventricular ejection fraction

We measured LVEF by one of two methods: Multiple gated-acquisition radionuclide ventriculography (MUGA) in 129 (51%) patients and echocardiography in 127 (49%) patients. MUGA is a reliable reference method, and the widely used echocardiographic method correlates fairly well with radionuclide imaging [19, 20]. LVEF >50% is considered to indicate normal left ventricular function, while LVEF <40% indicates reduced function. According to this classification we categorized LVEF as normal (LVEF >50%), intermediate (40–50%) or reduced (<40%).

Questionnaire

The questionnaire focused on HRQoL, using the EQ-5D Index, the EQ-5D Visual Analogue Scale (EQ-VAS), and the Kansas City Cardiomyopathy Questionnaire (KCCQ). In addition, we asked about subsequent cardiac events and revascularization procedures after hospital discharge for the index MI.

The KCCQ is a self-administered 23-item questionnaire designed for measuring HRQoL in patients with chronic heart failure. It comprises six scales: Symptoms, Symptom stability, Physical limitation, Social limitation, Self-efficacy and Quality of life [21]. Four of the scales, Symptoms, Physical limitation, Social limitations and Quality of life, are aggregated to an overall score, the KCCQ clinical summary score [21]. Each item is scored on a 5 to 7-point Likert scale [22]. Each scale score is calculated as the mean of its item scores and transformed to a 0–100 scale, with higher score indicating higher level of functioning. The KCCQ has been translated into Norwegian, and its psychometric properties have been documented in post MI patients [23]. Change in KCCQ score of 5, 10, and 15 points correspond with small, moderate, and large clinical change respectively [24].

The EQ-5D is a self-administered HRQoL instrument with 5 items: Mobility, Self-care, Usual activities, Pain/discomfort, and Anxiety/depression. Each item is scored on a 3-point Likert scale: no problems (score of 1), moderate problems (2), and extreme problems (3). Responses to these items can be converted to a utility score, the EQ-5D Index, by applying an algorithm derived from time trade-off valuations of health status obtained from the general population [25]. A score of 1.0 represents perfect health and 0 represents dead. For the EQ-5D Index negative utilities are possible, representing states perceived to be worse than dead. We used a UK time trade-off tariff [26]. The EQ-5D Index has been used and documented in post MI patients [27–29]. In addition to the QE-5D Index the EQ-5D questionnaire include the EQ-VAS, a visual analogue scale ranging current overall health by one single number on a scale from 0 (worst imaginable health state) to 100 (best imaginable health state) [28]. The EQ-VAS has documented acceptable reliability and validity in patients with CAD [29–31].

Statistical analysis

We present descriptive statistics with means and SDs, or proportions. For group comparisons, we used the t-test, analysis of variance, Kruskal-Wallis test for three independent groups, Wilcoxon rank-sum test, or chi-square test where appropriate.

We used multiple linear regression analysis to identify determinants for KCCQ clinical summary score, EQ-5D Index, and EQ-VAS at a mean of 2.5 years after MI. To reduce problems with multicollinearity, we checked pairwise Pearson correlations (r) between independent variables. However, none of the pairwise correlations had r > 0.70. Variables with p < 0.25 in bivariable linear regression analysis were included in multivariable modeling. In the multivariable models, we first included age at admission, sex, length of education in years, and LVEF in the models, and then added the other potential independent determinant variables in a forward stepwise fashion. In addition to age, sex, education, and LVEF, we retained all independent variables with p < 0.05 in multivavariable linear regression in the final model. The final models were checked for interactions.

The coefficient of determination (R-square) is a measure of explained variance in regression analysis. To determine the marginal contribution of LVEF to R-square, in KCCQ clinical summary score, EQ-5D Index score, and EQ-VAS, we compared the R-square in the final models adjusted for degrees of freedom, with R-square in the final models without LVEF.

We used a 5% significance level with two-sided tests. Standard statistical software was used for all analyses (SPSS version 12.0, SPSS, Chicago, IL). The Regional Committee for Medical Research Ethics and the Norwegian Data Inspectorate approved the study.

Demographics

Respondents (n = 408) were younger than non-respondents (n = 140), comprised a higher proportion of males, had less cardiovascular morbidity at admission, and fewer cardiovascular indications for medication at discharge. Respondents and non-respondents did not differ in the proportion of patients with ST-segment elevation at admission, Q-wave infarction, or localization of the index MI. Respondents who had their LVEF measured (n = 256) had higher LVEF than non-respondents who had their LVEF measured (n = 71) (normal, intermediate, reduced: 65%, 22%, 13% vs. 51%, 27%, 23%, p = 0.02). A more extensive comparison of respondents and non-respondents has been presented elsewhere [23].

Results

Respondents who had their LVEF measured (n = 256) during hospitalization for the index MI were younger than respondents who had not (n = 152), had less cardiovascular morbidity at admission, and a higher proportion were smokers. Further, a larger proportion of respondents who had their LVEF measured had ST-segment elevation MI, underwent acute revascularisation, and developed Q-wave MI, and a lower proportion had medication for angina pectoris at discharge (Table 1).

Table 1 Possible determinant variables
Full size table

Among respondents who had their LVEF measured, those with reduced LVEF were older and had increased prevalence of heart failure at admission. There was an increased prevalence of previous MI, anterior wall infarction, and use of medication on the indication heart failure with falling LVEF. Further a smaller proportion of respondents with reduced LVEF underwent acute revascularization or had subsequent percutaneous coronary intervention (Table 1).

Health-related quality of life

The mean score for all patients with LVEF measured was 80 for the KCCQ clinical summary scale, 0.80 for the EQ-5D Index, and 69 for the EQ-VAS. HRQoL scores differed between patients with different levels of LVEF both for the KCCQ clinical summary score (p < 0.001) the EQ-5D Index (p = 0.005), and the EQ-VAS (p = 0.001) (Table 2).

Table 2 Health-related quality of life scores
Full size table

In multivariable linear regression analysis, age ≥ 70 years, a history of chronic obstructive pulmonary disease (COPD), subsequent MI, and intermediate or reduced LVEF measured during hospitalization were all independent determinants of lower KCCQ clinical summary score 2.5 years after the index MI (Table 3). Female sex, medication for angina pectoris at discharge, and intermediate LVEF were independent determinants a lower EQ-5D Index score, while a history of peripheral vascular disease was associated with a higher EQ-5D Index score (Table 3). Age 70 ≥ years, a history of COPD, and reduced LVEF were independent determinants of lower EQ-VAS score (Table 3).

Table 3 Multivariable linear regression analyses
Full size table

In the final multivariable models, R-square was 0.16 for both KCCQ clinical summary score and EQ-5D Index, and 0.10 for the EQ-VAS (Table 3). When excluding LVEF in the final models, R-square was 0.09, 0.12, and 0.06 respectively, indicating that LVEF accounted for 25% to 44% of the variation explained by the final multivariable models.

One hospital measured LVEF routinely in all MI patients, using MUGA (n = 101). When applying our final multivariable models in this subset of patients, the relationship between LVEF and HRQoL was essentially the same as in all patients with measured LVEF. In this subset, using KCCQ clinical summary score as the dependent variable, the unstandardized regression coefficient (B) and 95% confidence interval (CI) for patients with intermediate LVEF and reduced LVEF were -10.4 (-21.0 to 0.3) (p = 0.06) and -13.6 (-26.9 to -0.4) (p = 0.04) respectively. With EQ-5D Index as dependent variable B and 95% CI were -0.13 (-0.25 to -0.02) (p = 0.02) and -0.02 (-0.16 to 0.12) (p = 0.7).

Discussion

In this study LVEF measured during hospitalization for the index MI was a determinant of HRQoL 2.5 years later, with poorer HRQoL in patients with reduced LVEF. This relationship persisted after adjusting for comorbidities, sociodemographic variables, and variables related to the index MI. The summary score of the condition-specific KCCQ questionnaire, which has been validated in an earlier study [23], and the EQ-VAS showed a trend of falling scores with falling LVEF, while the EQ-5D Index only captured a difference between patients with normal and intermediate LVEF. A difference in score for the KCCQ clinical summary score between patients with normal LVEF and intermediate or reduced LVEF of 10 and17 points respectively, indicates a moderate to large clinical difference between the groups of patients with different LVEF [24].

The observed falling HRQoL scores with falling LVEF both for KCCQ clinical summary score and EQ-VAS indicate that the level of systolic heart function is a determinant for HRQoL. However, some influence from the mere fact that an MI has occurred cannot be ruled out since also patients with normal LVEF tend to have reduced EQ-5D scores compared to US norms [32]. If so, it is possible that other cardiac pathophysiological mechanisms or psychological mechanisms are involved. An understanding of the way LVEF may influence HRQoL can be provided from a conceptual model outlined by Wilson and Cleary [33]. In their model biological and physiological variables influence symptoms, that is, patients with reduced LVEF may experience symptoms such as fatigue, dyspnoea, and sleep disturbances. These symptoms can in turn affect the patients' functional status, general health, and overall quality of life. The impact on individual patients is further modified by psychological and socioeconomic variables [33]. In our study the level of LVEF immediately after the index MI had a statistically significant impact on later HRQoL and in accordance with the usual interpretation of the KCCQ the clinical importance was moderate to large [24]. However, the observed absolute change in R-square was small indicating that the amount of variation in HRQoL scores explained by LVEF was moderate. A moderate amount of variation in HRQoL score explained by a single clinical variable can be expected if Wilson and Cleary's model is valid, as other interrelated variables intervene between pathophysiology of the heart and quality of life [33].

Three previous studies have observed an association between LVEF and HRQoL in patients with CAD [8–10]. However, two of these studies reported on patients not comparable to those in the present study. One reported on patients admitted to hospital with acute chest pain, thus including patients with acute MI, unstable angina, and chest pain of other reasons [8]. The second study presented results from patients enrolled in a clinical trial of thrombolysis, thus representing a highly selected group of MI patients [9]. In the third study Ecochard et al. showed that LVEF < 46% measured by ventricular angiography within a month after the index MI was associated with reduced function on the Physical mobility dimension of the Nottingham Health Profile (NHP) assessed at one year [10]. However, they did not observe any association between LVEF and the five other dimensions of the NHP (Energy level, Sleep, Pain, Emotional reactions, and Social isolation). By contrast, we found a relationship between LVEF and composite HRQoL scales covering physical, emotional, and social aspects of the HRQoL concept. Furthermore, we observed falling HRQoL scale scores with falling LVEF for the KCCQ clinical summary score and the EQ-VAS. Ecochard et al. did not find a similar fall by use of NHP, neither did we by use of the EQ-5D Index [10]. The dissimilarities might be due to the fact that both NHP and EQ-5D Index are generic instruments and thus supposed to be less sensitive to smaller changes in health status and disease severity than the disease-specific KCCQ [34]. Another reason why reduced LVEF was not independently associated with lower EQ-5D Index score in our study was the reduced statistical power due to low number of respondents with LVEF < 40%.

Studies that did not find an association between LVEF and later HRQoL also varied with regard to inclusion criteria and most of them reported on selective groups of patients and not on unselected acute MI patients as we did [12–16]. One reported on patients 65 years of age or older with CAD [12], two on clinical trials of post MI patients with reduced LVEF [13, 14], and one on patients with their first MI receiving thrombolysis [15]. McBurney et al. did not detect any difference in HRQoL between patients with LVEF < 40% and patients with normal and sub-normal LVEF in a patient sample comparable to ours [16]. However, they used a generic questionnaire, the short form 12 (SF-12) which probably is less sensitive to changes in health status and disease severity [34].

In our study on MI patients, age ≥ 70 years was associated with lower KCCQ clinical summary score. This contrasts with previous results on heart failure patients in which increased age independently correlated with higher KCCQ Quality of life scale score [35]. One possible explanation for this discrepancy is that the KCCQ clinical summery score, which we used as an HRQoL measure in our study, is an overall scale including, in addition to the KCCQ Quality of life scale, scales on symptoms, physical limitations, and social limitations. Another possible explanation is that in our sample of patients with previous MI, increasing age is associated with more advanced CAD and age might act as a surrogate for disease severity [36]. This might not be the case in a sample of patients with heart failure as the underlying cause in younger patients with heart failure more commonly is dilated cardiomyopathy or other cardiomyopathies rather than CAD [35]. We did not observe an association of age with EQ-5D Index scores even though EQ-5D Index US norms report a small decrease in scores with increasing age [32].

We identified sex as an independent determinant of EQ-5D Index score, but not of KCCQ clinical summary score. A difference in score between men and women who are otherwise comparable might be less likely when applying a disease specific instrument than a generic instrument which has a broader perspective. Thus, the EQ-5D Index US norms have reported a small difference between men and women with poorer score in women [32]. Our observations are in agreement with these observations.

Our study showed that the presence of COPD was associated with reduced HRQoL after MI. COPD and CAD share some causal risk factors, and might to some extent present with similar symptoms, for example dyspnoea. Therefore, it is not surprising that patients with COPD who suffer an MI are at increased risk of impaired HRQoL. Similarly, medication for angina pectoris was associated with reduced EQ-5D Index score, and presumably, the reason for this is the fact that such medication reflects enhanced disease severity. In our study the presence of peripheral vascular disease was associated with higher EQ-5D Index score. However, this finding is based on only 11 patients with peripheral vascular disease, and therefore should be interpreted with caution.

Due to the rather long time from the MI to measuring of HRQoL in our study, the association between LVEF and HRQoL could have been distorted. Although the patients reported on intervening major cardiac events, such as new MI or coronary revascularization procedures, other major life events, worsening or improvement of illness not reported in our study, might have had an effect on current HRQoL. We addressed this issue by entering the time between the index MI and HRQoL assessment as a variable in the multivariable analyses. This factor was not, however, independently associated with HRQoL.

In the context of study limitations the representativeness of the sample should be discussed. The eligible patients were representative of survivors of an unselected MI population. Three quarters of the patients responded to the survey, and LVEF was measured in two thirds of the respondents, thus we completed our analysis on approximately half of the eligible patients. This might have skewed the representativeness. However, results from a sub-group analysis of patients in one hospital in which all MI patients had their LVEF measured, were largely in line with the overall results, indicating that the main results pertains to unselected MI patients. Another limitation is the uncertainty of whether the clinicians categorizing the indications for drugs prescribed at discharge did assign the most important indication for each drug, as the protocol instructed. Cardiovascular drugs may have more than one indication for use, and we did not assess the reliability and validity of this classification. However, the classification was undertaken by experienced physicians, most of them cardiologists ensuring the best possible assessment.

Conclusion

LVEF measured during hospitalization for acute MI is an independent determinant for later HRQoL also after taking sociodemographic and clinical variables into account. The magnitude of the difference in HRQoL score between patients with normal, intermediate, and reduced LVEF was of clinical importance. As expected, in accordance with theoretical models, only a moderate amount of the observed variation in HRQoL score was explained by the level of LVEF.

Restoration of myocardial function after an MI is, in addition to being important for live expectancy, also crucial for long-term daily functioning after the event.

Abbreviations

CAD:

coronary artery disease

COPD:

chronic obstructive pulmonary disease

EQ-VAS:

EuroQol Visual Analogue Scale

HRQoL:

health-related quality of life

KCCQ:

Kansas City Cardiomyopathy Questionnaire

LVEF:

left ventricular ejection fraction

MI:

myocardial infarction

MUGA:

multiple gated-acquisition radionuclide ventriculography

NHP:

Nottingham Health Profile.

References

  1. Volpi A, De Vita C, Franzosi MG, Geraci E, Maggioni AP, Mauri F, Negri E, Santoro E, Tavazzi L, Tognoni G: Determinants of 6-month mortality in survivors of myocardial infarction after thrombolysis. Results of the GISSI-2 data base. The Ad hoc Working Group of the Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico (GISSI)-2 Data Base. Circulation. 1993, 88: 416-429.

    Article  CAS  PubMed  Google Scholar 

  2. Clayton TC, Lubsen J, Pocock SJ, Vokó Z, Kirwan BA, Fox KA, Poole-Wilson PA: Risk score for predicting death, myocardial infarction, and stroke in patients with stable angina, based on a large randomised trial cohort of patients. BMJ. 2005, 331: 869-10.1136/bmj.38603.656076.63.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Eichhorn EJ: Prognosis determination in heart failure. Am J Med. 2001, 110 (Suppl 7A): 14S-36S. 10.1016/S0002-9343(98)00384-2.

    Article  PubMed  Google Scholar 

  4. Rumsfeld JS, MaWhinney S, McCarthy MJ, Shroyer AL, VillaNueva CB, O'Brien M, Moritz TE, Henderson WG, Grover FL, Sethi GK, Hammermeister KE: Health-related quality of life as a predictor of mortality following coronary artery bypass graft surgery. JAMA. 1999, 281: 1298-1303. 10.1001/jama.281.14.1298.

    Article  CAS  PubMed  Google Scholar 

  5. Spertus JA, Jones P, McDonell M, Fan V, Fihn SD: Health status predicts long-term outcome in outpatients with coronary disease. Circulation. 2002, 106: 43-49. 10.1161/01.CIR.0000020688.24874.90.

    Article  PubMed  Google Scholar 

  6. Soto GE, Jones P, Weintraub WS, Krumholz HM, Spertus JA: Prognostic value of health status in patients with heart failure after acute myocardial infarction. Circulation. 2004, 110: 546-551. 10.1161/01.CIR.0000136991.85540.A9.

    Article  PubMed  Google Scholar 

  7. Westin L, Nilstun T, Carlsson R, Erhardt L: Patients with ischemic heart disease: quality of life predicts long-term mortality. Scand Cardiovasc J. 2005, 39: 50-54. 10.1080/14017430410003903.

    Article  CAS  PubMed  Google Scholar 

  8. Fleischmann KE, Lee RT, Come PC, Goldman L, Kuntz KM, Johnson PA, Weissman MA, Lee TH: Clinical and echocardiographic correlates of health status in patients with acute chest pain. J Gen Intern Med. 1997, 12: 751-756. 10.1046/j.1525-1497.1997.07160.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Coyne KS, Lundergan CF, Boyle D, Greenhouse SW, Draoui YC, Walker P, Ross AM: Relationship of infarct artery patency and left ventricular ejection fraction to health-related quality of life after myocardial infarction: the GUSTO-I Angiographic Study experience. Circulation. 2000, 102: 1245-1251.

    Article  CAS  PubMed  Google Scholar 

  10. Ecochard R, Colin C, Rabilloud M, de Gevigney G, Cao D, Ducreux C, Delahaye F: Indicators of myocardial dysfunction and quality of life, one year after acute infarction. Eur J Heart Fail. 2001, 3: 561-568. 10.1016/S1388-9842(01)00171-4.

    Article  CAS  PubMed  Google Scholar 

  11. Juenger J, Schellberg D, Kraemer S, Haunstetter A, Zugck C, Herzog W, Haass M: Health related quality of life in patients with congestive heart failure: comparison with other chronic diseases and relation to functional variables. Heart. 2002, 87: 235-241. 10.1136/heart.87.3.235.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ades PA, Savage PD, Tischler MD, Poehlman ET, Dee J, Niggel J: Determinants of disability in older coronary patients. American Heart Journal. 2002, 143: 151-156. 10.1067/mhj.2002.119379.

    Article  PubMed  Google Scholar 

  13. Gorkin L, Norvell NK, Rosen RC, Charles E, Shumaker SA, McIntyre KM, Capone RJ, Kostis J, Niaura R, Woods P: Assessment of quality of life as observed from the baseline data of the Studies of Left Ventricular Dysfunction (SOLVD) trial quality-of-life substudy. Am J Cardiol. 1993, 71: 1069-1073. 10.1016/0002-9149(93)90575-W.

    Article  CAS  PubMed  Google Scholar 

  14. Gorkin L, Follick MJ, Geltman E, Hamm P, Sollano J, Sylvia S, Jacobson K, Jacobson MJ, Cochrane BS, Sussex B, Klein M, Gaudette G, Goldman S, Carrol D, Holcombe R, Abern DK: Quality-Of-Life Among Patients Postmyocardial Infarction at Base-Line in the Survival and Ventricular Enlargement (Save) Trial. Quality of Life Research. 1994, 3: 111-119. 10.1007/BF00435254.

    Article  CAS  PubMed  Google Scholar 

  15. Crilley JG, Farrer M: Impact of first myocardial infarction on self-perceived health status. Qjm-Monthly Journal of the Association of Physicians. 2001, 94: 13-18.

    Article  CAS  PubMed  Google Scholar 

  16. McBurney CR, Eagle KA, Kline-Rogers EM, Cooper JV, Mani OC, Smith DE, Erickson SR: Health-related quality of life in patients 7 months after a myocardial infarction: Factors affecting the Short Form-12. Pharmacotherapy. 2002, 22: 1616-1622. 10.1592/phco.22.17.1616.34121.

    Article  PubMed  Google Scholar 

  17. Clark DO, Tu W, Weiner M, Murray MD: Correlates of health-related quality of life among lower-income, urban adults with congestive heart failure. Heart Lung. 2003, 32: 391-401. 10.1016/j.hrtlng.2003.07.005.

    Article  PubMed  Google Scholar 

  18. Reikvam A, Kvan E, Aursnes I: Use of cardiovascular drugs after acute myocardial infarction: a marked shift towards evidence-based drug therapy. Cardiovasc Drugs Ther. 2002, 16: 451-456. 10.1023/A:1022194604260.

    Article  CAS  PubMed  Google Scholar 

  19. Jensen-Urstad K, Bouvier F, Höjer J, Ruiz H, Hulting J, Samad B, Thorstrand C, Jensen-Urstad M: Comparison of different echocardiographic methods with radionuclide imaging for measuring left ventricular ejection fraction during acute myocardial infarction treated by thrombolytic therapy. Am J Cardiol. 1998, 81: 538-544. 10.1016/S0002-9149(97)00964-8.

    Article  CAS  PubMed  Google Scholar 

  20. van 't Hof AW, Schipper CW, Gerritsen JG, Reiffers S, Hoorntje JC: Comparison of radionuclide angiography with three echocardiographic parameters of left ventricular function in patients after myocardial infarction. Int J Card Imaging. 1998, 14: 413-418. 10.1023/A:1006082214191.

    Article  PubMed  Google Scholar 

  21. Green CP, Porter CB, Bresnahan DR, Spertus JA: Development and evaluation of the Kansas City Cardiomyopathy Questionnaire: a new health status measure for heart failure. J Am Coll Cardiol. 2000, 35: 1245-1255. 10.1016/S0735-1097(00)00531-3.

    Article  CAS  PubMed  Google Scholar 

  22. Streiner DL, Norman GR: Health measurements scales – a practial guide to their development and use. 1995, Oxford: Oxford University Press, 2

    Google Scholar 

  23. Pettersen KI, Reikvam A, Rollag A, Stavem K: Reliability and validity of the Kansas City cardiomyopathy questionnaire in patients with previous myocardial infarction. Eur J Heart Fail. 2005, 7: 235-242. 10.1016/j.ejheart.2004.05.012.

    Article  PubMed  Google Scholar 

  24. Spertus J, Peterson E, Conard MW, Heidenreich PA, Krumholz HM, Jones P, McCullough PA, Pina I, Tooley J, Weintraub WS, Rumsfeld JS: Monitoring clinical changes in patients with heart failure: a comparison of methods. Am Heart J. 2005, 150: 707-715. 10.1016/j.ahj.2004.12.010.

    Article  PubMed  Google Scholar 

  25. Dolan P, Gudex C, Kind P, Williams A: The time trade-off method: results from a general population study. Health Econ. 1996, 5: 141-154. 10.1002/(SICI)1099-1050(199603)5:2<141::AID-HEC189>3.0.CO;2-N.

    Article  CAS  PubMed  Google Scholar 

  26. Dolan P: Modeling valuations for EuroQol health states. Med Care. 1997, 35: 1095-1108. 10.1097/00005650-199711000-00002.

    Article  CAS  PubMed  Google Scholar 

  27. The EuroQol Group: EuroQol – a new facility for the measurement of health-related quality of life. Health Policy. 1990, 16: 199-208. 10.1016/0168-8510(90)90421-9.

    Article  Google Scholar 

  28. Brooks R: EuroQol: the current state of play. Health Policy. 1996, 37: 53-72. 10.1016/0168-8510(96)00822-6.

    Article  CAS  PubMed  Google Scholar 

  29. Nowels D, McGloin J, Westfall JM, Holcomb S: Validation of the EQ-5D quality of life instrument in patients after myocardial infarction. Qual Life Res. 2005, 14: 95-105. 10.1007/s11136-004-0614-4.

    Article  PubMed  Google Scholar 

  30. Schweikert B, Hahmann H, Leidl R: Validation of the EuroQol questionnaire in cardiac rehabilitation. Heart. 2006, 92: 62-67. 10.1136/hrt.2004.052787.

    Article  CAS  PubMed  Google Scholar 

  31. Ellis JJ, Eagle KA, Kline-Rogers EM, Erickson SR: Validation of the EQ-5D in patients with a history of acute coronary syndrome. Curr Med Res Opin. 2005, 21: 1209-1216. 10.1185/030079905X56349.

    Article  PubMed  Google Scholar 

  32. Fryback DG, Dunham NC, Palta M, Hanmer J, Buechner J, Cherepanov D, Herrington SA, Hays RD, Kaplan RM, Ganiats TG, Feeny D, Kind P: US norms for six generic health-related quality-of-life indexes from the National Health Measurement study. Med Care. 2007, 45: 1162-1170.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wilson IB, Cleary PD: Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA. 1995, 273: 59-65. 10.1001/jama.273.1.59.

    Article  CAS  PubMed  Google Scholar 

  34. Eurich DT, Johnson JA, Reid KJ, Spertus JA: Assessing responsiveness of generic and specific health related quality of life measures in heart failure. Health Qual Life Outcomes. 2006, 4: 89-10.1186/1477-7525-4-89.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Masoudi FA, Rumsfeld JS, Havranek EP, House JA, Peterson ED, Krumholz HM, Spertus JA: Age, functional capacity, and health-related quality of life in patients with heart failure. J Card Fail. 2004, 10: 368-373. 10.1016/j.cardfail.2004.01.009.

    Article  PubMed  Google Scholar 

  36. Manolio TA, Furberg CD: Age as a predictor of outcome: what role does it play?. Am J Med. 1992, 92: 1-6. 10.1016/0002-9343(92)90007-X.

    Article  CAS  PubMed  Google Scholar 

Pre-publication history

Download references

Acknowledgements

We thank the following physicians for participating in the study: E. Anker, T. Dahl, H.P. Dørum, T. Grønvold, J. Hærem, T. Indrebø, K. Knutsen, K.T. Lappegård, A. Mangschau, C. Platou, J. Vegsundvåg, A. von der Lippe, K. Waage, and A. Zalmai.

Author information

Authors and Affiliations

  1. Norwegian Knowledge Centre for the Health Services, Oslo, Norway

    Kjell I Pettersen & Knut Stavem

  2. Medical Division, Akershus University Hospital, Lørenskog, Norway

    Kjell I Pettersen, Arnfinn Rollag & Knut Stavem

  3. Department of Pharmacotherapeutics, Faculty Division Rikshospitalet, Faculty of Medicine, University of Oslo, Oslo, Norway

    Kjell I Pettersen, Elena Kvan & Aasmund Reikvam

  4. Helse Øst Health Services Research Centre, Lørenskog, Norway

    Knut Stavem

  5. Faculty Division Akershus University Hospital, Faculty of Medicine, University of Oslo, Lørenskog, Norway

    Knut Stavem

Authors
  1. Kjell I Pettersen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elena Kvan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arnfinn Rollag
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Knut Stavem
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aasmund Reikvam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kjell I Pettersen.

Additional information

Competing interests

The authors declare that they have no competing interests. The work was performed at the Norwegian Knowledge Centre for the Health Services and at the Department of Pharmacotherapeutics, University of Oslo, Oslo, Norway. The project had no external funding or grants.

Authors' contributions

KIP: Had the idea to the study, organized the data collection and data preparation, performed statistical analysis, drafted the first version of the manuscript, revised the manuscript and approved the final version. EK: Participated in data collection and data preparation, participated in discussion of study findings, revision of the manuscript and approved the final version. AR: Participated in discussion of study findings, revision of the manuscript and approved the final version.

KS: Participated in study design, statistical analysis, manuscript preparation and revision, and approved the final version. AR: Participated in data collection, discussion of study findings, manuscript preparation and revision, and approved the final version.

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Pettersen, K.I., Kvan, E., Rollag, A. et al. Health-related quality of life after myocardial infarction is associated with level of left ventricular ejection fraction. BMC Cardiovasc Disord 8, 28 (2008). https://doi.org/10.1186/1471-2261-8-28

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1471-2261-8-28

Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us