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Q J Med 2001; 94: 13-18
© 2001 Association of Physicians

Impact of first myocardial infarction on self-perceived health status

J.G. Crilley and M. Farrer

From the Department of Cardiology, Sunderland Royal Hospitals, Sunderland, UK

Received 7 April 2000 and in revised form 30 October 2000


    Summary
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
Despite recent advances in the acute management of myocardial infarction (MI), few studies have evaluated self-perceived quality of life in the longer term after MI. We mailed a questionnaire incorporating the short form 12 (SF-12) and seeking information on symptoms, drug therapy, recent investigations and employment status, to 149 patients who had a first MI 2 years previously. The response rate was 82%. Mean physical and mental summary scores were significantly lower in patients than ‘normative’ controls (physical summary score: 37.0±11.5 vs. 50.9±9.4; p<0.001 and mental summary score: 46.2±12.8 vs. 52.1±8.7; p<0.001, respectively). Physical and mental summary scores were closely associated with continuing chest pain at 2 years, level of limitation on daily activities and employment status. We found the SF-12 to be a useful tool for monitoring health status and believe it could be used to evaluate the impact of interventions on quality of life after acute MI. Self-perceived health status 2 years after a first MI remains poor despite advances in management.


    Introduction
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
Although the mortality associated with myocardial infarction (MI) has much improved in recent years due to the impact of thrombolysis and secondary pharmacological prevention measures, few studies have addressed the impact of MI on quality of life, and results have been mixed.1–4 We therefore studied self-perceived health status after 2 years in a cohort of patients having their first MI, all of whom received thrombolysis, from an area of the UK with a high coronary heart disease burden. We used the short form 12 (SF-12) questionnaire, an abbreviated version of the short form 36 (SF-36), to evaluate our patients.

The SF-36 is a 36-item general health questionnaire which measures self-perceived health status. It is thought to be better than existing questionnaires, for example the Nottingham Health Profile, at detecting low levels of social and physical functioning.5 It has been validated in the US and several European countries, and shows conformity of results across all societies in which it has been tested.6 The SF-36 seeks information in eight domains which can then be aggregated to give summary physical and mental health scores. In order to facilitate more widespread use of the questionnaire, the authors designed a shorter version, the SF-12, which comprises 12 items representing the eight domains of the larger questionnaire. Similarly, the answers to the 12 items with appropriate weighting factors are summed to give physical (PS) and mental (MS) summary scores. In validation studies, the PS and MS scores derived from the SF-12 were in good agreement with scores obtained using the SF-36.6,7


    Methods
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
Patients
We recruited 165 patients with a first MI from the coronary care unit at Sunderland Royal Hospital from October 1996 to October 1997. Patients underwent a number of assessments including echocardiography, brain natriuretic peptide assay and an annual health status assessment. Only the health status data at 2 years is presented here. Inclusion criteria for the study were first MI, survival to 3 days and receivership of thrombolysis (93% streptokinase; 7% tissue plasminogen activator). Patients were excluded if death, reinfarction or post-infarction angina occurred within 3 days (n=32), unable or refused consent (n=14), poor echocardiography window (n=5) or premature discharge (n=26). MI was diagnosed if patients satisfied two of the following three criteria: chest pain lasting longer than 30 min; >1 mm ST elevation in two limb leads or >2 mm ST elevation in two chest leads; or a rise in creatine kinase of twice the upper limit of normal. Sixteen patients (10%) died in the first 2 years.

Questionnaire
A questionnaire incorporating the SF-12 and items seeking information on symptoms, employment status, cardiac investigations and current drug therapy was mailed to patients 2 years after their initial infarct date (with a pre-paid reply envelope) and a reminder after 2–3 weeks if no reply was received.

Score calculation
Summary scores from the responses to each component of the SF-12 were calculated using the weightings in the manual from the Medical Outcomes Trust.8 These weightings allow the PS and MS summary score to be derived from the same responses to each of the 12 questions. The results are standardized to a mean score of 50, the general population norm.9 We compared our results with control PS and MS scores for the SF-12.5 We also compared our results with earlier data based on the SF-36 (from a cohort of patients 4 years after MI).4 As only the scores for the individual domains were available for this data set, we calculated the PS and MS scores from the mean scores for each of the eight domains using the formulae given in the SF-36 user's manual.9

Statistical analysis
Results are presented as means±SD with a significance level of 0.05 being accepted. Statistical analysis was facilitated by the use of the SPSS (v. 8)10 and S-Plus11 software packages. The {chi}2 or an unpaired t-test was used to compare baseline variables between responders and non-responders. A one-sample t-test was used to compare mean scores from our patients with the scores for ‘normative’ data (for which there was only a mean result available). Non-parametric statistical methods were used to explore relationships between scores and variables. The Mann-Whitney U-test or Kruskal-Wallis test was used to compare scores between groups of patients with different baseline characteristics or employment status. The Spearman rank test was used to explore correlations of summary scores with severity, frequency and impact of chest pain symptoms. We used multiple regression with a stepwise procedure for variable selection to model PS score and MS score as a function of the co-variables of sex, age, smoking status, diabetes, hypertension, cholesterol >=6.5 mmol/l, chest pain presence at 2 years and employment status. Graphical representations of the regression models were obtained using regression trees.12


    Results
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
The response rate for the whole questionnaire was 82%, with 82% of these having completed all the items on the SF-12, thus enabling the summary scores to be calculated. The baseline characteristics of responders and non-responders are summarized in Table 1Go. Non-responders were more likely than responders to have been smokers at the time of the infarct (p<0.001). They were also more likely than responders to be on ß-blocker therapy (p<0.05) and less likely to be on lipid-lowering therapy (p<0.01). There were no other significant differences in the characteristics of responders and non-responders. There were no significant differences in any of the baseline characteristics between those who fully completed the SF-12 (n=101) and those who did not (n=22).


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Table 1. Characteristics of responders and non-responders

 
Physical (PS) and mental (MS) summary scores
The mean PS and MS scores for all the patients were significantly lower than for ‘normative’ controls (37.0±11.5 vs. 50.9±9.4, p<0.001; and 46.2±12.8 vs. 52.1±8.7, p<0.001, respectively). After dividing the score data set into patients under and over 65 years, the mean PS scores for the Sunderland patients were significantly lower (36.7±11.3 vs. 49.1±10.6; p<0.001 (under 65 years) and 37.5±12.0 vs. 45.3±11.2; p<0.001 (over 65 years)) than scores for ‘normative’ controls in both age groups (Figure 1Go). The mean MS score was also lower in patients than ‘normative’ controls (44.9±12.9 vs. 51.4±9.8; p<0.001 (under 65 years) and 48.3±12.6 vs. 53.2±9.1; p<0.02 (over 65 years)) in both age groups (Figure 1Go).



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Figure 1. Mean PS and MS scores for ‘normative’ controls (UK norms) and MI patients from Sunderland (Sund). MI, myocardial infarction; filled symbols, PS score; open symbols, MS score; *p<0.001; **p<0.02.

 

Scores and baseline characteristics
PS scores were similar in patients both with and without conventional risk factors for MI (Table 2aGo). MS scores were significantly lower in patients who were smokers at the time of their infarct (Table 2aGo; p=0.004).


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Table 2a. PS and MS scores for patient groups

 

Scores and chest pain symptoms
Forty-nine percent of respondents reported persistent chest pain symptoms at 2 years. These patients had significantly lower PS and MS scores (Table 2aGo) than patients who reported an absence of chest pain. However, in the patients who reported freedom from chest pain, the mean PS score but not the MS score, remained significantly lower than controls (42.6±11.6 vs. 50.9±9.4; p<0.001). For the patients who reported continuing chest pain, lower PS and MS scores correlated with more frequent symptoms of chest pain (r=-0.49; p<0.01 and r=-0.24; p<0.05, respectively; Figure 2aGo), level of activity precipitating pain (r=-0.29; p<0.05 and r=-0.37; p<0.01, respectively; Figure 2bGo) and greater impact on social and physical functioning (r=-0.65; p<0.01 and r=-0.28; p<0.05, respectively; Figure 2cGo).



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Figure 2. Filled symbols, PS score; open symbols, MS score. a Mean PS and MS scores vs. frequency of chest pain symptoms. b Mean PS and MS scores vs. activities precipitating chest pain symptoms. c Mean PS and MS scores vs. limitation imposed by chest pain symptoms.

 

Scores and employment status
PS and MS scores were significantly lower in patients who were unemployed at the time of their MI in comparison with those who were employed or age-retired (Table 2bGo). PS scores were of a similar level in those who did not return to work after the MI compared to those who had been unemployed at the time of their MI (31.8±10.1 vs. 31.8±7.9). Patients who initially returned to work but subsequently became unemployed had similar PS scores to those who had remained employed following their MI (43.8±13.1 vs. 46.4±10.3). MS scores showed a similar pattern (Table 2bGo).


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Table 2b. PS and MS scores by employment group

 

Multiple regression models
These showed that for PS score the two significant coefficients were those of chest pain at 2 years (-3.9) and employment status (2.1). For MS score, the only significant coefficient was for employment status (-2.1). The regression trees (Figure 3Go) illustrate that persistent chest pain at 2 years is by far the determining factor of PS score and employment status the greatest influence on MS score.



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Figure 3. Regression trees showing the influence of the different co-variables on PS score (upper) and MS score (lower). The small perpendicular lines in each diagram represent the extent of weighting towards the side of the indicated variable.

 


    Discussion
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
Despite advances in the management of MI, patients having their first MI have significantly lower levels of self-perceived health status after 2 years than control subjects of a similar age. This reduced level of self-perceived health status is associated with persistent cardiac symptoms and lack of employment.

PS scores were significantly lower (Figure 1Go) than scores for ‘normative’ controls in patients aged both under and over 65 years, although the magnitude of the difference was less in the older patients. MS scores were also significantly lower than ‘normative’ control scores in both age groups. Although our results were similar to those obtained using the SF-36,4 we found that our PS scores remained lower than published SF-12 PS scores for ‘normative’ controls in both older and younger patients. This is in contrast to the findings of Brown et al.4 who found that their older patients had similar SF-36 PS scores to a group of ‘normative’ controls. This may relate to the age distribution of the control group in each study. Since 90% of our responders were <=75 years, we used the control scores given for healthy subjects in the 65–74 age band6 to compare with our older patients. However PS score is closely related to age in older subjects and there is a marked fall-off of the PS score in healthy subjects over 75 years. If the control group of Brown et al.4 contained a greater proportion of elderly subjects than the patient group, this might explain the difference in our findings.

The most striking finding of our survey was the association between scores and employment status. In our patient group, <50% of eligible patients were employed at the time of their MI, and <50% of these were still in work after 2 years. Failure to be in work or to return to work after a major illness can be either a cause or a consequence of reduced health status. Although unemployed status at the time of the MI was most strongly associated with MS score, persistent chest pain at 2 years was the major influence on PS score. This is illustrated further in the regression tree diagrams (Figure 3Go). For PS score, employment status, followed by age under 62 years, further influenced the score, while being a smoker at the time of the MI, followed by age under 56 years, further influenced MS score. Although we did not seek detailed information on the reasons for failing to return to work, most patients gave ‘their health’ as the cause. Although many patients who initially returned but did not persist in work had continuing chest pain at 2 years, over half the patients lost their jobs at the time of the event, and therefore persistent chest pain symptoms could not have influenced this. The association of such low scores with persistent unemployed status highlights the effect of long-term employment on patients' self-worth.

The good correlation between PS and MS scores and chest pain frequency, severity and impact on lifestyle suggests that the SF-12 is able to detect reduced levels of physical and social functioning. The strongest influence on both PS and MS score was governed by the impact of chest pain symptoms on daily lifestyle. This is not surprising given that it is the patient's own perception of the limitation placed on them by their symptoms that is most likely to influence quality of life.

There are few previous studies assessing self-perceived health status in the medium and long term after MI, and only one assessed patients who were not part a major clinical treatment trial.4 However, such assessments may mirror important decreases in patients' perceptions of health status after MI. Particularly in areas of higher unemployment, a reduced expectation of one's health status will have important implications for hope of returning to work.

Since the persistence of chest pain symptoms and employment status were the principal determinants of quality of life in this patient group, it would seem that these two questions alone might identify patients who could be recalled for further evaluation. In particular, targetting further investigation of chest pain in a pro-active manner and providing advice on alternative employment opportunities could help such patients return to the workforce and result in an improved self-perceived health status. However, such strategies would optimally need to be initiated at an earlier time-point than 2 years to prevent long-term unemployment.

To summarize, the SF-12 may prove to be a useful tool in the assessment of self-perceived health status in patients after MI, and gives comparable results to the SF-36 while being easier and quicker for the patient to complete. The results highlight the impact of a first MI on patients self-perceived health status even 2 years after the event.


    Acknowledgments
 
We gratefully acknowledge the help of Sister Carole Nelson and staff of the Coronary Care Unit for recruiting the patients, and Helen Murray, clinical audit clerk, for sending and collecting the questionnaires, both of Sunderland Royal Hospital, Sunderland, Tyne and Wear, UK. We also thank Dr Mario Cortina Borja, Department of Statistics, University of Oxford, UK, for statistical advice.


    Notes
 
Address correspondence to Dr J.G. Crilley, MRC-MRS Unit, John Radcliffe Hospital, Oxford OX3 9DU. e-mail: jcrilley{at}bioch.ox.ac.uk Back


    References
 Top
 Summary
 Introduction
 Methods
 Results
 Discussion
 References
 
1. Glasziou PP, Bromwich S, Simes RJ. Quality of life 6 months after myocardial infarction treated with thrombolytic therapy. AUS_TASK group. Australian arm of international tPA/SK mortality trial. Med J Aust1994; 161:532–6.[Web of Science][Medline]

2. Wiklund I, Herlitz J, Hjalmarson A. Quality of life five years after myocardial infarction. Eur Heart J1989; 10:464–72.[Abstract/Free Full Text]

3. Westin L, Carlston R, Israelsson B, Willenheimer R, Cline C, McNeil TF. Quality of life in patients with ischaemic heart disease: a prospective controlled study. J Intern Med1997; 242:239–47.[Web of Science][Medline]

4. Brown N, Melville M, Gray D, Young T, Munro J, Skene AM, Hampton JR. Quality of life four years after acute myocardial infarction: short form 36 scores compared with a normal population. Heart1999; 81:352–8.[Abstract/Free Full Text]

5. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M. Cross-validation of item selection and scoring for the SF-12 health survey for nine countries: results from the IQOLA project. J Clin Epidemiol1998; 51:1171–8.[Web of Science][Medline]

6. Brazier JE, Harper R, Jones NMB, O'Caithain A, Thomas KJ, Usherwood T, Westlake L. Validating the SF-36 health survey questionnaire: new outcome measure for primary care. Br Med J1992; 305:160–4.

7. Melville M, Brown N, Young T, Gray D. Quality of life 4 years after myocardial infarction: are the physical and mental summary scales of the SF-12 as reliable and sensitive at measuring quality of life as those of the SF-36? Eur Heart J1999; 20 (Abstr suppl.):1041.

8. Ware JE, Kosinski M, Keller SD. SF-12: How to score the SF-12 physical and mental summary scales. Lincoln RI, Quality Metric; and Boston MA, The Health Assessment Lab, 1998.

9. Ware JE. SF-36 physical and mental health summary scales: a user's manual. Boston MA, Health Assessment Lab, 1994.

10. SPSS Inc. Headquarters, 11th floor, 233 S Wacher Drive, Chicago, IL 60606, USA.

11. S-Plus, Mathsoft Inc., 101 Main Street, Cambridge, MA, USA.

12. Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and Regression Trees. Belmont CA, Chambers, 1984.


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