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Symptom expectations and delay in acute myocardial infarction patients
  1. Department of Health Psychology
  2. *Department of Medicine
  3. Faculty of Medical and Health Sciences
  4. The University of Auckland, Private Bag 92019
  5. Auckland, New Zealand
  6. Centre for Health Care Research
  7. University of Brighton
  8. Brighton, West Sussex, UK
  9. kj.petrie{at}

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The efficacy of the timely administration of thrombolytic treatment in the clinical management of acute myocardial infarction (MI) is well established. Large scale clinical trials have conclusively shown that the earlier the administration of such treatment, the greater the morbidity and mortality advantage.1 The demonstration of this time dependent relation has prompted research into factors that contribute to the delay interval between symptom onset and hospital presentation. The failure of sociodemographic and clinical factors to be consistently related to pre-hospital delay2 has recently focused attention on how patients make sense of their symptoms and determine whether they need urgent medical help.

Building on a recent study which found that patient delay was associated with a discrepancy between symptom experience and prior symptom expectation of MI,3 we extended the scope of this research by also investigating whether delay was related to having a family member present or to behaviours such as self medication before calling for help. We evaluated a consecutive sample comprising 47 participants with a confirmed diagnosis of acute MI (38 men and nine women with a mean (SD) age of 62 (13.4) years). Thirty eight per cent of the sample had a family history of MI and 15% of participants had experienced a previous MI.

Patients were required to recall both the symptoms experienced as part of their MI and the symptoms they expected using a list of 18 symptoms. Patients also rated the match between the symptoms experienced and the symptoms expected on a single visual analogue scale scored from 0 (no match) to 10 (exact match). Patients were asked what, if any, attempts at self treatment, such as resting or taking medication, they had made before reaching the decision to go to hospital. Patients were also asked whether an ambulance was called and if a doctor was consulted before arriving at hospital.

Differences in mean pre-hospital delay times were analysed using independent samples t tests and one way analyses of variance. In those instances where the data were continuous, Pearson correlations were employed to test associations. A multiple regression analysis was used to examine which variables were most closely associated with pre-hospital delay time. All tests of statistical significance were two tailed and probability values of p < 0.05 were considered significant.

The majority of participants experienced their initial symptoms while at home (72.3%) and in the presence of another person (66%). Seventy four per cent of participants talked with someone following symptom onset. Consistent with previous studies4 the distribution of pre-hospital delay variable was highly positively skewed and required log transformation. The mean (SE) and median pre-hospital delay times were 15.3 (4.1) and 4.0 hours, respectively. Pre-hospital delay was unrelated to age, sex or the following clinical variables: site of MI, peak creatine kinase (CK) concentration, previous MI, family history of heart disease, current smoker, previously diagnosed diabetes mellitus, hypertension, and previous cardiac rehabilitation. However, shorter delay times were demonstrated in patients who experienced symptom onset in the presence of a family member (1.6 hours v 6.1 hours; t (45) = 2.23; p = 0.03) and who talked to another person (4.0 hours v 10.8 hours; t (45) = 2.17; p = 0.04) or a family member following symptom onset (2.2 hoursv 6.5 hours; t = 2.25; df = 45; p = 0.03).

Eighty one per cent of the sample attempted to self treat their symptoms before seeking professional medical care, and this was associated with a significantly longer delay time (t (45) = 2.07; p = 0.05). An ambulance was called in the case of 66% of patients and this was associated with significantly shorter pre-hospital mean delay times (3.8 v 9.3 hours; t (45) = −0.10; p = 0.04). Fifty five per cent of the sample consulted a physician before hospital presentation and there was a trend for this to be associated with longer delay times (7.1 v3.5 hours; t (45) = 1.75; p = 0.09).

The MI symptoms experienced and expected by patients are shown in table 1. The most common symptoms expected and experienced were chest pain, chest discomfort, loss of strength, fatigue, and radiating pain or shoulder pain. However, there was a discrepancy for many patients mostly in terms of symptoms they expected but were not experienced. The symptoms of collapse, dizziness, irregular heart beat, and loss of consciousness had significantly higher levels of expectation than experience. On the other hand, an upset stomach was expected by significantly fewer patients than in fact experienced the symptom. The majority of the sample reported experiencing some degree of mismatch between experienced and expected symptoms, with only two participants reporting experiencing an exact match. As predicted, the degree of match was significantly correlated with delay (r = −0.45, p = 0.002), with a greater discrepancy between expectations and experience being associated with longer delays before reaching hospital. When patients were divided into three equivalent groups according to degree of match between expected and experienced symptoms, there was a highly significant effect for the length of pre-hospital delay (F(2,44) = 108.5; p < 0.001).

Table 1

Symptoms expected and experienced (%) as part of onset of myocardial infarction

In order to determine the most important variables associated with pre-hospital delay, the factors significantly associated with delay in the univariate analyses were entered into a stepwise multiple regression model. Two variables entered the equation (R = 0.45, F(2,44) = 8.64, p = 0.001) with the majority of the variance (18%) being explained by the match between expected and experienced symptoms (β = −0.43, p = 0.001). Conversing with someone during symptom onset added an additional 6% of variance to the equation (β = −0.28, p = 0.03).

This study further highlights the role of symptom interpretation in determining the length of the pre-hospital delay time. We found none of the sociodemographic or clinical factors assessed to be significantly associated with pre-hospital delay times. Rather, delay was most closely related to the mismatch between expected and experienced symptoms. Conversation with someone about the symptoms during symptom onset also reduced delay. The importance of this finding is that, unlike previous studies that have focused on the clinical and demographic factors in delay, this newer approach provides a target for community education programmes and a way of evaluating the effectiveness of these interventions.

While the study is limited by the retrospective recall of symptoms, the data suggest that the reality for many patients in this study was that the onset of symptoms of MI were less dramatic than expected. Most patients had more dramatic expectations of symptoms of MI than actually occurred. These data suggest the need for public education to broaden the range of symptoms expected as part of the onset of an MI. Given that the role of another person seems to be critical in facilitating the decision to seek immediate help, intervention programmes targeted at widening the perception of symptom of MI onset should not just be restricted to those individuals at risk.


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