Published online before print June 26, 2003, doi: 10.1161/01.STR.0000079818.08343.8C
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(Stroke. 2003;34:2050.)
© 2003 American Heart Association, Inc.
Comments, Opinions, and Reviews |
Differences in Vascular Risk Factors Between Etiological Subtypes of Ischemic Stroke
Importance of Population-Based Studies
From the Stroke Prevention Research Unit, Department of Clinical Neurology, University of Oxford, Oxford, UK.
Correspondence to Dr P.M. Rothwell, Stroke Prevention Research Unit, Department of Clinical Neurology, University of Oxford, Radcliffe Infirmary, Woodstock Rd, Oxford OX2 6HE UK. E-mail peter.rothwell{at}clneuro.ox.ac.uk
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Abstract |
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Background— To understand the mechanisms of stroke and to target prevention, we need to know how risk factors differ between etiological subtypes. Hospital-based studies may be biased because not all stroke patients are admitted. If risk factors differ between patients who are admitted and those who are not, then case-control studies will be biased. If the likelihood of admission also depends on stroke subtype, then case-case comparisons may also be biased.
Methods— We compared risk factors and ischemic stroke subtypes (TOAST classification) in hospitalized and nonhospitalized patients in 2 population-based stroke incidence studies: the Oxford Vascular Study (OXVASC) and Oxfordshire Community Stroke Project (OCSP). We also performed a meta-analysis of risk factor–stroke subtype associations with other published population-based studies.
Results— In OXVASC and OCSP, stroke subtypes differed between hospitalized (293 of 647) and nonhospitalized patients (P<0.0001), with more cardioembolic strokes (odds ratio [OR], 1.8; 95% CI, 1.3 to 2.6) and fewer lacunar strokes (OR, 0.4; 95% CI, 0.3 to 0.7). Premorbid blood pressure and cholesterol were higher in hospitalized patients (both P<0.0001). Risk factor–stroke subtype associations in hospitalized patients were consequently biased (P=0.001). Meta-analysis of data from all patients in OXVASC, OCSP, and 2 other studies demonstrated consistent risk factor–stroke subtype associations. However, contrary to previous hospital-based studies, there was only a weak (OR, 1.4; 95% CI, 1.1 to 1.8) and inconsistent (Pheterogeneity=0.01) association between small-vessel stroke and hypertension and no association with diabetes (OR, 1.0; 95% CI, 0.7 to 1.3).
Conclusions— Prevalences of risk factors and stroke subtypes differ between hospitalized and nonhospitalized patients with ischemic stroke, which may bias hospital-based risk factor studies. Meta-analysis of population-based studies suggests that vascular risk factors differ between stroke subtypes.
Key Words: etiology • risk factors • stroke • stroke classification
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Introduction |
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In contrast to coronary heart disease, stroke is a highly heterogeneous disorder. The vast majority of acute coronary syndromes are due to medium- and large-artery atheroma,1 whereas ischemic stroke may also be due to other pathologies, including intracranial small-vessel disease, cardioembolism, and prothrombotic disorders. We need to know how risk factors differ between these different subtypes of ischemic stroke to understand the mechanisms of disease and to target preventive treatments. The first requirement is to obtain reliable data on the differences in the frequency of established risk factors between subtypes of ischemic stroke.
Many studies of risk factors for stroke have not considered pathological and etiological subtypes separately and often have not even differentiated fully between subarachnoid hemorrhage, intracerebral hemorrhage, and cerebral infarction.2–4 Of those studies that have categorized strokes as ischemic or hemorrhagic, most have not subdivided ischemic stroke according to the different clinical or etiological subtypes.5,6 A few studies have compared the prevalence of risk factors between the different subtypes of ischemic stroke and have reported important differences in the frequency of established vascular risk factors.7–11 However, these studies were hospital based; therefore, it is possible that some of the observed differences in risk factors were due to inclusion bias.
Between 10% and 40% of stroke patients are not admitted to hospital.12,13 If risk factors differ between patients who are admitted and those who are not, then case-control studies will be biased. If the likelihood of admission also depends on the subtype of stroke, then case-case comparisons may also be biased. Therefore, our first aim was to compare risk factors and stroke subtypes in hospitalized and nonhospitalized patients in 2 population-based stroke incidence studies—the Oxford Vascular Study (OXVASC) and Oxfordshire Community Stroke Project (OCSP)14–16—and to quantify any bias in analyses confined to hospitalized patients. Our second aim was to determine risk factor–stroke subtype associations as reliably as possible in all patients in population-based stroke incidence studies. We therefore performed a systematic review of all such studies that reported the frequency of risk factors according to the Trial of Org 10172 for Acute Stroke Treatment (TOAST) classification of ischemic stroke.17
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Methods |
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OCSP and OXVASC
We studied vascular risk factors by subtype of ischemic stroke in 2 population-based studies: the OCSP and the pilot phase of the OXVASC study. The methods and results of OCSP, which ran from 1981 to 1986, have been published previously.14,15 The OXVASC pilot study was started in 2002 and used methods of ascertainment of stroke and transient ischemic attack (TIA) identical to those used in OCSP.14,16 Briefly, through collaboration with general practices (10 practices in OCSP, 9 practices in OXVASC), an urban and rural population (105 000 people in the OCSP, 91 000 in OXVASC) was studied. General practitioners (GPs) were encouraged to report all patients who might have suffered a TIA or stroke during the study periods. Strokes were also identified by daily assessment of hospital registers, hospital diagnostic coding, review of referrals for brain and vascular imaging, and review of all death certificates and coroner’s reports when relevant. In both studies, a study neurologist assessed all cases as soon as possible after notification. When possible, all patients underwent CT brain imaging. Details of the presenting event, clinical characteristics, and medical history were recorded from the patient, GP records, and hospital records. For patients who were dysphasic or who died before assessment, information was obtained from relatives and from GP and hospital records. Patients were followed up, and stroke severity was assessed by 30-day mortality and the Rankin Scale score at 30 days. Study methods conformed to the quality criteria for population-based stroke incidence studies devised by Malmgren et al18 and Sudlow and Warlow.19
In OXVASC, patients routinely undergo Doppler scanning of the carotid and vertebral arteries and echocardiography. Stroke etiology is classified prospectively according to the TOAST criteria.17,20 In OCSP, the subtype of ischemic stroke had been categorized according to the classification of Bamford et al,21 but the investigators had also originally prospectively categorized stroke according to etiology. Detailed clinical and imaging data had also been collected. This allowed us to reclassify all ischemic strokes according to the same etiological categories as used in the TOAST study17,20: large-vessel stroke, small-vessel stroke, cardioembolic stroke, other defined etiology, and undefined etiology. It has been shown that the TOAST classification can be applied retrospectively with accurate and reproducible results,20 and we were able to adhere to the TOAST criteria in 4 of the 5 etiological categories. However, we could not follow the exact criteria for large-vessel strokes (stenosis >50%) because Doppler ultrasound was not yet routinely available in OCSP. Carotid disease was diagnosed by arterial angiography, which was performed only if large-vessel disease was suspected because of the clinical assessment. The large-artery disease definition was based primarily on the angiographic imaging. However, we also included some strokes for which the original investigators had a high index of clinical suspicion that large-artery disease was responsible but angiography could not be performed.
In both studies, we analyzed the association between ischemic stroke subtype and the following risk factors: sex, age, hypertension (history, currently on treatment, or blood pressure [BP] >160 mm Hg systolic and/or 95 mm Hg diastolic before stroke), diabetes mellitus (history or currently on treatment), previous TIA (history according to patient or GP and hospital notes), current smoking, alcohol use (daily consumption versus occasional/never), systolic and diastolic BPs (most recent measurement before stroke), and plasma cholesterol (mmol/L). Plasma cholesterol was checked on admission (usually within a few hours of stroke onset) in hospitalized patients and at the time of clinic assessment (sometimes several days after the event) in nonhospitalized patients. We recorded the time of cholesterol assessment because cholesterol levels may change after 48 hours in patients with severe strokes. We also compared stroke etiology and risk factor prevalence between hospitalized and nonhospitalized patients. Some patients were treated as outpatients but were admitted to hospital electively some time after their stroke for further investigations, eg, as day cases for cerebral angiography. These patients were also regarded as nonhospitalized.
Systematic Review
To identify population-based stroke incidence studies that reported data on the frequency of vascular risk factors according to the TOAST classification of ischemic stroke (or similar), we (1) identified all stroke incidence studies referenced in previous published reviews12,18,19,22,23 and searched MEDLINE and EMBASE for any follow-up or secondary studies using the author and study names from the primary study; (2) performed a further search of MEDLINE using the search terms "stroke and incidence," "stroke and risk factors," and "stroke and subtype"; and (3) hand-searched the journals Stroke and Cerebrovascular Diseases from 1990 to 2002.
We had 4 main inclusion criteria. First, to be eligible, studies had to satisfy the 12 quality criteria related to definitions, methods, and mode of data presentation published by Malmgren et al18 and Sudlow and Warlow.19 These criteria are strict but are widely accepted.18 Second, studies should have ascertained strokes in all sections of the population rather than in specific racial groups.24 Third, studies must have had a combined brain imaging or autopsy rate of at least 80% to reliably exclude hemorrhagic stroke in most cases. Finally, studies must have reported the frequency of vascular risk factors in ischemic strokes classified according to the TOAST criteria or a broadly comparable classification.
Statistical Analysis
In the OCSP and OXVASC study, we calculated the frequency of vascular risk factors for each stroke subtype. In the meta-analysis of all the studies, we compared the odds of a risk factor being present in a particular ischemic stroke subtype to the odds of it being present in the remainder of the population, and we compared the odds between specific subtypes (large vessel versus small vessel, large vessel versus cardioembolic, and small vessel versus cardioembolic). In the meta-analysis, the odds ratios (OR) from individual studies were combined by use of the Mantel-Haenzel-Peto method to produce pooled estimates.
In the OCSP and OXVASC study, we determined the association between ischemic stroke subtype and each of the risk factors after adjustment for differences in age, sex, and study in a multivariate logistic regression analysis. We compared stroke subtypes, risk factor prevalence, and stroke severity between hospitalized and nonhospitalized patients with a 
2 test for categorical variables and with analysis of variance for continuous variables. To determine the effect of any ascertainment bias in hospital-based studies, we analyzed stroke subtype–risk factor associations in a multivariate logistic regression analysis separately for inpatients only and for the entire study cohort, adjusting for age, sex, and study. We then compared the absolute size of the log ORs obtained from the inpatient analysis and the whole-group analysis for each of the associations tested. A 1-sample t test was used to test for any significant differences in the size of the log ORs between the 2 groups. All analyses were performed with SPSS version 10.0 (SPSS Inc).
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Results |
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Of the 675 patients registered in OCSP with a first-ever stroke, 596 (88.3%) had CT scanning or autopsy, and 545 patients were classified as having had a first-ever ischemic stroke. In the OXVASC pilot study, 124 patients were registered with an incident stroke from April 1, 2002, to December 31, 2002, of whom 118 (95%) had CT scanning or autopsy, and 102 (52 men) were found to have had an ischemic stroke. The prevalence of the different etiological subtypes is shown in Table 1.
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In OXVASC and OCSP, 293 (45%) patients were admitted to hospital, and 354 (55%) were treated as outpatients or in the community. Admission rates were higher in OXVASC than in OCSP (57% versus 43%, P=0.01) Brain imaging was done less often in patients who were admitted (91% versus 84%, P=0.012), but there were no differences in other investigations (ECG, echocardiography, angiography) or in the availability of risk factor data. However, the pattern of stroke subtypes did differ (P<0.0001; Table 2). For example, in hospitalized patients, cardioembolic strokes were more common (28.3% versus 17.8%), and small-vessel strokes were less common (14.3% versus 27.5%). Similarly, some risk factors differed between hospitalized and nonhospitalized patients. For example, BP levels were significantly higher in nonhospitalized than in hospitalized patients (Table 2). Mean cholesterol levels were also higher in nonhospitalized compared with hospitalized patients (P<0.0001; Table 2). They were checked at a median of 5 days (interquartile range, 2 to 8 days) after stroke in nonhospitalized patients and 1 day (interquartile range, 0 to 4 days) in hospitalized patients (P<0.0001, Wilcoxon test). Mean age did not differ, but patients <50 or >90 years of age were most likely to be admitted. As expected, outcome also differed between hospitalized and nonhospitalized patients (Table 2).
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The differences between hospitalized and nonhospitalized patients in risk factors and stroke subtypes influenced the risk factor associations. These were, on average, stronger in hospitalized patients (P=0.001) than in the cohort as a whole. Table 3 shows the data for patients with large-vessel disease versus other subtypes. In hospitalized patients, large-vessel disease was positively associated with hypertension, previous TIA, systolic BP, and cholesterol. However, only the association with cholesterol was present in outpatients. Although the sample size was too small to test reliably for statistical heterogeneity between these associations, the differences between hospitalized and nonhospitalized patients still approached significance (P
0.1) for previous TIA, systolic BP, and diastolic BP.
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The associations between risk factors and stroke subtypes for the entire study cohort are shown in Table 4. Large-vessel disease was strongly associated with male sex (OR, 1.77; 95% CI, 1.12 to 2.78; P=0.014), previous TIA (OR, 2.81; 95% CI, 1.72 to 4.60; P<0.0001), and raised cholesterol (OR, 1.56; 95% CI, 1.29 to 1.89; P<0.0001), whereas cardioembolic stroke was negatively associated with cholesterol (OR, 0.64; 95% CI, 0.54 to 0.76; P<0.0001). Small-vessel disease was not associated with a history of hypertension or diabetes.
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Systematic Review
We identified 22 published population-based stroke incidence studies in which brain imaging or autopsy had been performed in 
80% (references available from authors). However, only 3 studies had reported data on baseline clinical characteristics by etiological subtype of ischemic stroke25–27; all 3 were based on the TOAST criteria. One of these compared the prevalence of risk factors in stroke patients versus nonstroke patients and reported only hazard ratios, so we were unable to include that study in the meta-analysis.27 A similar etiological subclassification of ischemic stroke, which predated the TOAST classification, was used in the Perth study,28 but no risk factor data were reported. Risk factor data were therefore only available from 2 previous studies and from OCSP and OXVASC.
Table 1 shows the distribution of ischemic stroke subtypes for the 4 studies. Apart from strokes of other defined etiology, which were rare, the prevalence of the other etiological categories did not differ between studies (Pheterogeneity=0.39). Neither the Erlangen nor the Rochester study reported specific diagnoses for strokes of other defined etiology.
The Rochester and Erlangen studies reported data on 5 risk factors: sex, age, hypertension, diabetes, and smoking. The Rochester study also reported prior TIA. All of these data were available in OCSP and OXVASC. The definitions of risk factors were generally consistent across the studies. Hypertension was defined as a history reported by the patient or a relative, current medication for hypertension, or BP >160/95 mm Hg before stroke. Smoking was recorded as the patient smoking regularly up to the date of stroke. A history of TIA was obtained from the patient or GP or hospital notes. There were some differences between studies in the definitions of diabetes: on treatment for diabetes mellitus in OCSP and OXVASC; fasting glucose >5.8 mmol/L in Rochester; and history of or on treatment for diabetes mellitus or fasting blood glucose 6.66 mmol/L in Erlangen. In OCSP, OXVASC, and the Rochester study, "young stroke" was defined as 50 years. The closest definition in the Erlangen study was age <55 years.
The prevalence of risk factors differed across the studies (Table 5). Men were most prevalent in OCSP and in OXVASC, whereas current smoking and hypertension were most frequent in the Rochester study. The prevalence of diabetes was lowest in OCSP and OXVASC, but there were differences in definition.
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Figure 1 shows the risk factor–stroke subtype associations. There were several significant differences between stroke subtypes, most of which were consistent across the studies. Large-vessel disease was highly consistently associated with male sex (OR, 2.1; 95% CI, 1.6 to 2.8; P<0.0001) and previous TIA (OR, 2.3; 95% CI, 1.6 to 3.3; P<0.0001) and less consistently (Pheterogeneity=0.002) with smoking (OR, 2.3; 95% CI, 1.8 to 3.1; P<0.0001). In contrast, there were consistent negative associations between cardioembolic stroke and male sex (OR, 0.7; 95% CI, 0.6 to 0.9; P=0.01), smoking (OR, 0.6; 95% CI, 0.5 to 0.8; P=0.002), and age <50 years (OR, 0.5; 95% CI, 0.3 to 0.9; P=0.02).
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For small-vessel disease, only the Erlangen study showed an association with hypertension. None of the studies showed any association between small-vessel stroke and diabetes (OR, 1.1; 95% CI, 0.8 to 1.4; P=0.82), and there were no other consistent associations. Stroke of undetermined etiology was consistently negatively associated with hypertension and prior TIA. The numbers of strokes of other defined etiology were very small, so the meta-analysis is not shown. However, there were consistent associations with age <50 years (OR, 9.2; 95% CI, 4.9 to 17.3; P<0.0001) and female sex (OR, 1.9; 95% CI, 1.1 to 3.3; P=0.04).
We also compared the frequency of risk factors between individual stroke subtypes (Figure 2). This comparison emphasizes the association of large-vessel disease with male sex and smoking compared with small-vessel disease and cardioembolic strokes, and the negative association of cardioembolic stroke with smoking compared with large- and small-vessel disease.
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Discussion |
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Our study has 2 main findings. First, the prevalences of etiological subtypes of ischemic stroke and of vascular risk factors differ between hospitalized and nonhospitalized patients. Stroke subtype–risk factor associations in hospital-based studies may therefore be biased, particularly if minor strokes that are investigated in the outpatient clinic are not reliably ascertained. Overall, our results support the need for population-based studies to obtain reliable data on differences in the frequency of established vascular risk factors between different subtypes of ischemic stroke. Otherwise, case-control studies are likely to be biased because risk factors differ between patients who are admitted and those who are not, and case-case comparisons will be biased because the likelihood of admission is related to stroke subtype.
Second, our meta-analysis of population-based studies demonstrated several consistent associations of risk factors with particular subtypes of ischemic stroke and failed to confirm some associations that have been reported in hospital-based studies. Multivariate analysis of the OCSP and OXVASC data showed that most of these associations were independent of differences in age and sex, although pooled analyses of individual patient data from a larger number of studies is necessary to allow adjustment for more potentially confounding variables.
Large-vessel disease was consistently associated with male sex and smoking. This is in keeping with large-vessel disease in other circulations29 and with previous hospital-based studies of extracranial atherosclerosis.30,31 The association with male sex may partly explain why more men than women undergo carotid endarterectomy.32 In all studies for which data were available, prior TIA was also associated with large-vessel disease, in keeping with hospital-based studies.8–10 In the OCSP and OXVASC study, we also showed a positive association between large-vessel disease and cholesterol levels. Cholesterol levels may be affected by stroke and therefore should be checked within 48 hours, but it is unlikely that this influenced our results. In hospitalized patients with severe strokes, cholesterol was checked on admission (usually within hours of the stroke). Although there was a median delay of 5 days in nonhospitalized patients, these were usually minor strokes that would be less likely to affect cholesterol levels. We therefore think that any associations between stroke subtypes and cholesterol level in our study are likely to be genuine.
Hospital-based studies suggest that small-vessel strokes are associated with hypertension and diabetes.33,34 However, an association with diabetes was not present in the population-based studies, and although there was a statistically significant overall association with hypertension, this was accounted for mainly by 1 study.
Cardioembolism was least frequent among young strokes, and prevalence increased with age in OCSP and OXVASC, probably reflecting the increasing prevalence of atrial fibrillation with age. Cardioembolic stroke was also associated with female sex, but this association was not present after correction for age in OCSP and OXVASC.
It has been suggested that strokes of uncertain etiology may often be due to atheroma.17 However, strokes of undefined etiology were not associated with the same risk factors as large-vessel strokes. The results were inconsistent between the studies, and the overall profile did not resemble that of any of the other stroke subtypes. This suggests that strokes of undefined etiology may be due to a variety of different pathologies, the prevalence of which may vary between different populations. Strokes of other defined causes were rare in all 4 studies.
Potential Shortcomings
One shortcoming of the OCSP analysis was the retrospective assignment of the TOAST classification. This was unavoidable because OCSP was conducted before publication of the TOAST criteria. However, the investigators, using a very similar in-house classification, had prospectively categorized stroke etiology as resulting from atherosclerosis, cardioembolism, small-vessel disease, or some other cause. Thus, the categories used were the same as the categories in the TOAST classification, and the criteria used were similar, apart from the category of large-vessel disease when imaging data were not always available. However, given the lack of heterogeneity between the studies for the prevalence of large-vessel disease or the association with risk factors, the classification used in the OCSP was reasonable.
Our comparison of hospitalized and nonhospitalized stroke patients relates to the United Kingdom, where only about half of the patients are admitted. Admission practices in other countries vary, usually with higher admission rates, and our data may not be entirely generalizable. Higher admission rates are likely to lead to less bias in hospital-based studies. However, complete ascertainment is difficult to achieve in hospital-based studies because of death before referral, nonreferral because of extreme old age, refusal to be admitted, or investigation in nonstudy hospitals (5% of strokes in OXVASC occurred while the patients were on holiday and were not admitted to their home hospitals). Only in population-based studies in which all physicians in the community are regularly contacted will such cases be ascertained. Unfortunately, it was impossible to determine in OXVASC and OCSP which patients would not have been ascertained by equivalent hospital-based studies. There is no doubt that hospital-based studies do produce useful data, but population-based studies are required if bias is to be minimized.
The definitions of risk factors used in the 4 studies were generally similar, and availability of individual patient data in OCSP and OXVASC allowed us to adjust some risk factor definitions to be in keeping with the other 2 studies. The BP cutoff value of 160 mm Hg systolic and/or 95 mm Hg diastolic for hypertension, which was used in all 4 studies, is no longer in line with recent criteria. However, both the Erlangen and Rochester studies were started before the recent revision of the World Health Organization criteria for hypertension,35 so we had to use this cutoff to have a comparable definition across the studies.
The main difference in risk factor definitions was for diabetes. However, this should not have led to any major bias. All analyses were performed within individual studies, and meta-analysis of within-study estimates is methodologically valid even when definitions differ between studies. Although different, the definitions used in each of the individual studies were entirely reasonable and should not have obscured any association of diabetes with a specific stroke subtype if one existed. However, differences between studies in risk factor definitions and in risk factor prevalence are a possible source of bias and are important to bear in mind when meta-analyses are performed. Ideally, these problems could be overcome by performing a meta-analysis of individual patient data, which could be adjusted for study.
Finally, there are shortcomings with all etiological classifications of ischemic stroke. We used the TOAST classification because it is the most widely used system and because it was used in the Erlangen and Rochester studies. However, there are undoubtedly multiple different pathologies within each of the TOAST subcategories. This is clearly the case for strokes of undefined etiology but also for small-vessel and cardioembolic stroke.
Conclusions
Prevalences of risk factors and stroke subtypes differ between hospitalized and nonhospitalized patients with ischemic stroke, so hospital-based studies of risk factor associations are potentially biased. Meta-analysis of population-based studies shows that the frequency of vascular risk factors differs between stroke subtypes. More data, ideally pooled individual patient data from other population-based studies, are required to determine risk factor associations reliably. One such collaborative study (International Stroke Incidence Study Data Pooling Project) is currently underway.
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Acknowledgments |
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Dr Rothwell is funded by the Medical Research Council, and Dr Schulz is funded by the Wellcome Trust. We thank Professor Charles Warlow and the Oxford Community Stroke Project Collaborators for allowing us access to their data. We are very grateful to the OXVASC collaborators for their help with this study.
Received September 23, 2003; revision received March 4, 2003; accepted March 11, 2003.
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