During the last decade, several studies have established an association between HIV infection and cardiovascular disease. Recent studies have shown an increased risk of myocardial infarction associated with HIV infection, HAART and abacavir [1–4].
Less attention has been paid to the possibly increased risk of cerebrovascular disease. Previous studies, which are primarily from the pre-HAART era, are inconclusive but favor an increased risk of stroke in HIV-infected individuals [4–23].
We conducted a Danish nationwide, population-based cohort study to examine the risk of cerebrovascular events (CVEs) in HIV-infected individuals compared with the general population. As the underlying mechanism for a possibly increased risk of cerebrovascular disease is unclear, we further examined the impact of proven risk factors, risk factors often associated with HIV infection [e.g. injection drug abuse (IDU)], immunodeficiency, use of antiretroviral drugs and the HIV infection per se on risk of CVEs. We further examined the risk of CVEs in parents of HIV-infected individuals to evaluate the impact of family-related risk factors.
As of 1 January 2010, Denmark had a population of 5.5 million , with an estimated HIV prevalence of 0.1% among adults. Medical care, including antiretroviral treatment, is tax-supported and provided free-of-charge to all HIV-infected residents of Denmark. Treatment of HIV infection is restricted to eight specialized medical centers where patients are seen on an outpatient basis at intended intervals of 12 weeks. During our study's follow-up period, national criteria for initiating HAART were HIV-related disease, acute HIV infection, pregnancy, CD4 cell count less than 300 cells/μl and, until 2001, plasma HIV-RNA higher than 100 000 copies/ml.
We used the unique 10-digit civil registration number assigned to all individuals in Denmark to link data from the following registers.
The Danish HIV Cohort Study
The Danish HIV Cohort Study (DHCS), which has been described in detail elsewhere, is a nationwide, prospective, population-based cohort study of all Danish HIV-infected individuals treated at Danish hospitals since 1 January 1995 [25,26].
The Danish Civil Registration System
The Danish Civil Registration System (DCRS), established in 1968, stores information on vital status, residency and immigration/emigration for all Danish residents .
The Danish National Hospital Registry
The Danish National Hospital Registry (DNHR), established in 1977, records data on all admissions to nonpsychiatric hospitals in Denmark, classified according to the International Classification of Diseases [8th revision (ICD-8) until 31 December 1993 and 10th revision (ICD-10) thereafter] .
The Danish Cancer Register
The Danish Cancer Registry (DCR), established in 1942, records all cancer diagnoses according to a modified edition of the International Classification of Diseases [7th revision (ICD-7) since 1943 and according to the 10th revision (ICD-10) and ICD-O (for oncology) since 1994 (the cancer diagnoses from 1978 to 1994 was later converted to ICD-10 and ICD-O)] .
We identified all Danish HIV-infected individuals older than 16 years at the date of HIV diagnosis from DHCS. The index date was defined as the date of HIV diagnosis, date of arrival to Denmark or 1 January 1995, whichever was more recent. Individuals diagnosed with cerebrovascular disease or cerebral comorbidity (defined as central nervous system (CNS) tumor, cancer, lymphoma, metastasis, non-HIV-associated cerebral infections, HIV-associated cerebral opportunistic infections and AIDS dementia) prior to index date, were excluded (Fig. 1 of online Appendix II, http://links.lww.com/QAD/A154).
General population comparison cohort
A comparison cohort consisting of nine age-matched and sex-matched population controls who were alive and living in Denmark on index date and not diagnosed with cerebrovascular disease or cerebral comorbidity prior to index date of the HIV-infected individual were identified from DCRS. Index date was defined as date of index date of the matched HIV-infected individual.
From DCRS, we identified parents of all Danish HIV-infected individuals and their matched comparison cohort in whom the offspring was born after 1952 and for whom at least the mother was identifiable. Parents diagnosed with cerebrovascular disease and cerebral comorbidity prior to index date were excluded. Index date of the parents was defined as the start of the DNHR (1 January 1977), date of arrival to Denmark or date of birth of the offspring, which ever was more recent.
The primary outcome was time to first ever CVE defined as the first date an individual was registered with a diagnosis of nontraumatic subarachnoid hemorrhage, intracerebral hemorrhage, cerebral infarction, unspecified stroke or transient ischemic attack in DNHR. Diagnoses obtained from emergency rooms but not confirmed subsequently were not included. The diagnosis stroke sequels were included as CVE if no prior CVE diagnosis was registered and categorized as unspecified stroke.
The diagnoses and ICD8/ICD10 codes are provided in online Appendix I, http://links.lww.com/QAD/A154.
Outcomes (CVEs) were classified as ‘CVEs with proven risk factor’ if at least one risk factor, as defined in online Appendix I, http://links.lww.com/QAD/A154, was registered in DNHR, DCR or DHCS prior to or within 30 days after an event (for cancer up to 90 days after an event) [30–41]. The remaining outcomes were classified as ‘CVEs with no proven risk factors’.
Time was computed from index date until date of CVE, date of other cerebrovascular disease than CVE, 30 days prior to date of cerebral comorbidity, date of death, emigration, lost to follow-up or 1 August 2010, whichever came first. To illustrate the probability of overall CVE, we used cumulative incidence function to illustrate time to first CVE recognizing other cerebrovascular disease as well as cerebral comorbidity and death as a competing risk. We used Cox regression analyses to calculate incidence rate ratios (IRRs) as estimates of the relative risk and 95% confidence intervals (CIs) for total CVE as well as for CVE subgroups. In the comparisons of HIV-infected individuals and their matched comparison cohorts, the analyses were stratified according to the initial match criteria (age and sex) and adjusted for country of birth (Denmark vs. outside Denmark). The estimated IRRs for the parents were adjusted for age at index date (categorized into five age intervals: 0–30, 31–45, 46–60, 61–75 and >75 years), calendar year [categorized into five time intervals (index date: 1977–1985, 1986–1990, 1991–1995, 1996–2000 and 2001–2010)] and country of birth.
Due to the different characteristics and risk profiles of individuals with and without IDU (IDU/non-IDU), all analyses were stratified on the basis of IDU.
Because the accuracy of coding may differ in the discharge diagnoses, we performed a robustness analysis excluding individuals registered with stroke sequels as first diagnosis of CVE and patients registered with hepatitis C (hepatitis testing is performed routinely at the first visit).
To examine the impact of immunodeficiency (CD4 cell count ≤200 cells/μl), HAART in general as well as HAART regimens including protease inhibitors, indinavir, didanosin, tenofovir and abacavir on the risk of CVE, time-dependent Cox regression analyses were used to compute IRRs in the non-IDU HIV-infected population. In these calculations, time was divided into four periods: time from index date until first CD4 cell count less than or equal to 200 cells/μl occurring before initiation of HAART, time from first CD4 cell count less than or equal to 200 cells/μl until initiation of HAART, time from initiation of HAART until first occurrence of a CD4 cell count higher than 200 cells/μl and time on HAART with a CD4 count higher than 200 cells/μl until the end of observation. To specifically estimate the impact of treatment with specific antiretroviral drugs, we performed analyses in which only HIV-infected individuals who initiated HAART were included, and handled first initiation of the drug as a time-updated variable (first date of CD4 cell count higher than 200 cells/μl after the start of HAART was included for confounder control). In these analyses, an individual who initiated a specific antiretroviral drug was considered on this drug for the rest of the observation period independent of cessation or changes in antiretroviral therapy. Finally, we performed an analysis in which the date of first abacavir cessation was included. The estimated IRRs in the time-dependent analysis on the non-IDU HIV-infected individuals were adjusted for age at index date (categorized into four age intervals: 16–30, 31–45, 46–60 and >61 years), sex, calendar year [categorized in five time intervals (index date: 1995–1997, 1998–2000, 2001–2003, 2004–2006 and 2007–2010) and place of birth.
Statistical analyses were performed using SPSS version 17.0 and R version 2.11.1. The study was approved by the Danish Data Protection Agency (jr. no. 2008–41–1781).
We identified 5031 HIV-infected individuals and 45 279 comparison cohort individuals. 536 (10.7%) HIV-infected individuals were IDU individuals. The median age at index date was almost identical in the non-IDU and IDU HIV-infected individuals (36.9 vs. 35.6 years), but more non-IDU HIV-infected individuals than IDU HIV-infected individuals were older than 50 years at the index date (15.3 vs. 1.9%). Additional characteristics of HIV-infected individuals and the two matched comparison cohorts are provided in Table 1. The registered risk factors are provided in Table 1 of online Appendix II, http://links.lww.com/QAD/A154.
Overall, CVE was diagnosed in 123 (2.7%) non-IDU HIV-infected individuals (43.9% with no proven risk factors) and in 17 (3.2%) IDU HIV-infected individuals. In the comparison cohorts, CVE was observed in 998 (2.5%) individuals from the non-IDU comparison group (40.7% with no proven risk factors) and 84 (1.7%) of the IDU comparison group (39.3% with no proven risk factors). Additional information on CVE subtypes is provided in Table 1.
The cumulated incidences of CVE for the four groups including 5 and 10 years risk of CVE after the index date are shown in Fig. 1.
As illustrated in Table 2, we found a higher risk of total CVEs in the HIV-infected population compared with the comparison cohorts. The risk was substantially higher in the IDU than in the non-IDU HIV-infected population (adjusted IRR 3.94; 95% CI 2.16–7.16 vs. adjusted IRR 1.60; 95% CI 1.30–1.95). The increased risk in the non-IDU HIV-infected individuals was due to a higher risk of CVEs with (adjusted IRR 1.55; 95% CI 1.19–2.03) and without proven risk factors (adjusted IRR 1.65; 95% CI 1.21–2.26). Furthermore, the increased risk of CVE was mainly due to a statistically significant higher risk of cerebral infarction, unspecified stroke and transient ischemic attack. In the IDU HIV-infected population, risk of subarachnoid hemorrhage, intracerebral hemorrhage, cerebral infarction and unspecified stroke was all substantially increased compared with the comparison cohort; however, only intracerebral hemorrhage and unspecified stroke were statistically significant. The increased risk of CVE was seen in both sexes and a trend towards a higher risk in patients reporting HIV transmission by heterosexual contact was observed (Table 2).
We found a significantly increased risk of total CVEs in non-IDU HIV-infected individuals with a CD4 cell count of 200 cells/μl or less who had not initiated HAART (adjusted IRR 2.26; 95% CI 1.05–4.86) (Table 3). After the initiation of HAART, the risk was identical to that of the pre-HAART period with a CD4 count higher than 200 cells/μl. In the period with low CD4 cell count before the start of HAART, we also observed a higher risk of CVEs with and without proven risk factors, although this was statistically insignificant (Table 3). In individuals who had initiated HAART, the risk of CVE was increased after first exposure to abacavir (adjusted IRR 1.66; 95% CI 1.03–2.68). The risk, however, stayed high after first cessation of abacavir (as a fraction of patients re-initiated abacavir, only 70.2% of the remaining observation time was time without abacavir treatment). This was also seen for CVE with and without proven risk factors, although the latter two results were statistically insignificant. Initiating protease inhibitor, indinavir, didanosin or tenofovir did not change the estimated risk of CVEs (Table 3).
The performed robustness analysis, in which individuals registered with stroke sequels as first diagnosis of CVE and individuals registered with hepatitis C infection were excluded, showed no major changes in CVE risk estimates.
We identified 2509 mothers and 2289 fathers of HIV-infected individuals as well as 21 982 mothers and 21 009 fathers of comparison cohort individuals (Table 2 of online Appendix II, http://links.lww.com/QAD/A154). The parents were comparable with respect to age and place of birth and the median time of follow-up was almost 30 years for all groups (Table 2 of online Appendix II, http://links.lww.com/QAD/A154). The parents of the HIV-infected individuals had a slightly increased risk of CVEs, which was almost exclusively driven by a substantially increased risk seen in the parents of offspring reporting IDU as the route of HIV transmission (Table 4).
We found a higher risk of CVEs in HIV-infected individuals than in the general population comparison cohorts. The risk was higher for both CVEs with and without proven risk factors. In the non-IDU HIV-infected population, immunodeficiency (CD4 cell count ≤200 cells/μl) before the start of HAART and treatment with abacavir almost doubled the risk of CVEs, whereas protease inhibitor, indinavir, didanosine, tenofovir or HAART in general had no impact on the risk of CVEs. Finally, the risk of CVEs was only increased in the parents of HIV-infected individuals who reported IDU as the route of transmission.
A main strength of our study is its nationwide population-based design with long and complete follow-up. The access to several Danish registries allowed us to identify population-based comparison cohorts and extract data on family members. Furthermore, data on study endpoints and comorbidity were obtained from the same data sources, thereby minimizing the impact of misclassification on our relative risk estimates. Importantly, we excluded patients with opportunistic cerebral infections, HIV dementia, non-HIV-associated cerebral infections and CNS neoplasia in order to avoid misclassification. We adjusted the analyses for potential confounding factors and further stratified all analyses on the basis of IDU. To make sure that the increased risk of CVE was not due to potential misclassification of individuals with IDU, we performed a robustness analysis excluding all non-IDU HIV-infected individuals with hepatitis C infection and saw no changes in our estimates. We are not aware of other studies with a similar design.
Due to the study design, we had no access to patient files or results of imaging techniques and had to rely on hospital registry-based discharge diagnoses in order to identify diagnoses of CVE. We are aware that there might be some misclassification in CVE diagnoses as well as in the diagnoses used to exclude individuals with CNS comorbidity. Previous studies have shown that DNHR tends to overestimate the prevalence of cerebrovascular disease [42,43], but the access to modern diagnostic tools has probably increased the validity of stroke diagnoses today . As the DNHR was not initiated until January 1977, some parents might have had a CVE prior to study inclusion, why some parents might have stroke sequels categorized as endpoint in our study. Nevertheless, as age of the parents at study inclusion was low and did not differ markedly between the compared groups, we presume that this phenomenon has not biased our relative risk estimates substantially. Furthermore, sensitivity analysis, in which we excluded individuals registered in DNHR with stroke sequels as first ever CVE, did not change our risk estimates. As we used the same source of data to ascertain CVE for all study participants, we presume that any potential misclassification was nondifferential and therefore did not influence our estimates of relative risk. Low socioeconomic status is associated with a higher risk of stroke, which is partly explained by a greater burden of classical risk factors . We could not directly adjust for socioeconomic status. However, as we stratified the analyses on IDU, evaluated the impact of risk factors and analyzed the risk of CVEs in the parents of the two groups, this was indirectly accounted for. We did not have information on nonantiretroviral medication or smoking status of which the latter is a highly important risk factor. This could invalidate the potential causal association of CVE and HIV. However, chronical obstructive pulmonary disease, excessive alcohol consumption and other conventional risk factors were included in the analyses, many of which are highly associated with smoking . Abuse of cocaine, amphetamine, ecstasy and related drugs are important risk factors for stroke in young adults . But, as we had no access to information on the drug itself, we included all IDU, registered as route of HIV infection in DHCS, as a surrogate marker of drug abuse in general. We are aware of the potential bias this might introduce, as some drug abusers among the non-IDU HIV-infected individuals might have been lost and as the frequency of the drug abuse and the effect of being clean or in a treatment program with, for example methadone, could not be accounted for.
In a case–control study from South Africa, Hoffmann et al. found that cryptogenic stroke, but not stroke in general, was more common in the HIV-positive population than in an age-matched and sex-matched HIV-negative control population. In contrast, Engstrøm et al. conducted a retrospective study of 1600 AIDS patients aged below 45 years (patients with competing opportunistic infections were not excluded) and found that 0.75% had been diagnosed with cerebral infarction, which was compared with an annual incidence of 0.025% for cerebral infarction in the background population aged between 35 and 45 years. Cole et al. studied AIDS patients with no opportunistic CNS infections, HIV dementia or IDU and found a relative risk of stroke, which was increased by a factor 10 (adjusted relative risk 10.4; 95% CI 4.9–22.0) compared with a non-AIDS population from the same region. HIV-infected individuals, however, who did not fulfill the criteria for AIDS were included in the control group. In accordance with Cole et al., we revealed that HIV-infected individuals with no concomitant cerebral comorbidity have an increased risk of CVEs. We presume that the differences in the risk estimates in these reports rely on differences in characteristics of the study populations, definitions and access to data on cerebrovascular endpoints. We found a relative risk of CVEs in IDU HIV-infected individuals, which was more than twice that of the non-IDU HIV population, which emphasizes the impact of drug abuse. A number of possible mechanisms to explain this phenomenon have been thoroughly discussed elsewhere [41,46]. Despite the awareness of drug abuse as a risk factor of CVEs and the link between HIV and IDU, most risk estimates in other studies are biased by this confounder [5–10,15,16,18–20,22].
The increased risk of cerebrovascular disease in HIV-infected individuals has been ascribed to several different pathological mechanisms such as cerebral opportunistic infections, associated vasculitis or vasculopathies, intracranial neoplasm, endocarditis and coagulation disorders [46,47]. As studies have found a higher prevalence of smoking in HIV-infected individuals than in the general population of the same age [48,49], it has been speculated whether a HIV-positive status simply serves as a marker for differences in the prevalence of conventional risk factors . However, in our study, an uneven distribution of risk factors could not solely explain the increased risk of CVEs, as both the relative risks of CVEs with and without proven risk factors were increased. Smoking is a strong predictor of CVEs [32,45]. In a meta-analysis by Shinton and Beevers , smoking increased the risk of stroke almost three-fold in a population aged less than 55 years. Due to the lack of information on smoking in our comparison cohorts, we were not able to address the impact of this risk factor and cannot exclude that an increased frequency of smoking in the HIV-infected population partly explains the increased risk of CVEs we observed.
In accordance with our results, some studies have observed an increased risk of stroke in HIV-infected individuals with low CD4 cell counts [14,20]. Whether this association is due to the immunodeficiency per se, an association with the increased risk of cerebral opportunistic diseases or a general deteriorated condition in these patients has to be established.
Few studies have examined the impact of HAART on the risk of cerebrovascular disease [4,13,16,19,22,23]. The two largest studies, in which conflicting results of HAART exposure were found, used composite endpoints [13,16]. A study from Thailand reported a two-fold increased risk of stroke after the start of HAART, which contrasts the observations from an American study that found no correlation  and a Spanish study that observed a protective effect of HAART . In our analyses, HAART did not influence the risk of CVEs.
Abacavir has been associated with an increased risk of myocardial infarction, but the causal pathway for this effect is still controversial [3,4,50]. An association between abacavir and risk of stroke, however, could not be demonstrated in the D:A:D study . We observed a higher risk of CVEs in HIV-infected individuals on abacavir irrespective of low CD4 cell count. Protease inhibitor, indinavir, didanosin and tenofovir on the contrary showed no such association. We presume that the mechanisms for this phenomenon are equivalent to that seen for myocardial infarction, but we cannot exclude that patients with an a priori increased risk of CVEs had a higher chance of being treated with abacavir (channeling bias) [3,50].
We registered an increased risk of CVEs in parents of IDU HIV-infected individuals. This association suggests that family-related risk factors are a complex combination of shared socioeconomic factors, a possible tendency to ‘risk-taking behavior’ and a genetic component [51,52].
We conclude that HIV infection is associated with an increased risk of CVEs with and without proven risk factors. The risk is associated with IDU, low CD4 cell count and treatment with abacavir, but not with HAART in general. Family-associated risk factors seem vaguely associated with the increased risk of CVEs in HIV-infected individuals.
We are grateful to the staff of our clinical departments for their continuous support and enthusiasm. We thank Preben and Anna Simonsen's Foundation, the NOVO Nordic Foundation, University of Southern Denmark and the Clinical Institute of Copenhagen University for financial support.
Conflicts of interest
N.O. has received research funding from Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, GlaxoSmith-Kline, Abbott, Boehringer Ingelheim, Janssen-Cilag and Swedish Orphan Drugs.
F.N.E. has received research funding from Merck Sharp & Dohme.
C.P. has received research funding from Abbott, Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, GlaxoSmithKline, Swedish Orphan Drugs and Boehringer Ingelheim.
J.G. has received research funding from Abbott, Roche, Bristol-Myers Squibb, Mecrk Sharp & Dohme, Pharmasia, GlaxoSmithKline, Swedish Orphan Drugs and Boehringer Ingelheim.
H.C. has received honorariums and sponsorships from Boehringer-Ingelheim, Abbott/Solvay, Medtronics, Sanofi-Avensis and Atrietech.
L.D.R. and G.K. report no conflicts of interest.
Author contributions: Conception and design: L.D.R., F.N.E., H.C., N.O.
Analysis and interpretation of the data: L.D.R., F.N.E., N.O.
Drafting of the article: L.D.R.
Critical revision of the article for important intellectual content: L.D.R., F.N.E., C.P., J.G., G.K., H.C., N.O.
Final approval of the article: L.D.R., F.N.E., C.P., J.G., G.K., H.C., N.O.
Provision of study materials or patients: C.P., G.K., J.G., N.O.
Statistical expertise: L.D.R., F.N.E., N.O.
Obtaining of funding: N.O.
Administrative, technical, or logistic support: L.D.R., N.O.
Collection and assembly of data: C.P, G.K., J.G., N.O.
Centers in the Danish HIV Cohort Study: Departments of Infectious Diseases at Copenhagen University Hospitals, Rigshospitalet (J.G., N.O.) and Hvidovre (G.K.), Odense University Hospital (C.P.), Aarhus University Hospitals, Skejby (C.S.L.) and Aalborg (G.P.), Herning Hospital (A.L.L.), Helsingør Hospital (L.N.) and Kolding Hospital (J.J.).
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