Article

Risk of cerebrovascular events in persons with and without HIV: A Danish nationwide population-based cohort study

Department of Infectious Diseases, Odense University Hospital, Denmark.
AIDS (London, England) (Impact Factor: 5.55). 06/2011; 25(13):1637-46. DOI: 10.1097/QAD.0b013e3283493fb0
Source: PubMed
ABSTRACT
To assess the risk of cerebrovascular events (CVEs) in HIV-infected individuals and evaluate the impact of proven risk factors, injection drug abuse (IDU), immunodeficiency, HAART and family-related risk factors.
Nationwide, population-based cohort study.
The study population included all Danish HIV-infected individuals, a population-based comparison cohort and parents of both cohorts - all with no prior cerebral comorbidity. We computed incidence rate ratios (IRRs) of overall CVEs and CVEs with and without proven risk factors, stratifying the analyses on IDU. Impact of immunodeficiency, HAART, protease inhibitors, indinavir, didanosin, tenofovir and abacavir on risk of CVEs was analyzed using time-dependent Cox regression analyses.
HIV-infected individuals had an increased risk of CVEs compared with the comparison cohorts [(non-IDU HIV adjusted IRR 1.60; 95% confidence interval [CI] 1.32-1.94), (IDU HIV adjusted IRR 3.94; 95% CI 2.16-7.16)]. The risk was increased with and without proven risk factors. A CD4 cell count of 200 cells/μl or less before the start of HAART and exposure to abacavir increased the risk of CVE [(adjusted IRR 2.26; 95% CI 1.05-4.86) and (adjusted IRR 1.66; 95% CI 1.03-2.68)]. Protease inhibitors, indinavir, didanosin, tenofovir and HAART in general had no impact. Risk of CVEs was only increased in the parents of IDU HIV-infected individuals.
HIV-infected individuals have an increased risk of CVEs with and without proven risk factors. The risk is associated with IDU, low CD4 cell count and exposure to abacavir, but not with HAART. An association with family-related risk factors seems vague except for parents of IDU individuals.

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Risk of cerebrovascular events in persons with and
without HIV: A Danish nationwide population-based
cohort study
Line D. Rasmussen
a
, Frederik N. Engsig
b
, Hanne Christensen
c
,
Jan Gerstoft
b
, Gitte Kronborg
d
, Court Pedersen
a
and Niels Obel
b
Objective: To assess the risk of cerebrovascular events (CVE) in HIV-infected individ-
uals and evaluate the impact of proven risk factors, injection drug abuse (IDU),
immunodeficiency, highly active antiretroviral therapy (HAART) and family-related
risk factors.
Design: Nationwide, population-based cohort study
Methods: The study population included all Danish HIV-infected individuals, a popu-
lation based comparison cohort and parents of both cohorts all with no prior cerebral
comorbidity. We computed incidence rate ratios (IRR) of overall CVE and CVE with and
without proven risk factors, stratifying the analyses on IDU. Impact of immunodefi-
ciency, HAART, protease-inhibitors, indinavir, didanosin, tenofovir and abacavir on
risk of CVE was analyzed using time-dependent Cox regression analyses.
Results: HIV-infected individuals had an increased risk of CVE compared with the
comparison cohorts {(non-IDU HIV adjusted IRR 1.60; 95% CI: 1.321.94), (IDU HIV
adjusted IRR 3.94; 95% CI: 2.167.16)}. The risk was increased with and without
proven risk factors. A CD4 count <¼ 200 cells/ml before start of HAART and exposure to
abacavir increased the risk of CVE {(adjusted IRR 2.26; 95% CI: 1.054.86) and
(adjusted IRR 1.66; 95% CI: 1.032.68)}. Protease-inhibitors, indinavir, didanosin,
tenofovir and HAART in general had no impact. Risk of CVE was only increased in the
parents of IDU HIV-infected individuals.
Conclusion: HIV-infected individuals have an increased risk of CVE with and without
proven risk factors. The risk is associated with IDU, low CD4 count and exposure to
abacavir, but not with HAART. An association with family-related risk factors seems
vague except for parents of IDUs.
ß 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
AIDS 2011, 25:000000
Keywords: abacavi r, AIDS, Cerebrovascular disease, HAART, HIV,
immunodeficiency, stroke
Introduction
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,
highly active antiretroviral therapy (HAART) and
abacavir [14].
a
Department of Infectious Diseases, Odense University Hospital, Odense, Denmark,
b
Department of Infectious Diseases,
Copenhagen University Hospital, Rigshospitalet, Denmark,
c
Department of Neurology, Copenhagen University Hospital,
Bispebjerg, Copenhagen, Denmark, and
d
Department of Infectious Diseases, Copenhagen University Hospital, Hvidovre
Hospital, Denmark.
Correspondence to Line Dahlerup Rasmussen, MD, PhD-student, Department of Infectious Diseases, Odense University Hospital
Sdr. Boulevard 29, 5000 Odense C, Denmark.
Tel: +45 65411321; fax: +45 66117418; e-mail: linedahlerup@hotmail.com
Received: 10 December 2010; revised: 23 May 2011; accepted: 27 May 2011.
DOI:10.1097/QAD.0b013e3283493fb0
ISSN 0269-9370 Q 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
1
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Less attention has been paid to the possibly increased risk
of cerebrovascular disease. Previous studies, which are
primarily from the pre-HAARTera, are inconclusive but
favour an increased risk of stroke in HIV-infected
individuals [423].
We conducted a Danish nationwide, population-based
cohort study to examine the risk of cerebrovascular events
(CVE) in HIV-infected individuals compared to the
general population. As the underlying mechanism for a
possibly increased risk of cerebrovascular disease is
unclear, we further examined the impact of 1) proven
risk factors, 2) risk factors often associated with HIV
infection (e.g. injection drug abuse (IDU)), 3) immu-
nodeficiency, 4) use of antiretroviral drugs, and 5) the
HIV infection per se on risk of CVE. We further
examined the risk of CVE in parents of HIV-infected
individuals to evaluate the impact of family-related
risk factors.
Methode
Setting
As of 1 January 2010 Denmark had a population of
5.5 million [24], 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 centres, 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 < 300 cells/ml, and, until 2001, plasma HIV-
RNA >100,000 copies/ml.
Data sources
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 (DHCS)
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 (DCRS)
DCRS, established in 1968, stores information on vital
status, residency, and immigration/emigration for all
Danish residents [27].
The danish national hospital registry (DNHR)
DNHR, established in 1977, records data on all
admissions to non-psychiatric hospitals in Denmark,
classified according to the Inter national Classification of
Diseases [8
th
revision (ICD-8) until Dec 31 1993 and 10
th
revision (ICD-10) thereafter] [28].
The danish cancer register (DCR)
DCR, established in 1942, records all cancer diagnoses
according to a modified edition of the International
Classification of Diseases [7
th
revision (ICD-7) since 1943
and according to the 10
th
revision (ICD-10) and ICD-O
(for oncology) since 1994 (The cancer diagnoses from
19781994 was later converted to ICD-10 and ICD-O)]
[29].
Study populations
HIV cohort
We identified all Danish HIV-infected individuals older
than 16 years at date of HIV diagnosis from DHCS. The
index date was defined as the date of HIV diagnosis, date
of arrival to Denmark or January 1 1995 whichever was
more recent. Individuals diagnosed with cerebrovascular
disease or cerebral comorbidity (defined as CNS tumour,
cancer, lymphoma, metastasis, non-HIV-associated
cerebral infections, HIV-associated cerebral opportunistic
infections and AIDS dementia) prior to index date, were
excluded (Appendix I, Figure 1).
General population comparison cohort
A comparison cohort consisting of 9 age- and gender
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.
Parent cohorts
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 Danish
National Hospital Registry (January 1 1977), date of
arrival to Denmark or date of birth of the offspring which
ever was more recent.
Outcome measures
The primary outcome was time to first ever CVE defined
as the first date an individual was registered with a
diagnosis of non-traumatic subarachnoid haemorrhage,
intracerebral haemorrhage cerebral infarction, unspeci-
fied stroke or transient ischemic attack in DNHR.
Diagnoses obtained from emergency rooms but not
confirmed subsequently were not included. The diag-
nosis stroke sequels were included as CVE if no prior
CVE diagnosis was registered and categorized as
unspecified stroke.
2 AIDS 2011, Vol 00 No 00
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(The diagnoses and ICD8/ICD10 codes are provided in
appendix I)
Outcomes (CVE) were classified as ‘‘CVE with proven
risk factor’’ if at least one risk factor, as defined in
appendix I, 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) [3041]. The remaining outcomes
were classified as ‘‘CVE with no proven risk factors’’.
Statistical analysis
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 cerebro-
vascular disease as well as cerebral comorbidity and death
as a competing risk. We used Cox regression analyses to
calculate incidence rate ratios (IRR) as estimates of the
relative risk and 95% confidence intervals (CI) 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 gender) and adjusted for country
of birth (Denmark vs. outside Denmark). The estimated
IRRs for the parents were adjusted for age at index date
(categorized in five age intervals: 030, 3145, 4560,
6075 and 75 þ years), calendar year (categorized in five
time intervals (index date: 19771985, 19861990,
19911995, 19962000 and 20012010)) and country
of birth.
Due to the different characteristics and risk profiles of
individuals with and without IDU (IDU/non-IDU) all
analysis were stratified on the basis of IDU.
Because the accuracy of coding may differ in the
discharge diagnoses, we performed a robustness analysis
excluding 1) individuals registered with stroke sequels as
first Aofovir 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 time periods: 1)
time from index date until first CD4 count <¼ 200cells/
ml occurring before initiation of HAART, 2) time from
first CD4 count <¼ 200cells/ml until initiation of
HAART, 3) time from initiation of HAART until first
occurrence of a CD4 count > 200cells/ml and 4) time on
HAART with a CD4 count > 200 cells/ml until end of
observation. To specifically estimate the impact of
treatment with specific antiretroviral drugs, we per-
formed 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 > 200 cells/ml after start of HAARTwas 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 in four age intervals: 1630,
3145, 4660, and 61 þ years), gender, calendar year
(categorized in five time intervals (index date: 1995
1997, 19982000, 20012003, 20042006 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 2008411781).
Results
We identified 5,031 HIV-infected individuals of whom
536 (10.7%) were IDUs and 45,279 comparison cohort
individuals. The median age at index date was almost
identical in the non-IDU and IDU HIV-infected
individuals (36.9 years vs. 35.6 years), but more non-
IDU HIV-infected individuals than IDU HIV-infected
individuals were older than 50 years at index date (15.3%/
1.9%). Additional characteristics of HIV-infected indi-
viduals and the two matched comparison cohorts are
provided in Table 1. The registered risk factors are
provided in appendix II, Table 1.
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 index date are
shown in Fig. 1.
As illustrated in Table 2, we found a higher risk of total
CVE in the HIV-infected population compared to the
comparison cohorts. The risk was substantially higher in
the IDU than the non-IDU HIV-infected population
(adjusted IRR 3.94; 95% CI: 2.167.16 versus adjusted
IRR 1.60; 95% CI: 1.301.95). The increased risk in the
non-IDU HIV-infected individuals was due to a higher
risk of CVE with (adjusted IRR 1.55; 95% CI: 1.19
2.03) and without proven risk factors (adjusted IRR 1.65;
95% CI: 1.212.26). Furthermore, the increased risk of
CVE was mainly due to a statistically significant higher
HIV and risk of cerebrovascular events Rasmussen et al. 3
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risk of cerebral infarction, unspecified stroke and transient
ischemic attack. In the IDU HIV-infected population risk
of subarachnoid haemorrhage, intracerebral haemor-
rhage, cerebral infarction and unspecified stroke were all
substantially increased compared to the comparison
cohort, however only intracerebral haemorrhage and
unspecified stroke were statistically significant. The
increased risk of CVE was seen in both genders 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 CVE in
non-IDU HIV-infected individuals with a CD4 count
<¼ 200 cells/ml who had not initiated HAART (adjusted
IRR 2.26; 95% CI: 1.054.86) (Table 3). After initiation
of HAART the risk was identical to that of the pre-
HAART period with a CD4 count > 200 cells/ml. In the
period with low CD4 count before start of HAART, we
also observed a higher risk of CVE with and without
proven risk factors although this was statistically insig-
nificant (Table 3). In individuals who had initiated
HAART, risk of CVE was increased after first exposure to
abacavir (adjusted IRR 1.66; 95% CI: 1.032.68). 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 PI, indinavir,
didanosin or tenofovir did not change the estimated risk
of CVE (Table 3).
The performed robustness analysis, in which 1)
individuals registered with stroke sequels as first diagnosis
of CVE and 2) individuals registered with hepatitis C
infection were excluded, showed no major changes in
CVE risk estimates.
We identified 2,509 mothers and 2,289 fathers of HIV-
infected individuals as well as 21,982 mothers and 21,009
fathers of comparison cohort individuals (Appendix II,
4 AIDS 2011, Vol 00 No 00
Table 1. Characteristics of HIV-infected individuals and comparison cohort individuals.
Non-IDU HIV-infected
individuals (N ¼ 4,495)
Comparison cohort
individuals (N ¼ 40,455)
IDU HIV-infected
individuals (N ¼ 536)
Comparison cohort
individuals (N ¼ 4,824)
Age at index date, median years (IQR) 36.9 (30.645.1) 36.9 (30.645.1) 35.6 (31.040.7) 35.6 (31.040.7)
Age above 50 years, N (%) 687 (15.3) 6,183 (15.3) 10 (1.9) 90 (1.9)
Male gender, N (%) 3,475 (77.3) 31,275 (77.3) 346 (64.6) 3,114 (64.6)
Caucasian race, N (%) 3,519 (78.3) 511 (95.3)
Born in Denmark, N (%) 3,140 (69.9) 39,810 (98.4) 464 (86.6) 4,746 (98.4)
Infection mode:
MSM, N (%) 2,278 (50.7)
Heterosexual contact, N (%) 1,831 (40.7)
IDU, N (%) 536 (100)
Other/unknown, N (%) 386 (8.6)
Hepatitis C positive, N (%) 340 (7.6) 471 (87.9)
No of patients diagnosed with HIV-infection
prior to 1995, N (%)
1,569 (34.9) 305 (56.9)
No of patients with AIDS diagnosed prior
to index date, N (%)
375 (8.3) 36 (6.7)
Median CD4 cell count at index date,
cells/mL (IQR)
286 (117480) 341 (184550)
Median VL at index date, copies/ml (IQR) 45,246 (5,863190,140) 34,300 (8,72086,300)
No. of patients initiating HAART prior to
or in the observation period, N (%)
3,463 (77.0) 364 (67.9)
No. of patients initiating Abacavir prior to
or in the observation period, N (%)
2,075 (46.2) 190 (35.4)
Duration of follow-up, person-years 36,161 410,666 4,225 59,582
Duration of follow-up, median-years (IQR) 7.6 (3.113.4) 10.8 (5.715.6) 7.6 (3.112.6) 15.6 (9.115.6)
Death during follow-up, N (%) 681 (15.2) 1,692 (4.2) 239 (44.6) 141 (2.9)
Emigration during follow-up, N (%) 184 (4.1) 525 (1.3) 14 (2.6) 77 (1.6)
Lost to follow-up, N (%) 19 (0.4) 11 (0.0) 1 (0.2) 2 (0.0)
First hospitalisation for cerebrovascular
events (CVE) after index date:
Total no. of CVE, N (%) 123 (2.7) 998 (2.5) 17 (3.2) 84 (1.7)
Subarachnoid haemorrhage, N (%) 9 (0.2) 54 (0.1) 2 (0.4) 8 (0.2)
Intracerebral haemorrhage, N (%) 8 (0.2) 80 (0.2) 5 (0.9) 2 (0.0)
Cerebral infarction, N (%) 35 (0.8) 263 (0.7) 3 (0.6) 27 (0.6)
Unspecified stoke, N (%) 40 (0.9) 354 (0.9) 6 (1.1) 28 (0.6)
Transient ischemic attack, N (%) 31 (0.7) 247 (0.6) 1 (0.2) 19 (0.4)
CVE with proven risk factors, N (%) 69 (56.1) 592 (59.3) 17 (100) 51 (60.7)
CVE without proven risk factors, N (%) 54 (43.9) 406 (40.7) 33 (39.3)
Age at CVE, median age (IQR) 55.3 (43.262.0) 56.0 (48.463.4) 43.6 (40.848.8) 51.8 (46.456.0)
Initiated HAART prior to CVE diagnosis, N (%) 88 (71.5) 12 (70.6)
Initiated Abacavir prior to CVE diagnosis, N (%) 54 (43.9) 7 (41.2)
Median CD4 cell count when diagnosed
with CVE, cells/mL (IQR)
442 (260666) 269 (91473)
Median VL when diagnosed with CVE, copies/ml (IQR) 40 (397,375) 752 (2942,685)
Index date: Date of diagnosis of HIV-infection (if diagnosed before 1995, index date was January 1 1995; if diagnosed before arrival to Denmark,
index date was date of arrival to Denmark). IDU, Intravenous drug user; IQR, Interquartile range; MSM, Men who have sex with men.
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Table 2). 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 (Appendix II, Table 2). The
parents of the HIV-infected individuals had a slightly
increased risk of CVE, which was almost exclusively
driven by a substantially increased risk seen in the parents
of offspring reporting IDU as route of HIV transmission
(Table 4).
HIV and risk of cerebrovascular events Rasmussen et al. 5
Fig. 1. Cumulative incidence for first cerebrovascular event (CVE) in non-IDU and IDU HIV-infected individuals and
comparison cohort individuals.
[Non-IDU HIV-infected individuals: 5 years risk: 1.28 (95%CI: 0.961.67); 10 years risk:
2.68 (95%CI: 2.163.30). Comparison cohort individuals: 5 years risk: 0.79 (95%CI: 0.710.89); 10 years risk: 2.07 (95%CI:
1.922.24). IDU HIV-infected individuals: 5 years risk: 1.43 (95%CI: 0.642.82); 10 years risk: 3.08 (95%CI: 1.764.98).
Comparison cohort individuals: 5 years risk: 0.26 (95%CI: 0.140.44); 10 years risk: 1.00 (95%CI: 0.731.35)]. 95% CI:
Confidence Interval.
Table 2. Relative risk of cerebrovascular events (CVE) in HIV-infected individuals.
IRR (95% CI)
Non-IDU HIV-infected individuals versus
Comparison cohort individu als
IDU HIV-infected individuals versus
Comparison cohort individuals
Outcome: Unadjusted Adjusted
a
Unadjusted Adjusted
a
Total cerebrovascular events (CVE) 1.60 (1.321.94) 1.60 (1.301.95) 3.70 (2.106.52) 3.94 (2.167.16)
Subarachnoid haemorrhage 1.85 (0.903.81) 1.72 (0.803.69) 4.41 (0.8124.09) 4.41 (0.8124.09)
Intracerebral haemorrhage 1.43 (0.683.03) 1.47 (0.673.20) 22.13 (4.29114.11) 35.62 (4.04314.17)
Cerebral infarction 1.76 (1.222.53) 1.63 (1.102.41) 2.11 (0.607.48) 1.90 (0.507.19)
Unspecified stroke 1.48 (1.062.07) 1.54 (1.082.18) 4.02 (1.5310.58) 4.62 (1.6313.11)
Transient ischemic attack 1.58 (1.082.33) 1.64 (1.102.44) 0.99 (0.137.80) 1.19 (0.159.67)
CVE with proven risk factors 1.54 (1.191.99) 1.55 (1.192.03)
CVE without proven risk factors 1.68 (1.252.25) 1.65 (1.212.26)
Stratified on gender
Male 1.63 (1.332.00) 1.59 (1.291.97) 3.61 (1.896.90) 3.83 (1.897.77)
Female 1.37 (0.762.46) 1.69 (0.893.23) 4.00 (1.2312.99) 3.82 (1.1812.41)
Stratified on route of HIV transmission
MSM 1.31 (1.001.73) 1.31 (0.991.74)
Heterosexual 1.90 (1.412.56) 1.95 (1.402.70)
IRR, Incidence rate ratio. 95% CI: Confidence Interval
a
Adjusted for country of birth (Denmark versus outside Denmark) and stratified according to the initial match criteria (age and gender).
MSM: men who have sex with men.
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Discussion
We found a higher risk of CVE in HIV-infected
individuals than in the general population comparison
cohorts. The risk was higher for both CVE with
and without proven risk factors. In the non-IDU HIV-
infected population immunodeficiency (CD4 count
<¼ 200 cells/ml) before start of HAART and treatment
with abacavir almost doubled the risk of CVE, while PI,
indinavir, didanosine, tenofovir or HAART in general
had no impact on the risk of CVE. Finally, the risk of
CVE was only increased in the parents of HIV-infected
individuals who reported IDU as route of transmission.
A main strength of our study is its nationwide population-
based design with long and complete follow-up. The
6 AIDS 2011, Vol 00 No 00
Table 3. Impact of CD4 cell count, HAART and abacavir on risk of cerebrovascular events (CVE) in HIV-infected individuals with no intravenous
drug abuse (Non-IDU HIV).
IRR (95%CI)
Non-IDU HIV-infected individu als
Time-updated variables: Unadjusted Adjusted
a
Total CVE
CD4 > 200 cells/ml and non-HAART 1 (ref)’’ 1 (ref)’’
Cd4 < 200 cells/ml and non-HAART 2.28 (1.094.76) 2.26 (1.054.86)
Cd4 < 200 cells/ml and HAART 1.51 (0.653.55) 1.17 (0.502.75)
CD4 > 200 cells/ml and HAART 1.00 (0.591.69) 0.80 (0.471.36)
On HAART before first exposure to protease inhibitors 1 (ref.)’’ 1 (ref.)’’
On HAART after first exposure to protease inhibitors 0.93 (0.531.62) 0.88 (0.461.68)
On HAART before first exposure to indinavir 1 (ref)’’ 1 (ref)’’
On HAART after first exposure to indinavir 1.08 (0.701.68) 0.98 (0.611.58)
On HAART before first exposure to tenofovir 1 (ref.)’’ 1 (ref.)’’
On HAART after first exposure to tenofovir 0.94 (0.551.60) 1.01 (0.581.76)
On HAART before first exposure to didanosin 1 (ref.)’’ 1 (ref)’’
On HAART after first exposure to didanosin 0.89 (0.551.44) 0.75 (0.451.24)
On HAART before first exposure to abacavir 1 (ref.)’’ 1 (ref.)’’
On HAART after first exposure to abacavir 1.69 (1.072.68) 1.66 (1.032.68)
On HAART after first exposure until first cessation of abacavir 1.61 (0.982.66) 1.58 (0.942.65)
On HAART after first cessation of abacavir 1.87 (1.043.37) 1.83 (1.003.34)
CVE with proven risk factors
CD4 > 200 cells/ml and non-HAART 1 (ref)’’ 1 (ref)’’
CD4 < 200 cells/ml and non-HAART 2.37 (0.787.21) 2.26 (0.727.14)
CD4 < 200 cells/ml and HAART 0.54 (0.074.26) 0.39 (0.053.09)
CD4 > 200 cells/ml and HAART 1.77 (0.813.88) 1.34 (0.612.94)
On HAART before first exposure to abacavir 1 (ref.)’’ 1 (ref.)’’
On HAARTafter first exposure to abacavir 1.88 (1.033.44) 1.78 (0.953.34)
On HAART after first exposure until first cessation of abacavir 1.85 (0.973.52) 1.72 (0.883.36)
On HAART after first cessation of abacavir 1.96 (0.904.24) 1.93 (0.874.25)
CVE with no proven risk factors
CD4 > 200 cells/ml and non-HAART 1 (ref)’’ 1 (ref)’’
CD4 < 200 cells/ml and non-HAART 2.22 (0.835.97) 2.29 (0.826.39)
CD4 < 200 cells/ml and HAART 2.16 (0.825.71) 1.79 (0.674.76)
CD4 > 200 cells/ml and HAART 0.55 (0.261.13) 0.46 (0.220.96)
On HAART before first exposure to abacavir 1 (ref.)’’ 1 (ref.)’’
On HAARTafter first exposure to abacavir 1.45 (0.712.98) 1.47 (0.703.10)
On HAART after first exposure until first cessation of abacavir 1.31 (0.592.91) 1.38 (0.613.14)
On HAART after first cessation of abacavir 1.76 (0.714.40) 1.64 (0.654.17)
IRR, Incidence rate ratio 95% CI: Confidence Interval ‘‘ Ref: Reference time
a
Adjusted for age, gender, calendar year and country of birth. Analyses on protease inhibitors, tenofovir and abacavir were also adjusted for CD4
cell count.
Table 4. Relative risk of cerebrovascular events (CVE) in parents of HIV-infected individuals.
IRR (95% CI)
Mothers Fathers
Outcome: Unadjusted Adjusted Unadjusted Adjusted
Total cerebrovascular events (CVE) 1.16 (1.021.33) 1.15 (1.011.32) 1.09 (0.971.23) 1.05 (0.931.18)
CVE with proven risk factors 1.19 (1.001.42) 1.10 (0.921.31) 1.18 (1.031.37) 1.13 (0.981.30)
CVE without proven risk factors 1.12 (0.911.38) 1.10 (0.901.36) 0.95 (0.781.16) 0.92 (0.751.12)
Stratified on transmission-group of the offspring:
MSM: 1.10 (0.911.31) 1.06 (0.881.27) 1.13 (0.961.32) 1.04 (0.891.22)
Heterosexually: 0.98 (0.731.32) 0.99 (0.741.33) 1.12 (0.901.41) 1.09 (0.871.36)
IDU 1.85 (1.382.49) 2.06 (1.532.78) 1.20 (0.881.62) 1.25 (0.921.70)
IRR, Incidence rate ratio. 95% CI: Confidence Interval MAdjusted for age, calendar year and country of birth. MSM, men who have sex with men
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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 co-morbidity were obtained from the same data
sources, thereby minimising the impact of misclassifi-
cation 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 [42]. As the Danish National Hospital registry was
not initiated until January 1977, some parents might have
had a CVE prior to study inclusion, why some parents
might have stroke sequels categorised 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. Since
we used the same source of data to ascertain CVE for all
study subjects, we presume that any potential misclassi-
fication was non-differential and therefore did not
influence our estimates of relative risk. Low socio-
economic status is associated with a higher risk of stroke
which is partly explained by a greater burden of classical
risk factors [44]. 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 CVE in the parents of the two groups,
this was indirectly accounted for. We did not have
information on non-antiretroviral medication or smok-
ing status of which the latter is a highly important risk
factor. This could invalidate the potential causal
association of CVE and HIV. However, COPD, excessive
alcohol consumption and other conventional risk factors
were included in the analyses, many of which are highly
associated with smoking [45]. Abuse of cocaine,
amphetamine, ecstasy and related drugs are important
risk factors for stroke in young adults [41]. 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 non-
IDU drug abusers might have been lost and as the
frequency of the drug abuse and the effect of being clean
or in a treatment program with e.g. 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- and gender-matched HIV-
negative control population [11]. In contrast, Engstrøm
et al. conducted a retrospective study of 1600 AIDS
patients with an age 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 between 35 and 45 years [6]. 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: 4.922.0) compared to a non-
AIDS population from the same region [17]. HIV-
infected individuals however, who did not fulfil 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 CVE. 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 cerebro-
vascular endpoints. We found a relative risk of CVE 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 CVE and the
link between HIV and IDU, most risk estimates in other
studies are biased by this confounder [510,15,16,18
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, intra-
cranial 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 conventionally risk
factors [48]. .However, in our study an uneven
distribution of risk factors could not solely explain the
HIV and risk of cerebrovascular events Rasmussen et al. 7
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QAD 202675
increased risk of CVE, as both the relative risk of CVE
with and without proven risk factors were increased.
Smoking is a strong predictor of CVE [32,45]. In a meta-
analysis by Shinton et al. smoking increased the risk of
stroke almost 3 fold in a population less than 55 years [45].
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 CVE
we observed.
In accordance with our results some studies have observed
an increased risk of stroke in HIV-infected individuals
with low CD4 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 HAARTon 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 twofold increased risk
of stroke after start of HAART which contrasts the
observations from an American study which found no
correlation [23], and a Spanish study which observed a
protective effect of HAART [22]. In our analyses
HAART did not influence the risk of CVE.
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 [4]. We observed a
higher risk of CVE in HIV-infected individuals on
abacavir irrespective of low CD4 cell count. PI,
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 CVE had a
higher chance of being treated with abacavir (channelling
bias) [3,50].
We registered an increased risk of CVE in parents of IDU
HIV-infected individuals. This association suggests that
family-related risk factors are a complex combination of
shared socio-economic factors, a possible tendency to
‘risk taking behaviour’ and a genetic component
[51,52].
We conclude that HIV infection is associated with an
increased risk of CVE 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 increased risk of CVE in HIV-
infected individuals.
Acknowledgments
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.
Author Contributions: Conception and design: Rasmus-
sen LD, Engsig FN, Christensen H, Obel N.
Analysis and interpretation of the data: Rasmussen LD,
Engsig FN, Obel N.
Drafting of the article: Rasmussen LD.
Critical revision of the article for important intellectual content:
Rasmussen LD, Ensig FN, Pedersen C, Gerstoft J,
Kronborg G, Christensen H, Obel N.
Final approval of the article: Rasmussen LD, Engsig FN,
Pedersen C, Gerstoft J, Kronborg G, Christensen H,
Obel N.
Provision of study materials or patients: Pedersen C,
Kronborg G, Gerstoft J, Obel N.
Statistical expertise: Rasmussen LD, Engsig FN, Obel N.
Obtaining of funding: Obel N.
Administrative, technical, or logistic support: Rasmussen
LD, Obel N.
Collection and assembly of data: Pedersen C, Kronborg G,
Gerstoft J, Obel N.
Centers in the Danish HIV Cohort Study: Departments of
Infectious Diseases at Copenhagen University Hospitals,
Rigshospitalet (J Gerstoft, N Obel) and Hvidovre (G
Kronborg), Odense University Hospital (C Pedersen),
Aarhus University Hospitals, Skejby (CS Larsen) and
Aalborg (G Pedersen), Herning Hospital (AL Laursen),
Helsingør Hospital (L Nielsen) and Kolding Hospital (J
Jensen).
Conflicts of interest: N Obel ha s received research
funding from Roche, Bristol-Myers Squibb, Merck
Sharp & Dohme, GlaxoSmithKline, Ab bott, Boehringer
Ingelheim, Janssen-Cilag an d Swedish Orphan Drugs.
FN Engsig has received research funding from Merck
Sharp & Dohme.
8
AIDS 2011, Vol 00 No 00
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CE: ; QAD/202675; Total nos of Pages: 13;
QAD 202675
C. Pedersen has received research funding from
Abbott, Roche, Bristol-Myers Squibb, Merck Sharp &
Dohme, GlaxoSmithKline, Swedish Orphan Drugs and
Boehringer Ingelheim.
J Gerstoft has received research funding from Abbott,
Roche, Bristol-Myers Squibb, Mecrk Sharp & Dohme,
Pharmasia, GlaxoSmithKline, Swedish Orphan Drugs
and Boehringer Ingelheim.
H Chr istensen has received honorariums and sponsor-
ships from Boehringer-Ingelheim, Abbott/Solvay, Med-
tronics, Sanofi-Avensis and Atrietech.
LD Rasmussen and G Kronborg report no conflicts of
interest.
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Appendix I
World Health Organization International Disease Classifi-
cation (ICD) Codes, ICD-8 and ICD-10 used for the
present classification.
CEREBROVASCULAR DISEASE:
SUBARACHNOID HAEMORRHAGE:
ICD8: 43000-43099
ICD 10: I 60.060.9
INTRACEREBRAL HAEMORRHAGE:
ICD8: 43100, 4310843190, 43198-43199
ICD 10: I61.061.9
CEREBRAL INFARCTION:
ICD8: 4320043299, 4330943399, 43409-43499
ICD10: I63.063.9
UNSPECIFIED STROKE:
ICD 8: 43600-43699
ICD10: I64.9
TRANSIENT ISCHEMIC ATTACK:
ICD8: 43509-43599
ICD 10: G45.045.9
OTHER CEREBROVASCULAR DISEASES:
ICD8: 43101, 43191, 4370943799, 43809-43899
ICD10: I62.062.9, I65.065.9, I66.066.9, I67.067.9,
I68.068.8, G46.046.8
STROKE SEQUELS:
ICD 10: I69.069.8)
Cases registered with two or more subgroups of
cerebrovascular disease on the same date were categorized
with the specific diagnosis (subarachnoid haemorrhage,
intracerebral haemorrhage, cerebral infarction, unspeci-
fied stroke and transient ischaemic attack) in preference
for the unspecific diagnoses (other cerebral vascular
disease or stroke sequels) and diagnoses belonging to the
longest admission were preferred. Next the primary
diagnosis (A-diagnosis) was chosen over the secondary
diagnosis (B-diagnosis). Cases in which this method did
not identify a specific diagnosis were categorized as
unspecified stroke.
CEREBRAL COMORBIDITY:
CEREBRAL INFECTIONS INCLUDING OPPORTU-
NISTIC DISEASES:
ICD8: 013.00013.99, 019.19, 036.09, 040.00040.09,
045.09045.99, 046.99, 052.01, 053.02, 054.03, 055.01,
056.01,
062.09062.99, 063.09063.99, 064.99, 065.99, 066.00
066.09, 071.99, 072.02, 075.01, 090.49, 094.00094.99,
130.09130.99, 320.09320.99, 322.00322.09, 323.00
323.01, 323.03323.09, 324.00324.09
10
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ICD10: A06.6, A17.0 17.1, A32.1, A39.0, A52.152.3,
A81.089.9,
B00.300.4, B01.001.1, B02.002.1, B05.005.1,
B06.0, B22.0, B25.3,B26.126.2, B45.1, B58.2,
B90.0, B94.1
G00.006.1, G07.9, G09.9
Co-morbidity diagnoses from The Danish HIV
Cohorte Study: Toxoplasmosis, Cryptococcus, Lym-
phoma further sub classified to cerebral lymphoma),
PML, aidsdemensia, CMV chorioretinitis
CEREBRAL CANCER/TUMOR/LYMPHOMA/
METASTASIS:
ICD7: 931937, 19201925, 19301933, 1954, 2930
2932, 49224923, 49304937,6920, 69306932, 7930
7932,
89208923, 89308932, 8935, 8954
ICD10: C69.072.9 C75.175.3, C79.3, D32.033.9,
D35.235.4, D42.043.9, D44.344.5
RISK FACTOR S:
Outcomes (CVE) were classified as ‘‘CVE with proven risk
factor’ if at least one of the following risk factors 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).: diabetes,
hypertension, atrial fibrillation/flutter, hyperlipidemia, myo-
cardial infarction, heart failure, patentforamenovale, sicksinus
syndrome, cardiomyopathy, mitral and/or aortic valve disease,
peripheral arteriosclerosis, carotid artery stenosis, obesity,
excessive alcohol intake, increased- or impaired coagulation,
chronickidneydisease,chronicobstructivepulmonarydisease,
infectious endocarditis, cancer and IDU if registered as routeof
HIV transmission in the HIV patient.
ATIAL FLUTTER/FIBRILATION:
ICD 8: 427.93, 427.94
ICD 10: I48.9
HYPERTENSION:
ICD 8: 400.09404.99, 410.09, 411.09, 412.09, 413.09,
414.09, 435.09, 437.00- 437.09, 438.09
ICD 10: I10.915.9
MYOCARDIAL INFARCTION:
ICD 8: 410.9, 410.99
ICD 10: I21.022.9
HEART FAILURE:
ICD 8: 425.99, 427.09427.19, 427.99, 428.99
ICD 10: I50.050.9
CARDIOMYOPATHY:
ICD8: 746.40746.49
ICD10: I 42.043.8
SICK SINUS SYNDROME:
ICD 10: I49.5
PATENT FORAMEN OVALE:
ICD 8: 746.40746.49
ICD 10: Q21.1
MITRAL AND AORTIC VALVE DISEASE:
ICD 8: 394.00396.99
ICD 10: I05.006.9, I08.008.9, I34.035.9
DIABETES:
ICD 8: 249.00250.09
ICD 10: E10.014.9
EXCESSIVE ALCOHOL CONSUMPTION:
ICD 8: 291.09291.99, 303.09303.90
ICD 10: F10.110.9
PERIFERAL ATHEROSCLEROSIS:
ICD 8: 440.20440.30
ICD 10: I70.2
CAROTID ARTERY STENOSIS:
ICD 8: 432.90
ICD 10: I65.2
HYPERLIPIDEMIA:
ICD8: 279.00
HIV and risk of cerebrovascular events Rasmussen et al. 11
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CE: ; QAD/202675; Total nos of Pages: 13;
QAD 202675
ICD 10: E78.078.5
OBESITY:
ICD8: 277.99
ICD 10: E66.066.9
CHRONICAL KIDNEY DISEASE:
ICD 8: 581.00582.09
ICD 10: N03.004.9, N07.007.9, N18.019.9
CHRONICAL OBSTRUCTIVE PULMONARY DIS-
EASE:
ICD8: 491.00492.00
ICD 10: J44.0-J44.9
INFECTIOUS ENDOCARDITIS:
ICD8: 421.00421.99
ICD 10: I33.033.9
COAGULATION DISORDERS:
ICD8: 208.99, 282.50, 286.09286.99, 287.09287.99
ICD10: D45.9, D47.3, D57.057.8, D65.969.9, D75.2
MALIGNANCIES:
ICD 7: 140.0204.4
ICD 10: C0.00C97.9, B21.021.9
12
AIDS 2011, Vol 00 No 00
Appendix II
Fig. 1 Summary of the study design.
Page 12
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CE: ; QAD/202675; Total nos of Pages: 13;
QAD 202675
HIV and risk of cerebrovascular events Rasmussen et al. 13
Table 1 Proven risk factors diagnosed in HIV-infected individuals and comparison cohort individuals.
Non-IDU HIV-infected
individuals
Comparison cohort
individuals
IDU HIV-infected
Individuals
Comparison
cohort individuals
(n ¼ 4,495) (n ¼ 40,455) (n ¼ 536) (n ¼ 4,824)
Proven risk factors registered prior to and
up to 30 days (90 days for malignancy)
after the end of the observation period:
Myocardial infarction, N (%) 123 (2.7) 749 (1.9) 8 (1.5) 64 (1.3)
Heart failure, N (%) 83 (1.8) 513 (1.3) 17 (3.2) 33 (0.7)
Patent foramen ovale, N (%) 3 (0.1) 3 2 (0.1) 1 (0.2) 1 (0.0)
Sick sinus syndrome, N (%) 3 (0.1) 35 (0.1) 0 (0) 1 (0)
Cardiomyopathy, N (%) 28 (0.6) 160 (0.4) 3 (0.6) 16 (0.3)
Mitral and/or aortic valve disease, N (%) 27 (0.6) 228 (0.6) 9 (1.7) 21 (0.4)
Atrial flutter/Atrial fibrillation, N (%) 62 (1.4) 711 (1.8) 2 (0.4) 55 (1.1)
Carotid artery stenosis, N (%) 9 (0.2) 38 (0.1) 0 (0) 3 (0.1)
Arterial hypertension, N (%) 219 (4.9) 2,418 (6.0) 19 (3.5) 250 (5.2)
Hyperlipidemia, N (%) 122 (2.7) 1,148 (2.8) 2 (0.4) 133 (2.8)
Obesity, N (%) 54 (1.2) 1,211 (3.0) 4 (0.7) 168 (3.5)
Excessive alcohol consumption, N (%) 275 (6.1) 1,483 (3.7) 128 (23.9) 176 (3.6)
Diabetes, N (%) 147 (3.3) 1,445 (3.6) 16 (3.0) 137 (2.7)
Peripheral arteriosclerosis, N (%) 39 (0.9) 273 (0.7) 9 (1.7) 14 (0.3)
Chronic kidney disease, N (%) 68 (1.5) 244 (0.6) 12 (2.2) 21 (0.4)
Chronic obstructive pulmonary disease, N (%) 109 (2.4) 682 (1.7) 48 (9.0) 56 (1.2)
Thrombophila and other coagulation
disorders including thrombocytopenia, N (%)
151 (3.4) 282 (0.7) 27 (5.0) 43 (0.9)
Endocarditis, N (%) 8 (0.2) 38 (0.1) 45 (8.4) 4 (0.1)
Malignancy, N (%) 558 (12.4) 1,837 (4.5) 24 (4.5) 183 (3.8)
Table 2 Characteristics of parents of HIV-infected individuals and comparison cohort individuals.
Mothers of HIV positive
individuals (N ¼ 2,509)
Fathers of Comparison
cohort individuals (N ¼ 21,982)
HIV positive individuals
(N ¼ 2,289)
Comparison cohort
individuals (N ¼ 21,009)
Median age at index date, median years (IQR) 38.0 (31.844.7) 37.5 (31.643.9) 41.0 (34.148.5) 40.3 (33.847.5)
Number in whom observation time started
after 1. January 1977 (%)
296 (11.8) 2,343 (10.7) 282 (12.3) 2,417 (11.5)
Born in Denmark, N (%) 2,354 (93.8) 21,318 (97.0) 2,189 (95.6) 20,553 (97.8)
Duration of follow up:
Duration of follow-up, pers on years 70,430 647,168 58,412 561,407
Duration of follow-up, median years (IQR) 33.6 (24.433.6) 33.6 (27.833.6) 29.5 (19.233.6) 31.6 (21.633.6)
Death, N (%) 641 (25.5) 4,380 (19.9) 809 (35.3) 6,634 (31.6)
Emigration, N (%) 29 (1.2) 114 (0.5) 33 (1.4) 151 (0.7)
Lost to follow, N (%) 2 (0.1) 0 (0) 3 (0.1) 4 (0)
First hospitalisation for cerebrovascular
event (CVE) after index date:
Total no. of CVE, N (%) 245 (9.8) 2,003 (9.1) 316 (13.8) 2,851 (13.6)
Subarachnoid haemorrhage, N (%) 19 (0.8) 153 (0.7) 13 (0.6) 77 (0.4)
Intracerebral haemorrhage, N (%) 24 (1.0) 151 (0.7) 31 (1.4) 186 (0.9)
Cerebral infarction, N (%) 63 (2.5) 501 (2.3) 85 (3.7) 746 (3.6)
Unspecified stoke, N (%) 92 (3.7) 734 (3.3) 120 (5.2) 1,178 (5.6)
Transient ischemic attack, N (%) 47 (1.9) 464 (2.1) 67 (2.9) 664 (3.2)
CVE with proven risk factors, N (%) 147 (60.0) 1,179 (58.9) 208 (65.8) 1,741 (61.1)
CVE without proven risk factors, N (%) 98 (40.0) 824 (41.1) 108 (34.2) 1,110 (38.9)
Median age at CVE, median years (IQR) 65.5 (59.373.6) 66.9 (59.173.8) 65.9 (60.372.8) 66.8 (60.373.5)
Risk of CVE after 5 years, % (95%CI): 0.32 (0.150.61) 0.28 (0.220.36) 0.75 (0.451.17) 0.47 (0.380.57)
Risk of CVE after 10 years, % (95%CI): 0.68 (0.421.07) 0.68 (0.570.79) 1.68 (1.212.27) 1.38 (1.231.54)
95% CI: Confidence Interval.
Page 13
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    • "This study found that the incidence rates of all-cause, ischemic, and hemorrhagic strokes were 2.08, 1.54, and 0.54 per 1,000 py among PLWHA, respectively. In a comparison with other countries, the rate of incident all-cause stroke among PLWHA in Taiwan was lower than that in Danish HIV cohort (2.68 per 1000 PY) [21]. Also, the rate of incident ischemic stroke among PLWHA in Taiwan was similar to that in Swiss HIV cohort (1.73 per 1000 PY) [22], but lower than that among PLWHA in U.S. (5.27 per 1000 PY) [22].An association between CKD, chronic kidney disease; HTN, hypertension; CHD, coronary heart disease; TB, tuberculosis; HAART, highly active antiretroviral therapy. "
    [Show abstract] [Hide abstract] ABSTRACT: Objectives: Cytomegalovirus (CMV) infection might increase the risk of cardiovascular event. However, data on the link between incident stroke and co-infections of CMV and human immunodeficiency virus (HIV) are limited and inconsistent. This nationwide population-based cohort study analyzed the association of CMV end-organ disease and stroke among people living with HIV/AIDS (PLWHA). Methods: From January 1, 1998, this study identified adult HIV individuals with and without CMV end-organ disease in the Taiwan National Health Insurance Research Database. All patients were observed for incident stroke and were followed until December 31, 2012. Time-dependent analysis was used to evaluate associations of CMV end-organ disease with stroke. Results: Of the 22,581 PLWHA identified (439 with CMV end-organ disease and 22,142 without CMV end-organ disease), 228 (1.01%) had all-cause stroke during a mean follow-up period of 4.85 years, including 169 (0.75%) with ischemic stroke and 59 (0.26%) with hemorrhagic stroke. After adjusting for age, sex, comorbidities, opportunistic infections after HIV diagnosis, and antiretroviral treatment, CMV end-organ disease was found to be an independent risk factor for incident all-cause stroke (adjusted hazard ratio [AHR], 3.07; 95% confidence interval [CI], 1.70 to 5.55). When stroke type was considered, CMV end-organ disease was significantly positively associated with the risk of ischemic stroke (AHR, 3.14; 95% CI, 1.49 to 6.62) but not hemorrhagic stroke (AHR, 2.52; 95% CI, 0.64 to 9.91). Conclusions: This study suggested that CMV end-organ disease was an independent predictor of ischemic stroke among PLWHA.
    Preview · Article · Mar 2016 · PLoS ONE
  • Source
    • "This abacavir uptake was not inhibited by an excess of non-radioactive abacavir, indicating that abacavir uptake in HUVECs was primarily mediated by passive diffusion. Another hypothesis is that abacavir may act on adenosine receptors to induce relaxation as abacavir is a nucleoside analog and its chemical structure is similar to that of the physiological vasodilator, adenosine [27,28]. To determine whether abacavir-induced relaxation of basilar arteries was adenosine receptor-mediated, the effects of CGS-15943 (1 μM; a non-selective adenosine receptor antagonist) and ZM-241385 (1 μM; a selective A 2 receptor antagonist) were examined. "
    [Show abstract] [Hide abstract] ABSTRACT: The use of abacavir has been linked with increased cardiovascular risk in patients with human immunodeficiency virus infection; however, the mechanism involved remains unclear. We hypothesize that abacavir may impair endothelial function. In addition, based on the structural similarity between abacavir and adenosine, we propose that abacavir may affect vascular contractility through endogenous adenosine release or adenosine receptors in blood vessels. The relaxation effect of abacavir on rat basilar arteries was studied using the myograph technique. Cyclic GMP and AMP levels were measured by immunoassay. The effects of abacavir on nucleoside transporters were studied using radiolabeled nucleoside uptake experiments. Ecto-5' nucleotidase activity was determined by measuring the generation of inorganic phosphate using adenosine monophosphate as the substrate. Abacavir induced the relaxation of rat basilar arteries in a concentration-dependent manner. This relaxation was abolished when endothelium was removed. In addition, the relaxation was diminished by the nitric oxide synthase inhibitor, L-NAME, the guanylyl cyclase inhibitor, ODQ, and the protein kinase G inhibitor, KT5820. Abacavir also increased the cGMP level in rat basilar arteries. Abacavir-induced relaxation was also abolished by adenosine A2 receptor blockers. However, abacavir had no effect on ecto-5' nucleotidase and nucleoside transporters. Short-term and long-term treatment of abacavir did not affect acetylcholine-induced relaxation in rat basilar arteries. Abacavir induces acute endothelium-dependent relaxation of rat basilar arteries, probably through the activation of adenosine A2 receptors in endothelial cells, which subsequently leads to the release of nitric oxide, resulting in activation of the cyclic guanosine monophosphate/protein kinase G-dependent pathway in vascular smooth muscle cells. It is speculated that abacavir-induced cardiovascular risk may not be related to endothelial dysfunction as abacavir does not impair relaxation of blood vessels. The most likely explanation of increased cardiovascular risk may be increased platelet aggregation as suggested by other studies.
    Full-text · Article · Apr 2015 · PLoS ONE
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    • "In contrast, longer treatment with cART showed no further increase in CVE in recent studies [9, 41, 42]. The latter seems consequential since low levels of CD4+ cells and a high viral load represent significant risk factors of stroke [9, 11] . Therefore , cART has to start early enough before the onset of any neuromanifestions of the HIV infection. "
    [Show abstract] [Hide abstract] ABSTRACT: Purpose/aim: Cerebrovascular events (CVE) in HIV infected patients have become an increasingly relevant neurological complication. Data about the prevalence and clinical features of CVE in HIV infected patients since the introduction of combined Anti-Retroviral Therapy (cART) are rare. Methods: A retrospective study of HIV-infected patients with a CVE was performed from 2002 to 2011. During this time period 3203 HIV-infected patients were admitted to the University hospital of Münster, Germany. All patients had access to regular and long term treatment with cART. The clinical features were analyzed and the prevalence of ischemic stroke (IS), transient ischemic attack (TIA) and intracerebral bleeding (ICB) was calculated. Results: The total prevalence of all CVE was at 0.6% (95% CI: 0.3, 0.8) (0.4% for IS (95% CI: 0.2, 0.6), 0.2% for TIA (95% CI: 0.0, 0.3) and 0.1% for ICB (95% CI: 0.0, 0.2)) and the crude annual incidence rate at 59 per 100.000 for all events. The median CD4 cell count was 405/μl (25th to 75th percentile: 251-568). The majority of patients had AIDS. The median age was at 49 years (25th to 75th percentile: 40-69). Some events were associated with HIV-associated vasculopathy or viral co-infections. Most patients presented with multiple vascular risk factors. Conclusion: The study confirms that CVE occur in HIV-infected patients with a good immune status and at a young age. HIV infection has to be considered in young stroke patients. The rate of CVE in this study was constant when comparing to the pre-cART era. HIV associated vasculopathy and viral co-infections need to be considered in the diagnostics of stroke.
    Full-text · Article · Aug 2014 · International Journal of Neuroscience
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