Depression and anxiety symptoms post-stroke/TIA: Prevalence and associations in cross-sectional data from a regional stroke registry

Abstract

Mood disorders are commonly seen in those with cerebrovascular disease. Literature to-date has tended to focus on depression and on patients with stroke, with relatively little known about post-stroke anxiety or mood disorder in those with transient ischaemic attack (TIA). We aimed to describe prevalence of depression and anxiety symptoms in stroke and TIA cohorts and to explore association with clinical and socio-demographic factors.
We used a city wide primary care stroke registry (Glasgow Local Enhanced Service for Stroke - LES). All community dwelling stroke-survivors were included. We described cross-sectional prevalence of depression and anxiety symptoms using the Hospital Anxiety and Depression Scale (HADS). Data on clinical and demographic details was collected and univariable and multivariable analyses performed to describe associations with HADS scores. We examined those with a diagnosis of ‘stroke’ and ‘TIA’ as separate cohorts.
From 13,283 potentially eligible stroke patients in the registry, we had full HADS data on 4,079. Of the 3,584 potentially eligible TIA patients, we had full HADS data on 1,247 patients. Across the stroke cohort, 1181 (29%) had HADS anxiety scores suggestive of probable or possible anxiety; 993 (24%) for depression. For TIA patients, 361 (29%) had anxiety and 254 (21%) had depression. Independent predictors of both depression and anxiety symptoms were female sex, younger age and higher socioeconomic deprivation score (all p < 0.001).
Using HADS, we found a high prevalence of anxiety and depression symptoms in a community-based cohort of patients with cerebrovascular disease.

Full text

R E S E A R C H A R T I C L E Open Access
Depression and anxiety symptoms post-stroke/TIA:
prevalence and associations in cross-sectional data
from a regional stroke registry
Niall M Broomfield
1,2
, Terence J Quinn
1
, Azmil H Abdul-Rahim
1*
, Matthew R Walters
1
and Jonathan J Evans
3
Abstract
Background: Mood disorders are commonly seen in those with cerebrovascular disease. Literature to-date has
tended to focus on depression and on patients with stroke, with relatively little known about post-stroke anxiety or
mood disorder in those with transient ischaemic attack (TIA). We aimed to describe prevalence of depression and
anxiety symptoms in stroke and TIA cohorts and to explore association with clinical and socio-demographic factors.
Methods: We used a city wide primary care stroke registry (Glasgow Local Enhanced Service for Stroke - LES). All
community dwelling stroke-survivors were included. We described cross-sectional prevalence of depression and
anxiety symptoms using the Hospital Anxiety and Depression Scale (HADS). Data on clinical and demographic
details was collected and univariable and multivariable analyses performed to describe associations with HADS
scores. We examined those with a diagnosis of ‘stroke’and ‘TIA’as separate cohorts.
Results: From 13,283 potentially eligible stroke patients in the registry, we had full HADS data on 4,079. Of the
3,584 potentially eligible TIA patients, we had full HADS data on 1,247 patients. Across the stroke cohort, 1181
(29%) had HADS anxiety scores suggestive of probable or possible anxiety; 993 (24%) for depression. For TIA
patients, 361 (29%) had anxiety and 254 (21%) had depression. Independent predictors of both depression and
anxiety symptoms were female sex, younger age and higher socioeconomic deprivation score (all p < 0.001).
Conclusion: Using HADS, we found a high prevalence of anxiety and depression symptoms in a community-based
cohort of patients with cerebrovascular disease.
Keywords: Mood, Stroke, TIA, Anxiety, Depression, Prevalence
Background
Mood disorders are common in stroke-survivor cohorts
and are associated with increased morbidity and mortality.
Meta-analyses of point-prevalence rates suggest one third
of stroke-survivors develop post-stroke depression and
one quarter develop post-stroke anxiety [1,2]. More than
half of stroke survivors will be affected by depression at
some point [3]. These summary data are important and
strongly suggestive of a high stable prevalence of post-
stroke mood disorder, but meta-analyses are limited by all
the caveats that accompany data pooled from various
studies and populations.
Stroke-survivor populations are heterogenous and there
is still value in describing contemporary patterns of post-
stroke mood problems in a suitably large population. A
group who are not well represented in the available litera-
ture are those whose index event would be classified as a
Transient Ischaemic Attack (TIA) or “minor stroke”.Al-
though the evidence would suggest that TIA is associated
with depression, the literature is characterised by studies
of only modest sample size and is far from definitive [4-8].
No large study has examined mood problems in both
stroke and TIA samples, using an identical assessment
procedure, to compare. Further, we are not aware of any
suitably large studies of anxiety incidence or prevalence
following TIA. It seems plausible that the psychological
effects of TIA may differ from stroke and a focussed ana-
lysis of mood disorder in TIA patients seems warranted.
* Correspondence: Azmil.Abdul-Rahim@glasgow.ac.uk
1
Institute of Cardiovascular and Medical Sciences, University of Glasgow,
Glasgow, UK
Full list of author information is available at the end of the article
© 2014 Broomfield et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the
Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public
Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this
article, unless otherwise stated.
Broomfield et al. BMC Neurology 2014, 14:198
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Despite their prevalence, post-stroke mood disorders
are relatively under researched compared to stroke re-
lated physical disabilities. A better understanding of the
risk factors for depression and anxiety following stroke
and TIA could help inform research and target interven-
tions. Of particular interest are the effects of age; socio-
economic deprivation (SED); smoking and co-morbidity
on mood disorder. We know that these factors are as-
sociated with mood disorder in unselected non-stroke
cohorts [9-12] and these variables are also risk factors
for stroke itself [13].
A robust population level assessment of post-stroke
mood disorder, that describes association with important
socio-demographic variables and includes TIA or minor
stroke, could provide useful data for clinical practice and
service planning. We used a stroke specific, city-wide
clinical registry to describe patterns and associations of
post stroke depression and anxiety.
Our aims were:
a) To describe point prevalence of depression and
anxiety symptoms in a large cohort of urban,
community dwelling stroke-survivors.
b) To perform a subgroup analysis to describe
depression and anxiety symptoms in those whose
index event was classified as “TIA”.
c) To describe the association of potential post
stroke depression and anxiety with clinical and
socio-demographic variables.
Methods
We present a cross-sectional analysis of a city-wide primary
care administered data resource. Conduct and report-
ing of all analyses was in accordance with Strengthening
the Reporting of Observational Studies in Epidemiology
(STROBE) guidelines [14].
Setting
Greater Glasgow and Clyde Health Board (GG&C) pro-
vides services to a population of 1.2 million people in
Glasgow, United Kingdom. Glasgow is typical of urban
settings in industrialised nations, albeit with high levels of
cardiovascular disease and socio-economic deprivation.
Annual admissions to secondary care with stroke are
around 3,000. For the calendar year of 2012–13, GG&C
had 15,524 people registered with a primary care practice
who were recorded as having had previous stroke event
(including TIA).
Data source
We used the Glasgow, Local Enhanced Services (LES) data-
base (a clinical resource) for our analyses [15]. The Glasgow
LES is a contractual arrangement with primary care ser-
vices, incentivising all Glasgow General Practitioners (GPs)
to improve the management of exemplar chronic diseases
(in the first instance these were ischaemic heart disease;
heart failure and stroke). LES augments the basic patient-
level data collection that is required through the General
Medical Services (GMS) Quality and Outcome Framework
(QOF) specification, by providing financial incentives to en-
courage proactive case finding, by delivering annual nurse
led reviews and by managing and quality controlling centra-
lised data storage. To ensure data quality, the LES initiative
funds annual practice nurse training in assessment and data
input and employs data managers to ensure validity of
input data. LES funding and support is available to all
GP practices in GG&C and in total 209 out of 213 prac-
tices actively participate in stroke data collection and
upload.
Participants
We identified all living stroke-survivors from the LES
stroke database, using the last available calendar year
with full data entry and completed quality control (year
2012–13). We excluded care-home residents or house-
bound subjects using LES specific read-codes.
Clinical diagnoses recorded in LES are linked to hos-
pital discharge records and primary care registers. In the
GP practices covered by the LES resource, cerebrovascu-
lar diagnoses were primarily made by stroke specialist
services in secondary care with access to neuro-imaging
and other supplementary investigations considered
standard at the time.
Diagnoses of “stroke”and “TIA”conformed to the clas-
sical World Health Organisation (WHO) definitions. We
created a data subgroup limited to those with TIA diagno-
sis. Where a patient had both TIA and stroke recorded
they were excluded from the TIA analysis.
Patient level data
Our primary descriptor of interest was presence of
depression or anxiety symptoms. We collated data on
potential anxiety and depression using Hospital Anxiety
and Depression Scale (HADS) scores. HADS is a mood
screening tool designed for use with physically ill pa-
tients to assess for clinical anxiety and depression [16].
HADS has been validated in stroke-survivor cohorts
showing reasonable test accuracy and is one of the com-
monest mood measures employed in stroke clinical
practice [17,18]. HADS comprises part of the routine an-
nual LES stroke assessment; all practice staff recording
LES data are trained in HADS assessment with stroke
patients by a specialist stroke clinical psychology service.
HADS comprises two sub scales: HADS-anxiety
(HADS-A) and HADS-depression (HADS-D). We exam-
ined individual scores for each component. Within the
stroke LES, HADS data are operationalised as HADS
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0–7“normal score”;HADS8–10 “possible caseness”;and
HADS ≥11 “probable caseness”.
We also collated data on sociodemographic and clinical
variables. We described age, sex and race of all included
patients. We assessed socioeconomic status using Scottish
Index of Multiple Deprivation (SIMD). The SIMD is
assigned on the basis of residence (datazone) and incorpo-
rates domains of income, employment, health, education,
geographic access to services, crime, and housing [19].
We used postcode data within the LES to assign SIMD
and described data as quintiles with quintile 1 represent-
ing the most deprived area. We described rates of exces-
sive alcohol intake (defined at practice level) and smoking
(defined as any current use of cigarettes or other related
products). To describe co-morbidity we collated data on
presence of ischemic heart disease, heart failure, diabetes,
chronic obstructive pulmonary disease (linking LES to
practice level clinical diagnostic data from patients’pri-
mary care records).
Our study was approved a priori by the West of
Scotland Research Ethics Service, the local (GG&C)
Caldicott Guardian and the Greater Glasgow Chronic
Disease Management Overseeing Data Group.
Statistical methods
We described the total stroke-survivor cohort and “TIA”
cohort separately, grouping each cohort’s baseline charac-
teristics by trichotomised (normal, possible, probable)
HADS-A and HADS-D scores respectively. We described
mean (standard deviation [SD]) or median (inter-quartile
range [IQR]) for continuous variables and count (percent-
age) for categorical variables as appropriate. Unadjusted
comparisons of individual variables by HADS grouping
score-groups were conducted using ANOVA or χ
2
test
depending on the distribution and nature of the data. We
recorded “significance”of univariable analysis at the con-
ventional level (P< 0.05). To correct for multiple analyses
we also used the sequentially rejective Bonferroni method
[20], under this correction “significance”was defined as
P< 0.005 (significant level/number of variables, 0.05/
10 = 0.005).
We calculated odds ratios (OR) and corresponding 95
percent confidence intervals (95% CI) to express the odds
of depression or anxiety. For these analyses, we defined
caseness for anxiety as HADS-A score ≥8 (i.e. possible and
probable cases), and caseness for depression as HADS-D
score ≥8 [17]. We performed a series of univariable ana-
lyses using binary logistic regression employing di-
chotomized outcome measures for both anxiety and
depression. We used these results to inform the choice
of factors to include in the multivariable analyses. Final
choice of input variables to the model were: age, sex,
socio-economic deprivation (SIMD), current smoker and
previous history of COPD. All analyses were undertaken
using SAS version 9.2 (SAS Institute, Inc., Cary, NC,
USA).
Results
Stroke cohort
The LES Stroke Database for April 2012- March 2013
contained case reviews on 15,247 stroke patients. Of the
total number potentially available, 1,964 were excluded
as care-home residents or housebound status. From the
remaining 13,283 stroke patients; 2,131 declined to
complete the HADS assessment, and 7,073 had missing
HADS data; leaving a cohort with full data of 4,079 (29%
of review attendees) (Figure 1a). The median age of the
stroke cohort was 70.3 years (IQR: 11.3) and 2,323 persons
were male (57%) (Table 1).
In our stroke-survivor cohort, 604 (15%) of stroke
patients were classified as definite abnormal for anxiety
symptoms (HADS-A: ≥11) and 577 (14%) were classified
as possible abnormal (HADS-A: 8–10); while 458 (11%)
were definite abnormal and 535 (13%) were possible abnor-
mal for depression symptoms.(Additional file 1: Table S1
and S2) 1,445 (35%) stroke patients had any mood dis-
order that comprises of 2,174 caseness for either anxiety or
depression.
On univariable analyses, female sex; younger age; higher
level of SED; smoking and presence of COPD diagnosis
were all strongly associated with higher anxiety and de-
pression scores.(Additional file 1: Figure S1 and S2) On
multivariable analysis, sex, age and SED were independ-
ently associated with both anxiety and depression symp-
toms (Additional file 1: Table S3 and S4).
TIA cohort
From all LES stroke entries, 4,050 case reviews were
completed for patients with a clinical diagnosis of TIA
and no stroke.Of these, 466 were excluded as care-
home residents or housebound status, 532 refused the
HADS assessment and 1,805 had missing HADS data.
Thus, the total TIA dataset with useable data comprised
1,247 patients (Figure 1b). The TIA group had median
age 70.8 years (IQR: 10.9) and 643 were male (52%).
Comparison of the baseline characteristics of stroke and
TIA cohorts were given in Table 1.
In the TIA cohort, 179 (14%) were classified as definite
abnormal anxiety symptoms and 182 (15%) possible
abnormal; while 107 (9%) were definite abnormal for
depression symptoms and 147 (12%) were possible ab-
normal (Tables 2 and 3) 415 (33%). TIA patients had
any mood disorder that comprises of 615 caseness for
either anxiety or depression. Significant univariable asso-
ciations were: younger age; female sex (anxiety only);
SED; smoking and COPD diagnosis (Figures 2 and 3).
After multivariable analysis, all remained independently
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associated with anxiety and depression other than smok-
ing (Table 4).
Given the substantial proportion with missing data, we
performed post-hoc analyses comparing those with and
without HADS data (declined or data missing) (Additional
file 1: Table S5 for stroke patients and Additional file 1:
Table S6 for TIA patients). Within the group who did not
contribute HADS data, we compared those who refused
HADS, with those for whom no data were recorded for
other reasons, “refusers”were more likely to be male,
smokers and have other co-morbidities (Additional file 1:
Table S7 for stroke patients and Additional file 1: Table S8
for TIA patients).
Discussion
To our knowledge, this is the first study to present
population level data, describing post-stroke anxiety and
depression symptom prevalence in stroke and TIA sam-
ples, using an identical assessment procedure (HADS), to
compare. Our data add to the literature on mood disorder
and stroke [21], in particular post-stroke anxiety and
mood problems following TIA have received limited re-
search attention to date and we designed our analyses to
focus on those groups.
Our data suggest that depression and anxiety symptoms
are common following stroke events, including TIA. In-
deed, it is noteworthy that depression and anxiety levels
are similar between these two patient groups. The single
time point, cross-sectional data presented, does not allow
Figure 1 Flow chart for selection of; a) stroke cohort and, b) minor stroke/TIA cohort; from the local enhanced service stroke database.
Table 1 Baseline characteristics of stroke and TIA cohorts
Cohort P-value
Stroke TIA
(n = 4,079) (n = 1,247)
Male 2,323 (57.0) 643 (51.6) <0.001
Age; median (IQR) 70.3 (11.3) 70.7 (10.9) 0.178
Caucasian 3,819 (93.6) 1,167 (93.6) 0.524
Socioeconomic deprivation 0.024
SIMD I (most deprived) 1,610 (39.5) 550 (44.1)
SIMD II 767 (18.8) 200 (16.0)
SIMD III 483 (11.8) 145 (11.6)
SIMD IV 447 (11.0) 141 (11.3)
SIMD V (least deprived) 715 (17.5) 195 (15.6)
Alcohol intake excessive 200 (4.9) 50 (4.0) 0.192
Current smoker 920 (22.6) 306 (24.5) 0.145
Co-morbidities
Ischaemic heart disease 784 (19.2) 310 (24.9) <0.001
Heart failure 263 (6.5) 70 (5.6) 0.287
Diabetes 1,088 (26.7) 262 (21.0) <0.001
COPD 553 (13.6) 192 (24.5) 0.101
HADS; median (IQR)
HADS-anxiety 4 (5) 5 (5) 0.469
HADS-depression 4 (4) 4 (5) 0.008
Significant values after Bonferroni correction (P < 0.005) in bold. SIMD: Scottish
Index of Multiple Deprivation-described as quintiles. IQR: inter-quartile range.
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Table 2 Baseline characteristics of TIA cohort according to HADS-anxiety scores
All patients, n (%) HADS anxiety scores P-value
0-7 8-10 ≥11
(N = 1,247) (n = 886) (n = 182) (n = 179)
Male 643 (51.6) 489 (55.2) 70 (38.5) 84 (47.0) <0.001
Age; median (IQR) 70.8 (10.9) 72.3 (10.6) 69.0 (10.7) 65.0 (10.5) <0.001
Caucasian 1167 (93.6) 828 (93.45) 174 (95.6) 165 (92.2) 0.166
Socioeconomic deprivation <0.001
SIMD I (most deprived) 550 (44.1) 334 (37.7) 98 (53.9) 118 (66.0)
SIMD II 200 (16.0) 146 (16.5) 28 (15.4) 26 (14.5)
SIMD III 145 (11.6) 115 (13.0) 18 (9.9) 12 (6.7)
SIMD IV 141 (11.3) 116 (13.1) 11 (6.0) 14 (7.8)
SIMD V (least deprived) 195 (15.6) 166 (18.7) 22 (12.1) 7 (3.9)
Alcohol intake excessive 50 (4.0) 35 (4.0) 7 (3.9) 8 (4.5) 0.942
Current smoker 306 (24.5) 181 (20.4) 60 (33.0) 65 (36.3) <0.001
Co-morbidities
Ischaemic heart disease 310 (24.9) 213 (24.0) 48 (26.4) 49 (24.9) 0.563
Heart failure 70 (5.6) 55 (6.2) 10 (5.5) 5 (2.8) 0.194
Diabetes 262 (21.0) 187 (21.1) 36 (19.8) 39 (21.8) 0.889
COPD 192 (15.4) 111 (12.5) 34 (18.7) 47 (26.3) <0.001
Significant values after Bonferroni correction (P < 0.005) in bold. SIMD: Scottish Index of Multiple Deprivation-described as quintiles. IQR: inter-quartile range.
Table 3 Baseline characteristics of TIA cohort according to HADS-depression scores
All patients, n (%) HADS depression scores P-value
0-7 8-10 ≥11
(N = 1,247) (n = 993) (n = 147) (n = 107)
Male 643 (51.6) 511 (51.5) 71 (48.3) 61 (57.0) 0.386
Age; median (IQR) 70.8 (10.9) 71.6 (10.7) 69.3 (11.1) 65.0 (10.6) <0.001
Caucasian 1167 (93.6) 932 (93.9) 138 (93.9) 97 (90.7) 0.280
Socioeconomic deprivation <0.001
SIMD I (most deprived) 550 (44.1) 404 (40.7) 79 (53.7) 67 (62.6)
SIMD II 200 (16.0) 159 (16.0) 23 (15.7) 18 (16.8)
SIMD III 145 (11.6) 120 (12.1) 15 (10.2) 10 (9.4)
SIMD IV 141 (11.3) 124 (12.5) 8 (5.4) 9 (8.4)
SIMD V (least deprived) 195 (15.6) 174 (17.5) 18 (12.2) 3 (2.8)
Alcohol intake excessive 50 (4.0) 39 (3.9) 8 (5.4) 3 (2.8) 0.547
Current smoker 306 (24.5) 213 (21.5) 43 (29.3) 50 (46.7) <0.001
Co-morbidities
Ischaemic heart disease 310 (24.7) 237 (23.9) 45 (30.6) 28 (26.2) 0.199
Heart failure 70 (5.6) 58 (5.8) 7 (4.8) 5 (4.7) 0.788
Diabetes 262 (21.0) 205 (20.6) 40 (27.2) 17 (15.9) 0.075
COPD 192 (15.4) 125 (12.6) 30 (20.4) 37 (34.6) <0.001
Significant values after Bonferroni correction (P < 0.005) in bold. SIMD: Scottish Index of Multiple Deprivation-described as quintiles. IQR: inter-quartile range.
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us to look at temporal sequence and so we can make no
inferences about causation. However, these data are in
keeping with other studies that suggest stroke disease may
be responsible for increased rates of mood disorder [1,2].
Certainly, the prevalence rates we describe are higher than
seen in “unselected”community populations assessed with
HADS (11.4% depressed) and in patients with coronary
heart disease (11.8% depressed) [22,23].
As noted, we found that those with TIA had similar
rates and predictors of mood disorder as those with
stroke. This finding has implications for services. Many
current guidelines suggest cognitive and mood screening
Figure 2 Forrest plot shows variable’s association with caseness for anxiety in TIA cohort (unadjusted univariable analysis).
IHD: ischaemic heart diease; COPD: Chronic Obstructive Pulmonary Disease. OR and corresponding 95% CI express the odds of caseness for
anxiety in univariable analysis.
Figure 3 Forrest plot shows variable’s association with caseness for depression in TIA cohort (unadjusted univariable analysis).
IHD: ischaemic heart diease; COPD: Chronic Obstructive Pulmonary Disease. OR and corresponding 95% CI express the odds of caseness for
depression in univariable analysis.
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of stroke-survivors but do not make specific comment
on those with TIA. Our data would suggest that mood
assessment should be similar for both groups and TIA
should not be regarded as a “benign”diagnosis. We note
recent work showing substantial cognitive deficits in
patients with TIA and no stroke [24].
We assessed clinical and demographic associations
with post-stroke mood symptoms. Ideally, through describ-
ing predictors of an outcome, services can target interven-
tion. Mood disorder was increased in those with SED, a
group who are often difficult to engage with chronic
disease management. The finding of increased mood
disorder in females is in keeping with patterns in the
general (non-stroke) population [24,25], albeit our preva-
lence of disorder was considerably higher.
Within our mood disorder group will be a number of
patients with psychological problems that predate the
stroke event and have continued, rather than incident
post stroke mood disorder. There is a complex inter-
action between mood and vascular disease and mood
disorder may be a risk factor for vascular events [26].
We are unable to differentiate incident and prevalent
mood problems using these cross sectional data. The
data available do not allow us to look at time since event
as a covariate and this limits interpretation. In terms of
service design and access to mood intervention, perhaps
the more important matter is the absolute proportion of
stroke-survivors with problems rather than the timing
or potential aetiology and the data are suited to this
purpose.
The strength of our analysis is the large dataset,
derived from a population representative of “real world”
stroke survivors. We further demonstrate that the LES
resources provide a substrate for describing health care
and outcomes that can be used to shape practice [27].
Our inclusion of both depression and anxiety should
give a better description of post-stroke mood disorder
than previous studies that had a focus on depression
alone; while including equivalent test data for both clas-
sical stroke and TIA allows for comparisons between
these groups.
We acknowledge limitations in our study method-
ology. The main limitation was missing data, particularly
HADS data. The missing data is unfortunate but not
uncommon in large clinical registries. We offer some
description of the groups with and without HADS data
but recognise that fundamental differences are likely to
exist between the groups and the stroke-survivors in-
cluded in our analysis may not be representative. We ac-
knowledge cognitive/communication disability may have
limited participation and this may impact on prevalence
of mood problems recorded. There are assessments that
can be used where direct interview is not suitable, for
example observational based depression and anxiety
measures [28-30]. Where patients refused HADS testing,
there is no simple solution to improving data capture.
For those with data not recorded we note the high pro-
portion who are non-Caucasian. It seems plausible that
nurses performing reviews may feel unable to collect
data in those with limited spoken English or where socio-
cultural factors may impact on the significance of a mood
disorder diagnosis. We will use this finding to review how
we train nurses in mood assessments. The proportion
with missing data had a high prevalence of our independ-
ent risk factors for mood disorder (female sex; greater
deprivation) and it is possible that our data are an under-
representation of the true burden of post stroke mood
disorder.
Our mood disorder assessment metric was based on
HADS. We accept that HADS is not a substitute for
expert derived clinical diagnosis and that HADS has
complex four-choice response format requiring intact
working memory. HADS has been validated for use in
stroke, albeit utility is poor in acute stroke settings
[31] and has been shown to have good diagnostic accuracy
for making diagnosis of depression or anxiety [17]. There
remains a lack of consensus regarding optimal sub-scale
cut-offs for stroke [32]. LES therefore employs standard
cut points (≥8) to detect caseness, following recommenda-
tion by the scale authors and consistent with previous
stroke research [33]. We were interested in “TIA”patients
and looked specifically at this group. We recognise that
the time based definition of TIA used in this analysis is
becoming obsolete. A tissue based definition of TIA would
have been preferable but was not possible in this historical
cohort. As a group of patients with no residual neurology
at 24 hours, our “TIA”cohort may be better described as
TIA or minor stroke.
Conclusions
In conclusion we have described a high prevalence of
both depression and anxiety symptoms in a cohort of
Table 4 Multivariable analysis of caseness for anxiety or
depression in TIA cohort
OR (95% CI) P-value
Caseness for anxiety
Female (vs. Male) 1.68 (1.29-2.18) <0.001
Age (increasing by 1 year) 0.96 (0.95-0.97) <0.001
Socioeconomic deprivation (SIMD I vs SIMD V) 2.37 (1.51-3.72) <0.001
COPD (vs. those not) 1.81 (1.28-2.56) 0.001
Caseness for depression
Age (increasing by 1 year) 0.97 (0.96-0.99) <0.001
Socioeconomic deprivation (SIMD I vs SIMD V) 2.04 (1.22-3.40) 0.001
COPD (vs. those not) 2.17 (1.52-3.12) <0.001
SIMD: Scottish Index of Multiple Deprivation- described as quintiles.
Input covariates detailed in main manuscript.
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community dwelling stroke survivors. Rates of depres-
sion and anxiety symptoms were similar for TIA and
stroke, suggesting that mood assessments and interven-
tions should not be reserved for those with classical
stroke only.
Additional file
Additional file 1: Online-only supplementary materials.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
NMB acquired the data. NMB, TJQ and AHAR designed the study and
analysed the data. AHAR performed the statistical analysis. NMB, TJQ and
AHAR interpreted the data, drafted the manuscript and contributed to
critical revision of the manuscript for important intellectual content. MRW
and JJE performed critical supervision of the manuscript. All authors read
and approved the final manuscript.
Acknowledgements
We wish to acknowledge Dr Anne Scoular, all the practice nurses and other
primary care colleagues involved in clinical care to stroke patients in Greater
Glasgow, members of NHS Greater Glasgow & Clyde Stroke Managed Clinical
Network especially Dr Christine McAlpine for their organisational support of
this work and Peter Welsh and Julie Boyd, Information Analysts, for their
considerable time and effort in preparing the data for secondary analysis.
Author details
1
Institute of Cardiovascular and Medical Sciences, University of Glasgow,
Glasgow, UK.
2
Rehabilitation Assessment Directorate, NHS Greater Glasgow
and Clyde, Glasgow, UK.
3
Institute of Health and Wellbeing, University of
Glasgow, Glasgow, UK.
Received: 4 July 2014 Accepted: 25 September 2014
References
1. Hackett ML, Yapa C, Parag V, Anderson CS: Frequency of depression after
stroke: a systematic review of observational studies. Stroke 2005,
36(6):1330–1340.
2. Campbell Burton CA, Murray J, Holmes J, Astin F, Greenwood D, Knapp P:
Frequency of anxiety after stroke: a systematic review and meta-analysis
of observational studies. Int J Stroke 2013, 8(7):545–559.
3. Ayerbe L, Ayis S, Crichton S, Wolfe CD, Rudd AG: The natural history of
depression up to 15 years after stroke: the South London Stroke
Register. Stroke 2013, 44(4):1105–1110.
4. Luijendijk HJ, Stricker BH, Wieberdink RG, Koudstaal PJ, Hofman A, Breteler
MM, Tiemeier H: Transient ischemic attack and incident depression. Stroke
2011, 42(7):1857–1861.
5. Steffens DC, Stechuchak KM, Oddone EZ: How asymptomatic is
asymptomatic carotid stenosis? Radiology 2007, 244(1):317–318. author
reply 318–319.
6. Rao R, Jackson S, Howard R: Depression in older people with mild stroke,
carotid stenosis and peripheral vascular disease: a comparison with
healthy controls. Int J Geriatr Psych 2001, 16(2):175–183.
7. Hickie I, Simons L, Naismith S, Simons J, McCallum J, Pearson K: Vascular
risk to late-life depression: evidence from a longitudinal community
study. Aust Nz J Psychiat 2003, 37(1):62–65.
8. Wu KY, Liu CY, Chau YL, Chang CM: Transient ischemic attack and
incidence of depression in old age: evidence from a population-based
analysis in Taiwan. Am J Geriat Psychiat 2010, 18(5):382–387.
9. Glassman AH, Helzer JE, Covey LS, Cottler LB, Stetner F, Tipp JE, Johnson J:
Smoking, smoking cessation, and major depression. JAMA 1990,
264(12):1546–1549.
10. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE: Lifetime
prevalence and age-of-onset distributions of DSM-IV disorders in the
National Comorbidity Survey Replication. Arch Gen Psychiatry 2005,
62(6):593–602.
11. Ostler K, Thompson C, Kinmonth AL, Peveler RC, Stevens L, Stevens A:
Influence of socio-economic deprivation on the prevalence and outcome
of depression in primary care: the Hampshire Depression Project.
Br J Psychiatry 2001, 178(1):12–17.
12. Patten SB: Long-term medical conditions and major depression in a
Canadian population study at waves 1 and 2. J Affect Disord 2001,
63(1–3):35–41.
13. European Stroke Organisation (ESO) Executive Committee, and the ESO
Writing Committee: Guidelines for management of ischaemic stroke and
transient ischaemic attack 2008. Cerebrovasc Dis 2008, 25(5):457–507.
14. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP,
Initiative S: The Strengthening the Reporting of Observational Studies in
Epidemiology (STROBE) statement: guidelines for reporting observational
studies. J Clin Epidemiol 2008, 61(4):344–349.
15. Chronic Disease in the NHS Greater Glasgow & Clyde. Insights from
Local Enhanced Services 2008–2009. [http://www.google.co.uk/url?
sa=t&rct=j&q=local%20enhanced%20service%20glasgow%202010&
source=web&cd=1&ved=0CCwQFjAA&url=http%3A%2F%2Flibrary.nhsggc.
org.uk%2FmediaAssets%2FMy%2520HSD%2FInsights%2520from%2520LES%
25202008-2009.doc&ei=zQSRUZCVBoa_0QXy5oHwDw&usg=
AFQjCNEd9axDLJirF-W5XGPxeDuBQRiTEQ]
16. Zigmond AS, Snaith RP: The hospital anxiety and depression scale.
Acta Psychiatr Scand 1983, 67(6):361–370.
17. Turner A, Hambridge J, White J, Carter G, Clover K, Nelson L, Hackett M:
Depression screening in stroke: a comparison of alternative measures
with the structured diagnostic interview for the diagnostic and statistical
manual of mental disorders, fourth edition (major depressive episode) as
criterion standard. Stroke 2012, 43(4):1000–1005.
18. Lees R, Fearon P, Harrison JK, Broomfield NM, Quinn TJ: Cognitive and
mood assessment in stroke research: focused review of contemporary
studies. Stroke 2012, 43(6):1678–1680.
19. Scottish Index of Multiple Deprivation (SIMD). [http://www.scotland.gov.
uk/Topics/Statistics/SIMD]
20. Gordi T, Khamis H: Simple solution to a common statistical problem:
interpreting multiple tests. Clin Ther 2004, 26(5):780–786.
21. Broomfield NM, Scoular A, Welsh P, Walters M, Evans JJ: Poststroke anxiety
is prevalent at the population level, especially among socially deprived
and younger age community stroke survivors. Int J Stroke 2013.
doi:10.1111/ijs.12109. [Epub ahead of print].
22. Crawford JR, Henry JD, Crombie C, Taylor EP: Normative data for the HADS
from a large non-clinical sample. Brit J Clin Psychol 2001, 40(Pt 4):429–434.
23. Rothenbacher D, Hahmann H, Wusten B, Koenig W, Brenner H: Symptoms
of anxiety and depression in patients with stable coronary heart disease:
prognostic value and consideration of pathogenetic links. Eur J Cardiov
Prev R 2007, 14(4):547–554.
24. Sachdev PS, Lipnicki DM, Crawford JD, Wen W, Brodaty H: Progression of
cognitive impairment in stroke/TIA patients over 3 years. J Neurol
Neurosur Ps 2014. doi:10.1136/jnnp-2013-306776. [Epub ahead of print].
25. Piccinelli M, Wilkinson G: Gender differences in depression. Critical review.
Br J Psychiatry 2000, 177:486–492.
26. Pan A, Sun Q, Okereke OI, Rexrode KM, Hu FB: Depression and risk of
stroke morbidity and mortality: a meta-analysis and systematic review.
JAMA 2011, 306(11):1241–1249.
27. Abdul-Rahim AH, Wong J, McAlpine C, Young C, Quinn TJ: Associations
with anticoagulation: a cross-sectional registry-based analysis of stroke
survivors with atrial fibrillation. Heart 2014, 100(7):557–562.
28. Kneebone II, Neffgen LM, Pettyfer SL: Screening for depression and
anxiety after stroke: developing protocols for use in the community.
Disabil Rehabil 2012, 34(13):1114–1120.
29. Linley-Adams B, Morris R, Kneebone I: The Behavioural Outcomes of
Anxiety scale (BOA): a preliminary validation in stroke survivors.
Brit J Clin Psychol 2014. doi:10.1111/bjc.12056. [Epub ahead of print].
30. Sutcliffe LM, Lincoln NB: The assessment of depression in aphasic stroke
patients: the development of the Stroke Aphasic Depression
Questionnaire. Clin Rehabil 1998, 12(6):506–513.
31. Lees R, Stott DJ, Quinn TJ, Broomfield NM: Feasibility and diagnostic
accuracy of early mood screening to diagnose persisting clinical
depression/anxiety disorder after stroke. Cerebrovasc Dis 2014,
37(5):323–329.
Broomfield et al. BMC Neurology 2014, 14:198 Page 8 of 9
http://www.biomedcentral.com/1471-2377/14/198

32. Burton LJ, Tyson S: Screening for mood disorders after stroke: a
systematic review of psychometric properties and clinical utility.
Psychol Med 2014, 1–21. doi:10.1017/S0033291714000336
[Epub ahead of print].
33. De Wit L, Putman K, Baert I, Lincoln NB, Angst F, Beyens H, Bogaerts K,
Brinkmann N, Connell L, Dejaeger E, De Weerdt W, Jenni W, Kaske C,
Komarek A, Lesaffre E, Leys M, Louckx F, Schuback B, Schupp W, Smith B,
Feys H: Anxiety and depression in the first six months after stroke. A
longitudinal multicentre study. Disabil Rehabil 2008, 30(24):1858–1866.
doi:10.1186/s12883-014-0198-8
Cite this article as: Broomfield et al.:Depression and anxiety symptoms
post-stroke/TIA: prevalence and associations in cross-sectional data from a
regional stroke registry. BMC Neurology 2014 14:198.
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