1. health and fitness
2. disease

Cardiovasc Intervent Radiol (2013) 36:1241–1246
DOI 10.1007/s00270-013-0636-9
CLINICAL INVESTIGATION
ARTERIAL INTERVENTIONS
Neurointerventional Treatment in Acute Stroke. Whom to Treat?
(Endovascular Treatment for Acute Stroke: Utility of THRIVE
Score and HIAT Score for Patient Selection)
Lars Fjetland • Sumit Roy • Kathinka D. Kurz
Tore Solbakken • Jan Petter Larsen •
Martin W. Kurz
•
Received: 10 January 2013 / Accepted: 15 April 2013 / Published online: 11 May 2013
Ó Springer Science+Business Media New York and the Cardiovascular and Interventional Radiological Society of Europe (CIRSE) 2013
Abstract
Purpose Intra-arterial therapy (IAT) is used increasingly
as a treatment option for acute stroke caused by central
large vessel occlusions. Despite high rates of recanalization, the clinical outcome is highly variable. The authors
evaluated the Houston IAT (HIAT) and the totaled health
risks in vascular events (THRIVE) score, two predicting
scores designed to identify patients likely to benefit from
IAT.
Methods Fifty-two patients treated at the Stavanger
University Hospital with IAT from May 2009 to June 2012
were included in this study. We combined the scores in an
additional analysis. We also performed an additional
analysis according to high age and evaluated the scores in
respect of technical efficacy.
L. Fjetland (&) S. Roy K. D. Kurz
Department of Radiology, Stavanger University Hospital,
4068 Stavanger, Norway
e-mail: lars.fjetland@lyse.net
S. Roy
e-mail: sumit.roy@sus.no
K. D. Kurz
e-mail: kathinka.dehli.kurz@sus.no
L. Fjetland J. P. Larsen M. W. Kurz
The Norwegian Center for Movement Disorders, Stavanger
University Hospital, 4068 Stavanger, Norway
e-mail: jan.petter.larsen@sus.no
M. W. Kurz
e-mail: martin.kurz@sus.no
T. Solbakken J. P. Larsen M. W. Kurz
Department of Neurology, Stavanger University Hospital,
4068 Stavanger, Norway
e-mail: tore.solbakken@sus.no
Results Fifty-two patients were evaluated by the
THRIVE score and 51 by the HIAT score. We found a
strong correlation between the level of predicted risk and
the actual clinical outcome (THRIVE p = 0.002, HIAT
p = 0.003). The correlations were limited to patients successfully recanalized and to patients \80 years. By combining the scores additional 14.3 % of the patients could be
identified as poor candidates for IAT. Both scores were
insufficient to identify patients with a good clinical
outcome.
Conclusions Both scores showed a strong correlation to
poor clinical outcome in patients\80 years. The specificity
of the scores could be enhanced by combining them. Both
scores were insufficient to identify patients with a good
clinical outcome and showed no association to clinical
outcome in patients aged C80 years.
Keywords Neurointerventions Endovascular treatment Stroke therapy Thrombectomy Thrombolysis Brain/
neurological/nervous system Stroke
Introduction
Stroke is the fourth leading cause of mortality and the
leading cause of functional disability in the adult population. Approximately 85 % of all strokes are considered to
be ischemic, due to occlusion of an artery providing the
brain tissue oxygen and nutrition [1–4]. The therapeutic
effect of intravenous thrombolysis (IVT) during the first
hours after the onset is well documented in multiple trials
and has established itself as the first-line treatment for
ischemic stroke [5]. Yet, the thrombolytic effect of IVT is
more evident in peripheral small vessels than in central
large vessel occlusions where a reperfusion rate of just
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30 % is reported [6]. In addition, the narrow time window
for IVT implies that only a minority of patients is suitable
for this treatment. Thus, a more aggressive intra-arterial
therapy (IAT) using intra-arterial thrombolysis and
mechanical thrombectomy devices has been introduced as
a treatment option in patients with central large vessel
occlusions. Adoption of this approach also has expanded
the therapeutic window to 8 h after symptom onset, from
the 4.5 h available for IVT [7, 8].
Trials studying IAT report reperfusion rates varying
from 69.5 to 100 % [9, 10]. However, these excellent
reperfusion figures are only partially reflected in the clinical results. In most studies only 40–50 % [9, 11, 12] of the
patients who are successfully recanalized exhibit a good
clinical outcome [13–15]. The fact that early cerebral
reperfusion alone is not synonymous with good clinical
outcome is of more than academic significance. IAT
requires highly specialized expertise and entails the use of
a considerable amount of health care resources. What is
even more important, it has the nonnegligible potential to
cause harm. As a consequence, the current inability to
confidently identify the patients most likely to benefit from
IAT represents an important hurdle to progress in the
therapy of acute stroke.
During the past decade, a number of factors have been
identified that probably contribute to the outcome achieved
after the treatment of acute stroke. These factors comprise
age, severity of the stroke at admission measured by NIHSS,
hyperglycemia at admission, comorbidity, site of the culprit
lesion, collateral cerebral circulation and interval between
ictus, and start of treatment [6, 13, 16–22]. By incorporating
the most relevant of the clinical factors based on published
data, two methods of stratifying patients have been developed: the totaled health risks in vascular events (THRIVE)
score [18] and the Houston intra-arterial therapy (HIAT)
score [13]. The primary goal of this study was to determine
retrospectively whether these scores, independently or
jointly, have the potential to serve as a clinical tool for the
triage of patients presenting with acute stroke secondary to
occlusion of a relatively large vessel. Another object of this
study was to evaluate whether the specificity of the scoring
systems can be increased by combining them. A secondary
goal was to determine whether the utility of the scores was a
function of the age of the patient and the technical efficacy
(successful vs. unsuccessful recanalization).
Materials and Methods
Patients
From May 2009 to June 2012, all patients admitted to our
hospital within 8 h after symptom onset of an acute stroke
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L. Fjetland et al.: Neurointerventional Treatment in Acute Stroke
were considered for study inclusion. All patients underwent
cerebral computed tomography (CT). The initial examination included unenhanced CT, perfusion CT, and CT
angiography. Patients with an occlusion of M1 segment of
the middle cerebral artery (MCA, M1), internal carotid
artery (ICA), or basilar artery (BA) on CT angiography,
and with no signs of intracranial hemorrhage or distinct
demarcation of an infarction [1/3 of the vessel territory
were considered potential candidates for IAT within 8 h
after symptom onset.
Patients with a central arterial occlusion eligible for IVT
who arrived at the hospital within 4.5 h from ischemic
symptom onset were pretreated with intravenous recombinant tissue plasminogen activator (rt-PA) (Actilyse, Boehringer Ingelheim, Germany). These patients were
transferred with ongoing rtPA infusion to the angiography
suite for interventional treatment. Those patients arriving
later than 4.5 h after symptom onset were transferred
directly to the interventional laboratory. No patients were
excluded due to old age, recent surgery, or elevated INR.
The patients were included in the study after angiographically confirmed large cerebral vessel occlusion.
Revascularization Procedures
The endovascular treatment was performed by five experienced vascular interventional radiologists. The patients
early in the recruitment period were treated with intraarterial thrombolysis; later, two mechanical thrombectomy
devices were added to the therapeutic armamentarium: the
Penumbra SystemÒ (Penumbra Inc., Alamenda, CA) and
the SolitaireÒ FR Revascularization Device (ev3 Neurovascular, Irvine, CA). The performed procedures were
described in detail in a previous publication [10].
Efficacy Evaluation
Efficacy of the interventional procedure was assessed by
the frequency of recanalization of the target vessel. The
angiographic recanalization was assessed according to the
thrombolysis in myocardial infarction (TIMI) grades.
Before treatment, the patients were required to have
angiographic documentation of TIMI 0 or TIMI 1 flow in
the target vessel at the site of primary occlusion. Successful revascularization was defined by angiographic
demonstration of TIMI 2 or TIMI 3 flow in the target
vessel [23, 24]. Because arterial recanalization is an
independent predictor for good clinical outcome in stroke
patients [25], we evaluated the validity of the scoring
systems in respect of technical successful reopening of the
occluded vessel.
L. Fjetland et al.: Neurointerventional Treatment in Acute Stroke
1243
Clinical Evaluation
Statistical Analysis
Neurologic deficit was graded on admission, the first day
after intervention, and at discharge using National Institutes of Health Stroke Scale (NIHSS) [26]. Functional
status was assessed at 3 months and assigned a score on the
modified Rankin scale [27]. Good clinical outcome was
defined as mRS of 2 or less.
All statistical analyses were performed using SPSS Statistics version 20 (IBM Corporation, USA). Baseline
variables and variable changes were examined using oneway analysis of variance (ANOVA) and Pearson’s Chi
squared test as appropriate. The positive predictive value
(PPV) was calculated with 95 % confidence interval (CI).
THRIVE and HIAT Scores
Results
The THRIVE and the HIAT score are elucidated in
Table 1. For evaluation, the THRIVE scores were trichotomized into a low THRIVE score group with 0–2 points, a
medium THRIVE score group with 3–5 points, and a high
THRIVE score group with 6–9 points.
A HIAT score of 0 or 1 point was considered ‘‘low-risk’’
and 2 or 3 points was considered ‘‘high-risk’’ [23].
To evaluate whether the specificity of the scoring systems can be enhanced without introducing new parameters,
we combined both scores in an additional analysis. For this
purpose, the THRIVE score was dichotomized into a ‘‘lowmedium risk’’ group (THRIVE 0–5) and a ‘‘high risk’’
group (THRIVE 6–9). The HIAT score was used without
modifications.
Because age C80 years is an independent predictor for
poor outcome in stroke patients [28], we dichotomized our
patients around age 80 years and evaluated the validity of
the scoring systems in both age groups separately.
A total of 52 patients were included in the study. Two
patients were intubated before admission because they
were unconscious. Because both underwent an abbreviated
neurologic examination, they were assumed to have a NIHSS score[21 for the purpose of calculating THRIVE and
HIAT scores. The demographic data of the patients included in the study are listed in Table 2. Because the only
baseline variable, age was related to clinical outcome
(p = 0.004).
Fifty-two patients could be scored with the THRIVE
predictive scoring system. The data on THRIVE scores in
relation to mRS and mortality are summarized in Table 3.
The mean THRIVE score in our cohort was 4.6 (SD 1.9)
points. We found a strong correlation between the level of
predicted risk by the THRIVE score and the clinical outcome (p = 0.002). The correlation between the score and
clinical outcome was limited to the subgroup of patients
successfully recanalized (p = 0.001).
51.9 % of all patients were classified at medium risk
(THRIVE 3–5); patients categorized in this group exhibited
a heterogeneous outcome (37 % good clinical outcome).
16 of the 17 patients categorized as high-risk patients
Table 1 Calculation of the predictive scores
HIAT
THRIVE
Points
Age (year)
Table 2 Demographics of the patients
Points
Age (year)
Patients
52
Mean age (year)
70.32 ± 13.27
B 75
0
B 59
0
Age C 80 year
15 (28.8)
[ 75
1
60–79
1
Female
15 (28.8)
C 80
2
Male
37 (71.2)
Mean NIHSS at admissiona
17.4 ± 5.88
Baseline NIHSS score
Baseline NIHSS score
B 18
0
[ 18
1
Baseline glucose level
B 10
0
Baseline glucose C150 mg/dl at admissionb
6 (10.9)
11–20
2
History of hypertension
35 (67.3)
C 21
4
History of diabetes mellitus
7 (13.5)
History of atrial fibrillation
20 (38.5)
Medical history
\ 150 mg/dl
0
Diabetes mellitus
1
History of previous ischemic heart disease
5 (9.6)
C 150 mg/dl
1
Atrial fibrillation
1
History of previous brain infarction
6 (11.5)
1
0–9
a
Data missing in two patients
b
Baseline glucose value is missing in one patient
Range of possible scores
0–3
Hypertension
Range of possible scores
HIAT score [13] THRIVE score [18]
Values represent numbers of patients (%), ±SD
123
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L. Fjetland et al.: Neurointerventional Treatment in Acute Stroke
Table 3 Association of the THRIVE predictive scoring system with
poor clinical outcome (mRS C 3) and mortality by 90 days
All
Patients 52
(100 %)
mRS C 3
Mortality
THRIVE 0–2 (%)
8 (15.38)
2 (25)a
0 (0)b
THRIVE 3–5 (%)
27 (51.92)
17
(62.97)a
6 (22.2)b
THRIVE 6–9 (%)
17 (32.69)
16 (94.1)a
8 (47)b
1 (14.29)c
0 (0)d
Recanalized (TIMI 2, 3)
THRIVE 0–2 (%)
THRIVE 3–5 (%)
40 (100 %)
7 (17.5)
19 (47.5)
9 (47.37)
c
4
(21.05)d
THRIVE 6–9 (%)
Not recanalized (TIMI 0,
1)
14 (35)
1 (100)
0 (0)
(42.85)d
THRIVE 0–2 (%)
1 (8.33)
THRIVE 3–5 (%)
8 (66.67)
8 (100)
2 (25)
THRIVE 6–9 (%)
3 (25)
3 (100)
2 (66.67)
Pearson Chi square, p = 0.002
b
Pearson Chi square, p = 0.04
Pearson Chi square, p = 0.001
d
6
12 (100 %)
a
c
13
(92.86)c
Pearson Chi square, p = 0.09
(THRIVE 6–9) exhibited a poor clinical result (mRS C 3)
and the PPV for a poor outcome was 94.1 % (95 % CI
69.2–99.7). In the patient group \80 years, we found a
strong correlation between the THRIVE score and the
clinical outcome (p = 0.01). Yet in the patient group
C80 years, there was no correlation between the score and
the clinical outcome (p = 0.6). Although we found a weak
correlation between the THRIVE score and mortality in the
entire cohort (p = 0.04), the score did not correlate with
mortality in either patients group when dichotomized by
age.
Due to a missing baseline glucose level in one patient,
only 51 patients could be scored with the HIAT predictive
scoring system. The data on HIAT scores in relation to
mRS and mortality are summarized in Table 4. The mean
HIAT score was 1 (SD 0.9). We found a strong correlation
between the HIAT score and the clinical outcome
(p = 0.003) and mortality (p \ 0.001) at 90 days in the
entire cohort. The correlations between the score and both
clinical outcome (p = 0.002) and mortality (p \ 0.001)
were limited to the subgroup of patients successfully
recanalized.
A total of 66.7 % of the patients were categorized in the
low-risk HIAT group (HIAT 0–1); patients in this group
exhibited a heterogeneous clinical outcome (47.1 % good
outcome). Sixteen of the 17 patients categorized in the
high-risk group (HIAT 2–3) had a poor clinical outcome at
90 days and the PPV for a poor outcome was 94.1 %
(95 % CI 69.2–99.7). In the group of patients \80 years,
123
we found a strong correlation between the HIAT score and
the clinical outcome (p = 0.008) and mortality at 90 days
(p \ 0.001). Yet, in the patients group C80 years, there
was no correlation between the score and the clinical outcome (p = 0.6) or mortality (p = 0.05).
Taking into consideration both the THRIVE and the
HIAT score increased the number of patients identified as
‘‘high risk’’ from 17 to 22. Twelve of the patients were
categorized as high risk irrespective of the score used. With
one exception, a 92-year-old man with a NIHSS score of 19
at admission, every of the patients in this group had a
mRS [ 2, giving a PPV for poor outcome of 95.5 % (95 %
CI 75.2–99.8). On the contrary, the PPV for good outcome
was only 53 % (95 % CI 35–71), if neither THRIVE nor
HIAT score predicted high risk. Thus, only 21 of the 35
(60 %) patients with poor clinical outcome would have
been identified even if both scores had been prospectively
used (Table 5).
Discussion
We found a strong correlation between the risk of bad
outcome as predicted by the THRIVE and HIAT scores and
the actual clinical outcome in patients treated with IAT for
acute stroke. For the entire cohort, the PPV for poor outcome was 94.1 % (95 % CI 69.2–99.7) for patients deemed
to be at high risk based on the THRIVE or the HIAT score.
If both scores were taken into consideration, the PPV
increased to 95.5 % (95 % CI 75.2–99.8). By simply
combining both scoring systems, we could correctly identify nearly 15 % more patients as being at high risk.
Flint et al. [18] developed the THRIVE score based on a
cohort of patients taking part in the MERCI [9] and the
Multi MERCI trials [29]. We used the same definition of
poor outcome (mRS C 3) in our study. They found poor
outcomes at 90 days in 35.3, 56.5, and 89.4 % of the
patients in the low-, medium-, and high-risk groups
respectively. Our corresponding figures were 25, 63, and
94.1 % (p = 0.002). Hallevi et al. [13] defined a poor
outcome as mRS C 4. Patients categorized in the HIAT
low-risk group exhibited a poor clinical outcome in
56.9 %, patients categorized in the HIAT high-risk group
in 97.7 % (p \ 0.001). Although we used a wider definition of poor clinical outcome in our cohort (mRS C 3), our
figures are in line, 52.9 and 94.1 % respectively
(p = 0.003). Ishkanian et al. [30] reported a correlation
(p = 0.03) between the THRIVE score and a poor outcome
(mRS C 4) but no correlation (p = 0.07) between the
HIAT score and outcome.
The association between the two scores and the clinical
outcome was in our study limited to patients successfully
recanalized. In the group of patients not recanalized, there
L. Fjetland et al.: Neurointerventional Treatment in Acute Stroke
Table 4 Association of the HIAT predictive scoring system with
poor clinical outcome (mRS C 3) and mortality by 90 days
All
Patients 51
(100 %)
mRS C 3
Mortality
HIAT 0–1 (%)
34 (66.67)
18
(52.94)a
2 (5.88)b
HIAT 2–3 (%)
17 (33.33)
16
(94.11)a
12
(70.58)b
Recanalized (TIMI 2, 3)
40 (100 %)
HIAT 0–1 (%)
27 (67.5)
11
(40.74)c
2 (7.4)d
HIAT 2–3 (%)
13 (32.5)
12 (92.3)c
8 (61.53)d
Not recanalized (TIMI
0, 1)
11 (100 %)
HIAT 0–1 (%)
7 (63.63)
7 (100)
0 (0)
HIAT 2–3 (%)
4 (36.36)
4 (100)
4
(100 %)
a
b
Pearson Chi square, p = 0.003
Pearson Chi square, p \ 0.001
c
Pearson Chi square, p = 0.002
d
Pearson Chi square, p \ 0.001
Table 5 Association of combined THRIVE and HIAT predictive
scoring systems with modified rankin scale (mRS) by 90 days
Modified
Rankin Scale
by 90 days
THRIVE score
0–5 and HIAT
score 0–1
Patients (%)
THRIVE score
6–9 or HIAT
score 2–3
Patients (%)
Total
0–2
16 (53.3)
1 (4.5)
17
(32.7)
3–6
14 (46.7)
21 (95.5)
35
(67.3)
6
2 (6.7)
12 (54.5)
14
(26.9)
Patients
(%)
Pearson Chi square, p \ 0.001
were no associations between the scores and the clinical
outcome. None of the patients not recanalized experienced
a good clinical outcome, highlighting the vital importance
of an early reperfusion.
The association between the two scores and the clinical
outcome was limited to patients \80 years in our study.
This indicates that both scoring systems have a weakness in
predicting the risk of patients aged C80 years correctly.
Because this group of patients is a growing challenge in the
future and because it is predicted that the number of incident strokes among the elderly (age 75?) will more than
double during the next 40 years [31], the scores seem to be
insufficient to advice in choosing the right treatment concept among the elderly.
1245
Flint et al. reported mortality rates at 90 days of 5.9,
30.1, and 56.4 % in the low-, medium-, and high-risk
groups, respectively. We found no association between the
THRIVE score and the mortality rate. Hallevi et al.
reported a mortality rate of 15.8 and 43.2 %, in the ‘‘lowrisk’’ and the ‘‘high-risk’’ group respectively. Our corresponding figures were 5.9 and 70.6 %. We found a strong
correlation between the HIAT score and mortality
(p \ 0.001) at 90 days in the entire cohort. However, in
patients C80 years the score did not predict mortality.
Neither the THRIVE nor the HIAT scores proved to be
very reliable to identify patients with a good clinical outcome. A not inconsiderable number of patients with poor
neurological outcome are categorized in the low- or medium-risk groups and the PPV for good clinical outcome
was only 53 % (95 % CI 35–71), even if neither THRIVE
nor HIAT score predicted high risk. Flint et al. also was
facing the same challenge with a large medium-risk group
containing 48.4 % of their patients, exhibiting quite a
variable outcome. Thus, the scores seem to be insufficient
to unambiguously identify patients who, despite being
apparently good candidates for endovascular intervention,
will profit from a transcatheter approach.
The relatively low number of patients treated limits
somewhat the validity of the conclusions that can be drawn
from our results. Yet, our results are in the line with those
reported by Flint et al. [18] and Hallevi et al. [13], which
do support our main conclusions.
A predicting score could be an important tool in an acute
stroke treatment algorithm and it is encouraging to demonstrate that it is possible to predict clinical outcome by
combining known clinical risk factors in an algorithm.
However, the weakness of the THRIVE and the HIAT
scores is their overall lack of capability to identify patients
with a good clinical outcome and their lack to identify the
risk of patients [80 years correctly. Another weakness is
that each scoring system categorizes a not inconsiderable
number of patients with poor neurological outcome as
patients with low- or medium-risk groups. By combining
both scores, the number wrongly classified can be reduced
but still 46.7 % of the patients experiencing a poor neurological outcome are not classified in the high-risk group.
Both scores are simple to administer and fast to perform;
thus, both scores seem to be suitable as treatment decision
tools in the hyperacute stroke phase where time is scarce.
Yet, the prime strength of the two predicting scores, either
used alone or in combination is their high predictive value
to identify patients, who, despite being apparently good
candidates for IAT, do not benefit from the procedure. Use
of both scores in the stratification of patients for therapy
has the potential to provide added benefit.
However, given the clinical and economic consequences
of fruitless IAT of acute stroke, further work to refine the
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two scores is urgently needed. A new score could implement radiological and clinical characteristics and should
have a high specificity to predict good clinical outcome as
well as poor clinical outcome. A prerequisite for a treatment decision score is that it can be used independent of
patient age.
Conflict of interest Martin W. Kurz has received payment for
lectures from Bayer Health Care and Boehringer Ingelheim. Jan Petter
Larsen has received payment for lectures from Lundbeck Pharma and
is a board member of the same company. The other authors declare
that they have no conflict of interest.
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