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RESEARCH ARTICLE
Use of a Diagnostic Score to Prioritize
Computed Tomographic (CT) Imaging for
Patients Suspected of Ischemic Stroke Who
May Benefit from Thrombolytic Therapy
Wen Yea Hwong
1,2
, Michiel L. Bots
2
, Sharmini Selvarajah
2
, L. Jaap Kappelle
3
,
Zariah Abdul Aziz
4
, Norsima Nazifah Sidek
5
, Ilonca Vaartjes
2
*
1National Clinical Research Centre, Kuala Lumpur General Hospital, Kuala Lumpur, Malaysia, 2Julius
Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands,
3Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center
Utrecht, Utrecht, the Netherlands, 4Department of Neurology, Hospital Sultanah Nur Zahirah, Terengganu,
Malaysia, 5Department of Pharmacy, Hospital Sultanah Nur Zahirah, Terengganu, Malaysia
*c.h.vaartjes@umcutrecht.nl
Abstract
Background
A shortage of computed tomographic (CT) machines in low and middle income countries
often results in delayed CT imaging for patients suspected of a stroke. Yet, time constraint
is one of the most important aspects for patients with an ischemic stroke to benefit from
thrombolytic therapy. We set out to assess whether application of the Siriraj Stroke Score is
able to assist physicians in prioritizing patients with a high probability of having an ischemic
stroke for urgent CT imaging.
Methods
From the Malaysian National Neurology Registry, we selected patients aged 18 years and
over with clinical features suggesting of a stroke, who arrived in the hospital 4.5 hours or
less from ictus. The prioritization of receiving CT imaging was left to the discretion of the
treating physician. We applied the Siriraj Stroke Score to all patients, refitted the score and
defined a cut-off value to best distinguish an ischemic stroke from a hemorrhagic stroke.
Results
Of the 2176 patients included, 73% had an ischemic stroke. Only 33% of the ischemic
stroke patients had CT imaging within 4.5 hours. The median door-to-scan time for these
patients was 4 hours (IQR: 1;16). With the recalibrated score, it would have been possible
to prioritize 95% (95% CI: 94%–96%) of patients with an ischemic stroke for urgent CT
imaging.
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 1 / 10
a11111
OPEN ACCESS
Citation: Hwong WY, Bots ML, Selvarajah S,
Kappelle LJ, Abdul Aziz Z, Sidek NN, et al. (2016)
Use of a Diagnostic Score to Prioritize Computed
Tomographic (CT) Imaging for Patients Suspected
of Ischemic Stroke Who May Benefit from
Thrombolytic Therapy. PLoS ONE 11(10):
e0165330. doi:10.1371/journal.pone.0165330
Editor: Jean-Claude Baron, "INSERM", FRANCE
Received: May 16, 2016
Accepted: October 10, 2016
Published: October 21, 2016
Copyright: ©2016 Hwong et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data for the present
study was retrieved from a third party (the
Malaysian National Neurology Registry). Relevant
aggregate data are available within the paper. Due
to ethical and patient confidentiality restrictions,
individual level data cannot be made fully available.
The data is only available for authorized
researchers. For access to the data or review
purposes, approval should be obtained from the
principal investigator of the data source whom can
be contacted via zaraziz_ayie@yahoo.com.
Conclusions
In settings where CT imaging capacity is limited, we propose the use of the Siriraj Stroke
Score to prioritize patients with a probable ischemic stroke for urgent CT imaging.
Introduction
Use of CT imaging is considered the gold standard diagnostic test to distinguish between an
ischemic and a hemorrhagic stroke.[1] In areas with inadequate resources, a majority of
stroke patients do not have immediate access to CT imaging. A Malaysian national report
showed that in 2010, there were 52 machines in 134 public hospitals (39%). In private hospi-
tals, only 44% had direct access to CT imaging.[2] Access to CT imaging is also hindered by
the limited availability of ambulances to transport patients. There were 793 functioning
ambulances throughout the country in 2010. This equated to a low 0.28 per 10,000 popula-
tion[3] when compared to the expected 1 for every 10,000 population in high income coun-
tries.[4]
This limitation of resources is a major challenge to stroke care in case of time constraints.
A delay in diagnosis reduces the eligibility of patients with an ischemic stroke for thrombolytic
therapy. Previously, scores to differentiate between the types of stroke were developed based
on clinical parameters to accommodate for the shortage of CT machines. Among the scores
available include the Siriraj Stroke Score (SSS)[5], the Guys’ Hospital Score or Allen Score[6],
the Besson Score[7] and the Greek Stroke Score[8]. Although several validation studies con-
cluded that the scores were not sensitive enough in their detection of hemorrhage to replace
CT imaging[9–11], there was a consistent trend of higher predictive abilities of the SSS to rule
out a hemorrhagic stroke and thus, increases the chance of detecting an ischemic stroke.[10]
Nevertheless, there remains a need to assess the ability of the SSS to identify ischemic stroke
patients who are potentially eligible for thrombolytic therapy in the Malaysian population.
Instead of replacing CT machines, the SSS is anticipated to act as a triage for prioritization of
CT imaging.
This study was therefore conducted to examine the predictive value of the Siriraj Stroke
Score to identify patients who are likely to have an ischemic stroke and are potentially eligible
for thrombolytic therapy. The identification of these patients would allow prioritization of
urgent CT imaging and increase the number of patients that can be treated with thrombolytic
therapy.
Methods
Cohort Enrollment
Between July 2009 and December2014, 7592 patients from 14 public hospitals were registered
in the Malaysian National Neurology Registry.[12] This is by far the largest and best available
representation of the Malaysian population for stroke patients. Public hospitals cover a major-
ity of total hospital admissions in the country; 66.2% of all hospital admissions in 2014 were in
public facilities.[13]
Collection of data for this registry follows local routine clinical practice. For the present
study, we included patients above 18 years old with signs and symptoms of stroke who arrived
in the hospital 4.5 hours or less from ictus. This time frame is in accordance to local and
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 2 / 10
Funding: WYH is funded by Julius Center for
Health Sciences and Primary Care under the
Honors Track Programme. IV is funded by the
Dutch Heart Foundation for project Facts and
Figures. The Honors Track Committee and the
Dutch Heart Foundation had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript. The
Malaysian National Neurology Registry is funded
by Ministry of Health Malaysia (ID: NMRR 08-
1631-3189). Ministry of Health Malaysia had no
role in the study design, analysis and preparation
of the manuscript.
Competing Interests: The authors have declared
that no competing interests exist.
international stroke management guidelines for the eligibility of intravenous thrombolytic
therapy.[14,15] We excluded patients who received CT imaging after 15 days from ictus.
Ethical approval was obtained from the Malaysian Ministry of Health’s research ethics com-
mittee (ID: NMRR 08-1631-3189). The approval includes data collection and use of data for
secondary analysis. With a waiver of informed consent, a public notice is displayed at all partic-
ipating sites and participants have the option to opt out.
Types of Stroke
A diagnosis of either a hemorrhagic or a non-hemorrhagic stroke is based on CT imaging.
Patients with an intracerebral hemorrhage, subarachnoid hemorrhage (SAH) or ischemia with
hemorrhagic transformations were included in the category of hemorrhagic strokes. Ischemic
strokes, transient ischemic attacks (TIA) and cerebral venous thrombosis were classified as
non-hemorrhagicstrokes. More than 90% of patients in thecategory of non-hemorrhagic
strokes consisted of patients with an ischemic stroke, and therefore, the term ‘ischemic stroke’
will be used in subsequent sections for easier interpretation.
CT imaging wasinterpreted by physicians andsubsequently verified by radiologists from
the participating hospitals. Stroke scores were not calculated prior to the interpretation of CT
imaging. Therewas no possibility that knowledgeof the scores could have an influenceon the
outcome.
The Siriraj Stroke Score (SSS)
For each patient, the SSS was calculated. Clinicalvariables which are needed for this score are
listed in Table 1. Some symptoms are not available in the registry. We substituted them with
comparable variables: ‘angina’ was replaced with ‘ischemic heart disease’, and instead of ‘inter-
mittent claudication’, we took ‘peripheral artery disease’. Data were obtained via routine exam-
ination of patients during their arrival in the hospitals. History of comorbidities was verified
with their past medical records.
Clinicians who developed the original SSS score proposed two cut-off values: <-1 for ische-
mic stroke and >1 for hemorrhagic stroke.[5] For patients who score between -1 and 1, a dis-
tinction between ischemic and hemorrhagic stroke cannot be made. The equation for the
Table 1. Variables in the Original Siriraj Stroke Score.
Variables Clinical Features Score
Level of consciousness Alert 0 (x2.5)
Drowsy/Stupor 1
Coma/Semi-comatose 2
Vomiting No 0 (x2)
Yes 1
Headache No 0 (x2)
Yes 1
Diastolic blood pressure (mmHg) (x0.1)
Atherosclerotic markers (diabetes mellitus, angina or
intermittent claudication)
None 0 (x3)
One or more 1
Constant (-12)
doi:10.1371/journal.pone.0165330.t001
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 3 / 10
original score is:
Logit Probability ðHemorrhagic stroke=Non hemorrhagic strokeÞ
¼2:5level of consciousness þ2headache þ2vomiting þ0:1
diastolic blood pressure 3atherosclerotic markers 12
Statistical Analysis
First, the proportion of missing data was evaluated for each predictor (S1 Table). We carried
out multiple imputation with m = 10 (number of imputations) to reduce the extent of bias
resulting from missing data.[16] For counts and descriptive statistics, we took the modes of
each imputed variable per individual patient. In the event of multiple modes, the mode with
highest value was taken. Multiple imputation was conducted with R version 3.1.1.[17]
Second, we fitted the SSS on our dataset. Performance of the predictive ability of the score is
evaluated via discrimination: area under the curve (AUC) of receiver operating characteristics
(ROC) curves is calculated[18]; and via calibration: the slope and intercept of calibrationplots
are estimated to assess differences between predicted and observed probabilities[19].
Thirdly, the analysis was extended with updating methods to obtain a ‘best, fitted score’.[20]
We recalibrated the intercept and the slope and adjusted the regression coefficients for predic-
tors ‘level of consciousness’ and ‘headache’. Details of the updatingmethods and operationali-
zation of each predictor are shown in S1 and S2 Tables. Furthermore, performance of the
recalibrated score is tested for its internal validity via bootstrapping. With bootstrap analysis,
the shrinkage factor and the optimism corrected AUC are calculated.[20]
Lastly, we took different cut-off values of the recalibrated SSS to assess its diagnostic perfor-
mance in distinguishing between a hemorrhagic and an ischemic stroke. We also attempted to
identify possible effect modifications for the score across age categories, sex and cardiovascular
risk factors including hypertension, hyperlipidemia and atrial fibrillation. As an additional
analysis, we validated the recalibrated score in a cohort where the inclusion time frame was
expanded to 6 hours from ictus. This is to accommodate ischemic stroke patients who were
potentially eligible for intra-arterial thrombolytic therapy.[14,15]
Statistical analysis was performed using Stata version 13.0.[21]
Results
Baseline Characteristics
Of 2176 patients who were included, 57% were males. The mean age was 62 (SD: 12) years
(Table 2). Cardiovascular risk factors were common: nearly three quarters of patients had
hypertension (73%), 40% with diabetes mellitus and 28% had dyslipidemia. Only 4% of the
included patients had a history of atrial fibrillation whereas almost 50% of them were current
smokers. Mean blood pressure upon arrival was 171mmHg (SD:36) for systolic and 94mmHg
(SD:21) for diastolic. The median door-to-scan time was 4 hours (IQR: 1;14) and the median
time taken for patients to arrive in the emergency departments was 2 hours (IQR: 1;3).
Fitting the Siriraj Stroke Score
Initial calibration of the original SSS showed a poor fit. There was overestimation at higher
observed probabilities and underestimation at lower observed probabilities. The recalibrated
score, in which the intercept and weights of the individual determinants were adjusted showed
a better fit with an AUC of 0.80 (95%CI: 0.78–0.83). Post bootstrap analysis, a shrinkage factor
of 0.99 and an optimism for theAUC of 2.18x10
-5
were found. The optimism-corrected AUC
was similar to that of the recalibrated score (results in S1 Fig and S3 Table). After simplification
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 4 / 10
of the coefficients,the equation for the recalibrated score is:
Logit Probability ðHemorrhagic stroke=Non hemorrhagic strokeÞ
¼1:0level of consciousness þ0:3headache þ0:7vomiting þ0:03
diastolic blood pressure 1:0atherosclerotic markers 4:5
Table 2. Baseline Characteristics.
Characteristics Patients in the study
n = 2176
Mean age(years) ±SD*62 ±12
Sex, n (%)
Male 1247 (57)
Female 929 (43)
Ethnic group, n (%)
Malay 1816 (83)
Non-Malay 360 (17)
Co-morbidities, n (%)
Hypertension 1584 (73)
Diabetes Mellitus 861 (40)
Dyslipidemia 615 (28)
Ischemic Heart Disease 310 (14)
Atrial Fibrillation 84 (4)
Previous TIA/stroke events 453 (21)
Life-style factors, n (%)
Obesity 173 (8)
Smoking status
Current 1063 (49)
Previous smoker (quit >30 days) 400 (18)
Never 713 (33)
Clinical presentation during admission
Mean Systolic BP(mmHg) ±SD 171 ±36
Mean Diastolic BP(mmHg) ±SD 94 ±21
Mean Pulse rate (bpm) ±SD 84 ±19
Median oxygen saturation rate (Sp02)% (IQR)
†
99 (98;100)
Headache 597 (27)
Vomiting 447 (21)
Seizure at onset of stroke 209 (10)
Median NIHSS
‡
score (IQR) 10 (3;22)
Level of consciousness
Alert 1402 (64)
Drowsy/Stupor 384 (18)
Semicomatose/Coma 390 (18)
Duration
Median Time of onset to door (hours) (IQR) 2 (1;3)
Median Time of door to scan (hours) (IQR) 4 (1;14)
Median Time of onset to scan (hours) (IQR) 6 (4;16)
*SD:standard deviation,
†
IQR: interquartile range,
‡
NIHSS: National Institute of Health Stroke Scale
doi:10.1371/journal.pone.0165330.t002
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 5 / 10
Potential effect modifierswere tested and no significantinteractions were found.
Use of the Recalibrated Siriraj Stroke Score in Prioritization of CT
Imaging
In the present cohort, 73% (n = 1594) of the patients had an ischemic stroke. Only one third of
these ischemic stroke patients (33%) who were potentially eligible for thrombolytic therapy
received CT imaging within the therapeutic window period of 4.5 hours.
Table 3 provides results of the application of the recalibrated SSS for identification of an
ischemic stroke. Depending on the choice of cut-off values, results differ. At a threshold of 0
(SSS equal or higherthan 0 defines a hemorrhagic stroke),95% (n = 1519) of the ischemic
stroke patients would have been correctly diagnosed, thus prioritized for urgent CT imaging.
By applying the recalibrated SSS, 83% of the cohort would have been sent for urgent CT
imaging. Ofthose, 84% would have had an ischemic stroke and 16% wouldhave been diag-
nosed with a hemorrhagic stroke. Around 5% of the ischemic stroke patients would not have
immediate CT imaging (Table 3).
Results from the additional analysis where the inclusion time frame was expanded from 4.5
hours to 6 hours (n = 2658) showed similar results to the above (S4 Table).
Discussion
Despite arriving withinthe therapeutic time for thrombolytictherapy, two-thirds of the ische-
mic stroke patients did not receive urgent CT imaging by 4.5 hours. This delay in diagnosis
inevitably eliminate their potential eligibility for thrombolytic therapy. With the recalibrated
SSS, 95% of patients with an ischemic stroke who were potentially eligible for thrombolytic
therapy, could be prioritized for urgent CT imaging.
Our results on the discriminative power of the SSS were comparable with two validation
studies who had reported an AUC of 0.78 (95% CI: 0.75–0.82)[22] and 0.80(95% CI not given)
[23]. Previous studies including a study of smaller sample size from Malaysia reported that the
original SSS has failed to achieve a high sensitivity to detect hemorrhagic stroke.[9–11,24] This
is particularly so in Western countries.[25,26] Nevertheless, higher specificities for the score
were found. This increasesthe predictive ability of the score to identify an ischemic stroke. For
example, Mwita et al[10] in a systematic review reported consistently higher specificities of the
SSS with a range from 65%–99% compared to its corresponding sensitivities in 18 validation
Table 3. Application of the Recalibrated Siriraj Stroke Score at Different Thresholds.
Cut-off
values
Sensitivity with
95% CI (%)
Specificity with
95%CI (%)
PPV
†
with
95% CI (%)
NPV
†
with
95% CI (%)
Number of missed
ischemic cases (%)
Number of
overdiagnosed cases, n
(%)
Number of urgent
CT imaging (%)
>= -1.5 84 (81–87) 63 (60–65) 45 (42–48) 92 (90–93) 591 (37) 91 (8) 1094 (50)
>= -1.0 74 (70–77) 80 (78–82) 57 (54–61) 89 (87–91) 320 (20) 154 (11) 1428 (66)
>= -0.5 62 (58–66) 90 (89–92) 69 (65–73) 87 (85–88) 158 (10) 223 (13) 1659 (76)
>= 0*49 (44–53) 95 (94–96) 79 (74–83) 84 (82–85) 75 (5) 300 (16) 1819 (83)
>= 0.5 34 (31–38) 98 (97–99) 88 (83–92) 80 (79–82) 28 (2) 382 (20) 1948 (90)
>= 1.0 19 (16–23) 100
‡
(99–100) 93 (87–97) 77 (75–79) 8 (0.5) 471 (23) 2057 (95)
>= 1.5 8 (6–10) 100
‡
(99.5–100) 96 (85–99) 75 (73–77) 2 (0.1) 537 (25) 2129 (98)
*cut-off value used in this study,
†
PPV: positive predictive value,
‡
NPV: negative predictive value.
doi:10.1371/journal.pone.0165330.t003
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 6 / 10
studies. This is in agreement with our specificity findings. The specificity for the recalibrated
score was further improved with a choice of a different cut-off value. Moreover, parallel to our
aims, some of the studies[22,27] supported the use of the higher predictive rule-out ability of
the SSS to detect ischemic stroke patients in areas with insufficient resources.
Previous validation studies focused on the ability of the SSS to replace CT imaging.[5,9–
11,22] Here, we propose to use this score to prioritize patients who are likely to have an ische-
mic stroke and are potentially eligible for thrombolytic therapy for urgent CT imaging. Up to
the present time, only few hospitals in the country are administering thrombolytic therapy.
Reasons for this poor uptake include strict exclusion criteria such as prior use of Vitamin K
antagonist, uncertainty over its benefit for elderly patients and patients with mild or very severe
stroke and most importantly, a narrow therapeutic window time.[28] Although this is a similar
picture globally[29], lack of infrastructure is often an additional barrier to the administration
of this therapy. The present study focuses on an aspect which is common in developing regions;
time delays resulting from a shortage of CT machines. Other criteria which deny patients from
their eligibility for thrombolytic therapy were not taken into account in our selection of the
best patients for prioritization of CT imaging.
Establishing a clinical diagnosis of an ischemic stroke with the SSS will thus, allow prioriti-
zation of the right patients for the right treatment at the right time. Moreover, there are only 5
clinical variables needed with the SSS; all easily retrieved during initial assessment of patients
with symptoms of stroke. The simplicity of this score and its practical application has been
commended in several studies.[5,10] Nevertheless, we are aware that the recalibrated SSS may
not be easily memorized or applied without a calculator. Future implementation of this score
with a possible smartphone application will be useful.
Our study had a sufficient sample size to validate the score. We performed multiple imputa-
tions to minimize possible biases from missing data. Moreover, instead of developing a new
score, we chose to revise the original SSS by applying updating methods. In this respect, the
score was adjusted to the new validated population without losing prior information from the
development dataset.[20,30]One limitation of the study is the lack of information on stroke-
mimicking diagnoses. Nevertheless, a huge majority of patients with stroke symptoms do have
a diagnosis of a stroke. Previous studiesshowed varying rates of stroke mimicsfrom 9–19%
[31–33]. Selection bias from our selection of cohort should therefore be minimal.
There are a few important points to be emphasized with regards to the score. First, there is
no intention to deprive patients from CT imaging. All suspected-for-stroke patients should
receive CT imaging for diagnostic purposes. Our target patients for prioritization are ischemic
stroke patients who reach the hospital within 4.5 hours because there is a tight time constraint
to maximize the benefits from thrombolytic therapy. In our cohort, despite having a similar
median duration of time taken to arrive at the hospital from stroke onset, patients with hemor-
rhagic stroke were found to have a shorter door-to-scan timein comparison to ischemic stroke
patients. The median door-to-scan time was 2 hours (IQR:1;8) for the former and twice as long
for the latter. While we acknowledge the urgency of a surgical procedure for patients who are
suspected of a subarachnoid hemorrhage, to our best knowledge, there is no specific window
period to perform surgical coiling or clipping.[34,35]
Second, the aim of this score is to guide decisions and not to overrule clinical concerns.
Other factors which may influence a physician’s judgment in prioritizing patients who are sus-
pected of a stroke for immediate CT imaging include age, other comorbidities and severity of
the condition. Third, this score was recalibrated to the Asian or specifically, the Malaysian pop-
ulation. Differencesin terms of prevalence of hemorrhagic stroke and other cardiovascular risk
factors between populations may limit the generalizability of the score’s utility. The perfor-
mance of this recalibrated score should be tested prior to its application in clinical practice for
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 7 / 10
other populations. Fourth and most importantly, at the cut-off value chosen, 5% of ischemic
stroke cases were underdiagnosed. We took the threshold of 0 to minimize this proportion of
patients and at the same time, finding the best balance between false positives and false nega-
tives. This may be less than ideal but in places that lack infrastructures,choices have to be
made and we consider this as the best alternative available. Preferences of choosing specific
cut-off values may differ according to the availability of resources in respective regions. With
the threshold chosen, we would have to prioritize 83% of patients for urgent CT imaging.
While prioritization improves efficiency in hospitals with limited CT machines, foreseeable
challenges lie in hospitals without CT machines that require inter-hospital transfers for urgent
CT imaging. One would be the capacity to transport these patients to hospitals with CT
machines available. Should a shortage in this aspect occur, cut-off values would have to be
reduced but, at the expense of a higher proportionof missed ischemic stroke cases for urgent
CT imaging. Another relevant point to note is the influence of the duration for inter-hospital
transfers on the eligibility for thrombolytic therapy. Having said that, about 50% of the sus-
pected patients in our cohort arrived at the hospital within 2 hours fromthe onset of their
symptoms. Priorities therefore, should be given to these patients once they scored below 0 (sus-
pected ischemicstroke) for immediate stabilization and transfer for urgent CT imaging.
Conclusions
While the best option is still to have immediate access to CT imaging for every stroke patient, a
shortage of CT machines would probably remain as a problem in the near future. Prioritization
with the Siriraj Stroke Score aims to reduce the issues of insufficientresources. More impor-
tantly, its application is targeted tooptimize stroke care especially for ischemic stroke patients
with time-dependent therapy.
Supporting Information
S1 Fig. Comparison of CalibrationPlots Prior to (original score) and after (recalibrated
score) Updating Methods.
(TIF)
S1 Table. Proportion of Missing Data and Operationalizationof Predictors.
(DOCX)
S2 Table. Updating Methods.
(DOCX)
S3 Table. Regression Coefficients for Each Predictor by Methods.
(DOCX)
S4 Table. Application of the RecalibratedSiriraj Stroke Score at Different Thresholds
(expanded time window of 6 hours).
(DOCX)
Acknowledgments
We thank the Director General of Ministry of Health, Malaysia for his permission to publish
this manuscript. We are grateful to Dr. Peter Zuithoff from the Julius Support for his expert
statistical advices. Our sincere thanks also goes to personnel from all participating hospitals for
their contribution in the data collection.
Use of a Diagnostic Score to Prioritize CT Imaging
PLOS ONE | DOI:10.1371/journal.pone.0165330 October 21, 2016 8 / 10
Author Contributions
Conceptualization:WYH MLB IV LJK.
Formal analysis: WYH MLB IV.
Methodology: WYH MLB IV.
Writing – original draft: WYH MLB IV.
Writing – review & editing: LJK SS ZAA NNS.
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