Content uploaded by Azan Nyundo
Author content
All content in this area was uploaded by Azan Nyundo on Mar 04, 2023
Content may be subject to copyright.
Content uploaded by Azan Nyundo
Author content
All content in this area was uploaded by Azan Nyundo on Aug 28, 2022
Content may be subject to copyright.
STUDY PROTOCOL
Predictors of post-stroke cognitive
impairment at three-month following first
episode of stroke among patients attended at
tertiary hospitals in Dodoma, central
Tanzania: A protocol of a prospective
longitudinal observational study metadata
Alphonce BarakaID
1,2
, John Meda
1,3
, Azan NyundoID
4,5
*
1Department of Internal Medicine, School of Medicine & Dentistry, The University Dodoma, Dodoma,
Tanzania, 2Department of Internal Medicine, The Benjamin Mkapa Hospital, Dodoma, Tanzania,
3Department of Cardiology, The Benjamin Mkapa Hospital, Dodoma, Tanzania, 4Department of Psychiatry
and Mental Health, School of Medicine, The University of Dodoma, Dodoma, Tanzania, 5Division of
Psychiatry, Department of Internal Medicine, The Benjamin Mkapa Hospital, Dodoma, Tanzania
*azannaj@gmail.com,azan.nyundo@udom.ac.tz
Abstract
Introduction
Neurocognitive deficits after stroke are a common manifestation and pose a significant
impact on the quality of life for patients and families; however, little attention is given to the
burden and associated impact of cognitive impairment following stroke. The study aims to
determine the prevalence and predictors of post-stroke cognitive impairment (PSCI) among
adult stroke patients admitted to tertiary hospitals in Dodoma, Tanzania.
Methodology
A prospective longitudinal study is conducted at tertiary hospitals in the Dodoma region,
central Tanzania. Participants with the first stroke confirmed by CT/MRI brain aged 18
years who meet the inclusion criteria are enrolled and followed up. Baseline socio-demo-
graphic and clinical factors are identified during admission, while other clinical variables are
determined during the three-month follow-up period. Descriptive statistics are used to sum-
marize data; continuous data will be reported as Mean (SD) or Median (IQR), and categori-
cal data will be summarized using proportions and frequencies. Univariate and multivariate
logistic regression analysis will be used to determine predictors of PSCI.
Introduction
Stroke is the leading cause of death and disability; approximately sixty-seven million people
worldwide suffer their first stroke yearly, of which close to six million die and five million live
PLOS ONE
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 1 / 15
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
OPEN ACCESS
Citation: Baraka A, Meda J, Nyundo A (2023)
Predictors of post-stroke cognitive impairment at
three-month following first episode of stroke
among patients attended at tertiary hospitals in
Dodoma, central Tanzania: A protocol of a
prospective longitudinal observational study
metadata. PLoS ONE 18(3): e0273200. https://doi.
org/10.1371/journal.pone.0273200
Editor: Tommaso Martino, Policlinico Riuniti of
Foggia: Neuroscience Department, S.C.
Ospedaliera of Neurology-Stroke Unit, ITALY
Received: August 3, 2022
Accepted: February 3, 2023
Published: March 2, 2023
Copyright: ©2023 Baraka 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 will be available
and shared as per agreement of terms and
conditions once the the data collection is
completed.
Funding: The author(s) received no specific
funding for this work.
Competing interests: The authors have declared
that no competing interests exist.
with associated disabilities [1,2]. The incidence of stroke often presents diverse outcomes,
including neurocognitive impairment, which significantly impacts the quality of life, increased
health care cost, loss of income, and social isolation for the patients [3–5].
PSCI prevalence ranges from 35 to 92 percent [6–8]; among the few studies conducted in
Sub-Saharan Africa, a three months prevalence of 40% was reported in Nigeria and a year
prevalence of 34% was observed in Ghanaian stroke survivors [9,10]. Several factors may con-
tribute to the discrepancy in prevalence across settings, differences in the screening and diag-
nostic tools used to assess PSCI in different studies such as MoCA, MSSE, or
neuropsychological test could partly explain the phenomenon, furthermore, the timing of
screening for cognitive impairment following a stroke, ethnicity, and cultural and educational
backgrounds may also predict the differences [11]
While an episode of stroke is an independent predictor for cognitive impairment, specific
patient may play a role in the development of PSCI. These include, advanced age, female gen-
der, fewer years of formal education, alcohol consumption, and cigarette smoking have been
linked to cognitive impairment after stroke. Cardiometabolic conditions such as, hyperten-
sion, diabetes, dyslipidemia, atrial fibrillation, stroke-specific characteristics, and neuropsychi-
atric symptoms at baseline have all been linked PSCI [12–17].
Therefore, the objective of the study is to assess the prevalence and predictors of early post-
stroke cognitive impairment after the first episode of stroke among patients admitted at ter-
tiary hospitals in Dodoma, Tanzania.
Materials and methods
Study aims
1. To determine the change in prevalence of cognitive impairment from baseline at one
month to three months following the first stroke among adult patients admitted at tertiary
hospitals in Dodoma, Tanzania.
2. To determine the incidence of improvement in cognitive functioning from the baseline at
one month to three-months following the first stroke episode among adult patients admit-
ted at tertiary hospitals in Dodoma, Tanzania.
3. To determine the predictors of post-stroke cognitive impairment at three-month after the
first stroke among adults admitted at tertiary hospitals in Dodoma, Tanzania.
4. To determine the disability after the first stroke survivors at one, three, and six months
among adults admitted at tertiary hospitals in Dodoma, Tanzania.
5. To determine the quality of life after the first stroke at baseline, one, three and six months
among adults admitted at tertiary hospitals in Dodoma, Tanzania.
Study design
A prospective longitudinal observational study
Study setting
This study is currently ongoing in the Internal Medicine Departments of the Dodoma
Regional Referral Hospital (DRRH) and Benjamin Mkapa hospital (BMH) with a bed capacity
of 480 and 400, respectively. The two hospitals cover the estimated 2.5 million population in
the Dodoma region as per the 2012 census (18). The hospitals also serve the neighboring
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 2 / 15
districts of Singida, Iringa, Manyara, and Morogoro regions. According to local statistics,
stroke is one of the leading causes of admission to referral hospitals in Dodoma, accounting
for 15 percent of all monthly admissions. In addition, Dodoma regional Referral Hospital and
Benjamin Mkapa Hospital are the designated teaching hospital for the University of Dodoma
for medical training in both undergraduate and residency programs. With its well-built infra-
structure, the Benjamin Mkapa Hospital is equipped with neuroimaging services including CT
scans and MRI serving Dodoma and the central part of Tanzania as a whole.
Sample size estimation
The sample size will be estimated utilizing formula for proportion in prospective cohort study
[18]
n¼
Za=2ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
rþ1
r
pð1pÞ
qþZbffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
p1ð1p1Þ
rþp2ð1p2Þ
q
2
ðp1p2Þ2
p ¼ p2þrp1
rþ1
r = ratio between the two groups
p
1
= PSCI three-month prevalence (obtained from literature)
p
2
= PSCI three-moth prevalence observed or expected from the study
p
1
–p
2
= effect size
Z
β
= standard normal variate for statistical power
Z
α/2
= standard normal variate for significance level
The prevalence of PSCI at 3 months based on MoCA score <23 (a cut off used to define
PSCI in this study) is 24% this figure is cited from a study conducted in Taiwan [19]
The one-month prevalence in this study is expected to be 20%
Therefore;
r = 1
p
1
= 24%
p
2
= 20%
p
1
–p
2
= 4.5%
Z
β
= 0.84 for statistical power of 80%
Z
α/2
= 1.96 for significance level of 95%
N = 130
Considering the 30% attrition rate in our setting [20]
Therefore, the minimum sample size estimated is 170 patients.
Inclusion criteria
1. Patients aged 18 years and above who are admitted with the first episode of stroke
2. Able to provide informed consent or a proxy consent from a close relative in case the
patient is incapable
3. Adults patient with first-ever stroke presenting within 14 days and confirmed by CT scan
or MRI brain
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 3 / 15
Exclusion criteria
1. Patient with traumatic intracerebral haemorrhage
2. Patient with intracerebral haemorrhage due to tumour
3. Patient with severe sensory impairment (blindness and deafness)
4. Patient with Transient Ischaemic Attack (TIA)
5. Patient with subarachnoid haemorrhage
6. Patients with previous neurological disorders such as epilepsy
Primary outcome
The outcome of interest is post-stroke cognitive impairment, which will be evaluated by a cer-
tified investigator one month after stroke onset as a baseline and again three months later [21].
The cognitive impairment will be assessed using Montreal cognitive assessment (MoCA) tools,
version 7.0, but participants with less than 12 years of education will receive an additional
point. The cognitive impairment will be set at a cutoff score of 23 out of 30 [22]. The cognitive
decline will be defined as a reduction in MoCA score by two or more points between baseline
assessment at one month and the second evaluation at three months, and cognitive improve-
ment as an increase of two or more points [23]
Secondary outcomes
Disability. At baseline, one month, three months, and six months after study enrollment,
the Modified Rankin Scale (mRS) was used to evaluate the outcomes of stroke and the severity
of disability following a stroke. This has a value of 0 for no symptoms, 1 for no major
impairment, 2 for mild impairment, 3 for moderate impairment, 4 for moderately severe
impairment, 5 for severe impairment, and 6 for death [24].
Quality of life. The Lawton-Brody Instrumental Activities of Daily Living Scale, is a
prominent evaluation of Instrumental Activities of Daily Living Scale (IADLs) that has been
validated in prior research involving stroke and cognitive impairment [25]. Ability to use the
toilet, shopping, food preparation, housekeeping, laundry, method of transportation, responsi-
bility for own medication, and ability to manage finances were the original eight items used in
this study [26] where stroke survivors will be assessed at one, three and 6 months.
Study variables
Aim 1 study variables. The variables address the change of prevalence of PSCI at one
month and three months using MoCA, which constitutes key cognitive domains including
visual-spatial executive functioning, sentence repetition, and a phonemic fluency task, short-
term memory, abstraction, attention and calculation, and orientation (time and space) (See
Table 1 for a listing and brief explanation of the variables for the Aim 1).
Aim 2 study variables. Assess the unit improvement of cognitive functioning from the
baseline (at one month) to the three-month point after the stroke episode. A minimum of two
Table 1. Summary and description of objective number 1 variables of the study.
Variable Method of measurement Operational definition Level of measurement
Post-stroke cognitive impairment at 1- and 3 months post-stroke Patient assessment MoCA <23 Dichotomous
https://doi.org/10.1371/journal.pone.0273200.t001
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 4 / 15
or more points decline in standardized MoCA between the time intervals will be considered a
significant decline [23]. (See Table 2 for a listing and a brief explanation of the variables for
Aim 2).
Aim 3 study variables. The variables address the predictors of PSCI at three months;
these include Age (in years), sex, alcohol use, smoking history, history of diabetes mellitus, dys-
lipidemia, atrial fibrillation, post-stroke depression, apathy, stroke type and characteristic (hae-
morrhagic/ischaemic, cortical/sub-cortical), stroke (infarct/hematoma) volume, presence of
Leukoaraiosis or brain atrophy (See Table 3 for listing and a brief explanation of the variables
for the Aim 3).
Aim 4 study variable. Assess the disability of stroke survivors using modified Rankin
Scale (mRS) at baseline, one month, three months and at 6 months post stroke (See Table 4 for
listing and a brief explanation of the variables for the Aim 4)
Table 2. Summary and description of objective number 1 variables of the study.
Variable Method of
measurement
Operational definition Level of
measurement
Incidence of cognitive improvement at 3 months
post-stroke
Patient assessment 2 improvement in MoCA scores from baseline (one month) to
three months
Dichotomous
https://doi.org/10.1371/journal.pone.0273200.t002
Table 3. Summary and description of objective number 3 variables of the study.
Variable Method of measurement Operational definition Level of
measurement
Age (years) Medical records/patient
report
Age in years Continuous
Sex Medical record/patient
report
Male versus female Dichotomous
Alcohol use Patient report, interview On average 2 drinks/day for males and 1 drink for females (previous drinker: ex
drinker for more than 1 year)
Dichotomous
Smoker Patient report, interview 2 cigarettes per day in men and 1 per day in women Dichotomous
Former smoker Patient report, interview who abstained from smoking for more than 12 months Dichotomous
Current smoker Patient report, interview Smoking in the past 12 months Dichotomous
Hypertension in
(mmHg)
Medical record/patient
report/assessment
Previously receiving antihypertensive medication or when the patient was previously
diagnosed with hypertension or detecting blood pressure of 140/90 mm/Hg for two
measurements
Dichotomous
Diabetes Patient report/medical
records/blood sample
Previously on oral hypoglycaemic agents/insulin treatment or had the diagnosis of any
type of DM or FBG 126mg/dl or RBG 200 mg/dl or glycosylated haemoglobin of
6.5%
Dichotomous
Hyperlipidaemia Medical record/patient
report/blood sample
Previous had history of hyperlipidaemia or using lipid-lowering medication or total
cholesterol 200 mg/dl, LDL cholesterol 100 mg/ dl, and HDL-cholesterol <40 mg/
dl for men or <50 mg/ dl for women, and/or serum triglyceride level 150 mg/ dl
Continuous
Atrial fibrillation Medical records The absence of P waves and irregular-irregular RR interval Dichotomous
Stroke severity Patient report/assessment NIHSS scale (1–42) Continuous
Post-stroke Depression Assessment PHQ-9 (1–27) Continuous
Apathy Assessment AES >38 Continuous
Stroke characteristics
Type
1. Volume of infarct/
hematoma
Medical records IS: hypodensity on CT scan/hypointense on MRI
ICH: hyperdense on CT scan/hyperintense on MRI Stroke volume: ellipsoid method A
+B+C/2,
Dichotomous
Continuous
Leukoaraiosis Medical records Bilateral Areas of patchy or diffuse hypodensity on CT or white matter hyperintensity
on MRI
Dichotomous
Brain atrophy Medical records the width of the third ventricle is less than 5 mm Dichotomous
Occlusion site Medical records through
MRI findings
Areas occluded: Anterior Cerebral Artery, Middle Cerebral Artery, Vertebrobasilar
artery, Isolated Internal Carotid Artery and T-type.
Categorical
https://doi.org/10.1371/journal.pone.0273200.t003
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 5 / 15
Aim 5 study variable. Assess the quality of life of stroke survivors using eight items Law-
ton-Brody Instrumental Activities of Daily Living Scale at one month, three months and six
months (See Table 5 for listing and a brief explanation of the variables for the Aim 5).
Participants’ characteristics
Participants are adults aged 18 years or older admitted to the Internal Medicine wards of either
DRRH or BMH with a diagnosis of the first stroke as per the World Health Organization,
defined as "rapid development of clinical signs of focal or global disturbance of cerebral func-
tion lasting more than 24 hours or leading to death, with no apparent cause other than vascular
origin" and confirmed by CT scan or MRI, with the duration of symptoms lasting not more
than 14 days [27].
Data collection process
Evaluation of the participants. As it stands, 100 patients who meet the inclusion criteria
have been enrolled since June of 2021. Participants who provided informed consent are inter-
viewed using a structured questionnaire that collects demographic data such as age, gender,
and level of education. A minimum of two contacts, one of the patient’s and that of the next of
kin, are recorded. Information regarding potential predictors of PSCI are also collected, these
include, alcohol consumption history (defined as alcohol consumption within the past 12
months), with an emphasis on duration and frequency [28,29]. Duration and number of ciga-
rettes packs per day, the history of current smoking, defined as smoking within the past year,
is also obtained [30]. A history of Hypertension (defined as a history of Hypertension or the
use of antihypertensive medications) and diabetes (defined as a history of diabetes or the use
of diabetic medications) are documented [31]
Clinical variable measurement
Post stoke cognitive impairment. At one and three months after a stroke, Montreal cog-
nitive assessment (MoCA) measures cognitive impairment; participants with a MoCA score
of <23/30 are considered to have screened positive for cognitive impairment [22]. Compared
to an initial cutoff score of 26, a MoCA score of 23 is considered more sensitive and lowers the
false positive rate and exhibits overall improved diagnostic accuracy [32]. [33] (33)(33) The
use of MoCA has been verified in Tanzania among the older population, a score of 22 indicates
a cognitive impairment with a sensitivity of 90% and specificity of 80% [33].
Table 4. Summary and description of objective number 4 variables of the study.
Variable Method of measurement Operational definition Level of measurement
Disability Modified Rankin Scale 0-no symptoms,
1-no significant disability,
2-slightly disability,
3-moderate disability,
4-moderate-severe disability,
5-severe disability and
6-dead.
Likert scale
https://doi.org/10.1371/journal.pone.0273200.t004
Table 5. Summary and description of objective number 5 variables of the study.
Variable Method of measurement Operational definition Level of measurement
Quality of life 8 item—Lawton Instrumental Activities of Daily Living Scale Any degree of difficulty (score 0) Dichotomous
https://doi.org/10.1371/journal.pone.0273200.t005
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 6 / 15
Given that the MoCA scale is less sensitive to milder forms of cognitive impairment and
susceptible to low educational levels, an additional point is usually added for those with less
than 12 years of formal education [34]. The use of MoCA instead of the ideal comprehensive
neuropsychological battery may reduce the diagnostic accuracy, MoCA remains among few
reliable scales in screening of cognitive functioning in a pragmatic clinical setting, indeed,
MoCA assess cognitive domains that reflects similar constructs to the measurements of com-
prehensive neuropsychological battery [35]
Post-stroke depression. The Patient Health Questionnaire (PHQ)– 9 with a total score of
27 is used to screen stroke survivors for post-stroke depression; a score of 1–4 is considered
minimal depression, 5–9 as mild depression, 10–14 as moderate depression, 15–19 as moder-
ately severe depression, and 20–27 as severe depression. At a PHQ score of 15, the likelihood
of having a major depressive disorder is marked. (Kroenke, Spitzer, & Williams, 2001). In
studies, the diagnostic validity of the 9-item PHQ-9 has been proven for Major Depressive Dis-
order; a PHQ-9 score of 10 indicated an 88 percent sensitivity and an 88 percent specificity
[36]. Individuals with a low PHQ-9 score of 4 had a 1 in 25 risk of becoming depressed [37]. A
study done in Tanzania proved that the PHQ-9 is the right tool for screening depressive symp-
toms equivalent to a major depressive episode in primary health care settings. The results
favour a cut off score of 9, with a sensitivity of 78% and a specificity of 87% for depressive
symptoms equivalent to a major depressive episode [38]
Post-stroke apathy. Apathy is evaluated at one month using the apathy evaluation scale;
those who met the criteria scored more than 38. This cutoff score (EAS >38) has sensitivity
and specificity of around 80% and 100%, respectively [39], to identify suggestive apathy symp-
toms [40]
Blood pressure measurement. A blood pressure (BP) reading are measured using an
automated digital machine of AD Medical Inc. brand, keeping with the 2018 AHA/ACC
Hypertension guideline for standard measurement of BP [41]. The affected arm is avoided to
minimize false readings from the impact of muscle tone changes; Hypertension will be defined
as BP 140/90 mmHg after three different reading measured at least 5 minutes apart or a
patient with a known history of hypertension or a patient on antihypertensive medications
[42].
Radial pulse measurement. Two operators assess the radial pulse measurement; "Opera-
tor 1" listens to the heart sounds with a stethoscope, while "operator 2" palpates the radial pulse
while the patient is seated. When both operators are ready, a timer will be utilized to begin
counting simultaneously. The technique is repeated, and the heart rate is recorded after 1 min-
ute. To eliminate bias, the two operators switch roles on different patients. The difference
between the rates counted by the two operators at the end of one minute are used to determine
the apex-pulse deficit. A deficit of ten or more is considered indicative of atrial fibrillation with
sensitivity and specificity of 62.8% and 85.7% respectively [43]. Furthermore, each operator
assigns a regular or irregular rhythm to the beat.
Stroke severity. On the day of enrollment, stroke clinical presentations are recorded, and
the NIHSS will be used to categorize stroke severity as minor, mild, moderate to severe [44]
Laboratory and imaging investigations
Collection of blood sample. The laboratory works for the study are based on standard
operating procedures from credited Dodoma Regional Referral Hospital. Each participant will
be asked to consent to venipuncture and finger prick then a laboratory technician follows the
aseptic procedure before taking blood samples. Before sample collection, tubes [EDTA (K2/
K3) sodium fluoride plain, no additives] are labeled with the hospital registration number
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 7 / 15
corresponding to the patient then a tourniquet is placed proximally on the upper arm approxi-
mately 60cm above the elbow joint. The intended site of venipuncture is cleaned with 70%
methylated spirit in an enlarging circulatory pattern, and the area is left to dry for 20 seconds.
Then 10mls of venous blood are taken from each arm using a 5cc syringe for lipid profile
(HDL, LDL, Total Cholesterol, and Triglycerides). Then the tourniquet is removed, and the
site of venipuncture pressed with a cotton swab to arrest bleeding. After disposing of the syrin-
ges and using gloves, the blood samples are transported into a cool box to a credited DRRH
laboratory within three hours of sample collection. However, hemolyzed blood is not be pro-
cessed rather venipuncture will be repeated. The serum sample is separated from whole blood
by centrifugation at 300 rpm for 5 minutes, and two aliquots are prepared, one for lipid profile
and another for serum electrolytes. A sample is stored at 2˚C– 8˚C if the analysis is expected
after 2 hours from sample collection; however, blood samples are stored at room temperature
if the analysis is expected to be done within 2 hours from sample collection. Analysis of the
sample is done using clinical chemistry automatic analyzer Erba machine XL– 180 serial num-
ber 160239 made in Germany.
For dyslipidemia: is defined as a high total cholesterol level above 200 mg/dL, or a low-den-
sity lipoprotein cholesterol level above 130 mg/dL, or a triglyceride level above 150 mg/dL, or a
high-density lipoprotein cholesterol level below 40 mg/dL for women and below 50 mg/dL for
men[10].
Blood Sugar measurement: a blood sample for measuring blood sugar is obtained from a
finger prick with the guidance of sample collection manual SM-1-03.3 of DRRH laboratory.
After the candidate’s consent, the palm is positioned side up, and then the fingertip of the
index, ring or middle finger is chosen; then, pressure is applied on the finger to increase blood
flow to the fingertip. The fingertip is cleaned with methylated spirit 70% from the middle to
the periphery after 15 minutes the finger will be dry. Using a new sterile lancet placed firmly
against the periphery of the fingertip to puncture the skin to increase blood flow, the finger is
held below the level of the elbow. Then the blood sample collected directly from the device
(ACCU- CHECK Active Roche glucometer machine). After collecting the sample, the client is
given a ball of cotton wool to press against the finger for 10 minutes to arrest bleeding, and the
lancet will be disposed to a sharp disposal box. Hyperglycemia is defined according to Ameri-
can Diabetes Association[45]; for non-diabetic patients, hyperglycemia is defined as random
blood sugar >11.1 mmol/L or fasting blood sugar >7.0 mmol/L, and diagnosis of diabetes will
be made with a fasting blood sugar 7.0 mmol/L, or random blood glucose 11.1 mmo/L
plus symptoms of hyperglycemia or glycated hemoglobin6.5%
To ensure validity and reliability of the results, the laboratory technician in respective hos-
pitals, the Benjamin Mkapa Hospital and Dodoma regional referral hospital, tends to run con-
trols in every machine every day before processing samples, and maintenance of machines is
done weekly, whereas critical services are done in every six months.
Electrocardiogram. The principal investigator, familiar with the manufacturer’s instruc-
tions, uses a 12-lead ECG (model C12G, manufactured by ARI Technology Medical Co. Ltd
2019) on each participant under the supervision of a consultant cardiologist. Before a 12-lead
ECG is recorded, the patient is informed about the procedure, privacy is respected in a com-
fortable environment enhance relaxation and reduce interference with the ECG trace’s clarity.
To attach the electrodes/leads to the patient, the appropriate equipment, such as the electrocar-
diograph, ECG paper, and ECG tabs, is provided. Ensuring that the ECG cables are not twisted
is critical, leading to ECG tracing interference. The patient’s ID number is entered into the
machine, consent obtained, and a patient is requested to lie down at an angle of 45˚ with the
head adequately supported and the backrest on the bed, with the inner aspect of the patient’s
wrist close to but not touching his or her waist.
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 8 / 15
Provided that wet gel electrodes are utilized, there is no need to shave the skin; then, limb
electrodes will be applied in the following order: red on the right inner wrist, yellow on the left
inner wrist, black on the right inner leg just above the ankle, green on the left inner leg just
above the ankle. The following is how the chest leads are organized: V1 is just to the right of
the sternum, V2 is just to the left of the sternum, V3 is halfway between V4 and V2, V4 is in
the fifth intercostal space, mid clavicular line, V5 is in the anterior axillary line, and V6 is in
the mid axillary line, the same horizontal line as V4 and V5. ECG cables should not lie to each
other, and tension should be avoided to decrease artifacts and increase the accuracy and qual-
ity of ECG tracing. The calibration signal on the ECG machine should be kept at a paper speed
of 25 millimeter/second and ECG size 1 millivolt/10-millimeter deflection. The patient is
requested to lie still and breathe regularly during the operation; the ECG trace should be clear
before recording. The patient’s name, hospital number, date of birth, and the day and time the
ECG was obtained are be written on the 12-lead ECG trace [46]. According to the American
College of Cardiology guideline for the management of patients with atrial fibrillation, Atrial
Fibrillation will be diagnosed by the absence of P waves and irregular-irregular RR interval
[47]
With a 24-hour ECG Holter monitoring, SEERTM 1000 made by GE Medical Systems
Information Technologies, Inc, patients with ischemic stroke and normal 12-lead ECG tracing
are assessed for paroxysmal atrial fibrillation [48].
As the American Heart Association (AHA) recommends [49], before application of a Hol-
ter ECG monitor, the followings should be met, date of application, patient data, relevant med-
ical use, and the existence of a pacemaker or an implantable cardioverter-defibrillator.
Whenever a patient experiences symptom, they should be timed and recorded. Changes
throughout the day are also noticed by the patient, such as time of sleep, resting periods, and
physical activity. Furthermore, the patient is informed about the basic guidelines for using
Holter equipment (for example, avoid using an electric blanket and do not shower) and what
to do if any of the electrodes become detached. A qualified cardiac physiologist analyses and
reports the Holter study; however, the supervising cardiologist is ultimately responsible for the
Holter analyses’ correct authorization. Atrial fibrillation is defined as chaotic atrial arrhythmia
with loss of p wave activity and irregular RR interval lasting for at least 30 seconds [50]
Echocardiography. Transthoracic Echocardiography (model Vivid
TM
T9 manufactured
by GE Healthcare, USA 2018) are recommended only in selected patients with ischemic stroke
and additional characteristics like evidence of cardiac disease on history, examination, or elec-
trocardiogram (ECG), suspected cardiac source of embolism (example infarctions in multiple
cerebral or systemic arterial territories), suspected aortic disease or paradoxical embolism and
for patients with no other identifiable causes of stroke [51]
Transthoracic Echocardiograms are read by cardiologists who are unaware of the patients’
neurologic condition or stroke subtype. Findings thought to be of potential diagnostic impor-
tance are extracted from the report view. Left atrial enlargement, patent foramen ovale (PFO)/
atrial septal defect (ASD), low ejection fraction (EF35%), intracardiac thrombus, and valve
vegetation or other valvular abnormalities being among them [52]
Brain imaging. All patients undergo an acute CT scan SIEMENS (SOMATOM Definition
Flash) to establish the stroke diagnosis and others undergo a brain MRI scan model MAGNE-
TUM SPECTRA A TIM +Dot System 3T as part of a routine diagnostic workup. In addition,
participants with stroke-like symptoms but negative CT scans for hemorrhagic stroke and
uncertain ischemic stroke status are recruited for a study-specific MRI brain scan within the
first 14 days after stroke. The MRI study protocol consists of 3D-T1, axial T2, 3D-FLAIR, DWI
and SWI sequences. All patients will be evaluated for renal function status before undergoing
brain imaging to reduce the risk of contrast-induced nephropathy [53]
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 9 / 15
The stroke volume (hematoma/infarct volume) is calculated using the ellipsoid method A
+B+C/2, where A represents the largest diameter, B represents the largest diameter perpendic-
ular to A, and C represents the product of slice thickness and number of slices. A, B, and C are
measured in centimeters, and the resulting volume are expressed in cm3 or milliliters [8,54]
Leukoaraiosis are defined as bilateral areas of patchy or diffuse hypodensity on CT or white
matter hyperintensity on MRI [55]. The global brain atrophy is classified as not present if the
width of the third ventricle is less than 5 mm, mild if the width is between 5 and 6 mm, moder-
ate if the width is between 6 and 7 mm, and severe if the width is greater than 7 mm [56]. All
images are transferred to a computer workstation with an SYNGOVIA viewer and evaluated
by two experienced radiologists.
Data management
Data are stored on password-protected and encrypted computers to maximize confidentiality
and security. Each subject is assigned a unique, anonymous identifier linked to all collected
data, including questionnaires and interviews. Data are identified only by ID numbers, and a
link between names and numbers will be stored separately and safely. All paper files are kept
in a secure, locked location accessible only to the research team. Data are only accessible to
trained study personnel and locked away.
Safety consideration
At any point during the study, if a participant reports suicidal or self-harming thoughts, the
research coordinator notifies the principal investigator immediately and the PI contacts the
participant to conduct a risk assessment. As necessary, the PI initiates psychiatric consulta-
tions. Participants determined to require intervention receives information about available
care resources, and those who do not need a higher level of care may continue to participate in
the study and safety will always take precedence over participation in studies.
Data analysis
Data are entered on a Microsoft Excel sheet for statistical analysis and then converted to IBM
SPSS PC version 26. Continuous variables are summarized as mean and standard deviation
(SD), or Median and interquartile ranges, for non-parametric variables; frequencies and per-
centages will be used for categorical variables. Demographic variables, cardiovascular predic-
tors of post-stroke cognitive impairment, stroke characteristics, and neuropsychiatric
manifestations at one-month post-stroke will be compared between stroke survivors with cog-
nitive impairment and without cognitive impairment using Chi-square in the case of categori-
cal variables and Mann Whitney U test for non-parametric variables. The predictors for the
multivariable regressions will be based on the literature that have established factors associated
with PSCI. These include, advanced age, female gender, fewer years of formal education, alco-
hol consumption, cigarette smoking, hypertension, diabetes, dyslipidemia, atrial fibrillation,
stroke-specific characteristics, and baseline neuropsychiatric symptoms [12,15]. It is widely
accepted that subject-matter knowledge must direct multivariable model development [57,
58]. Furthermore, factors with a p-value of 0.2 will also be considered for adjusted analysis.
A multivariate Logistic analysis will be used to identify independent risk factors for post-stroke
cognitive impairment at three months. At the same time, the odds ratio (OR) and the 95% con-
fidence interval (CI) will be determined. Statistical significance will be determined by a two-
sided p 0.05.
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 10 / 15
Ethical issues
The Vice Chancellor’s office at the University of Dodoma provided permission to conduct the
study after obtaining ethical clearance from the Directorate of Research and Publications (ref-
erence number MA.84/261/02). Following that, the administrative departments of Benjamin
Mkapa and Dodoma Regional Referral Hospitals approved data collection, respectively. Partic-
ipants are informed that their participation was fully optional and that they might opt out at
any moment without affecting their daily routine care. To ensure privacy and confidentiality,
participants’ names are substituted with identification numbers; however, their standard of
care are unaffected by their decision to participate or not. Stroke survivors who had depressed
symptoms are referred to a specialized psychiatric for additional e and treatment.
Study timeline
The duration of this study is expected to takes 18-months to reach the required sample size.
The first patient was recruited on the June 2020 and still on-going. Six months of follow-up is
needed for each patient; however, overall data collection will need at least eighteen months.
Discussion
Cross-sectional studies have investigated the relationship between cognitive impairment and
other difficulties, such as disability and executive function limitations. Dependence, compe-
tency, and disability have been linked to cognitive impairment [59,60]. Additionally, the cog-
nitive decline between seven days and three months was associated with an approximately
two-fold increased risk of mortality compared to cognitive stability [61,62]. The intervention
for PSCI among stroke survivors which is debatable, as only cognitive rehabilitation improves
cognitive impairment in stroke survivors, whereas there is no strong evidence for pharmaco-
therapy, lifestyle modifications, and cardiovascular risk factor interventions improve cognitive
performance in stroke survivors [63]
This study has the potential to inform the burden and predictors of cognitive impairment
among stroke survivors in our setting, considering the paucity of data in sub-Saharan Africa at
large[64]. However, as prospective cohort study is concerned, it is often difficult to maintain
contact with all cohort members, mainly if the cohort is large and the length of follow-up is
extensive. Loss of contact with many patients can lead to biased results, especially if the reason
for loss to follow-up is related to the risk factor or outcome of interest. Furthermore, cohort
study has limited capacity to infer causation from the observed association between stroke and
cognitive impairment among survivors due to lingering confounding variables.
The final results will be submitted to the University of Dodoma library, the study sites
(Dodoma regional referral hospital and the Benjamin Mkapa Hospital), and a manuscript will
be ready for submission in different peer-review journals before publication.
Supporting information
S1 File.
(PDF)
Acknowledgments
First and far most, we acknowledge the patients and the staff of Dodoma regional hospital and
Benjamin Mkapa hospital for their participation in the work.
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 11 / 15
Author Contributions
Conceptualization: Alphonce Baraka, Azan Nyundo.
Data curation: Alphonce Baraka.
Formal analysis: Alphonce Baraka.
Investigation: Azan Nyundo.
Methodology: Alphonce Baraka, John Meda, Azan Nyundo.
Supervision: John Meda, Azan Nyundo.
Writing – original draft: Alphonce Baraka.
Writing – review & editing: John Meda, Azan Nyundo.
References
1. Kulesh A, Drobakha V, Kuklina E, Nekrasova I, Shestakov V. Cytokine Response, Tract-Specific Frac-
tional Anisotropy, and Brain Morphometry in Post-Stroke Cognitive Impairment. Journal of Stroke and
Cerebrovascular Diseases. 2018 Jul 1. 27(7):1752–9. https://doi.org/10.1016/j.jstrokecerebrovasdis.
2018.02.004 PMID: 29610037
2. Zhu Z, Chen L, Guo D, Zhong C, Wang A, Bu X, et al. Serum Rheumatoid Factor Levels at Acute Phase
of Ischemic Stroke are Associated with Poststroke Cognitive Impairment. Journal of Stroke and Cere-
brovascular Diseases. 2019 Apr 1. 28(4):1133–40. https://doi.org/10.1016/j.jstrokecerebrovasdis.
2018.12.049 PMID: 30661971
3. Fride Y, Adamit T, Maeir A, Ben Assayag E, Bornstein NM, Korczyn AD, et al. What are the correlates
of cognition and participation to return to work after first ever mild stroke. Topics in Stroke Rehabilitation.
2015. 22(5):317–25. https://doi.org/10.1179/1074935714Z.0000000013 PMID: 26461878
4. Lees RA, Hendry BA K, Broomfield N, Stott D, Larner AJ, Quinn TJ. Cognitive assessment in stroke:
feasibility and test properties using differing approaches to scoring of incomplete items. International
Journal of Geriatric Psychiatry. 2017. 32(10):1072–8. https://doi.org/10.1002/gps.4568 PMID:
27526678
5. Pollock A, St George B, Fenton M, Firkins L. Top ten research priorities relating to life after stroke. Vol.
11, The Lancet Neurology. Lancet Neurol; 2012. p. 209. https://doi.org/10.1016/S1474-4422(12)70029-
7PMID: 22341029
6. Gong L, Gu Y, Yu Q, Wang H, Zhu X, Dong Q, et al. Prognostic Factors for Cognitive Recovery Beyond
Early Poststroke Cognitive Impairment (PSCI): A Prospective Cohort Study of Spontaneous Intracere-
bral Hemorrhage. Frontiers in Neurology. 2020. 11(April):1–10. https://doi.org/10.3389/fneur.2020.
00278 PMID: 32411073
7. Nys GMS, Van Zandvoort MJE, De Kort PLM, Jansen BPW, De Haan EHF, Kappelle LJ. Cognitive dis-
orders in acute stroke: Prevalence and clinical determinants. Cerebrovascular Diseases. 2007 May. 23
(5–6):408–16. https://doi.org/10.1159/000101464 PMID: 17406110
8. Sharma R, Mallick D, Llinas RH, Marsh EB. Early Post-stroke Cognition: In-hospital Predictors and the
Association With Functional Outcome. Frontiers in Neurology. 2020. 11(December):1–9. https://doi.
org/10.3389/fneur.2020.613607 PMID: 33424761
9. Akinyemi RO, Allan L, Owolabi MO, Akinyemi JO, Ogbole G, Ajani A, et al. Profile and determinants of
vascular cognitive impairment in African stroke survivors: The CogFAST Nigeria Study. Journal of the
Neurological Sciences. 2014. 346(1–2):241–9. https://doi.org/10.1016/j.jns.2014.08.042 PMID:
25238666
10. Sarfo FS, Akassi J, Adamu S, Obese V, Ovbiagele B. Burden and Predictors of Poststroke Cognitive
Impairment in a Sample of Ghanaian Stroke Survivors. Journal of Stroke and Cerebrovascular Dis-
eases. 2017. 26(11):2553–62. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.05.041 PMID:
28652059
11. fang Chi N, hwa Hu H, Chan L, yen Wang C, ping Chao S, kai Huang L, et al. Impaired cerebral autore-
gulation is associated with poststroke cognitive impairment. 2020.: 1092–102. https://doi.org/10.1002/
acn3.51075 PMID: 32468721
12. Pendlebury ST, Rothwell PM. Prevalence, incidence, and factors associated with pre-stroke and post-
stroke dementia: a systematic review and meta-analysis. The Lancet Neurology. 2009. 8(11):1006–18.
https://doi.org/10.1016/S1474-4422(09)70236-4 PMID: 19782001
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 12 / 15
13. Chander RJ, Lim L, Handa S, Hiu S, Choong A, Lin X, et al. Atrial Fibrillation is Independently Associ-
ated with Cognitive Impairment after Ischemic Stroke. Journal of Alzheimer’s Disease. 2017. 60
(3):867–75. https://doi.org/10.3233/JAD-170313 PMID: 28922154
14. Swardfager W, MacIntosh BJ. Depression, Type 2 Diabetes, and Poststroke Cognitive Impairment.
Neurorehabilitation and Neural Repair. 2017 Jan 1. 31(1):48–55. https://doi.org/10.1177/
1545968316656054 PMID: 27364648
15. Douven E, Ko
¨hler S, Schievink SHJ, van Oostenbrugge RJ, Staals J, Verhey FRJ, et al. Baseline Vas-
cular Cognitive Impairment Predicts the Course of Apathetic Symptoms After Stroke: The CASPER
Study. American Journal of Geriatric Psychiatry. 2018 Mar 1. 26(3):291–300. https://doi.org/10.1016/j.
jagp.2017.09.022 PMID: 29079017
16. Chen X, Duan L, Han Y, Tian L, Dai Q, Wang S, et al. Predictors for vascular cognitive impairment in
stroke patients. BMC Neurology. 2016. 16(1):1–8. https://doi.org/10.1186/s12883-016-0638-8 PMID:
27461245
17. al Fawal B, Ibrahim A, Abd Elhamed M. Post-stroke dementia: frequency, predictors, and health impact.
Egyptian Journal of Neurology, Psychiatry and Neurosurgery. 2021 Dec 1. 57(1):1–8. https://doi.org/
10.1186/S41983-021-00270-Y/FIGURES/3
18. Wang X, Ji X. Sample Size Estimation in Clinical Research: From Randomized Controlled Trials to
Observational Studies. Chest. 2020 Jul 1. 158(1S):S12–20. https://doi.org/10.1016/j.chest.2020.03.
010 PMID: 32658647
19. Chi NF, Chao SP, Huang LK, Chan L, Chen YR, Chiou HY, et al. Plasma amyloid beta and tau levels
are predictors of post-stroke cognitive impairment: A longitudinal study. Frontiers in Neurology. 2019
Jul 2. 10(JUL):715. https://doi.org/10.3389/fneur.2019.00715 PMID: 31312178
20. Okeng’o K, Chillo P, Gray WK, Walker RW, Matuja W. Early Mortality and Associated Factors among
Patients with Stroke Admitted to a Large Teaching Hospital in Tanzania. Journal of Stroke and Cerebro-
vascular Diseases. 2017 Apr 1. 26(4):871–8. https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.10.
037 PMID: 27913201
21. Jacquin A, Binquet C, Rouaud O, Graule-Petot A, Daubail B, Osseby GV, et al. Post-stroke cognitive
impairment: High prevalence and determining factors in a cohort of mild stroke. Journal of Alzheimer’s
Disease. 2014 Jan 1. 40(4):1029–38. https://doi.org/10.3233/JAD-131580 PMID: 24577459
22. Chaurasia RN, Sharma J, Pathak A, Mishra VN, Joshi D. Poststroke Cognitive Decline: A Longitudinal
Study from a Tertiary Care Center. Journal of Neurosciences in Rural Practice. 2019. 10(3):459–64.
https://doi.org/10.1055/s-0039-1697872 PMID: 31595118
23. Wang Y, Li S, Pan Y, Wang M, Liao X, Shi J, et al. The effects of blood pressure on post stroke cognitive
impairment: BP and PSCI. Journal of Clinical Hypertension. 2021. 23(12):2100–5. https://doi.org/10.
1111/jch.14373 PMID: 34800332
24. Banks JL, Marotta CA. Outcomes validity and reliability of the modified Rankin scale: implications for
stroke clinical trials: a literature review and synthesis. Stroke. 2007 Mar. 38(3):1091–6. https://doi.org/
10.1161/01.STR.0000258355.23810.c6 PMID: 17272767
25. Tong AYC, Man DWK. The validation of the Hong Kong Chinese Version of the Lawton Instrumental
Activities of Daily Living scale for institutionalized elderly persons. OTJR Occupation, Participation and
Health. 2002. 22(4):132–42. https://doi.org/10.1177/153944920202200402
26. Graf C. The Lawton instrumental activities of daily living scale. The American journal of nursing. 2008
Apr. 108(4):52–62. https://doi.org/10.1097/01.NAJ.0000314810.46029.74 PMID: 18367931
27. Coupland AP, Thapar A, Qureshi MI, Jenkins H, Davies AH. The definition of stroke. Journal of the
Royal Society of Medicine. 2017. 110(1):9–12. https://doi.org/10.1177/0141076816680121 PMID:
28084167
28. Walker RW, Jusabani A, Aris E, Gray WK, Unwin N, Swai M, et al. Stroke risk factors in an incident pop-
ulation in urban and rural Tanzania: A prospective, community-based, case-control study.The Lancet
Global Health. 2013. 1(5). https://doi.org/10.1016/S2214-109X(13)70068-8 PMID: 24748275
29. Zhou DHD, Wang JYJ, Li J, Deng J, Gao C, Chen M. Study on frequency and predictors of dementia
after ischemic stroke. Journal of Neurology 2004 251:4. 2004 Apr. 251(4):421–7. https://doi.org/10.
1007/S00415-004-0337-Z PMID: 15083286
30. Rusanen M, Kivipelto M, Quesenberry CP, Zhou J, Whitmer RA. Heavy smoking in midlife and long-
term risk of Alzheimer disease and vascular dementia. Archives of Internal Medicine. 2011 Feb 28. 171
(4):333–9. https://doi.org/10.1001/archinternmed.2010.393 PMID: 20975015
31. Chen A, Akinyemi RO, Hase Y, Firbank MJ, Ndung’u MN, Foster V, et al. Frontal White matter hyperin-
tensities, clasmatodendrosis and gliovascular abnormalities in ageing and post-stroke dementia. Brain.
2016 Jan 1. 139(1):242–58. https://doi.org/10.1093/brain/awv328 PMID: 26667280
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 13 / 15
32. Carson N, Leach L, Murphy KJ. A re-examination of Montreal Cognitive Assessment (MoCA) cutoff
scores. International Journal of Geriatric Psychiatry. 2018 Feb 1. 33(2):379–88. https://doi.org/10.
1002/gps.4756 PMID: 28731508
33. Masika GM, Yu DSF, Li PWC, Wong A, Lin RSY. Psychometrics and diagnostic properties of the Mon-
treal Cognitive Assessment 5-min protocol in screening for Mild Cognitive Impairment and dementia
among older adults in Tanzania: A validation study. International Journal of Older People Nursing. 2021
Jan 1. 16(1):e12348. https://doi.org/10.1111/opn.12348 PMID: 32920984
34. Goudsmit M, Van Campen J, Schilt T, Hinnen C, Franzen S, Schmand B. One Size Does Not Fit All:
Comparative Diagnostic Accuracy of the Rowland Universal Dementia Assessment Scale and the Mini
Mental State Examination in a Memory Clinic Population with Very Low Education. Dementia and Geri-
atric Cognitive Disorders Extra. 2018. 8(2):290–305. https://doi.org/10.1159/000490174 PMID:
30323830
35. Vogel SJ, Banks SJ, Cummings JL, Miller JB. Concordance of the Montreal cognitive assessment with
standard neuropsychological measures. Alzheimer’s and Dementia: Diagnosis, Assessment and Dis-
ease Monitoring. 2015. 1(3):289–94. https://doi.org/10.1016/j.dadm.2015.05.002 PMID: 27239512
36. Gilbody S, Richards D, Brealey S, Hewitt C. Screening for depression in medical settings with the
Patient Health Questionnaire (PHQ): A diagnostic meta-analysis. Journal of General Internal Medicine.
2007 Nov. 22(11):1596–602. https://doi.org/10.1007/s11606-007-0333-y PMID: 17874169
37. Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: Validity of a brief depression severity measure.
Journal of General Internal Medicine. 2001. 16(9):606–13. https://doi.org/10.1046/j.1525-1497.2001.
016009606.x PMID: 11556941
38. Smith Fawzi MC, Ngakongwa F, Liu Y, Rutayuga T, Siril H, Somba M, et al. Validating the Patient
Health Questionnaire-9 (PHQ-9) for screening of depression in Tanzania. Neurology Psychiatry and
Brain Research. 2019. 31(October 2018):9–14. https://doi.org/10.1016/j.npbr.2018.11.002 PMID:
32863596
39. Santangelo G, Barone P, Cuoco S, Raimo S, Pezzella D, Picillo M, et al. Apathy in untreated, de novo
patients with Parkinson’s disease: validation study of Apathy Evaluation Scale. Journal of Neurology.
2014 Nov 25. 261(12):2319–28. https://doi.org/10.1007/s00415-014-7498-1 PMID: 25228003
40. Clarke DE, Ko JY, Kuhl EA, van Reekum R, Salvador R, Marin RS. Are the available apathy measures
reliable and valid? A review of the psychometric evidence. Journal of Psychosomatic Research. 2011
Jan 1. 70(1):73–97. https://doi.org/10.1016/j.jpsychores.2010.01.012 PMID: 21193104
41. Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Himmelfarb CD, et al. 2017 ACC/AHA/
AAPA/ABC/ACPM/AGS/APhA/ASH/ ASPC/NMA/PCNA guideline for the prevention, detection, evalua-
tion, and management of high blood pressure in adults: Executive summary: A report of the American
college of cardiology/American Heart Association task. Vol. 71, Hypertension. 2018. 1269–1324 p.
https://doi.org/10.1161/HYP.0000000000000066 PMID: 29133354
42. Maduagwu SM, Umeonwuka CI, Mohammad HH, Oyeyemi AY, Nelson EC, Jaiyeola OA, et al. Refer-
ence Arm for Blood Pressure Measurement in Stroke Survivors. Middle East Journal of Rehabilitation
and Health. 2018 Jan 30. 5(1). https://doi.org/10.5812/mejrh.62368
43. Rajkumar A, Bhattacharjee A, Selvaraj RJ. Diagnostic accuracy of apex-pulse deficit for detecting atrial
fibrillation. International Journal of Advanced Medical and Health Research. 2019. 6(2):52. https://doi.
org/10.4103/IJAMR.IJAMR_48_19
44. Johnston KC, Connors AF, Wagner DP, Haley EC. Predicting outcome in ischemic stroke: external vali-
dation of predictive risk models. Stroke. 2003 Jan 1. 34(1):200–2. https://doi.org/10.1161/01.str.
0000047102.61863.e3 PMID: 12511774
45. Johnson EL, Feldman H, Butts A, Billy CDR, Dugan J, Leal S, et al. Standards of Medical Care in Diabe-
tes—2019 Abridged for Primary Care Providers. Clinical Diabetes: A Publication of the American Diabe-
tes Association. 2019 Jan 1. 37(1):11. https://doi.org/10.2337/cd18-0105 PMID: 30705493
46. Jevon P. Procedure for recording a standard 12-lead electrocardiogram. British journal of nursing (Mark
Allen Publishing). 2010 May 27. 19(10):649–51. https://doi.org/10.12968/bjon.2010.19.10.48204
PMID: 20622761
47. Brugada J, Demosthenes G. Katritsis EA, Fernando Arribas JJB, Carina Blomstro¨m-Lundqvist HC,
Corrado Domenico, Spyridon G. Deftereos, Gerhard-Paul Diller, Gomez-Doblas Juan J., Gorenek
Bulent, Grace Andrew, Ho Siew Yen, Kaski Juan-Carlos, Karl-Heinz Kuck PDL, Frederic Sacher GSB,
et al. 2019 ESC Guidelines for the management of patients with supraventricular tachycardia The Task
Force for the management of patients with supraventricular tachycardia of the European Society of Car-
diology (ESC). 2020.: 655–720. https://doi.org/10.1093/eurheartj/ehz467 PMID: 31504425
48. Onder H, Yilmaz S. The Rationale of Holter Monitoring After Stroke. Angiology. 2017 Nov 1. 68
(10):926–7. https://doi.org/10.1177/0003319717703003 PMID: 28387127
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 14 / 15
49. Albers GW, Bernstein RA, Brachmann J, Camm J, Easton JD, Fromm P, et al. Heart Rhythm Monitoring
Strategies for Cryptogenic Stroke: 2015 Diagnostics and Monitoring Stroke Focus Group Report. Jour-
nal of the American Heart Association: Cardiovascular and Cerebrovascular Disease. 2016. 5(3).
https://doi.org/10.1161/JAHA.115.002944 PMID: 27068633
50. Jawad-Ul-Qamar M, Chua W, Purmah Y, Nawaz M, Varma C, Davis R, et al. Detection of unknown
atrial fibrillation by prolonged ECG monitoring in an all-comer patient cohort and association with clinical
and Holter variables. Open Heart. 2020. 7(1):1–6. https://doi.org/10.1136/openhrt-2019-001151 PMID:
32371464
51. Ringleb PA, Bousser MG, Ford G, Bath P, Brainin M, Caso V, et al. Guidelines for management of
ischaemic stroke and transient ischaemic attack 2008. Cerebrovascular Diseases. 2008. 25(5):457–
507. https://doi.org/10.1159/000131083 PMID: 18477843
52. Harris J, Yoon J, Salem M, Selim M, Kumar S, Lioutas VA. Utility of TransthoracicEchocardiography in
Diagnostic Evaluation of Ischemic Stroke. Frontiers in Neurology. 2020. 11(February):1–9. https://doi.
org/10.3389/fneur.2020.00103 PMID: 32132971
53. Li Q, Pan S. Contrast-Associated Acute Kidney Injury: Advances and Challenges. International Journal
of General Medicine. 2022. 15(February):1537–46. https://doi.org/10.2147/IJGM.S341072 PMID:
35210826
54. Morotti A, Goldstein JN. Diagnosis and Management of Acute Intracerebral Hemorrhage. Emergency
Medicine Clinics of North America. 2016. 34(4):883–99. https://doi.org/10.1016/j.emc.2016.06.010
PMID: 27741993
55. Marek M, Horyniecki M, Frączek M, Kluczewska E. Leukoaraiosis–new concepts and modern imaging.
Polish Journal of Radiology. 2018. 83:e76. https://doi.org/10.5114/pjr.2018.74344 PMID: 30038682
56. Renjen PN, Gauba C, Chaudhari D. Cognitive Impairment After Stroke. Cureus. 2015 Sep 29. 7(9).
https://doi.org/10.7759/cureus.335 PMID: 26543693
57. Sauerbrei W, Perperoglou A, Schmid M, Abrahamowicz M, Becher H, Binder H, et al. State of the art in
selection of variables and functional forms in multivariable analysis—outstanding issues. Diagnostic
and Prognostic Research 2020 4:1. 2020 Apr 2. 4(1):1–18. https://doi.org/10.1186/s41512-020-00074-
3PMID: 32266321
58. Babyak MA. What you see may not be what you get: a brief, nontechnical introduction to overfitting in
regression-type models. Psychosomatic medicine. 2004. 66(3):411–21. https://doi.org/10.1097/01.
psy.0000127692.23278.a9 PMID: 15184705
59. Barker-Collo S, Feigin V. The impact of neuropsychological deficits on functional stroke outcomes. Neu-
ropsychology Review. 2006. 16(2):53–64. https://doi.org/10.1007/s11065-006-9007-5 PMID:
16967344
60. Feigin V, Barker-Collo FS, Parag V, Senior H, Lawes C, Ratnasabapathy FY, et al. Auckland Stroke
Outcomes Study. Neurology. 2010. 75:1597.
61. Dowling NM, Singh R, Power MC, Nadareishvili Z. Abstract WP208: Post-stroke Cognitive Impairment
And The Risk Of Recurrent Stroke And Death: A Systematic Review. Stroke. 2022 Feb. 53(Suppl_1).
https://doi.org/10.1161/STR.53.SUPPL_1.WP208
62. Obaid M, Flach C, Marshall I, Wolfe CDA, Douiri A. Long-term outcomes in stroke patients with cogni-
tive impairment: A population-based study. Geriatrics (Switzerland). 2020. 5(2):1–14. https://doi.org/
10.3390/geriatrics5020032 PMID: 32443398
63. Quinn TJ, Richard E, Teuschl Y, Gattringer T, Hafdi M, O’Brien JT, et al. European Stroke Organisation
and European Academy of Neurology joint guidelines on post-stroke cognitive impairment. European
stroke journal. 2021 Sep 1. 6(3):I–XXXVIII. https://doi.org/10.1177/23969873211042192 PMID:
34746430
64. Akinyemi RO, Owolabi MO, Ihara M, Damasceno A, Ogunniyi A, Dotchin C, et al. Stroke, cerebrovascu-
lar diseases and vascular cognitive impairment in Africa. Vol. 145, Brain Research Bulletin. Brain Res
Bull; 2019. p. 97–108. https://doi.org/10.1016/j.brainresbull.2018.05.018 PMID: 29807146
PLOS ONE
Early predictors of post-stroke cognitive impairment
PLOS ONE | https://doi.org/10.1371/journal.pone.0273200 March 2, 2023 15 / 15
