INTRODUCTION
Stroke is one of the
major non-communicable diseases contributing to Global Disease Burden (GDB) for
its high mortality and morbidity.1 Deaths from stroke
accounted for 11.9% of all global deaths in 2015.2 In Africa, there
were over 483,000 new cases of stroke in 2009.3 This high incidence
was attributed to population growth and a rise in many modifiable vascular
disease risk factors including smoking, excessive use of alcohol, physical
inactivity, increased prevalence of hypertension, diabetes and obesity.3
Furthermore, the incidence of stroke is seen to be declining in developed
countries due to the vigorous effort at lowering blood pressure and reducing
smoking.4
In Nigeria, there is an increase in the prevalence of
stroke and other cardiovascular diseases due to the epidemiological transition
from a traditional socio-cultural setting to a Western, sophisticated life in
the city.5
CKD as a cause of death worldwide has risen by 31.7% between
2005 and 2015, with an increase in the ranking of total Years of Life Lost
(YLL) from the 21st to the 17th position over the same period.2 The
prevalence of impaired kidney function has been estimated to be between 10% and
20% of the adult population in most countries worldwide.6 In a
hospital-based study of the prevalence and pattern of cardiovascular disease
(CVD) among patients with CKD, Lawal et al found that
6% had a stroke, 18% had arrhythmias and peripheral arterial disease was found
in 4%, a combination of stroke and arrhythmia was present in 4% while 2% had ischaemic heart disease, congestive cardiac failure and
arrhythmias.7 A moderate-to-severe decrease in eGFR
was also associated with a high incidence of first-ever stroke and all-cause mortality
in an ethnic Chinese population-based cohort.8 Cerebrovascular
disease is more prevalent in patients with CKD than in the general population
and is because they both share traditional cardiovascular risk factors.9
AKI is characterized by abrupt deterioration in renal
function and has a deleterious prognosis in the final outcome of various
medical conditions notably stroke. However, it is a common comorbid condition
in the community and may be associated with other cardiovascular disease,
diabetes mellitus, hypertension and cerebrovascular events. It complicates 5-7%
of acute care hospitalizations and around 30% of those in intensive care units.10
Kidney failure has been associated with a high prevalence
of CVD and patients with reduced renal function are at high risk for the
subsequent development of cerebrovascular diseases including stroke.9
Renal function among patients with stroke has been studied in the developed
countries in hospital-based studies.11-12 Almost all types of vascular disease including stroke have been found to
be associated with varying degrees of kidney failure and the
severity of stroke could be an indication of the degree of injury in small
renal vessels.13 However, the
development of kidney failure following stroke has not been well investigated
in Africa, particularly in Nigeria, despite the rising incidence of stroke and
kidney failure following the event.
METHODS
Study Area
The study was conducted in the Accident and Emergency
(A&E) department, intensive care unit and the Department of Internal
Medicine, UPTH. The University of Port Harcourt Teaching Hospital is a 740-bed
hospital and referral centre for Rivers State and neighbouring states (Bayelsa, Abia, Cross Rivers, Edo, Delta and Imo states). It is
located in Alakahia in the Obio-Akpor
Local Government Area of Rivers State. Rivers State has a heterogeneous
population consisting of several local tribes as well as foreigners involved in
various activities in the area mainly of the oil and gas sector.
The hospital is made
up of a 130-bed space medical ward and a 30-bed space accident and emergency. A
total of 212 cases of stroke were admitted via the A & E of the hospital
from January 1st, 2021 to December 31st, 2021 (Data from
the hospitals’ A & E records).
The nephrology unit offers a range of inpatient and
outpatient nephrology services covering general nephrology, predialysis,
and dialysis care as well as post-transplant services.
Study Design
The study is a hospital-based prospective cohort study.
Study Population
This consisted of all consecutive adults (≥18
years) admitted for stroke.
Inclusion Criteria
1.
Adults
aged 18 years and above admitted to the hospital within 7 days of onset of stroke
2.
Patients
with neuroimaging evidence of stroke.
3.
Stroke
patients who grant informed consent
Exclusion Criteria
1.
Patients
with stroke mimics, for example, patients with subdural or epidural hematoma,
intracranial space-occupying lesions, and hypoglycemia.
2.
Patients
who died within 24 hours of admission.
3.
Patients
with repeat stroke
4.
Post-transplant
patients
5.
Patients
on hemodialysis
Sampling
Patients who satisfied the eligibility criteria and had
none of the exclusion criteria were recruited consecutively by purposive
sampling until a sample size of 150 was obtained.
Sample Size Determination
The minimum sample size required for this study was
calculated from the method of Kish14
n= z
pq/ d²
Where:
n= sample size
when the population is infinite
Z= the standard normal deviation, usually set at 1.96
which corresponds to a 95% confidence interval
P = Prevalence of renal dysfunction estimated at 9.3%15
Q = 1-p
d = degree of accuracy desired, 0.05%
n = (1.96)2 x 0.093 x 0.907/ (0.05)2
n =129.6
10% attrition gives 12.9 (approximate to 13)
Therefore, the minimum sample size would be 129.6 +13
=142.6
However, a sample size of 150 stroke patients
was recruited, for the study.
Study Proforma
A semi-structured questionnaire was used as the survey
instrument to collect information about the subjects’ socio-demographic
characteristics, risk factors for stroke, assessment of kidney disease,
assessment of stroke, anthropometry, laboratory investigations, radiological
features of the kidneys and interim outcomes.
Two research assistants were trained to administer the
questionnaire and extract data. They also helped in ensuring adequate follow-up
of the participants.
A semi-structured questionnaire was used as an instrument
to collect information about the respondent’s socio-demographic data, medical
history of renal disease in patient and family, diabetes, hypertension, alcohol
consumption, smoking, medication use, trauma, history of TIA/stroke,
cardiovascular disease etc. Information about the risk factors of stroke and
stroke assessment were also collected through the questionnaire which was
administered by the researcher after obtaining informed consent. Subsequently,
a baseline physical and neurological examination was performed.
Selected stroke patients were categorised
as having AKI, pre-existing CKD, acute-on-chronic CKD and no KF after
assessment of their renal function using electrolyte, urea and creatinine at presentation,
48 hours and 7th day post-stroke. In addition, urinalysis, renal
imaging and measurement of urine output were done to assess renal function.
Measurements
Anthropometric measurements were carried out with the
participants’ privacy duly respected and with a chaperone when required.
Participants’ Waist Circumference was measured at the
midpoint between the inferior margin of the last palpable rib and the top of
the iliac crest while the Hip Circumference was measured at the largest
posterior extension of the buttocks. Waist and Hip Circumferences were measured
to the nearest 0.1cm. Their Waist-to-Hip Ratio (WHR) was calculated using the formular, WHR = Waist Circumference (cm)/Hip Circumference
(cm). WHO cut-off for increased cardiovascular and metabolic risks using WHR is
≥ 0.90cm for men and ≥ 0.85cm for women.16
The blood pressure (BP) of the participants was measured
with a mercury sphygmomanometer and stethoscope to obtain both systolic blood
pressure (SBP) and diastolic blood pressure (DBP). A total of two BP readings
were taken for each arm.
Blood pressure measurement was done according to
recommendations of the American Heart Association Council on Hypertension17
as follows:
1
A
properly functioning Accoson mercury sphygmomanometer
which had been validated and well-calibrated was used.
2
The
measurement was made with the participant in the seated position, with the back
supported, arms at heart level and legs not crossed. The patients who were
unable to sit down had their measurements done in a supine position.
3
Participants
did not have caffeine-containing drinks engaged in exercise or smoked for at
least 30mins before the measurement. Participants were not allowed to talk or
move around for at least 3-5 minutes before the blood pressure was measured.
4
An
appropriate-sized cuff was placed on the patient’s bare skin. The cuff was
pulled taut with just enough allowance for a finger under the cuff, with
comparable tightness at the top and bottom edges of the cuff, around the upper
arm.
5
The
blood pressure was taken initially by the radial artery obliteration pressure,
to determine the approximate SBP and subsequently completely deflated.
The diaphragm of the stethoscope was then placed firmly
over the brachial artery, and the sphygmomanometer cuff was inflated to
20-30mmHg above the estimated SBP obtained by the palpation method.
The cuff was then deflated at the rate of 2mmHg/sec or
per heartbeat when the heart rate is <60bpm, till the appearance of the Korochoff sounds (1st Korochoff
sound) and this was recorded as the SBP. The cuff was further deflated till the
disappearance of the Korochoff sound (5th Korochoff sound) was observed and this was recorded as the
DBP. However, for individuals who had persistence of the muffled sound (4th Korochoff sound) till the cuff was completely deflated, the
point of onset of the 4th Korotkoff sound was
recorded as the DBP.
The cuff was completely deflated and the patient was
allowed to relax for about 1-2mins before another reading was taken.
Sample Collection
A spot urine sample was obtained in a clean dry universal
bottle provided for each participant. Each participant was required to produce
a 10 ml sample of first-morning urine. For participants on urethral catheter,
the morning urine sample was collected directly from the catheter, after
discarding the first 100mls of urine following an 8-hour spigotting
of the urethral catheter. The sample collected was used to assess for
proteinuria which is measured by dipstick using combi
9 (meditest combi 9 – Duren
Germany). Furthermore, stable participants were asked to empty their bladder by
8 am and collect subsequent urine in a container for a 24-hour period which
ended at 8 am the next morning, for patients who are unable to pass urine
normally, the catheter was emptied at 8 am and urine was measured over the next
24-hour period. This was also done by the researcher to estimate the 24-hour
urine output.
For biochemical investigations, five millilitres
(5mls) of whole blood were collected into a lithium heparin bottle from each
participant using the standard technique. The sample from each subject was
centrifuged at 2,500 revolutions per minute for 15 minutes. The plasma sample
obtained was aliquoted into a screw cap plane bottle
and stored frozen at -20ºC until the time of analysis. Plasma samples from the
subjects were analyzed in batches using the standards and controls provided by
the manufacturers of the reagent kits. The biochemical parameters that were
measured include plasma electrolytes (sodium, potassium, bicarbonate and
chloride), urea, and creatinine.
Serum creatinine was measured using the modified Jaffe
reaction method which involves the reaction of creatinine with picric acid in
an alkaline medium provided by sodium hydroxide, the yellowish-orange colour which develops within 15mins at room temperature was
measured at 520nm in a photometer18 serum creatinine urea &
electrolytes were measured at presentation and repeated after 48hours, on the 7th
day of admission and 6th-week post-stroke.
After an overnight fast of 8-10 hours, five millilitres (5mls) of blood sample were collected in a
fluoride oxalate bottle using standard techniques which was centrifuged and
stored in the same manner as the sample collected in the lithium heparin
bottle. The sample was used to estimate fasting plasma glucose. Lithium heparin
bottle was also used to collect the sample for the estimation of the following :Total Cholesterol (TC), High-Density Lipoprotein
Cholesterol (HDL-C), and Triglycerides (TG). Low-Density Lipoprotein
Cholesterol LDL-C was calculated using the Friedwald
equation19 
These samples were analyzed in the chemical pathology
laboratory of the hospital.
The eGFR was calculated using
the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation,20 as follows:
𝑒𝐺𝐹𝑅 = 141 × 𝑚𝑖𝑛 (𝑆𝐶𝑟/𝜅, 1) 𝛼 × 𝑚𝑎x (𝑆𝐶𝑟/𝜅, 1) −1.209 × 0.993𝐴𝑔𝑒 × 1.018 [𝑖𝑓 𝑓𝑒𝑚𝑎𝑙𝑒] × 1.159 [𝑖𝑓 𝐵𝑙𝑎𝑐𝑘]
Where,
eGFR = ml/ min/1.73m2
SCr (standard serum
creatinine)= mg/dl
Κ= 0.7 (females) or 0.9
(males)
α= -0.329 (female) or -0.411
(male)
Min=
indicates the minimum of SCr/κ or 1
Max=
indicates the maximum of SCr/κ or 1
Age=
in years
The severity of CKD was assessed by the Kidney Disease
Improving Global Outcome
(KDIGO)21
criteria to stratify CKD while the severity of AKI was stratified according to KDIGO as shown in Table 1.
DISCUSSION
Socio-demographic characteristics of the study population
This study observed
that more males than females were found among the study population. This was
similar to the finding by Shittu7 in Ogbomosho, Medhat
et al27 in Egypt, and Pereg
et al28 in Israel who reported more males among acute stroke
patients in their studies. This difference may be because of the improvement of
more women from stroke than men in some countries due to the sensitivity of
women to health information, health-seeking behaviours
and early access to primary prevention of stroke29 as well as
increased neurovascular risk factors such as current cigarette smoking, use of
illicit drugs and significant alcohol consumption in men.
The mean age of the
study population was 54.6 ±10.6 years. This is comparable
to the mean age of 53.9 ± 18.1 years reported in the study by Sulaiman et al30 in
Maiduguri, Nigeria. The preponderance of young and middle-aged acute stroke
patients in these studies may be attributed to the increasing prevalence of
stroke in the young globally. However, these findings are in contrast to those
reported by Okaka et al31
in Benin and Vijay et al32 in India with higher mean ages of 63.28 ±15.22 years and 60.36 ±10.7years respectively. The disparity may be attributed
to the small sample sizes used in their studies.
Risk factors for kidney failure in the study
This study showed
that obese stroke patients had an increased risk of developing AKI compared to
normal-weight patients and this was statistically significant (aOR=3.61, P – 0.003). This finding is similar to that
reported in the studies by
Druml et al33, and Danziger et al.34 There is a paucity of data on
obesity as a risk factor for AKI in stroke patients, hence the indirect
comparison of the findings from this study to that conducted by Druml et al and Danziger et al
which were carried out in different study populations.
Obese stroke patients
were also shown to have a higher risk of having CKD when compared to patients
with normal weight and this was statistically significant (aOR=6.45;
p – 0.044). This finding agrees with that reported by Olanrewaju
et al35 which demonstrated a significant
relationship between obesity and CKD, though their study was conducted among
obese patients in some urban communities who did not have a stroke.
Obesity is associated
with an increase in proinflammatory cytokines and adipokines and can be regarded as a state of chronic
low-grade inflammation. Obesity is also related to an increase in oxidative
stress and endothelial dysfunction. It is also challenging to assess the
intravascular volume status and adequacy of fluid resuscitation in obese
patients accurately. Dosing regimens are not aimed primarily at obese
populations, but general patients, so there is insufficient knowledge of the
efficacy and safety of many drugs that may be nephrotoxic. Many obese patients
have other complications, such as hypertension and diabetes, which can increase
the risk for AKI, directly or indirectly.36
The mechanisms
involved in the pathogenesis of CKD in obese patients have not been fully
elucidated. By increasing the risk of type 2 diabetes, hypertension, and
atherosclerosis, excess fat mass may ‘indirectly’ lead to CKD.37
Obesity may also have ‘direct’ pathophysiological effects on the kidney via
alterations in renal hemodynamics, inflammatory milieu, growth factor, and adipokine production.37 For example, obesity may
lead to mesangial expansion of the kidneys and
increased renal metabolic demand, resulting in glomerular hyperfiltration,
hypertrophy, and hypertension, leading to increased glomerular filtration
fraction, and subsequent glomerulosclerosis and
proteinuria.38
However, the finding
from this study is at variance with the work by Liu et
al39 who reported that obesity is not a significant risk factor for
AKI, Their finding may not be unconnected with the fact that the study was
conducted in a multi-ethnic general population and use of only BMI to make the
diagnosis of obesity. Similarly, the finding
from this study contrasts that reported by Ibitoba et al40 in Ado-Ekiti,
Nigeria which did not show a significant relationship between obesity and CKD.
This discrepancy in the findings could be explained by the population used for
the study (commercial motorcycle riders who are not stroke patients) whose
socioeconomic status may not increase the risk of obesity and consequently CKD
The use of herbal
concoction was found to be a risk factor for AKI. (aOR=2.08, p – 0.003). This finding is consistent with that
reported by Mamven et al41
in Abuja, Nigeria and Halles et al42 in
Cameroon, who reported that the use of herbal remedies increases the risk of
developing AKI. Though the studies by Mamven et al
and Halles et al were conducted in the general
population, it is expected that the use of herbal concoctions will cause AKI despite
the population of the patients. This study also revealed that ingestion of
herbal concoctions significantly increased the risk for CKD in stroke patients
(aOR=1.38, p – 0.046). This finding is similar to
that reported by Xu et al43
in China who demonstrated an increased prevalence of CKD in patients with
cerebrovascular lesions who used herbal concoctions.
The herbal concoction is commonly used by
stroke patients possibly to treat hemi-body weakness, seizure, or aphasia, its
effect on renal injury in this population has not been well defined in the
study environment.
There are multiple
mechanisms by which herbal concoctions cause AKI: a direct nephrotoxic effect
of the compound or its metabolites such as Aristcsholic
acid, chromium, and germanium which are present in some plant and animal-based
foods, toxicity of the additive compounds and adulterants used in manufacturing
the products including nonsteroidal anti-inflammatory
agents, which have a well-known nephrotoxic potential. The alterations in the
body homeostasis that result in nephrotoxic phenomena leading to AKI are
excessive diuresis, rhabdomyolysis, and
nephrolithiasis.44
The use of herbal
concoction has been previously associated with acute kidney injury (AKI) which
is a recognized precursor of CKD.45 Other suggested mechanisms of
herbal medications' role in CKD include direct nephrotoxicity augmented by
underlying predisposing conditions such as dehydration; contamination, or
adulteration of remedies; inappropriate use of preparation or interactions with
other medications.45
However, these
findings contrast with that reportedly Ibitoba et al40 which showed that the relationship
between the use of herbal concoctions and CKD was not significant, though the
study was carried out in the general population. The involvement of only male
respondents in their study may have accounted for this difference in the
results. This is because herbal preparations and mercury-containing cosmetic
products are commonly used among women in Nigeria and Africa, which may have
contributed to the increased prevalence of CKD among women Li et al.46
This study revealed
that the risk of developing AKI among stroke patients placed on mannitol is higher compared to patients who did not receive
mannitol following the stroke and this was
significant (a0R=3.37, p – 0.012). This finding is similar to the findings in
the study by Lin
et al47 (p – 0.002) who reported a significant relationship between mannitol use and the risk of developing AKI. The mechanisms
of mannitol-induced AKI include: renal
vasoconstriction produced by a high dose/concentration of mannitol;
profound diuresis, natriuresis and tubular
vacuolization.47
However, the result
from this study is at variance with that reported by Kim et al 48 which
revealed that mannitol administration following a
stroke was not a risk factor for AKI but the rate of mannitol
infusion was significantly associated with the development of AKI. These
discrepancies in the result may be due to the fact that only patients with intracerebral haemorrhage were
used in the study.
This study revealed
that the presence of diabetes was a significant risk factor for CKD (aOR=2.91. p – 0.033). These findings are similar to that
reported in the study by Poudyal et al49
and Ibitoba et al106 which demonstrated
that diabetes predisposes to the development of CKD with a significance level of ( p – 0.0001)
and ( p – 0.0001) respectively. Though the studies by Poudyal
et al and Ibitoba were done in the general
population, diabetes mellitus is a notable risk factor for CKD which may have
largely the same pathogenetic mechanisms in both the
general population and stroke patients.
Mechanisms that lead
to CKD in diabetes who develop stroke include hyperfiltration
injury, advanced glycosylation end products, and reactive oxygen species. At
the molecular level, numerous cytokines, growth factors, and hormones such as
transforming growth factor-beta and angiotensin II cause pathologic changes
associated with diabetic nephropathy.50
However, the findings
from this study are at variance with the findings in the study by Tsagalis
et al11 which showed that diabetes is not a risk factor for CKD in
stroke patients. The reason for the difference in the results from their
studies could be due to the definitions of diabetes mellitus used in their
study. They defined diabetes mellitus as the use of blood-sugar-lowering agents
before the occurrence of the stroke or if the fasting blood glucose level
exceeded 6.0mmml/l known before the stroke.
The presence of
Diabetes/Hypertension was shown as a significant risk factor for CKD in this
study (aOR=6.59, p – 0.035). There is a paucity of
data on the combination of Diabetes/Hypertension as a risk factor for CKD.
However, the synergistic effect of the two risk factors may have accounted for
this finding. Though hypertension was not a risk factor for CKD in this study
probably due to the low mean systolic and diastolic BP of the study
participants at presentation.
Dyslipidemia is
another risk factor for CKD that was shown in this study. This study
demonstrated that stroke patients with dyslipidaemia
had an increased risk for CKD (aOR=4.05, p – 0.041).
This finding of a positive relationship between dyslipidemia and CKD is
consistent with that reported by Yamagata et al,51
which is a community-based study in the general population making its
comparison with the findings from this study indirect.
Current studies have
shown that abnormal lipids in blood lead to the accumulation of ectopic lipids,
which can be deposited in almost all cell types from mesangial
cells to podocytes and proximal tubular epithelial
cells.52 Lipid-induced mitochondrial damage may also be more lethal
to proximal tubule cells.52 High cholesterol causes macrophage
infiltration and foam cell formation in the kidney. The accumulation of
triglycerides and lipid metabolism breakdown products in the blood of CKD
patients has a strong atherosclerosis and pro-inflammatory effect on the
vascular system in the renal parenchyma.
However, these
findings were in contrast to that demonstrated by Iseki et
al53 who found that hypercholesterolemia was not an independent
predictor of ESRD. Even though Iseki et al conducted their study in the general
population, the estimation of only total cholesterol in their study
participants may have accounted for this discrepancy in the findings, unlike
this study that estimated LDL-cholesterol, HDL-cholesterol, and triglyceride in
addition to the total cholesterol.
Comparison of stroke type and severity with renal
impairment in stroke patients
This study revealed
that the severity of stroke was significantly different in patients with
pre-existing CKD compared to patients without KF at the 6th
week post-stroke (a12.33, p
– 0.006). This result agrees with that which was demonstrated by Shittu7
who reported that the severity of stroke between patients with renal
dysfunction and those with normal renal function was statistically significant.
The Fukuoka Stroke Registry and the China National Stroke Registry both
reported a similar relationship between CKD and stroke severity in their
studies.9,54
The relationship
between pre-existing CKD and stroke severity can be attributed to the systemic
effects of proteinuria and advancing renal dysfunction leading to metabolic
changes in phosphate and calcium metabolism. Proteinuria and albuminuria are
associated with high levels of inflammatory cytokines and oxidative stress,
potentially causing excessive vascular damage at stroke onset9.
According to the Fukuoka Stroke Registry, proteinuria was associated with a
greater risk for neurological degeneration during hospitalisation
and mortality.9
The study also
demonstrated that disability was higher in patients who had no kidney failure
compared to patients with pre-existing CKD and this was statistically
significant ( 7.73, p -0.021). The findings from this
study are similar to the findings reported by Vijay et
al32 which reported that stroke patients with no renal dysfunction
had more disability when compared with patients with renal dysfunction. However, these findings
contrast with that reported by Hao et al55 which demonstrated that patients with KF had
more disability than those without KF. The difference in the findings between
this study and that of Vijay et al on the one hand and that by Hao et al on the other hand could be due to the higher
mortality in the former studies compared to the latter study which may have
involved most of the patients with kidney failure with disability.
Furthermore, patients
with pre-existing CKD
had more deaths compared to those without KF and this was
statistically significant ( p – 0.009). This is similar to the findings by Busari et al56, Seifu et al57 and Vijay et al47. The
high mortality in stroke patients with a pre-existing CKD may be due to the increased
risk of cardiovascular disease which is the commonest cause of mortality in
patients with CKD.58
Limitations
1.
Due
to the lack of an adequate renal database, some patients with pre-existing CKD
may have been missed.
2.
GFR
was assessed using prediction equations rather than by gold standard methods of
measurement.
Conclusion
·
The predictors of KF
among acute stroke patients demonstrated in this study include; diabetes,
DM/HTN, obesity, dyslipidemia, use of mannitol, and use of herbal concoctions.
·
AKI was more
prevalent among patients with haemorrhagic stroke while patients with
pre-existing CKD had a higher prevalence of ischemic stroke.
·
The study
demonstrated that stroke severity as represented by a high NIHSS Score was
associated with KF.
Recommendations
·
Patients’ education
to avoid the use of herbal concoctions in the treatment of any disease
specifically renal diseases.
·
More
studies on kidney failure in stroke patients should be conducted with follow-up
for at least 3 months to establish the proportion of patients that may develop
CKD from AKI or CKD ab initio following the stroke.
·
A
computerized renal database of all renal patients should be provided in all centres to aid in accurate patients’ renal history when
conducting future studies.
·
Larger
multi-centre studies are needed to corroborate the
results from this study to generalize the findings.
Conflict of interest: authors have declared that there was no conflict of
interest
Grant: There was no grant
for the study
Ethical approval:
In line with Helsinki declaration (revised 13th edition)
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