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Vol. 14(2), pp. 105-130, 2024
ISSN: 2276-7797
Copyright ©2024, the copyright of this article is retained by the author(s)
https://gjournals.org/GJMS
1 Department of Internal Medicine, University of Port Harcourt Teaching Hospital, Rivers State, Nigeria.
2 Department of Internal Medicine, Federal Medical Centre, Yenegoa, Bayelsa State, Nigeria
Type: Research
Full Text: PDF, PHP, HTML, EPUB
Published: 24/09/2024
*Corresponding Author
Ndu VO MBBCH, FMCP
E-mail: nduvictor5@ gmail.com
Background: Stroke is considered a leading cause of morbidity and mortality globally. Kidney failure is also increasing globally with a consequent increase in morbidity and mortality. Evidence from observational studies in patients suggests a cross-link between the brain and the kidney leading to the complex relationship between stroke and kidney failure. Therefore, early screening for kidney failure in stroke patients using certain tools is imperative. The early screening for kidney failure in stroke patients will also help distinguish acute kidney injury and existing CKD and promote attention to the care of AKI/CKD in stroke patients which may have adverse effects on stroke outcomes.
Objectives: The study sought to determine the risk factors of kidney failure; relationship between stroke type and severity among acute stroke patients admitted into the University of Port Harcourt Teaching Hospital (UPTH), Port Harcourt.
Methodology: This was a hospital-based, prospective cohort study conducted among acute stroke patients presenting at the UPTH. Selected stroke patients were categorised as having acute kidney injury (AKI), chronic kidney disease (CKD), acute-on-chronic kidney disease and no kidney failure after an assessment of their renal function using E/U/Cr at presentation, 48hrs and 7th day post-event. Urinalysis, urine output measurement and renal ultrasound scan were also done. Respondents were then followed up for 6 weeks for interim stroke and renal outcome. Data on sociodemographic characteristics, medical and social history, biochemical parameters, renal function, stroke severity, and stroke/renal outcome were collected using a structured questionnaire. Kidney Failure(KF) included AKI defined as either an increase in serum creatinine >26.5 µmol/l within 48 hours; or an increase in serum creatinine to >1.5 times baseline, which is known or presumed to have occurred within the prior 7 days or urine volume of <0.5ml/kg/hour for 6 hours; and pre-existing CKD considered present if the patient had hospital record of CKD, if patients or their relatives give a history of CKD, or have evidence of elevated serum creatinine (>1.5 mg/dl), persistent proteinuria (>300 mg/d), or abnormal renal ultrasound in the past 3 months. Determinants of KF(AKI and CKD) were investigated by Chi-square test, binary logistic regression and multivariate logistic regression. At the same time, the association between KF(AKI and CKD) and stroke type/severity was explored using the Chi-square test. A p-value of less than 0.05 was considered significant.
Result: Of the 150-respondent studied, there were 93(62.0%) male and 57(38.0%) female patients, with mean age of 54.6±10.6years. The risk factors for KF included obesity (aOR=3.61; p – 0.003), use of herbal concoctions (aOR=2.80; p – 0.030), and use of mannitol (aOR=3.37; p – 0.012) for AKI and diabetes (aOR=2.91 ;p – 0.033), DM/HTN (aOR=6.59; p – 0.035), obesity (aOR=6.45; p – 0.044), herbal concoction (aOR=1.38; p – 0.046) and dyslipidemia (aOR=4.05; p–0.041) for pre-existing-CKD. The severity of stroke as demonstrated by the NIHSS score showed a significant association (χ2=12.33;p–0.006) with pre-existing CKD at 6 weeks. Disability was higher among patients with AKI (54.2% Vs 43.6%) than those without KF which was statistically significant (χ2=6.56; p-0.038).
Conclusion: The risk factors of kidney failure in the study were hypertension, diabetes, hypertension/diabetes, family history of diabetes, use of herbal concoctions, use of mannitol, obesity and dyslipidemia. However, the predictors of KF were diabetes, hypertension/diabetes, obesity, dyslipidemia, use of mannitol and the use of herbal concoctions. The severity of stroke was found to be higher in patients with pre-existing CKD compared to patients with AKI.
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.
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.
The study is a hospital-based prospective cohort study.
This consisted of all consecutive adults (≥18 years) admitted for stroke.
Adults aged 18 years and above admitted to the hospital within 7 days of onset of stroke
Patients with neuroimaging evidence of stroke.
Stroke patients who grant informed consent
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.
The minimum sample size required for this study was calculated from the method of Kish14
n= zpq/ 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.
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.
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:
A properly functioning Accoson mercury sphygmomanometer which had been validated and well-calibrated was used.
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.
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.
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.
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.
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.
Table 1: Staging of Aki According to Kdigo
OR
≥0.3 mg/dl (≥26.5 µmol/l) increase within 48 hours
6–12 hours
≥12 hours
Increase in serum creatinine to
≥4.0 mg/dl (≥353.6 µmol/l)
Initiation of renal replacement therapy
In patients <18 years, decrease in eGFR to <35 ml/min per 1.73 m2
≥24 hours
Anuria for ≥12 hours
Renal USS was used to assess the features of CKD such as reduced bipolar length and transverse diameter, increased echogenicity, and loss of cortico-medullary differentiation. This was done by the researcher in the renal unit under a radiologist’s guidance while a mobile ultrasound machine was used for patients who could not be moved to the renal unit.
Participants were categorized into 4 groups:
Stroke patients with no kidney failure: which were considered as stroke patients who did not have any renal compromise: defined as serum creatinine of 52-106 µmol/l, an eGFR of > 90mL/min/1.73 m2 according to the guidelines of the National Kidney Foundation.20
Stroke patients that develop AKI: defined as either an increase in serum creatinine by ≥26.5µmol/l or 0.3mg/dl within 48hours or an increase in serum creatinine to >1.5 times baseline, which is known or presumed to have occurred within the prior 7 days with urine volume of <500ml/kg/hour for 6 hours.22
Stroke patients with pre-existing CKD: For this study, patients were considered to have a pre-existing CKD if they had a hospital record of CKD if patients or their surrogate gave a history of CKD, had evidence of elevated serum creatinine (>1.5 mg/dl), persistent proteinuria (>300 mg/d), or abnormal renal ultrasound for > 3months.23
Stroke patients with Acute-on-Chronic renal impairment: defined as stroke patients who develop AKI with background pre-existing CKD.
All patients received standard care and were monitored for 6 weeks to assess the interim renal outcomes (requirement of haemodialysis, improving or worsening of eGFR and recovery) and stroke outcomes (complete recovery, disability or death).
Respondents’ level of consciousness was assessed by the Glasgow Coma Scale (GCS) and rated as mild (GCS >13), moderate (GCS 8–13), or severe (GCS ≤7).
The severity of the stroke was graded according to the National Institute of Health Stroke Scale24 (NIHSS) score as shown in Table 2. The NIHSS questionnaire was administered by the researcher within 24 hours of presentation and on the 7th day of admission. The maximum score obtainable for the NIHSS is 42 and the minimum score is 0.25 The poor outcome was defined as less than 8-point improvement in the NIHSS score by the 7th day of admission or death on or before the 7th day.26
Table 2: National Institute of Health Stroke Score and Stroke Severity
Severe stroke
Data entry was done using a Microsoft Excel sheet and exported into a Statistical Package for Scientific Solutions (SPSS 23). The SPSS package was used for data cleaning and analysis. Before data entry was done into Microsoft Excel, the study questionnaire was thoroughly checked after the data collection exercise to ensure the correctness and completeness of each for all participants in the study.
Data analysis was done at the univariate and multivariate analysis levels. At the univariate analysis level, categorical variables like sex, educational level, ethnicity, type of stroke etc were summarized as frequencies and percentages while continuous variables like age, urine output, serum creatinine, serum potassium, eGFR were summarized using median and interquartile range since the data were not normally distributed (skewed).
Bivariate analysis was carried out to identify risk factors of kidney failure .All stroke patients with kidney failure were identified and the association between known risk factors of AKI and CKD were assessed by comparing the occurrence of the factors in stroke patients with AKI and CKD and stroke patients without any kidney failure using the Chi-square test. The risk factors compared included age, ethnicity, comorbidity like hypertension and diabetes, use of tobacco, participation in exercises, obesity, dyslipidaemia, and family history of chronic medical conditions like stroke, hypertension and diabetes. The use of herbal concoctions, mannitol and antihypertensive drugs like calcium channel blockers and ACE inhibitors were also compared between stroke patients with AKI and those without kidney failure. The comparison was also repeated for stroke patients with pre-existing CKD and stroke patients without kidney failure. A multivariate logistic regression analysis was carried out to further explore the predictors of kidney failure.
The type and severity of stroke were also compared between stroke patients with kidney failure (AKI and pre-existing CKD) and those stroke patients without kidney failure using the Chi-square test. The severity of stroke was assessed by the NIHSS score and GC score. The level of significance was set at p-value < 0.05.
Ethical clearance for the study was obtained from the Ethical Review Committee of the University of Port Harcourt Teaching Hospital, Port Harcourt.
Right of decline/withdrawal from the study: Written informed consent was obtained from the subjects (Appendix 1). The participants were informed that participation was voluntary and that they would not suffer any consequences if they chose not to participate.
Confidentiality of data: All information gathered was kept confidential, as access to this information was limited to the investigator, and the managing team when appropriate. All participants were identified using only serial numbers.
Beneficence to participants: All laboratory investigations were done at no cost to the participants, and results were released to aid the management of the participants. In addition, participants were counselled on the findings of their clinical data and the results of their laboratory investigations
The study consisted of 150 participants of which 93 were males and 57 were females with male to female ratio of 1.6:1. The age range of patients was between 30 and 75 years with a mean age of 54.6 ±10.6years.
Table 3 shows the sociodemographic characteristics of the study participants.
Table 3: Sociodemographic characteristics of stroke patients in the study
Others
The mean Waist Circumference of patients was 93.2 ± 9.8cm while the mean Waist-Hip ratio was 0.92 ± 0.44cm (Table 4). Fifthy-eight (38.7%) patients were obese based on the anthropometric measurements. ( Table 5)
The mean total cholesterol levels, triglycerides, LDL cholesterol and HDL cholesterol of patients in mmol/l are 5.2±0.5,1.5±3.0,3.3±0.3 and 1.5±0.8 respectively(Table 4) and eighty-one (54%) of patients had normal fasting lipid profile while sixty-nine (46%) of patients were seen to have dyslipidemia. (Table 5)
Table 4 shows the anthropometric measurements and fasting lipid profile, of the study participants.
Table 5 shows the proportion of patients with obesity and dyslipidemia among the study participants
Table 4: Anthropometric measurement and Biochemistry findings among stroke patients in UPTH, Port Harcourt
Parameter
Table.5: Proportion of patients with obesity and dyslipidemia among participants in the study
It was noted that eighteen (12%) patients were current smokers while majority of the patients (77.3%) live a sedentary life. Family history of hypertension was the most prominent family history of medical condition as found in 92 ( 61.3%) patients. Seventy-one (47.3%) patients and eighty (53.3%) patients had a history of changes in urination and history of changes in urine appearance respectively.
Medical and clinical characteristics of patients in the study are shown in Table 6
Table 6 :Medical history and clinical characteristics of patients in the study
Characteristics
Figure 1 shows that the median eGFR of the participants in the study at presentation was 40 mL/min/1.73m2 , with an interquartile range eGFR of (IQR – 20.0 – 88.3 ml /min/1.73m2). The median eGFR was 24.0 mL/min/1.73m2 (IQR: 12.0 – 87.3 ml/min/1.73m2) after 48 hours of presentation. The median eGFR rose to 67 mL/min/1.73m2 (IQR – 21.5 – 91.0 ml/min/1.73m2) on the 7th day and 87.0 (IQR – 31.0 – 97.0 ml/min/1.73m2) at 6th week post stroke.
At presentation, the median serum urea was noted to be 10.5mmol/l (IQR 5.9 – 18.0mmol/l; this increased to 14.0mmol/l (IQR 6.2 – 22.2mmol/l) after 48 hours of presentation. By the 7th day on admission, the median serum urea had dropped to 7.7mmol/l (IQR 5.9 – 18.0mmol/l). The decline in the serum urea was sustained till the 6th week after the stroke at a median value of 6.8mmol/l (IQR 5.8 – 14.0).
Potassium increased from 4.7mmol/l (IQR: 4.3 – 5.0mmol/l) at presentation to 4.9mmol/l after 48-hours, and increased to 5.2mmol/l by 7 days but later dropped to 4.7mmol/l (IQR: 4.4 – 4.9mmol/l) at 6th week post stroke event (Figure 1)
Figure 1 shows that the median serum creatinine at presentation was 145 µmol/l (IQR: 85.0 – 287.8 µmol/l); after 48 hours the median serum creatinine of patients increased to 230 µmol/l (IQR: 84.0 – 420.0 µmol/l). However, at 7th day post stroke the median serum creatinine had reduced to 102.5 µmol/l (IQR: 85.0 – 268.8 µmol/l) and declined to 82.0 µmol/l (IQR: 70.0 – 220.0 µmol/l) by 6-weeks post stroke ( Figure 1).
*eGFR – ml/min/1.73m2, creatinine – µmol/l, serum urea, sodium and potassium – mmol/l
Figure 1: Average values of eGFR, serum Urea, creatinine, Sodium and Potassium at presentation, 48 hours after presentation, 7th day and 6th week post-stroke among study participant.
On renal ultrasound, 94 (62.7%) patients had preserved corticomedullary differentiation (CMD), with loss of CMD noted in 56 (37.3%) patients. The kidneys of one hundred and three (68.7%) patients had normal echogenicity while that of forty-four (21.3%) had increased echogenicity. The majority of patients (84%) had no cysts in their kidneys. Only sixteen (10.7%) patients had calyceal dilatation. Furthermore, fourty-three (28.7%) patients has shrunken kidneys. (Table 7)
The right kidneys of patients had an average length of 9.0±2.0,breadth of 5.1±1.5,thickness of 6.2±0.6 and volume of 147.8±35.4 respectively compared to the left kidneys which showed an average length of 8.9±1.1,breadth of 4.8±0.7, thickness of 6.1±0.9 and volume of 148.7±32.8 respectively.(Table 8). The kidney dimensions of patients in the study in centimeters are shown in Table 8.
Table 7: Renal Ultrasound finding among stroke patients in the study
Table 8: Kidney dimensions among stroke patients in UPTH, Port Harcourt
Figure 2 shows the severity of stroke assessed by the NIHSS score and the median score for the stroke patients at presentation was 20 (IQR:18 – 24); on the 7th day post-stroke it was 10 (IQR: 8 – 14) while on the 6th week post-stroke it was 4 (IQR: 2 – 6).
Figure 2: Box and whisker chart showing the NIHSS scores in patients at presentation, 7th day and 6th-week post-stroke among study participants.
As shown in Table 9, the comparison of sociodemographic factors between patients with AKI and those without kidney failure reveals that only participants of Yoruba extraction ( χ2 = 13.15; p – 0.004) had a statistically significant relationship with the occurrence of AKI among stroke patients. Although the prevalence of AKI was higher among male patients (53.8%), the observed difference in the distribution of AKI between the sexes was not significant statistically (χ2 = 0.43; p – 0. 511). The age of participants (χ2 = 1.23; p – 0.873) did not show a significant relationship with the occurrence of AKI even though 66.7% of the elderly (>70 years) had AKI compared to 40.0% of patients in the 4th decade of life (30 – 39 years).
Table 9: Relationship between sociodemographic characteristics and AKI among stroke patients in the study
N = 59 (%)
N = 55 (%)
8 (44.4)
*Significant statistically; Note – Row percentages were reported
Table 10 showed that the risk of developing AKI in stroke patients was significantly higher in patients who are hypertensive (χ2 =3.99; p – 0.046), diabetic (χ2 =4.32; p – 0.037), hypertensive/diabetic ((χ2 = 8.18; p – 0.038) and the presence of obesity ( (χ2 = 9.54; p – 0.002). The use of herbal concoctions ((χ2 = 8.54; p – 0.003) and the use of mannitol ((χ2 =12.34; p – 0.001) were also significantly related to the occurrence of AKI in stroke patients in the study. (Table 10)
However, presence of dyslipidemia ((χ2 =1.90; p – 0.168) and a family history of diabetes ((χ2 =0.02; p – 0.896) did not significantly contribute to the occurrence of AKI among the patients in the study. (Table 10)
Table 10: Relationship between medical history, family history of chronic medical condition, use of herbal concoction and medication use with AKI among stroke patients in the study
Family history of hypertension
44 (45.4)
*Significant statistically; Note – Row percentages were report
Table 11: revealed that only obesity (aOR=3.61; 95% CI: 1.10 – 7.12, P – 0.003), use of herbal concoction ( aOR= 2.80; 95% CI: 1.57-8.33, P -0.030) and use of mannitol ( aOR=3.37;95% CI:1.64- 8.52, p – 0.012) were the predictors of AKI in stroke patients using multivariate logistic regression in the study. (Table 11)
Table 11: Predictors of Acute kidney injury among stroke patients in UPTH, Port Harcourt
(95%CI)
Ethnicity was the only sociodemographic characteristic tested in the study that was significantly related to the occurrence of pre-existing CKD (χ2 = 7.96; p – 0.047). This is shown in Table 12.
Sex (χ2 = 0.18; p – 0.674), Age (χ2 = 3.48; p – 0.481), educational level (χ2 = 4.36; p – 0.225), Religion (χ2 = 0.52; p – 0.770), and income (χ2 = 0.91; p – 0.635) were not significantly associated with pre-existing CKD in stroke patients in this study (Table 12).
Table 12: Relationship between sociodemographic characteristics with pre-existing CKD among stroke patients in the study
N = 107
N = 52 (%)
*Significant statistically; Note – Row percentages were reported.
The presence of hypertension (χ2 = 4.15; p – 0.043), diabetes (χ2 = 13.45, p – 0.001), Hypertension/ Diabetes mellitus ((χ2 = 15.03; p – 0.002); obesity ((χ2 =14.61; p – 0.001), dyslipidemia ((χ2 =6.78; p – 0.009) and the use of herbal concoction (χ2 = 18.56; p – 0.001) among stroke patients is significantly associated with pre-existing CKD in this study. (Table 13).
Stroke patients who had a family history of diabetes mellitus had a higher risk of occurrence of pre-existing CKD and this was statistically significant (χ2 =7.1; p – 0.007). This is shown in Table 13.However, the use of mannitol following the stroke (χ2 = 3.43; p –0.062) and stroke patients who had a family history of diabetes mellitus (χ2 =3.15; p – 0.076) were not significantly related to the presence of CKD. (Table 13)
Table 13: Relationship between medical history, family history of chronic medical conditions, use of herbal concoction and medication with pre-existing CKD among stroke patients in the study
Chronic Kidney Disease
*Significant statistically; HTN – Hypertension; DM – Diabetes mellitus; Note – Row percentages were reported.
Table 14: demonstrated that diabetes (aOR=2.91, 95% CI: 1.16- 21.39, p – 0.033), combined HTN/DM ( aOR=6.59, 95% CI:1.01-43.40, p – 0.035), use of herbal concoction ( aOR=1.38, 95% CI:1.03-5.84, p – 0.046), obesity ( aOR= 6.45, 95% CI:1.90- 46.32, p – 0.044) and dyslipidemia ( aOR=4.05, 95% CI: 1.06 – 15.48, P – 0.041) were predictors of pre-existing CKD using multivariate logistic regression in the study. ( Table 14)
Table 14: Predictors of Chronic Kidney diseases among stroke patients in UPTH, Port Harcourt
Haemorrhagic stroke was slightly more common among patients with AKI (39.0% Vs 29.1%) than among those without KF. However, Ischaemic stroke was commoner among patients with KF compared to patients with AKI (70.9% Vs 61.0%); hence there was no significant difference (χ2 = 1.24; p – 0.266) in the distribution of stroke type between patients with AKI and those without KF (Table 15).
The severity of stroke at presentation was not significantly (χ2 = 3.13; p – 0.209) different between patients with AKI and those without KF. (Table 15). At presentation, 15.3%, 28.8%, and 55.9% had ‘moderate’, ‘moderate to severe’ and ‘severe’ stroke symptoms among patients with AKI, while 18.2%, 36.4%, and 45.5% among those without KF had ‘moderate’, ‘moderate to severe’ and ‘severe’ stroke symptoms respectively (Table 15). This trend was also seen on the 7th day (χ2 = 3.08; p – 0.545) and 6th week (χ2 = 3.56; p – 0.313) post-stroke, the severity of stroke among patients with AKI and those without KF was not significantly different (Table 15)
The stroke recovery using the improvement in NIHSS score on the 7th-day post-stroke was also not significantly (χ2 =1.85 ; p – 0.398) different between the patients with AKI and those without KF (Table 15).
Table 15: shows that 16 of 55 patients (29.1%) without KF had complete recovery, while 6 out of 59 patients (10.2%) with AKI had complete recovery. (Table 4.14). The difference in the stroke recovery rates between those with AKI and those with no KF was statistically significant (χ2 = 6.56; p – 0.038). Though mortality was higher among patients with AKI (35.6% Vs 27.3%) compared to those with no kidney failure, the difference is not statistically significant.
Table 15: Comparison of stroke type, severity and outcomes among stroke patients with AKI and those without kidney failure.
N = 114
aFisher’s exact test
Comparison of stroke type, severity and outcome among stroke patients with pre-existing CKD and those without kidney failure
Ischaemic stroke was slightly more common among patients with pre-existing CKD (75.0% Vs 70.9%) than those without KF. The reverse was the case for haemorrhagic stroke which was more common (25.0% Vs 29.1%) among those without KF than those with pre-existing CKD. The relationship between stroke type and renal status is not significant ((χ2 = 0.22; p – 0.636) (Table 4.15). The severity of stroke at presentation (χ2 = 1.78; p – 0.411). and on Day 7 after stroke (χ2 = 4.26; p – 0.372). was not significantly different between patients with pre-existing CKD and those patients without KF (Table 16). By the 6th-week post-stroke only one patient among those with pre-existing CKD (1.9%) had “no stroke symptoms”, 9 patients (16.4%) among those without kidney failure had “no stroke symptoms” (Table 16). This showed that severity was significantly different (χ2 = 12.33; p – 0.006) between patients with pre-existing CKD and those without KF by 6th-week post-stroke. Whereas about half of patients (51.9%) with pre-existing CKD died by 6 weeks post-stroke, about a quarter of patients without KF (27.3%) died by 6 weeks post-stroke. The recovery using the improvement in NIHSS score on the 7th-day post-stroke was also not significantly different between patients with pre-existing CKD and those without KF (χ2 = 2.70; p – 0.259). (Table 16).
The proportion of patients who had complete recovery (13.5% Vs 29.1%), disability (34.6% Vs 43.6%), or died (51.9% Vs 27.3%) among those with pre-existing CKD and those without KF respectively, was significantly different (χ2 = 7.73; p – 0.021) in this study (Table 16). Furthermore, Table 16 showed that a significantly higher proportion (χ2 = 6.75; p – 0.009) among patients without KF (72.7%) survived the stroke event than patients with pre-existing CKD (48.1%).
Table 16: Comparison of stroke type, severity and outcome among patients with pre-existing CKD and without kidney failure among study participants
aFisher’s exact.
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.
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.
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
Due to the lack of an adequate renal database, some patients with pre-existing CKD may have been missed.
GFR was assessed using prediction equations rather than by gold standard methods of measurement.
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.
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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