Kidney Function in Children with Severe Malaria Seen at the University of Ilorin Teaching Hospital, Ilorin

Abstract

Background: Malaria is the leading cause of hospital admission in Africa and constitutes the greatest disease burden in the region. More than one hundred nations are affected worldwide with children and pregnant women being mostly vulnerable. Children under the age of five years suffer severe forms. Malaria is said to be severe when the acute illness is associated with a life-threatening event(s). Several organ systems including the kidney can be involved. In most cases, severe malaria if untreated tends to result in Acute kidney injury. Therefore, the objective of this study is to examine kidney function in children with severe malaria seen at the University of Ilorin Teaching Hospital (UITH), Ilorin. A prospective case-control study was conducted in the Emergency Paediatrics Unit (EPU), the Children’s ward, and the General Outpatient Department (GOPD) of the UITH over one year. A total of 164 children were recruited into the study, of which 82 had severe malaria served as subjects and 82 with uncomplicated malaria served as controls. The male-to-female ratio was 1:1 in the subjects and 1.4:1 in the controls. The median age was 36.0 months in the subjects and 36.0 months in the controls, both groups were comparable (p > 0.05). Children between the ages of 1 to 5 years constituted 62.2% of the entire population studied. The estimated Glomerular Filtration Rate (eGFR) in children with severe malaria was compromised in 30% of cases. Improved Global Outcomes (KDIGO) and World Health Organization (WHO) criteria; an increase in serum creatinine value of 0.3 mg/dl (5.4 mmol/l) within 48 hours of admission was applied. Correspondingly the serum urea and creatinine were compromised in the same group of patients. The prevalence of acute AKI in this study was 30.5%. The mean eGFR, potassium, sodium, urea, and creatinine at admission were 74.6 ± 56.3 ml/min/1.73m2, 5.4 ± 0.5 mmol/l, 143.9 ± 12.3 mmol/l, 117.2 ± 27.5 µmol/l and 6.3 ± 5.6 mmol/l respectively. Outside sodium, these parameters were higher in subjects than in controls.

Share and Cite:

Ajetomobi, A., Mark, F., Lawal, R., Olanrewaju, P.O., Owa, J.A., Toye, I.I., Oyeleke, F., Oladipe, T.T., Adedigba, E.O., Adedoyin, O.T. and Ojuawo, A. (2025) Kidney Function in Children with Severe Malaria Seen at the University of Ilorin Teaching Hospital, Ilorin. Open Access Library Journal, 12, 1-21. doi: 10.4236/oalib.1113064.

1. Introduction

The World Health Organization (WHO) World Malaria Report 2019 estimates 228 million cases of malaria worldwide, causing 405,000 deaths in the year 2018, many under the age of 5 years [1]. In 2018, nineteen sub-Saharan African countries and India carried approximately 85% of the global malaria burden [1] [2]. Malaria is said to be severe when the acute illness is associated with life-threatening event(s) [2]-[7]. Several organ systems including the kidney can be involved [8]-[14]. The main manifestations of severe malaria among semi-immune, residents of malaria-endemic countries are cerebral malaria and severe anaemia. Acute kidney injury is not uncommon [3] [15]-[25]. In some cases of kidney involvement malaria, damage to the kidneys might persist beyond the acute illness, as described in P. malariae infection and this could progress to nephrotic syndrome [3] [4].

More children particularly under-fives are now observed to present with renal impairment as a component of severe malaria despite improvements in case management and malaria control programmes, in Nigeria [1] [19] [26]-[28]. Survivors are commonly left with long-term morbidities [5]. Determination of the presence of acute kidney injury in severe malaria is essential for appropriate clinical management of patients with malaria as it may determine the subsequent use of drugs and fluid. The estimated glomerular filtration rate (eGFR), which is the volume of plasma that can be completely cleared of a particular substance by the kidneys in a unit of time remains the best indicator of kidney function [29]-[39].

Malaria constitutes about 25% of the disease burden in children in Nigeria with its attendant effects on virtually all organs of the body [19] [28]. The extent to which renal function is affected in Nigerian children, particularly in the north-central region is not known, hence, this study aims at determining the effects of severe malaria on the kidneys. The understanding of the degree of renal involvement in children with severe malaria will enhance case management through the use of appropriate therapies to prevent renal damage, particularly in our sub-region where facilities for Renal Replacement Therapy (RRT) are not within easy reach (See Table 1).

Table 1. Definitions of acute kidney injury.

RIFLE, 2004

Pediatric RIFLE, 2007

AKIN, 2007

KDIGO, 2012

Urine output

Criteria

Creatinine Definition

Criteria

Creatinine Definition

Criteria

Creatinine Definition

Criteria

Creatinine Definition

Risk

≥1.5x increase in SCr from baseline or decrease in GFR ≥ 25%

Risk

Decrease in GFR ≥ 25

Stage 1

≥0.3 mg/dL increase in SCr within 48 hrs or ≥1.5x increase in SCr from baseline

Stage 1

≥0.3 mg/dL increase in SCr within 48 hrs or ≥1.5x increase in SCr from baseline

<0.5 mL/kg/h for >6 hrs

Injury

≥2x increase in SCr from baseline or decrease in GFR ≥ 50%

Injury

Decrease in GFR ≥ 50%

Stage 2

≥2x increase in SCr from baseline

Stage 2

≥2x increase in SCr from baseline within 7 days

<0.5 mL/kg/h for ≥12 hrs

Failure

≥3x increase in SCr from baseline or decrease in GFR ≥ 75%, SCr ≥ 4.0 mg/ dL with an acute increase of >0.5 mg/Dl

Failure

Decrease in GFR ≥ 75% or an eGFR < 35 mL/ min per 1.73m2

Stage 3

≥3x increase in SCr from baseline, SCr ≥ 4.0 mg/dL with an acute increase of >0.5 mg/dL or initiation of KRT

Stage 3

≥3x increase in SCr from baseline within 7 days, SCr ≥ 4.0 mg/dL with an acute increase of >0.5 mg/dL or initiation of KRT

<0.3 mL/kg/h for ≥24 hrs or anuria for ≥12 hrs

Loss

Failure for >4 weeks

Loss

Failure for >4 weeks

ESRD

Failure for >3 months

ESRD

Failure for >3 months

2. Objective of the Paper

The specific objectives of the paper:

1) Estimate glomerular filtration rate, serum electrolyte, urea, and creatinine of children with severe malaria.

2) Find out the prevalence of AKI in children with severe malaria.

3. Methods

Study Design

This was a prospective case-control observational study conducted in the Emergency Paediatrics Unit (EPU), the Children’s ward, and the General Outpatient Department (GOPD) of the UITH over one year. Improved Global Outcomes (KDIGO) and World Health Organization (WHO) criteria; an increase in serum creatinine value of 0.3 mg/dl (5.4 mmol/l) within 48 hours of admission was applied.

Study Site

UITH is located within north-central Nigeria, situated in Southern Guinea Savannah belt of Nigeria, a sub-humid zone, enjoys two climatic seasons, dry and wet seasons, with a mean temperature range of 21.5˚C - 38.5˚C and an annual rainfall of 1080 mm and length of growing period of 175 to 190 days, both of which favours plasmodium and vector development and survival [1]-[4].

Study Subjects

The study was conducted among children between the ages of 6 months and 14 years with severe malaria, and children of the same ages with uncomplicated malaria served as controls.

Inclusion Criteria (Cases)

a) Children with clinical features suggestive of severe malaria

b) Children with laboratory features suggestive of severe malaria

Inclusion Criteria (Controls)

Children with clinical and/or laboratory features of malaria with no life-threatening event(s).

Exclusion Criteria Cases and Controls

a) Children with history of renal illness before the onset of malaria.

b) Children on drugs that affect renal function such as aminoglycosides.

c) Children with concomitant illnesses.

Sample Size

The minimum sample size was determined using the formula

n= Z 2 Pq d 2 [8]

where;

n = desired sample size

Z = the standard normal deviation usually set at 1.96% (or simply at 2.0) which corresponds to 95% confidence interval.

P = the proportion in the target population estimated to have a particular characteristic (renal impairment in severe malaria).

A reasonable estimated mean was 5.9% (WHO, 1996). The quoted estimate was that of renal involvement in severe malaria as reported by several authors in the earlier studies [11] [25]-[29].

d=tolerable margin of error usually set at0.05 q=1.0p =1.00.05=0.95

Thus, the minimum sample size:

n= 1.96×1.96×0.059×0.95 0.05×0.05 n= 3.8416×0.0475 0.0025  n=73.074=74

The minimum sample size was 74.

Allowing for an attrition rate of 10%, a total of 82 children with severe malaria and 85 children with uncomplicated malaria were recruited into the study.

Ethical Considerations

Ethical clearance was obtained from the Ethics and Research Committee (ERC) of the Hospital. Informed consent was obtained from the mother, parents, or caregiver before subject recruitment after clearly explaining the study in the language they best understood.

Subject Recruitment

Children between the ages of 6 months and 11 years presenting in the EPU with features of severe malaria were recruited consecutively as they presented. Those with features of uncomplicated malaria presenting in the General Outpatient Department (GOPD) as well as EPU between the ages of 6 months to 11 years were recruited as controls.

Severe malaria is commonest in children under the age of five years when the morbidity and mortality are highest. Children older than five years are, however, not spared even though at a lower rate when compared to children aged 5 years and below [3] [5] [8]-[12]. It was not the intention of the researcher to restrict the subject to under-five as older children have been known to have cerebral malaria. This informed the decision to also study children above five years up to 11 years.

Recruitment Procedures

Detailed history of the illness in each child recruited into the study was obtained from a reliable informant(s). A thorough physical examination was carried out on each child and features of severe malaria such as; severe anaemia, cerebral malaria, hyperpyrexia, prostration, and jaundice among others were noted in a proforma, where they were found. Glasgow coma scoring was done where appropriate. The height of children aged one to eleven years was assessed using a stadiometer. The length of children less than one year was assessed using an infantometer. The weight assessment was done using a weighing scale as appropriate for the age of the child. The weighing scale was standardized using standard weight periodically. The length of children (irrespective of age) who were unconscious was also determined as described above. The weight of unconscious patients was estimated by weighing each patient with the mother or the caregiver, subsequently, the mother’s (caregiver’s) weight was subtracted from the sum to arrive at the patient’s weight. The height/length measurements of the subjects were documented sequentially. The essence of detailed anthropometric measurements was to aid appropriate drug and fluid management of the patients, it was also needed for the estimation of eGFR in each subject. Details of home interventions and/or remedies were documented appropriately. The social class of each child was determined using the Social Classification model [27], by estimating the mean of four scores, to the nearest whole number of the parental (mother and father) educational attainments and professions. The controls were recruited consecutively at the Children’s Emergency Unit and General Outpatient Department of UITH.

Sample Collection

1) Blood Sample and Laboratory Procedure

2) Sampling was done in an aseptic manner using a sterile 23G needle attached to a 5ml syringe. The researcher collected 5 mls of blood with the assistance of the registrars working in EPU. Of this, random blood sugar was determined by glucometer using a drop of whole blood; the test strips used were the ACCU-CHEK [28]-[31] following standard operational procedure as prescribed by the manufacturer, two milliliters was dispensed into a specimen bottle containing dipotassium salt of ethylene diamine tetra-acetic acid (EDTA) for complete blood count and malaria parasite identification and quantification. The World Health Organisation [28] [29], procedure was adopted to detect and identify malaria parasites. Thin and thick blood smears were made. The thin film was fixed in methanol. The thick film was stained in 2% Giemsa stain for 30 minutes while the thin film was stained in Leishman stain. The slides were rinsed in phosphate buffer (PH 7.2) for three seconds, dried, and examined with x 100 objectives for malaria parasites. Parasite count was done via a count of parasites in a field containing 200 white blood cells (WBC) in the thick film, and the number of asexual forms per microlitre was calculated from the WBC count using the formula

PC x TLC

200

where

PC = Parasite count

TLC = Total leucocyte count

An observation of a parasitaemia rate of 5% and above for the red blood cells (RBC) was regarded as severe. The counting was done under the supervision of the Chief Laboratory Technologist in the Haematology Laboratory of UITH.

The packed cell volume (PCV) was expressed as the volume of erythrocytes per litre of whole blood so that it indicated the relative proportions of plasma and red cells. A heparinized capillary tube was used to take blood from the EDTA specimen bottle and centrifuged using the microhaematocrit centrifuge at 1000 revolutions per second for five minutes. The capillary tube was transferred to the haematocrit reader and the column of the Red Blood Cells (RBCs) was measured and this corresponded to the PCV [29].

Serum Electrolytes Urea and Creatinine Estimation

The remaining three milliliters of venous blood were collected in a plain specimen bottle for serum creatinine, urea, sodium, and potassium. The estimation of serum creatinine was done by a Laboratory scientist at the UITH Chemical Pathology Laboratory using the Jaffe’s method on Corning colorimeter reading at 520 nanometers. [30]-[33] The serum sodium and potassium were analysed by the flame photometry method [15]-[18] using the Galenkamp flame photometer. The serum urea and creatinine were determined by the diacetyl monixime method on a Corning colorimeter reading at an optical density (OD) of 520 nanometers [15]-[17].

The coefficient of variation was ±2% for within-run samples and ±4% for between-day samples using serum. When analysis was not done on the day of sample collection; blood was stored in the refrigerator at 4˚C without freezing and then sent to the laboratory the next working day. Creatinine estimation was done both in the acute phase of illness and at the fourth week for each child. The estimated glomerular filtration rate (eGFR) was determined using Schwartz’s formula [33] as shown below to overcome the problems associated with accurately timed urine collection in the estimation of GFR. The eGFR was determined at the onset and four weeks later, clinical and laboratory recovery was expected before this time [16]-[26].

Schwartz’s formula:

GFR= kL Scr ml/ min / 1.73 m 2

where:

k = Constant of proportionality

k = 0.55 for children less than 13 years

k = 0.77 for children greater than 13 years

L = Body height in cm.

Scr = Serum creatinine in mg/dl.

Urinalysis

About 15 - 20 mls of freshly voided urine was collected from each child into a sterile universal bottle. Urinalysis was performed immediately by the investigator using the dipstick method. Ten milliliters of urine were tested, using Multistix 10SG (Bayer Diagnostics, with a sensitivity of 98.5%) [9] [10].

A) Physical characterization of urine

Urine collected in the Universal bottle was subjected to direct observation for

1) Colour

2) Clarity

B) Dipstick reagent strip

Procedure [9] [10]

Part (10 mls) of the collected uncentrifuged urine was properly mixed before testing.

All reagent pads of the strip were immersed in the urine specimen and the strip was removed immediately.

The edge of the strip was run against the rim of the container to remove excess urine.

The test strip was held horizontally and the colour changes on the test areas were compared closely with colour chart on the container.

The colour changes were read at the times specified by the manufacturer.

All instructions as regarding the storage and handling of the reagent strip were observed as stipulated by the maker [9] [10].

Statistical Analysis

Data were analyzed using SPSS 13.0 software. Data collected on the study proforma were entered using numeric codes. Frequency distribution tables of demographic variables were generated. Measures of central tendency and dispersion of quantitative variables were determined. The chi-square test (with Yates correction or Fisher’s exact where applicable) and student t-test were used to test for the significance of the difference between categorical variables and continuous variables respectively. The level of significance was put at p value of less than 0.05.

4. Result

General characteristics of the study population

A total of 164 children were recruited into the study out of which 82 (50%) had severe malaria and another 82, without severe malaria, serving as controls. The male-to-female ratio was 1: 1 in the subjects and 1.4:1 in the controls. The median age was 36.0 months in the subjects and 36.0 months in the controls, both groups were comparable (p > 0.05). Children between ages 1 to 5 years constituted 62.2% of the entire population studied (Table 2).

Table 2. Gender and age distribution of the study population.

Sex

Total

Subject

Controls

n = 82 (%)

n = 82 (%)

Male

88

40 (45.5)

48 (54.5)

Female

76

42 (55.3)

34 (44.7)

M:F

1:01

1:01

1.4:1

Age in months

6 - 12

25

11 (44.0)

14 (56.0)

13 - 24

48

22 (54.9)

26 (45.1)

25 - 36

39

19 (48.7)

20 (51.3)

37 - 48

26

16 (40.6)

10 (59.4)

49 - 60

13

8 (61.5)

5 (38.5)

61 - 72

8

4 (50.0)

4 (50.0)

≥73

5

2 (40.0)

3 (60.0)

Total

164

82 (50.0)

82 (50.0)

Socio-economic classification, anthropometric measurements, and clinical features in the study population.

There was no statistically significant difference in the socio-economic classification of the subjects and the controls (p = 0.08).

The mean weight of the subjects was 15.1 ± 6.9 kg, while the mean length or height was 98.4 ± 15.5 cm. There were no statistically significant differences when compared with those obtained in the controls (p = 0.06).

The leading clinical feature in the study population was fever which occurred in 69 (82.0%) subjects and 75 (95.1%) controls (p = 0.48). This was closely followed by pallor in 79.3% of subjects and was significantly higher than what was obtained in the control (p = 0.001). Other clinical features of note included difficulty in breathing 50.0%, oliguria 28.1%, vomiting 25.1%, and convulsion 20.7% (Table 3).

Table 3. Clinical features in the study population.

Clinical Feature

Subject

Control

χ2

P

N = 82 (%)

n = 82 (%)

Vomiting

21 (25.1%)

15 (18.3%)

2

0.157

Pallor

65 (79.3%)

38 (46.3%)

14.16

0.001

Difficulty with

breathing

41 (50.0%)

0 (0.0)

Fever

69 (84.0%)

75 (91.5%)

0.5

0.48

Convulsions

17 (20.7%)

0 (0.0)

Yellowness of eyes

18 (22.0%)

0 (0.0)

Passage of dark

urine

16 (19.5%)

0 (0.0)

Oliguria

23 (28.1%)

0 (0.0)

Severe dehydration

12 (14.6%)

Home remedy in the study population

Several forms of remedies were offered to the subjects before presenting in the hospital, ranging from chloroquine (12.2%), paracetamol (18.3%), artesunate (11.0%), quinine (4.9%) and herbal preparations (15.9%). Herbal preparations were mostly used in the subjects (9.8%) than in the controls (2.4%) (χ2 = 7.2, p = 0.001) (Table 4).

Table 4. Home remedies in the study population.

Home Remedies

Subjects

Controls

χ2

P

n = 82 (%)

n = 82 (%)

Paracetamol (PCM)

15 (18.3)

13 (15.9)

0.29

0.593

Chloroquine

10 (12.2)

14 (17.1)

1.33

0.248

Artesunate

3 (3.7)

6 (7.3)

2

0.157

Herbal preparation

8 (9.8)

2 (2.4)

7.2

0.001

Chloroquine+ PCM

20 (24.4)

22 (26.8)

0.98

0.332

Artesunate + PCM

6 (7.3)

9 (11.0)

1.2

0.273

Herbal preparation + PCM

10 (12.2)

5 (6.1)

3.33

0.067

Quinine

4 (4.9)

0 (0.0)

Fansidar

3 (3.7)

6 (7.3)

2

0.157

No remedy

3 (3.7)

5 (6.1)

1

0.317

Total

82 (100.0)

82 (100.0)

Malaria Parasite density observed in the study population

The mean parasite density in the subjects was 243,235 ± 19.4/200WBC, while the mean in the controls was 107,257 ± 21.0/200WBC and the difference was significant (p = 0.001). Most of the children in the study population, 46 (56.1%) had a parasite density < 50,000/200WBC, while only 7 (8.5%) had hyperparasitaemia. The parasite density in the subjects was significantly higher than that in the controls. (Yates corrected χ2 = 5.37, p = 0.020), (Table 5).

Table 5. Malaria parasite density of the study population.

Parasite density

Subjects

Controls

n = 85 (%)

n = 85 (%)

χ2

p

0 - 50,000

48 (56.5)

76 (89.4)

13.07

0.003

50,001 - 100,000

12 (14.1)

3 (3.7)

9.14

0.003

100,001 - 150,000

10 (12.2)

4 (4.7)

7.54

0.006

150,001 - 200,000

4 (4.9)

2 (2.4)

0.33

0.564

200,001 - 249,999

4 (4.9)

0 (0)

8.00

0.005

≥250,000

7 (8.5)

0 (0)

14.00

0.000

Total

85(100.0)

85 (100.0)

χ y 2 = 5.37, p = 0.020.

Biochemical profiles in the study population at admission

The mean serum sodium of the study population was 143.9 ± 12.3 mmol/l compared to 133.6 ± 12.9 mmol/l in the control group (p = 0.555). The mean serum potassium was 5.4 ± 0.5 mmol/l compared to 3.2 ± 0.7 mmol/l in the controls (p = 0.002). The mean serum urea and creatinine in the subjects were 6.3 ± 5.6 mmol/l and 117.2 ± 27.5 µmol/l respectively while values for the controls were 3.1 ± 2.3 mmol/l and 91.1 ± 8.6 µmol/l respectively. The subjects’ serum potassium, urea, and creatinine were significantly higher in the subjects than in the controls (p < 0.05) (Table 6). This finding is partly due to fever and catabolism in the acute state of illness.

Table 6. Biochemical profiles in the study population at admission.

Biochemical

Profiles

Subjects

Controls

T

P

n = 85

n = 85

Sodium in mmol/l

Mean (SD)

146.9 ± 11.3

136.8 ± 10.9

0.583

0.55

Range

134.5 - 159.1

133.6 - 159.1

Potassium in mmol/l

Mean (SD)

5.7 ± 0.4

3.3 ± 0.8

3.54

0.002

Range

3.0 - 7.2

2.6 - 5.7

Urea in mmol/l

Mean (SD)

6.3 ± 5.6

3.1 ± 2.3

4.791

0.001

Range

1.0 - 31.0

1.6 - 15.4

Creatinine in µmol/l

Mean (SD)

118.2 ± 27.5

90.8 ± 8.6

Range

17.0 - 678.0

82.5 - 102.7

3.571

0.002

Biochemical profiles in the subjects at admission and fourth week

The means potassium (5.7 ± 0.5 mmol/l) and creatinine (118.2 ± 27.5 µmol/l) were significantly higher at admission but had returned to values within the normal range by the fourth week. There was a statistically significant difference in the values obtained at admission and fourth week for the two parameters (<0.05). However, between admission and four weeks into recovery, urea levels were significantly higher, (t =7.57, p = 0.001) though values remained within normal range. Serum sodium was within the normal range at admission and remained within the normal range in the fourth week (p= 0.524) (Table 7).

Table 7. Biochemical profiles in the subjects at admission and at four weeks into recovery.

Biochemical

Profiles

Subjects at admission

Subjects at four weeks

T

P

n = 82

n = 79

Sodium in mmol/l

Mean (SD)

143.9 ± 12.3

135.2 ± 2.7

0.64

0.524

Range

134.5 - 159.1

132.6 - 139.7

Potassium in mmol/l

Mean (SD)

5.4 ± 0.5

3.2 ± 0.5

3.15

0.002

Range

4.9 - 5.8

2.7 - 4.5

Urea in mmol/l

Mean (SD)

6.3 ± 5.6

3.3 ± 2.9

7.57

0.001

Range

1.0 - 31.0

0.4 - 6.1

Creatinine in µmol/l

Mean (SD)

117.2 ± 27.5

54.4 ± 50.2

5.4

0.001

Range

19.0 - 680

4.1 - 112.7

Study subjects with deranged biochemical profiles at admission

Elevated serum creatinine (creatinine > 88 µmol/l) and azotaemia (serum urea > 6.4 mmol/l) occurred in 25 (30.5%) and 24 (29.3%) subjects respectively. None of the controls had elevated serum creatinine, while 8 (9.8%) controls had azotaemia. The occurrence of elevated serum creatinine and azotaemia was significantly higher in subjects as compared to the controls (t = 50.0, p = 0.001). However, hypernatraemia and hyponatraemia occurred in 3.7% and 31.7% respectively, while hyperkalaemia occurred in 13.4% of the subjects (Table 8).

Table 8. Derangements of biochemical profiles in the study population at admission.

Biochemical Indices

Subjects

Controls

χ2

P

n = 82 (%)

n = 82 (%)

Sodium in mmol/l

Hypernatraemia (>145 mmol/l)

3 (3.7)

1 (1.2)

0.04

0.243

Hyponatraemia (<138 mmol/l)

26 (31.7)

25 (30.5)

0.17

0.843

Normal (138 - 145 mmol/l)

53 (64.6)

56 (68.3)

0.18

0.684

Potassium in mmol/l

Hyperkalaemia (>4.7 mmol/l)

11 (13.4)

10 (12.2)

0.1

0.757

Hypokalaemia (<3.4 mmol/l)

0 (0)

2 (2.4)

12.46

0.001

Normal (3.4 - 4.7 mmol/l)

71 (86.6)

70 (85.4)

0.01

0.905

Urea in mmol/l

Azotaemia (>6.4 mmol/l)

24 (29.3)

8 (9.8)

16

0.001

Normal Urea (1.8 - 6.4 mmol/l)

58 (70.7)

74 (90.2)

3.88

0.049

Creatinine in µmol/l

Elevated (>88 µmol/l)

25 (30.5)

0 (0)

50

0.001

Normal (27 - 88 µmol/l)

57 (69.5)

82 (100)

8.99

0.001

Urinalysis in the study population at admission

Proteinuria occurred in 62 (75.6%) of subjects and in 26 (31.7%) controls (p = 0.01). However, no massive proteinuria was observed in the study population. Twenty-two (26.8%) and 13 (15.9%) subjects had haematuria and bilirubinuria respectively (p < 0.05). The urine pH was normal in 90.3% of the subjects and 100% of the controls. Eight (9.8%) of the subjects had alkaline pH. The specific gravity was also normal in 86.6% of the subjects, while eleven (13.4%) of the subjects had high specific gravity. Specific gravity was normal in 95.1%, high in 3.7% and low in 1.2% of the control group (p < 0.05).

There were significant differences in the urinalysis findings at the fourth week and those obtained at admission. Sixty-nine (87.3%) of the subjects four weeks later had no protein in their urine (p = 0.0001). The urine pH and specific gravity were normal in all subjects at four weeks (Table 9).

Table 9. Urinalysis in the study population at admission and four weeks into recovery.

Urinalysis

Subject at admission

Subject at fourth week

χ2

P

n = 82 (%)

n = 79 (%)

Proteinuria

nil

20 (24.4)

69 (87.3)

53.96

0.001

1+

50 (61.0)

9 (11.4)

56.98

0.001

2+

12 (14.6)

1 (1.3)

18.62

0.001

Urinary Ph

Normal pH

74 (90.3)

79 (100.0)

0.33

0.567

Acidic pH

0 (0.0)

0 (0.0)

Alkaline pH

8 (9.8)

0 (0.0)

Specific gravity (SG)

Normal (1015 - 1030)

71 (86.6)

79 (100.0)

High (>1030)

11 (13.4)

0 (0.0)

Low (<1010)

0 (0.0)

0 (0.0)

Haematuria

13 (15.9)

0 (0.0)

Bilirubinuria

22 (26.8)

0 (0.0)

 

 

The mean eGFR of the study population

The mean eGFR of the subjects, 74.55 ± 56.27 ml/min/1.73m2 was significantly lower than that of the control, 164.6 ± 71.10 ml/min/1.73m2. (p = 0.001) (Table 10 and Figure 1).

Table 10. The estimated glomerular filtration rate (eGFR) of the study population at admission.

Subject

Control

T

P

n = 82

n = 82

Mean (SD)

74.6 ± 56.2

164.6 ± 71.1

7.841

0.001

Range

11.6 - 259.0

50.7 - 258.7

Figure 1. Bar chart showing the mean eGFR of the subjects and controls.

The mean GFR of the subjects at fourth week was significantly higher than the GFR at presentation, (p = 0.001) (Table 11 and Figure 2).

Table 11. The eGFR of the study population at presentation compared with the eGFR at fourth week.

Subject at admission

Subject at 4 weeks

t

P

n = 82

n = 79

GFR ml/min/1.73m2

Mean (SD)

74.6 ± 56.3

123.8 ± 73.6

5.737

0.001

Range

11.6 - 259.0

14.7 - 263.7

Figure 2. Bar chart showing the mean eGFR of the subjects at admission and four weeks later.

Classification of eGFR of the study population at admission

Only 18 (22.0%) of the subjects had eGFR of >100 ml/min/1.73m2 compared to 44 (53.7%) of the control. The lowest eGFR was 11.6 ml/min/1.73m2 in children with severe malaria. There were no significant differences in the mean eGFR of the subjects and the controls when eGFR of 50 ml/min/1.73m2 and above were compared (Table 12).

Table 12. Classification of eGFR of the study population at admission.

eGFR

ml/min/1.73m2

Subject

Control

χ2

P

n = 82 (%)

n = 82 (%)

≥100

18 (22.0)

56 (68.3)

14.37

0.001

75 - 99

14 (17.1)

25 (30.5)

0.15

0.695

50 - 74.9

28 (34.2)

1 (1.2)

10.89

0.001

25 - 49.9

16 (19.5)

0 (0.0)

28.13

0.001

<25

6 (7.3)

0 (0.0)

8.33

0.001

eGFR of the subjects at admission and the fourth week

The number of subjects with eGFR > 100 ml/min/1.73m2 increased from 18 (22.0%) at admission to 66 (78.5%) in the fourth week (p < 0.05). Similarly, by the fourth week, there was no subject with eGFR < 50 ml/min/1.73m2. However, 11 (13.9%) subjects had eGFR between 50 - 99 ml/min/1.73m2 (Table 13).

Table 13. Classification of eGFR of the subjects at admission and fourth week.

eGFR

Ml/min/1.73m2

Subject at admission

Subject at fourth week

χ2

P

n = 82 (%)

n = 79 (%)

≥100

18 (22.0)

66 (83.5)

54.86

0.001

75 - 99

14 (17.1)

11 (13.9)

0.72

0.4

50 - 74.9

28 (34.2)

0 (0.0)

5.2

0.001

25 - 49.9

16 (19.5)

0 (0.0)

28.13

0.001

<25

6 (7.3)

0 (0.0)

8.33

0.002

Low eGFR in the subjects

Twenty-four (29.3%) children had low eGFR for age as well as azotaemia. Twenty-five (30.5%) children had elevated serum creatinine. The eGFR was normal in the remaining 58 (70.7%) children and the controls (Table 14).

Table 14. Comparison of estimated eGFR with the normal value for age.

Age in

Months

Normal Range

eGFR for age

ml/min/1.73m2

No of pts

Normal

eGFR

Low

eGFR

n (%)

n (%)

n (%)

6 mo - 23 mo

74 - 118

31 (37.8)

22 (71.0)

9 (29.0)

24 mo - 60 mo

106-160

45 (54.9)

31 (68.9)

14 (31.1)

61 mo - 144 mo

106- 160

6 (7.3)

5 (83.3)

1 (16.7)

Total

82 (100.0)

58 (70.7)

24 (29.3)

Prevalence of acute kidney injury (AKI) using the three parameters of reduced eGFR, Azotaemia and elevated creatinine

The prevalence of AKI using the three parameters of reduced eGFR, azotaemia and elevated creatinine ranged from 29.3% - 30.5%.

Twenty-four children (29.3%) had low eGFR, azotaemia and elevated serum creatinine respectively, while a patient (1.4%) had elevated serum creatinine with normal eGFR (Table 15).

Table 15. Prevalence of acute renal failure (AKI) in the study population.

Parameter

No. of children with AKI

Prevalence

eGFR (ml/min/1.73m2)

24

29.3%

Azotaemia

24

29.3%

Elevated serum creatinine µmol/l)

25

30.5%

The socio-demographic (and biochemical) characteristics of the twenty-five children with AKI in the study population.

Most of the children 15 (60%) with AKI belonged to the lower social classes IV and V, while 5 (20.0%) children belonged to social class III and the rest 5 (20%) children belonged to social classes I and II. The majority of the children were also females 13 (52%) while the rest 12 (48%) were males. The age range of the children was 11 - 135 months. The majority of them 15 (60%) were >5 years old, while the rest 10 children were <5 years. All the 25 children except two had received one form of home remedy or the other and these ranged from paracetamol to chloroquine, herbal remedies, artesunate and quinine. There was no indication for dialysis in any of the children with AKI, as they all recovered following effective malaria treatment and intravenous fluid management.

The outcome of the patients with severe malaria in the study population

Out of the 82 subjects recruited into the study, 79 were managed and discharged, while 3 patients died in the course of the study, two children died from severe anaemia while the third had cerebral malaria given a case fatality of 4% (Table 16).

Table 16. Summary of the outcome of subjects in the study population.

Total number of patients:

82

Discharged and followed up:

79

Death:

3

Case fatality for severe malaria in the study:

4%

5. Discussion

The prevalence of AKI of 30.5% in children with severe malaria in this study is higher than the findings of other scholars [14] [16] [18]-[23]. This may be related to the late presentation by the subjects in this study [34]-[36]. Most patients in the study would have tried home remedies before presentation [38] [39]. This assertion is corroborated by the findings that as much as 96.3% of the subjects had used chloroquine, quinine, Sulfadoxine-Pyrimethermine (S-P) combinations, herbal preparations, paracetamol (PCM) and artesunate before presentation. The prevalence of AKI of 30.5% in this study is lower than that of the 58% prevalence reported by Folake et al when only eGFR is used in determining the prevalence of AKI in children with severe malaria [25]. Studies have shown that when these initial home remedies are applied, they are administered at sub-optimal doses due to ignorance or lack of sufficient funds to procure the full dosage [18]-[23]. The study indicated that most of the children had received one form of home remedy or the other. Most of these children who received home remedies also belonged to low socio-economic class families.

Furthermore, it is known that there is already a high level of resistance to some of these remedies like chloroquine and S-P combination. The content and efficacy of the herbal remedies are questionable and indeed there is a probability yet unprovened that some could have nephrotoxic effects. The higher prevalence of AKI in this study may also be related to the fact that other workers did not use age-related eGFR, urea and creatinine standards in determining the presence of renal impairment. It is well established that arbitrary adult cut-off values cannot be extrapolated to the paediatric age group. The eGFR, serum creatinine, urea and other biochemical indices possess age-related standard values. Above all, the findings of a study conducted by Kwambele, et al. (2023) reveal that there is a high prevalence of acute kidney injury among children with severe malaria in Kiryandongo General Hospital [16]. Acute kidney injury among children with severe malaria was associated with the low level of education of caretakers, young age of children (less than 5 years), history of receiving NSAIDs, and anaemia (moderate and severe) [26] [34]-[36] [40] [41].

The same group of children had elevated creatinine, azotaemia and low eGFR accounting for between 29.3% - 30.5% prevalence of renal insufficiency in the study. While this was reassuring or heartwarming, it was also surprising because serum creatinine is known not to be sensitive to substantial decline in eGFR [16]. Glomerular filtration rate may be reduced by up to 50% before serum creatinine becomes elevated [4] [21] [23] [25]. The fact that it is filtered and excreted by the kidney makes it an imperfect measure of eGFR, hence this study used the trio of eGFR, Azotaemia and elevated serum Creatinine. However, it remains the most widely used indirect measure of eGFR. It is easy and inexpensive to measure even though it is not accurate. Serum urea has a similar problem as it could be elevated in a state of dehydration and after consumption of protein.

There were strong negative correlations between eGFR and serum potassium, urea, creatinine, and parasite density. A positive correlation existed between serum sodium and eGFR; as sodium continues to accumulate in acute kidney injury there is associated water retention resulting in hyponatraemia. The failed kidneys cannot excrete potassium so it accumulates resulting in hyperkalaemia. Similarly, there is a build-up of serum urea resulting in azotememia or uraemia. Creatinine also builds up due to failure of its excretion as the kidney begins to fail. The higher the parasite density, the lower the eGFR. This perhaps may be due to lyses of parasitized red cells resulting in the release of a substantial amount of haemoglobin which plugs the tubules thereby interfering with tubular excretion. Similarly, heavy parasitemia is associated with accentuation of symptoms of malaria such as vomiting which results in loss of fluid causing hypovolemia which could produce a pre-renal failure [8] [19].

Four weeks into recovery, eGFR had increased and returned to normal in keeping with the findings of other workers [18]-[22]. Similarly, the elevated serum creatinine returned to normal and azotaemia normalized in agreement with the findings of other workers [18]-[20]. The renal dysfunction associated with severe malaria is reversible when there is prompt and accurate intervention as all our patients did recover.

The urine pH and specific gravity remained largely within normal limit at admission and in the fourth week indicating that tubular function may not have been as compromised as glomerular function. This is in keeping with the findings of other workers [16] [18]. However, proteinuria was observed in the subjects. This was in agreement with the findings of Weber [19] and Shieban [18], however, massive proteinuria was not recorded in any of the patients. The proteinuria could be due to fever or may reflect the transient glomerular dysfunction due to severe malaria. The latter reason is plausible because the proteinuria returned to normal by the fourth week. The three deaths recorded in the study population were not due to renal impairment as the three children had normal renal function. Two children died from severe anaemia while the third had cerebral malaria. AKI does occur following severe malaria. It is reversible once prompt and adequate treatment of malaria and conservative management of AKI are offered. Renal replacement therapy may not be required as seen in this study.

This study was conducted over a decade ago; when the world was facing the challenge of high levels of resistance to malaria parasites. It is believed that with the introduction of newer antimalarial drugs based on the advice from the outcome of interventional research such as Africa Quinine versus Artesunate Trial (AQUAMAT) [26], the prevalence of AKI may be lower currently than the finding of this study.

6. Conclusions

Based on the findings of this study, the following conclusions and inferences can be drawn:

The eGFR in children with severe malaria was compromised in 30% of cases, correspondingly the serum urea and creatinine were compromised in the same group of patients.

The prevalence of acute renal failure in this study was 30.5%. The mean eGFR, potassium, sodium, urea, and creatinine at admission were 74.6 ± 56.3 ml/min/1.73m2, 5.4 ± 0.5 mmol/l, 143.9 ± 12.3 mmol/l, 117.2 ± 27.5 µmol/l and 6.3 ± 5.6 mmol/l respectively. Outside sodium, these parameters were higher in subjects than in controls.

Deteriorating eGFR correlated strongly with the presence of jaundice and proteinuria and rising potassium, creatinine, urea, and increasing parasite density.

The features of AKI noticed at inception had normalized four weeks into recovery.

7. Recommendations

1) More studies would need to be carried out particularly in other geopolitical zones of the country to determine the prevalence of AKI secondary to malaria.

2) Renal compromise occurs sufficiently enough in children with severe malaria (30%) to warrant screening.

3) Routine serum creatinine evaluation would be of relevance as it correlated well with eGFR which could be tasking and cumbersome.

4) Severe malaria predisposes to AKI and measures to reduce its incidence would be invaluable tools in preventive nephrology in the region and perhaps other parts of the tropics.

Conflicts of Interest

The authors declare no conflicts of interest.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Roll Back Malaria (ARBM) in Africa (2000) African Summit on Roll Back Malaria.
[2] Adedoyin, O.T. and Adeniyi, A. (2001) Quartan Malaria Nephropathy. Postgrad Doctor 23; 72-Declaration 75.
[3] Hendrickse, R.G., Adeniyi, A., Edington, G.M., Glasgow, E.F., White, R.H.R. and Houba, V. (1972) Quartan Malarial Nephrotic Syndrome. The Lancet, 299, 1143-1149.
https://doi.org/10.1016/s0140-6736(72)91373-6
[4] Adebisi, S.A., Adekunle, B.A. and Etu, A.K. (2001) Creatinine Clearance: An Alternative Approach to Traditional 24-Hour Urine Collection in Normal Individuals. African Journal of Medical Sciences, 30, 27-30.
[5] Allan, R. (2001) Parasites and Guns: Waging a War on Malaria. Africa Health, 24, 12-15.
[6] Kalyesubula, R., Fabian, J., Nakanga, W., Newton, R., Ssebunnya, B., Prynn, J., et al. (2020) How to Estimate Glomerular Filtration Rate in Sub-Saharan Africa: Design and Methods of the African Research into Kidney Diseases (ARK) Study. BMC Nephrology, 21, Article No. 20.
https://doi.org/10.1186/s12882-020-1688-0
[7] Marsh, W.H., Fingerhut, B. and Miller, H. (1965) Automated and Manual Direct Methods for the Determination of Blood Urea. Clinical Chemistry, 11, 624-627.
https://doi.org/10.1093/clinchem/11.6.624
[8] Araoye, M.O. (2003) Subject Selection. Research Methodology for Health and Social Sciences. Nathadex (Publ.), 115-129.
[9] Bradley, G.M. and Benson, E.S. (1969) Urine Examination. In: Israel, D. and Bernard, J.H., Eds., Todd-Stanford Clinical Diagnosis by Laboratory Methods, W.B. Saunders, 30-106.
[10] Cheesebrough, M. (2002) Examination of Urine. In: District Laboratory Practice in Tropical Countries, Cambridge University Press, 711-712.
[11] Marzuillo, P., Pezzella, V., Guarino, S., Di Sessa, A., Baldascino, M., Polito, C., et al. (2021) Acute Kidney Injury in Children Hospitalized for Community Acquired Pneumonia. Pediatric Nephrology, 36, 2883-2890.
https://doi.org/10.1007/s00467-021-05022-x
[12] Hendrickse, R.G. and Adeniyi, A. (1979) Quartan Malarial Nephrotic Syndrome in Children. Kidney International, 16, 64-74.
https://doi.org/10.1038/ki.1979.103
[13] Scholz, H., Boivin, F.J., Schmidt-Ott, K.M., Bachmann, S., Eckardt, K., Scholl, U.I., et al. (2021) Kidney Physiology and Susceptibility to Acute Kidney Injury: Implications for Renoprotection. Nature Reviews Nephrology, 17, 335-349.
https://doi.org/10.1038/s41581-021-00394-7
[14] Oshomah-Bello, E.O., Esezobor, C.I., Solarin, A.U. and Njokanma, F.O. (2019) Acute Kidney Injury in Children with Severe Malaria Is Common and Associated with Adverse Hospital Outcomes. Journal of Tropical Pediatrics, 66, 218-225.
https://doi.org/10.1093/tropej/fmz057
[15] Marzuillo, P., Baldascino, M., Guarino, S., Perrotta, S., Miraglia del Giudice, E. and Nunziata, F. (2021) Acute Kidney Injury in Children Hospitalized for Acute Gastroenteritis: Prevalence and Risk Factors. Pediatric Nephrology, 36, 1627-1635.
https://doi.org/10.1007/s00467-020-04834-7
[16] Kwambele, L., Ndeezi, G., Ortiz, Y.A., Twesigemuka, S., Nduwimana, M., Egesa, W.I., et al. (2023) Factors Associated with Acute Kidney Injury among Children with Severe Malaria at Kiryandongo General Hospital, Uganda. International Journal of Pediatrics, 2023, Article ID: 2139016.
https://doi.org/10.1155/2023/2139016
[17] World Health Organization (WHO) (1996) World Health Organization Fact Sheet No. 94 (Revised December 1996) Malaria.
[18] Sheiban, A.K. (1999) Prognosis of Malaria Associated Severe Acute Renal Failure in Children. Renal Failure, 21, 63-66.
https://doi.org/10.3109/08860229909066970
[19] Weber, M.W., Zimmermann, U., Hensbroek, M.B., Frenkel, J., Palmer, A., Ehrich, J.H.H., et al. (1999) Renal Involvement in Gambian Children with Cerebral or Mild Malaria. Tropical Medicine & International Health, 4, 390-394.
https://doi.org/10.1046/j.1365-3156.1999.00409.x
[20] Fabian, J., George, J.A., Etheredge, H.R., van Deventer, M., Kalyesubula, R., Wade, A.N., et al. (2019) Methods and Reporting of Kidney Function: A Systematic Review of Studies from Sub-Saharan Africa. Clinical Kidney Journal, 12, 778-787.
https://doi.org/10.1093/ckj/sfz089
[21] Batte, A., Starr, M.C., Schwaderer, A.L., Opoka, R.O., Namazzi, R., Phelps Nishiguchi, E.S., et al. (2020) Methods to Estimate Baseline Creatinine and Define Acute Kidney Injury in Lean Ugandan Children with Severe Malaria: A Prospective Cohort Study. BMC Nephrology, 21, Article No. 417.
https://doi.org/10.1186/s12882-020-02076-1
[22] Conroy, A.L., Hawkes, M., Elphinstone, R.E., Morgan, C., Hermann, L., Barker, K.R., et al. (2016) Acute Kidney Injury Is Common in Pediatric Severe Malaria and Is Associated with Increased Mortality. Open Forum Infectious Diseases, 3, ofw046.
https://doi.org/10.1093/ofid/ofw046
[23] Lagos-Arevalo, P., Palijan, A., Vertullo, L., Devarajan, P., Bennett, M.R., Sabbisetti, V., et al. (2014) Cystatin C in Acute Kidney Injury Diagnosis: Early Biomarker or Alternative to Serum Creatinine? Pediatric Nephrology, 30, 665-676.
https://doi.org/10.1007/s00467-014-2987-0
[24] World Health Organization (WHO) (2019) World Malaria Report.
[25] Afolayan, F.M., Adedoyin, O.T., Abdulkadir, M.B., Ibrahim, O.R., Biliaminu, S.A., Mokuolu, O.A., et al. (2020) Acute Kidney Injuries in Children with Severe Malaria. Sultan Qaboos University Medical Journal [SQUMJ], 20, e312-317.
https://doi.org/10.18295/squmj.2020.20.04.006
[26] Dondorp, A.M., Fanello, C.I., Hendriksen, I.C., Gomes, E., Seni, A., Chhaganlal, K.D., et al. (2010) Artesunate versus Quinine in the Treatment of Severe Falciparum Malaria in African Children (AQUAMAT): An Open-Label, Randomised Trial. The Lancet, 376, 1647-1657.
https://doi.org/10.1016/s0140-6736(10)61924-1
[27] Oyedeji, G.A. (1985) Socio-Economic and Cultural Background of Hospitalized Children in Ilesha. Nigerian Journal of Paediatrics, 12, 111-117.
[28] Ogala, W.N. (1999) Malaria. In: Azubike, J.C. and Nkanginieme, K.E.O., Eds., Paediatrics and Child Health in a Tropical Region, Vol. 53, African Educational Services, 426-437.
[29] WHO (1991) Basic Laboratory Methods in Medical Parasitology. 6-20.
[30] Tietz, N.W., Pruden, E.L. and Siggard-Anderson, O. (1987) Electrolytes, Blood Gases and Acid Base Balance. In: Tietz, N.W., Ed., Fundamentals of Clinical Chemistry, W.B. Saunders Company, 614-668.
[31] Narayanan, S. and Appleton, H.D. (1980) Creatinine: A Review. Clinical Chemistry, 26, 1119-1126.
https://doi.org/10.1093/clinchem/26.8.1119
[32] Manjunath, G., Sarnak, M.J. and Levey, A.S. (2001) Estimating the Glomerular Filtration Rate. Postgraduate Medicine, 110, 55-62.
https://doi.org/10.3810/pgm.2001.12.1065
[33] Schwartz, G.J., Brion, L.P. and Spitzer, A. (1987) The Use of Plasma Creatinine Concentration for Estimating Glomerular Filtration Rate in Infants, Children, and Adolescents. Pediatric Clinics of North America, 34, 571-590.
https://doi.org/10.1016/s0031-3955(16)36251-4
[34] Plewes, K., Leopold, S.J., Kingston, H.W.F. and Dondorp, A.M. (2019) Malaria: What’s New in the Management of Malaria? Infectious Disease Clinics of North America, 33, 39-60.
https://doi.org/10.1016/j.idc.2018.10.002
[35] Ouma, B.J., Ssenkusu, J.M., Shabani, E., Datta, D., Opoka, R.O., Idro, R., et al. (2020) Endothelial Activation, Acute Kidney Injury, and Cognitive Impairment in Pediatric Severe Malaria. Critical Care Medicine, 48, e734-e743.
https://doi.org/10.1097/ccm.0000000000004469
[36] Sowunmi, A. (1996) Renal Function in Acute Falciparum Malaria. Archives of Disease in Childhood, 74, 293-298.
https://doi.org/10.1136/adc.74.4.293
[37] Snow, R.W. (2015) Global Malaria Eradication and the Importance of Plasmodium Falciparum Epidemiology in Africa. BMC Medicine, 13, Article No. 23.
https://doi.org/10.1186/s12916-014-0254-7
[38] Oyebola, D.D.O. (1983) Cow’s Urine Concoction, Its Chemical Composition, Pharmacological Actions and Mode of Lethality. African Journal of Medical Sciences, 12, 57-63.
[39] Nakhjavan-Shahraki, B., Yousefifard, M., Ataei, N., Baikpour, M., Ataei, F., Bazargani, B., et al. (2017) Accuracy of Cystatin C in Prediction of Acute Kidney Injury in Children; Serum or Urine Levels: Which One Works Better? A Systematic Review and Meta-Analysis. BMC Nephrology, 18, Article No. 120.
https://doi.org/10.1186/s12882-017-0539-0
[40] Muhamedhussein, M.S., Ghosh, S., Khanbhai, K., Maganga, E., Nagri, Z. and Manji, M. (2019) Prevalence and Factors Associated with Acute Kidney Injury among Malaria Patients in Dar Es Salaam: A Cross-Sectional Study. Malaria Research and Treatment, 2019, Article ID: 4396108.
https://doi.org/10.1155/2019/4396108
[41] George, J.A., Brandenburg, J., Fabian, J., Crowther, N.J., Agongo, G., Alberts, M., et al. (2019) Kidney Damage and Associated Risk Factors in Rural and Urban Sub-Saharan Africa (AWI-Gen): A Cross-Sectional Population Study. The Lancet Global Health, 7, e1632-e1643.
https://doi.org/10.1016/s2214-109x(19)30443-7

Copyright © 2025 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.