Chronic Kidney Disease Screening Practice Among High-Risk Patients During Follow-Up in Sub-Saharan Africa: A Systematic Review

Abstract

Background

Screening for Chronic Kidney Disease (CKD) for high-risk patients is essential to provide early detection, management, and delayed progression. In Sub-Saharan Africa (SSA), CKD screening remains variable and inadequate. Therefore, the review question was: what is the current practice of screening for CKD in high-risk patients (hypertension and diabetes) attending chronic care follow-up visits in SSA?

Methods

The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines. The review included studies published from 2010 to August 2025. Inclusion criteria included screening practices or early detection of chronic kidney diseases among high-risk patients during routine care in SSA. The review followed the JBI Condition, Context, and Population (CoCoPop) protocol. Two independent reviewers screened, appraised, and extracted data using the standardized JBI SUMARI data extraction form. Narrative synthesis of the findings was carried out to understand CKD screening practice in SSA.

Results

Out of 856 records identified, twelve studies from SSA focused on high-risk patients screened for CKD who met criteria and were included. Serum creatinine was the most common method used to screen CKD during routine follow-up of high-risk patients, followed by albuminuria and estimated glomerular filtration rate(eGFR). The prevalence of CKD screening during routine care varies from 8.4% to 38.5%. Older age, being a female, duration of diabetes and/or hypertension, and co-existence of hypertension and diabetes were identified as factors associated with CKD screening practice.

Conclusion and recommendations

Routine follow-up of high-risk patients demonstrated that CKD screening was effective in early patient identification. Most of the included studies relied on one-time screening, which may not accurately represent the true prevalence; therefore, confirmatory CKD screening should be conducted. Finally, healthcare providers should prioritize older age, female gender, duration of the high-risk conditions, and concomitance of hypertension and diabetes.

Keywords

screening practice chronic kidney disease hypertension diabetes SSA

Introduction

Chronic Kidney Disease(CKD) is defined as a glomerular filtration rate (GFR) < 60 mL/min/1.73 m² and or albuminuria for at least three months, irrespective of cause.¹ The recent recommendation is to use both eGFR and albuminuria for identifying both impairment and renal function.^1,2 There should be a confirmatory test at least two tests a month apart; otherwise, over estimation of CKD could be a problem³ due to different factors that could increase transient leakage of albumin in urine such as muscle mass, exercise and related health conditions.^1,4 In community pharmacy-based eGFR screening for early detection of CKD in high-risk patients(such as those with hypertension, diabetes, and so on), the initial test indicated abnormality in 56%, however, the confirmatory test showed only 17.1% to have CKD.⁵

The number of individuals affected by CKD globally is estimated to be 700 million,^6,7 which is underestimated due to the lack of effective CKD screening programs. It remains a major public health concern, with sub-Saharan Africa (SSA) experiencing a rising burden due to increasing prevalence of risk factors like hypertension, diabetes, and HIV.^8,9 The global prevalence of CKD ranges from 8% to 16% from which the majority of the cases occur in LMICs.^10,11 In Africa, the pooled prevalence of CKD in the general population was 10.1% (ranged from 2% to 41%), while it was 14% in Sub-Saharan African (SSA) countries.^12,13 This prevalence places Sub-Saharan Africa (SSA) among the world’s regions with the highest burden of CKD.¹⁴

CKD has deleterious effects on patients and their family’s quality of life, including the inability to work, and poor psychological and physical functioning.^15,16 Its care should start with screening people with risk factors, establishing a diagnosis, provision of information/education for patients about CKD, encouraging self-management behaviors, and carrying out other medical recommendations.¹⁷ Early detection of CKD during routine high-risk patient care is essential in significantly improving early management and reducing progression of kidney damage.^18,19 It was also well documented that target screening was found effective in early detection of CKD among high-risk patients rather than conducting population-based screening practice.^20,21 Screening tests commonly employed were albumin creatinine ratio and estimated glomerular filtration rate (eGFR),^21,22 and dipstick urinalysis.²¹ A review conducted using articles from developed nations showed confirmed CKD varied from 4.4% to 17.1%.²¹ Different factors were cited as affecting the prevalence of CKD in LMICs. Among which, older age, in a Bangladesh study²³ in an Ethiopia²⁴ and in a Nepal was identified as an association with increased CKD prevalence.²⁵ Existence of concomitants high-risk conditions such HTN and DM have increased risk of CKD in the Bangladesh study.²³ Another Nepalese study showed a concomitant presence of hypertension (HTN) and diabetes (DM), increasing duration of type 2 DM, anemia,²⁵ and prolonged duration of DM²⁶ were found to be factors associated with increased CKD diagnosis. However, to date in SSA, CKD screening practice among high-risk patients (HTN and DM) is lacking. Thus, this review is designed to generate evidence on CKD screening practice during routine care among high-risk patients using peer-reviewed published studies.

Review Question

What is the current practice of screening for CKD in high-risk patients (hypertension and diabetes) attending chronic care follow-up visits in SSA?

Methods

This review was organized and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement.²⁷ The protocol for this review was registered on Open Science Framework (OSF) as https://doi.org/10.17605/OSF.IO/A7V5K. The findings of the study were reported per PRISMA 2020 checklist (Supplementary Table 1).

Search Strategy

Primary investigators conducted a comprehensive literature search to identify sources meeting the study criteria. Pre-identified sentinel articles were searched for keywords and subject headings related to the concepts of CKD screening in routine high-risk patients (e.g. renal function test, kidney evaluation), and high-risk populations (e.g. hypertension, diabetes). A search strategy was drafted for testing in PubMed where the results were assessed, and additional terms were added from titles, abstracts, and subject headings. A second draft search was created with the added terms and proximity operators and again tested in PubMed. Six bibliographic databases were searched: CINAHL, Embase, PubMed, OVID MEDLINE, Scopus, and Web of Science. Additionally, the websites African Index Medicus, Google Scholar and African Journals Online were searched. Searches were initially undertaken on July 20, 2025. Full search strategies for each database are found in supplementary table 2.

Settings and Types of Studies

This systematic review included peer-reviewed published papers of quantitative cross-sectional studies conducted in SSA countries (Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Central African Republic, Chad, Congo, Cote D’Ivoire, Democratic Republic of the Congo, Djibouti, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, Togo, Uganda, Zambia and Zimbabwe) on high-risk patients (hypertension, diabetes, or both).

Eligibility Criteria

Inclusion and Exclusion Criteria

The eligibility criteria for the review question were established based on the condition, context and population (CoCoPop) protocol to ensure thorough and systematic selection of participants. This systematic review included research conducted in SSA countries, specifically among adults (≥18 years) with a diagnosis of hypertension or diabetes or both diseases. The review considered primary studies published in peer reviewed journals with a report of CKD screening in SSA or discussed prevalence, incidence, barriers and facilitators of CKD screening documented for routine care among papers published in the English language. The inclusion of solely published articles aims to gather the most reliable evidence on the prevalence and factors associated with CKD screening. This review considered cross-sectional studies that report the prevalence of CKD screening and associated factors among high-risk patients such as those with hypertension and diabetes. The publication date range for articles included in the review spans from January 2010 to August 2025. The exclusion criteria included case reports or series, study protocols, review studies, letters to the editors, abstracts, instrumental psychometrics, and qualitative studies.

Outcomes

This review has two outcomes. The primary outcome was prevalence of CKD screening during routine healthcare for high-risk (HTN and DM) patients, and the secondary outcome was the factors associated with screening. CKD screening tests involve tests such as albuminuria or proteinuria and GFR in individuals having at least one known CKD risk factor to detect undiagnosed CKD by health care providers.^1,4 CKD is characterized by structural or functional abnormalities of the kidneys that persist for at least three months, with health implications. It is categorized according to its etiology, Glomerular Filtration Rate (GFR) classification (G1–G5), and Albuminuria classification (A1–A3), collectively referred to as CGA (Cause, GFR and Albuminuria).¹

Study Selection

After the search was finalized, identified citations from the databases were uploaded to EndNote version 21.0 to identify duplicates and removal. Potential articles were uploaded in to JBI System for Unified Management, Assessment and Review of Information (JBI SUMARI).²⁸ The title and abstract, and full screening for eligibility were performed independently by two investigators (HA & HG) against the eligibility criteria. We resolved conflicts between reviewers through discussion. The reasons for exclusion, the result of the selection, were recorded and reported in the PRISMA flow diagram.²⁷

Quality Assessment

Two independent reviewers, HG and HA, appraised all studies that were included in the review. Quantitative papers selected for retrieval were assessed by two independent reviewers at the study level for methodological validity before inclusion in the review using standardized critical appraisal instruments from JBI.²⁹ Regardless of their methodological quality results, all studies (see Table 1) underwent data extraction and synthesis.

Table 1.

Critical Appraisal of Eligible Analytical Cross-Sectional Study

Citation	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Total
Abene et al. 2020.³⁰	Y	Y	Y	Y	Y	Y	Y	Y	100
Ajayi et al., 2014.³¹	Y	U	Y	Y	U	U	Y	Y	62.5
Hunegnaw et al. 2021.³²	Y	Y	Y	Y	Y	Y	Y	Y	100
Otieno et al. 2020.³³	Y	Y	Y	Y	Y	Y	Y	Y	100
Rwegerera et al. 2018.³⁴	Y	N	Y	Y	Y	Y	Y	Y	87.5
Taderegew. 2020.³⁵	Y	Y	U	Y	Y	Y	Y	Y	87.5
Fiseha et al., 2014.³⁶	Y	Y	Y	Y	N	N	Y	Y	75
Fiseha et al., 2020.³⁷	Y	Y	Y	Y	Y	Y	Y	Y	100
Bahrey et al. 2019.³⁸	Y	Y	Y	Y	Y	Y	Y	Y	100
Kachimanga et al. 2019.³⁹	Y	Y	U	Y	Y	U	Y	Y	75
Mahamane et al. 2023.⁴⁰	Y	N	Y	Y	Y	Y	Y	Y	87.5
Kachimanga et al. 2021.⁴¹	Y	Y	Y	Y	Y	Y	Y	Y	100
%	100.0	75.0	83.33	100.0	83.33	75.0	100.0	100.0

Data Extraction

Data were extracted from studies included in the review by two independent reviewers (HA & HG) using the standardized JBI data extraction tool in JBI SUMARI.⁴² The data extracted included specific details about the populations, study methods, context, sample size, response rate, chronic kidney disease screening (urine dipstick test, serum creatinine, albuminuria), and outcomes of significance to the review objective. Any disagreements that arose between the reviewers were resolved through discussion.

Data Analysis

The extracted data were managed using JBI SUMARI software.^42,43 Researchers did not estimate pooled prevalence of CKD screening because of several factors such as heterogeneity in targeted risk factors, used screening tests, and used equations to estimate GFR. Therefore, systematic narrative synthesis of the study findings was carried out to understand CKD screening practice in the included studies in the region.

Results

The following PRISMA flowchart (Figure 1) displayed the findings of the search and review process for study selection and inclusion.²⁷ This review identified 856 records, 115 of which were found to be eligible for full-text screening, and 12 of these articles met all of the inclusion criteria. All the included studies are cross-sectional designs that assessed CKD screening of healthcare providers during routine follow-up care for a high risk patients. A total of 5,236 high-risk patients (HTN, DM or both) with an age range from 18 to 92 years were included. Gender-wise, 2759 participants were female.

Figure 1.

PRISMA flow diagram of the search and study selection process²⁷

Study Characteristics

The review included 12 studies as summarized in Table 1. Five studies were from Ethiopia,^32,35-38 two studies were from Nigeria^30,31 and the remaining studies were from different parts of SSA region, such as one each from Kenya,³³ Zambia,⁴⁰ Sierra Leone,⁴¹ Botswana,³⁴ and Malawi.³⁹ Half of the studies (n=6) included diabetes patients,^33-35,37-39 in four of the studies^30,32,40,41 hypertension patients included, whereas the other two studies^31,36 included both diabetes and hypertensive patients.

Assessment of Chronic Kidney Disease and Equations Used to Estimate Kidney Function

Diagnostic tests employed to early detect CKD during routine follow-up care for high-risk patients (HTN, DM, or both) in most of the included studies were serum creatinine,^{30,32,34-37,39} followed by albuminuria/proteinuria,^30,33,38,39 urine dipsticks,⁴¹ urea and electrolytes.⁴⁰ However, in one of the included papers, the kind of test used for detecting CKD was not specified; rather a report of CKD was used.³¹

All included studies used the standard CKD definition, which is eGFR of <60ml/min/1.73m² to estimate the kidney function impairment using different equations. The Modified Diet in Renal Disease (MDRD) equation was used in half of the included studies^30,31,34-37 followed by Cockroft-Gault’s (C-G) equation, which was used in five studies.^{32,33,35,36,38,40} The CKD-epidemiology collaboration (CKD-EPI) equation also used in three studies to estimate kidney function.^35,39,41 More than one equations (MDRD, CKD-EPI and/or Cockroft-Gault) were used for early detection of CKD among high-risk patients in two included studies^35,36 (see Table 2).

Table 2.

Characteristics of Included Studies

Study, country	Methods: Settings, design, participants and sampling	Outcomes measured	Finding summary	Quality
Fiseha et al., 2014³⁶	• The study conducted in Butajira Hospital, Southern Ethiopia	Chronic Kidney disease (CKD) confirmed when eGFR< 60 ml/min/1.73 m using: the simplified Modification of Diet in Renal Disease (MDRD) and Cockroft-Gault (C-G) equations to estimate GFR (eGFR) from serum creatinine.	• The mean age: 45±14.5 years (19 to 90), and 40 of them were above 60.	75%
Ethiopia	• Cross-sectional study included 214 diabetic patients, 123 males. Aged 18 years and above were drawn out using a table of random numbers constructed from the register.		• Mean BMI: 25.26±4.35Kg/m2, and 31 of them were obese.
			• Over half, 113 were hypertensive.
			• Mean serum creatinine was 1.07 ± 0.33 mg/dl.
			• The mean eGFR values according to the MDRD: 96.70±35.68 and C-G equations: 83.61±29.73 ml/min/1.73 m².
			• Prevalence of CKD: Based on the eGFR 39(18.2%) by the MDRD equation and 51(23.8%) by the Cockcroft–Gault (C-G) equation had CKD.
			• Only 48.7% and 37.3% of participants with eGFR <60 ml/min/1.73 m² according to the MDRD and C-G equations, respectively, had Creatinine values >1.5 mg/dl (the relevant range for detecting CKD [GFR <60 ml/min/1.73 m²]).
			• An increased risk of CKD was seen with: older age (AOR=5.30,CI1.81-15.56); female (AOR=3.34,CI1.38-8.10); longer duration of diabetes (AOR=4.08, CI 1.70-9.77); family history of kidney disease (AOR=3.16, CI 1.29-7.77); obesity (AOR=2.75, CI 1.01-7.51); and poor glucose control (AOR=4.65, CI 1.69-12.76) when renal function was estimated by the MDRD equation.
Fiseha et al., 2020.³⁷	A cross-sectional study was conducted in outpatient diabetes clinic of Dessie Referral Hospital, Northeast Ethiopia. A sample of 323 diabetes patients (aged ≥18 years) were included.	Chronic Kidney disease assessed using serum creatinine and albuminuria.	• The mean age of the participants was 44 ± 15.7 years (18 to 77 years), and 168 were males.	100%
Ethiopia		Serum creatinine was measured using a Jaffe kinetic method, with calibration traceable to IDMS reference material.	• 186 had duration of diabetes less than 5 years, and 62 had a family history of kidney disease.
		The presence of albuminuria (+1 or more) in urine was defined as albuminuria.	• Mean Creatinine was 1.01 ± 0.33 mg/dl.
		Then finally, the four-variable Modification of Diet in Renal Disease (MDRD) study equation was used to estimate glomerular filtration rate (eGFR).	• The mean eGFR was 100.6 ± 35.04 ml/min/1.73 m2.
		CKD was defined as eGFR < 60 ml/min/1.73 m2 and/or albuminuria on two occasions spaced by 2 weeks.	• 85 had Stage 1–5 CKD
			• Prevalence of CKD: 42 had eGFR < 60 ml/min/1.73 m², and 58 had albuminuria.
			• In patients with stage 3–5 CKD, serum creatinine was abnormal (> 1.5 mg/dl) in 23.5%, and albuminuria was absent in 31.8%.
			• Of the patients with CKD, only 10.6% of them were aware of their CKD.
			• Having albuminuria, high serum creatinine, a family history of kidney disease, and being obese were significantly associated with CKD awareness.
			• The prevalence of CKD was 46.9% in participants > 60 years.
			• CKD prevalence was lower in males (14.8%) than in females (36.9%; P < 0.001).
Taderegew MM. 2020.³⁵	A cross-sectional study on 422 Diabetes patient conducted in Debre Berhan Referral Hospital northeast of Ethiopia.	Chronic Kidney disease.	• 229 were female, and 260 were from urban areas.	87.5%
Ethiopia		• Estimated by; eGFR using the MDRD equation and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI).	• ages were ranged from 36 to 80 years, with a mean age of 54.16 (±10.61) years.
		• Renal impairment defined as eGFR< 60ml/min/1.73m2.	• The mean (±SD) of DM duration was 6.2(±4.6) years.
			• The mean eGFR (ml/min/1.73 m²) values of the participants according to the MDRD: 99.66 (±34.24), CKD-EPI: 88.78 (±22.32), and C-G equations: 84.87 (±29.18) ml/min/1.73 m².
			• The prevalence of renal impairment was 82(19.4%), 92(21.8%), and 103(24.4%), using the MDRD, CKD-EPI, and C-G equations, respectively.
			• From those with renal impairment, 43.9%, 51.1%, and 57.3% of participants had normal serum creatinine levels for the MDRD, CKD-EPI, and C-G equations, respectively.
			• Staging of renal impairments reveals that 227 (53.8%), 216 (51.2%), and 195 (46.2%) of the participants had a GFR of ≥ 90 mL/min/1.73 m², while 113 (26.8%), 114 (27.0%), and 124 (29.4%) had a GFR of 60–89.9 mL/min/1.73 m² in the MDRD, CKD-EPI, and C-G equations, respectively.
Otieno. 2020.³³	Across-sectional study conducted on 385 diabetes patients in County public Hospital, found in Central Kenya.	Chronic Kidney disease.	• 252 (65.5%) were females.	100%
Kenya	Aged > 30 years, on follow-up in the clinic for not less than 6 months and on anti-diabetic treatment.	The estimated glomerular filtration rate was calculated on the Cockroft-Gault formula and defined as eGFR (< 60 ml/min/1.73 m²).	• The population mean age was 63.3 years, IQR of 56-71 years.
			• 150(39.0%) patients diagnosed as CKD
			• 126(32.7%) had albuminuria.
			• The factors significantly associated with chronic kidney disease were age > 50 years, long duration with diabetes > 5 years and hypertension.
			• The proportions of the study subjects with CKD in the various KDIGO stages (by eGFR) were: G1 (> 90 ml/min/1.73m2)- 20%, G2 (60-90ml/min/1.73m2) - 41%, G3a (45-60 ml/min/1.73m2) - 21% and G3b (30-45 ml/min/1.73m2) -12.5%, G4 (15-30ml/min/1.73m2) - 4.7%, and G5 (< 15 ml/min/1.73m2) - 0.8%.
			• There were no gender differences in the proportions of subjects with albuminuria and those in the various CKD stages.
Hunegnaw et al., 2021.³²	An institutional based (University of Gondar Teaching Referral Hospital, Felege Hiwot Referral Hospital, and Debre Markos Referral Hospital) cross-sectional study using 581 hypertensive patients (Age 18 years and above) and who had medical records.	Chronic kidney disease was measured using proteinuria and GFR. It can be measured by using readily available equation: Cockcroft–Gault and defined as eGFR less than 60 mL/min per 1·73 m².	• 55.1% were females, the median and standard deviation of the age was 54.71 and 11.397, respectively.	100%
Ethiopia			• 476 were married, 120 had no formal education.
			• The prevalence of CKD among adult hypertensive patients was 103(17.6%).
			• Diastolic blood pressure ≥90 mmHg, duration of hypertension ≥10 years, stage II HTN, comorbid disease, proteinuria, dyslipidaemia, and serum creatinine ≥1 mg/dl were associated with chronic kidney disease among adult hypertensive patients.
Ajayi et al., 2014.³¹	A retrospective study in a tertiary health centre. A sample 628 (306 men and 322 women) hypertensive and diabetic patients were included.	Chronic kidney disease with eGFR and then CKD staging in asymptomatic newly diagnosed hypertensive and diabetic patients.	• 456 of the study population were aged 41–75 years.	62.5%
Nigeria		Chronic kidney disease was defined in this study as eGFR less than 60mL/min/1.73m² using MDRD.	• The mean age (SD) for men and women was 50.19 (12.41) and 48.63 (14.43), respectively.
			• 116 men and 230 women were known hypertensives. Thus, 461 (73.4%) were aware of being hypertensive, and 54 (8.6%) were aware that they had diabetes mellitus.
			• A total of 242 (38.5%) had CKD stages with a predominance of females: 184 vs. 58.
			• There was an association between CKD stage, gender (x²=5135.56, P<.001), and age (x²=530.83, P<.01).
			• 62 men had CKD stage 1, while 186 of men and 138 women had CKD stage 2.
			• There was an association between gender and CKD stage (x²=5134.84, P=.001) and between CKD stage and age category though patients in age categories 20 years and >75 years were fewer in number compared to other age categories (x²=527.73, P=.01).
			• The odds ratio for having an eGFR,60mL/min was 6.71 for females and 2.72 for the age category >65years
Mahamane et al., 2023.⁴⁰	A cross-sectional study was used to assess hypertension-induced CKD using 220 hypertensive patients. The study conducted at Victoria Chitepo Provincial Hospital Mutare which is in Manicaland province.	Hypertension induced chronic kidney disease using data reviewed from patient records.	• 76 cases were male, and 144 (65.5%) were female.	87.5%
Zambia	All adults (18 and above) patients who are adults with diagnosed hypertension.	• The patients’ results for the urea and electrolyte test and the GFR calculation in the record book was compared to the reference ranges of the laboratory to figure out chronic kidney disease.	• 44 of participants were below 30 years of age, 64 were between 30 and 50 years old, and 112 were over 50 years of age. The mean average age was 48, and the standard deviation was 11.3.
		• Documented evidence of CKD from the client’s medical chart used, which included an eGFR value of less than 60 mL/min/1.73 m, calculated using the Cockcroft-Gault equation as an indicator of CKD.	• Majority of study participants have a low GRF = 67.
			• CKD prevalence: 71 participants had developed different grades of kidney impairment while 43(19.55%) developed CKD. Of which, 39 were female. 11 (15.5%) participants were under 30 years old; 23 (32.4%) participants were between 30 and 50 years old, and 37 (52.1%) participants were over 50 years old.
			• 28 of the participants also had diabetes mellitus.
			• Gender (being male), History of diabetes mellitus(presence), History of antihypertensive medication were associated with HTN induced CKD.
Kachimanget al. 2019.³⁹	Retrospective audit of diabetic patients (April 2016 and January 2019) enrolled in an Integrated Chronic Care clinic in Neno District, Malawi. A sample 148 diabetes mellitus patients aged 18 years and above, enrolled in care for at least 3 months, with at least one serum creatinine and/or urine protein result were included. Patients with a pre-existing diagnosis of CKD were excluded from the study.	CKD measured from data extracted from Neno District’s electronic medical record (EMR).	• The mean age was 54 years, and about two-thirds of the patients (n = 77, 66.4%) were female.	75%
Malawi		• CKD was defined using Kidney Disease Improving Global Outcomes (KDIGO) as an estimated glomerular filtration rate (eGFR) of less than 60 ml/min/1.73 m2 and/or urinary protein 2+ or more, measured on two occasions at least 3 months apart.	• Many of the patients attended the clinic for over 2 years.
		• The eGFR was estimated based on serum creatinine using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula.	• 103 of the patients were hypertensive.
			• 39.2% (n = 58) of the patients had abnormal estimated glomerular filtration rate (eGFR), as estimated by CKD Epidemiology Collaboration formula and/or ≥ 2+ urine protein.
			• 20 of the patients had renal insufficiency based on eGFR of less than 60 ml/min/1.73 m² in first test.
			• 18 patients had CKD based on eGFR of less than 60 ml/min/1.73 m2 measured twice at least 3 months apart.
			• CKD was associated with older age, high systolic blood pressure and lower fasting blood sugar.
Bahrey et al. 2019.³⁸	A cross-sectional study conducted in Tigray teaching hospitals (from January 1, 2013, to December 30, 2018) using 578 adult hypertensive patients.	• CKD: Chronic kidney disease is defined as follows: we consider a patient to have CKD if the physician diagnosed them as having CKD and documented it in the patient’s medical chart.	• 290 of the patients were females.	100%
Ethiopia		• Chronic kidney disease is defined as eGFR < 60 mL/min/1.73 m by Cockcroft-Gault equations.	• The documented age of the patients ranges from 30 to 87 years with the median age of 54.14 years.
		• Proteinuria, according to the laboratory result if a patient has plus one or above; we classify this as having proteinuria.	• 163 with diabetes mellitus and 158 (27.3%) with dyslipidaemia.
			• CKD prevalence: 128 of the patients were patients with CKD which was considerably high. Of which 96% patients were having uncontrolled hypertension.
			• Independent variables associated with of CKD among hypertensive patients were age, uncontrolled hypertension, overweight/obese, dyslipidaemia, diabetic mellitus.
Abene, et al. 2020.³⁰	Across-sectional study on 1063 adults (18 and more) with Hypertension in three selected hospitals (Jos University Teaching Hospital, Federal Medical Centre, and Dalhatu Araf Specialist Hospital), Lafia in Nasarawa state. The patient had been followed for at least one year with a minimum of three visits. Hospitals laboratory data were used for estimation of eGFR.	CKD measured using serum creatinine and estimated glomerular filtration rate (eGFR) was assessed using the abbreviated MDRD equation.	• 671 females were included in the study.	100%
Nigeria		The outcome measures are proteinuria of >1+ and (c) eGFR <60 ml/min/1.73 m².	• The mean age of the participants was 55 ± 11 years, while the median duration of hypertension was 6 years.
			• 214 participants had coexistent with DM.
			• Proteinuria was seen in 130 patients.
			• Male gender and use of RAAS-blocking medications were independently associated with proteinuria.
			• CKD prevalence: reduced eGFR (<60 ml/min/1.73 m²) was found in 212(19.94%) of the participants.
			• Those treated with more than two medications were more likely to have reduced eGFR compared to the other participants.
Rwegerera et al. 2018.³⁴	Observational cross-sectional study in a leading tertiary clinic in Botswana using a cohort of 380 randomly selected patients and interviewed between July 2015 and September 2015.	CKD was defined as an eGFR < 60 ml/min/1.73 m².	• The mean age and duration of DM among study participants were 54.67 years (range 21–92 years) and 5.0 years, respectively.	87.5%
Botswana		The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet for Renal Disease equation based on measured serum creatinine levels. Patients were then categorized to have CKD if eGFR was < 60 ml/min per 1.73m2 and not to have CKD if eGFR was ≥ 60 ml/min per 1.73m².	• Over half, i.e. 213/370 and 232/370, had an average blood pressure greater than 140/90 mmHg and poor glycemic control (HbA1c > 7%), respectively.
			• CKD prevalence: 31/370 (8.4%) patients had CKD.
			• Age, level of education, and duration of diabetes were independently associated with CKD.
Kachimanget al. 2021.⁴¹	A cross-sectional study conducted at Koidu Government Hospital in Kono District, Eastern Sierra Leone. The study included 304 hypertensive patients receiving NCD services. During clinic screening, patients were enrolled if they had two blood pressure measurements ≥140/90 mmHg measured at least two minutes apart. hypertensive patients aged between 18- and 75-years receiving care at KGH NCD clinic. We excluded patients outside this age category, with pre-existing CKD, and patients with other diagnosis other than hypertension.	CKD was outcome variable. We used kidney disease: Improving Global Outcomes (KDIGO) definition of CKD defined as persistent estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73m2 for more than 3 months.	• The median age of eligible patients was 55 years (IQR 48–63 years) and over two-thirds were females (n = 207).	100%
Sierra Leone		We used CKD epidemiology (CKD-Epi) formula to calculate eGFR.	• CKD prevalence: 91(29.9%) patients with HTN had CKD.
		Laboratory tests performed at the hospital laboratory by trained technicians: Creatinine and urine dipsticks	• CKD was found in 70 female patients.
			• Over half, 47 of CKD patients were over the age of 60.
			• Age and female gender were associated with higher odds of CKD.
			• Currently taking herbal medications as treatment of hypertension was associated with four times the odds of having CKD. Finally, patients who were overweight and/or obese had more than two times the odds of having CKD in comparison to patient who had BMI less than 25 kg/m2.

Prevalance of CKD Screening and Its Assciated Factors

In the included studies, CKD prevalence ranges from 8.4%³⁴ to 38.5%,³¹ 13.0%³⁷ to 39%,³³ 12.2%³⁹ to 29.9%⁴¹ using the MDRD, C-G and CKD-EPI GFR estimation equations, respectively. Among documented CKD cases in either hypertensive or diabetic patients, older age was highly associated with increased risk of CKD.^{31,33,34,36-39,41} Females who were high-risk had a higher prevalence of CKD.^31,36,37,41 Longer duration of either diabetes or hypertension was also associated with a higher prevalence of CKD diagnosis.^32-34,36,40 Co-existence/concomitants of diabetes and hypertension have been linked to increased prevalence of CKD.^31,32,38,40 Obesity was another significant factor associated with increased prevalence of CKD.^36-38,41 Uncontrolled conditions of high risk factors (HTN and DM) were documented as associated factors for increased CKD prevalence.^34,36,38,39 Patients with dyslipideimia were associated with documented CKD.^32,38

Discussion

The main aim of this systematic review was to generate data on CKD screening among high-risk patients on follow-up in SSA. The review covered a fifteen year time frame (from January 2010 to September 2025) of published studies in the region. This systematic review complements a previous systematic review conducted as a risk-factor-based CKD screening using studies conducted in middle to high income countries.²¹

This review identified variable types of tests for CKD screening and its prevalence among high-risk patients in SSA. Although the current recommendation for detecting CKD accroding to Kidney Disease Improving Global Outcomes (KDIGO) guidelines is to use both the eGRF and albuminuria,² serum creatinine test was commonly used in our review, which is inconsistent with a systematic review conducted using studies published in high-income countries.²¹ The difference could be related to the study population and the availability of diagnostic infrastructure. Similarly, our review finding is also inconsistent with a review conducted using studies conducted in community settings, which identified albumin creatinine ratio and eGFR as commonly employed screening tests.²² However, our review findings concur with existing recommendation that use of serum creatinine is a standard as a marker of kidney function and estimation of GFR during routine follow-up care, as other factors such as muscle mass, health condition, and exercise could affect albuminuria.¹

Our review also identified a variable cutoff value for the estimation of albuminuria. At the same time, the included studies also lack uniformity in terms of the use of albuminuria with GFR to grade CKD. Proteinuria/albuminuria was defined as +1 or more in seven studies,^{30,32,33,37,38,41} +2 or more in one study³⁹ and the rest have not defined the cutoff value for albuminuria.^31,34-36,40 Only one of the included studies³⁷ used the current KDIGO recommondation of using both eGFR and/or albuminuria¹ for diagnosis and grading of the kidney function. This implies healthcare providers in SSA may need updated educational preparation based on the current recommendations. Additionally, the healthcare system is better prepared in diagnostic facilities for screening CKD. We also found a single screening test and estimate used in most of the included studies,^30-34,38,40 but a confirmatory follow-up test was used in only four included studies.^35-37,39,41 Limited health infrastructure and awareness of existing guidelines could potentially contribute to these gaps. However, a lack of confirmatory tests could lead to overestimation of CKD^3,5 due to different factors such as muscle mass, exercise, and other health conditions that could increase transient leakage of albumin in urine.^1,4 The current recommondation for CKD diagnosis is to identify abnormalities of kidney structure or function, followed up for a minimum of three months based on two dimensions of GFR and degree of albuminuria. Thus, to confirm the existence of CKD, the recommendation is to perfom confirmatory tests at least twice a month apart, and the GRF should be less 60 mL/min/1.73m² and/or confirmed renal damage diagnostically lasting over a three month period.¹

The review also identified different equations used across studies to estimate GFR. In half of the included studies, the MDRD equation was used to estimate GFR, which is inconsistent with similar systematic reviews where CKD-EPI is commonly used²¹ but concurs with other review conducted using studies conducted in community settings.²² The possible explanation for the difference could be that our review used studies from resource-limited settings whereas MDRD is recommonded compared to CKD-EPI, which fits perfectly with well structured healthcare system.

The review identified a better prevalence of CKD screening (8.4-38.5%) compared to a systematic review conducted in high income countries (4.4-17.1%)²¹ and a systematic review using a study conducted in a community setting (ranging from 7.0% to 60.3%).²² Possible reasons for this gap could be differences in the popualtion of the study, the kind of test used, and differences in cutoff values across the included studies in these three systematic reviews. A scoping review also demonstrated that early detection of CKD cases could be possible through targeted screening.²⁰ Thus, our review and other existing evidence showed the effectiveness of targeted screening in early detection of CKD among high-risk patients. However, there were different factors that required more attention during the screening/diagnosis of CKD among high-risk patients. Our review found that the prevalence of documented CKD was higher in older high-risk patients compared to younger patients, which aligns with individual studies conducted in Bangladesh,²³ Ethiopia,²⁴ and Nepal,²⁵ as well as a systematic review of global studies.⁴⁴ Therefore, it is critical to give due attention to older high-risk patients as a priority to screen in the area of resource limitations. Co-existence of DM and HTN has been linked with increased risk of CKD in a study conducted in Bangladesh²³ and Nepal,²⁵ which is consistent with our review findings. Individuals who bear the dual burden of both HTN and DM demand greater attention compared to those who only suffer from one disease. Patients with HTN or DM with a history of longer duration were associated with increased risk of CKD prevalence, which is in line with a single study conducted in Nepal²⁵ and Saudi Arabia.²⁶ This implies longer duration of uncontrolled diabetes and hypertension could accelerate structural and functional kidney damage that could contribute to an overtime decline in kidney function.

Strengths and Limitations of the Study

This systematic review invloved a comprehensive search of existing evidence. The current findings could bridge the gap in CKD screening in resources-limited settings. The review also showed the effectivenss of target screening, as reflected in a higher documented CKD prevalence. The study has several limitations. First, the study included cross-sectional studies with variable measures of outcomes, which made conducting pooled prevalence impossible. Second, the review included studies that addressed only two high-risk patient populations, which could underestimate the prevalence of CKD, as HIV patients were recently categorized as high-risk for CKD. Third, the study included cross-sectional studies, which limite understanding of screening effectiveness of the last fiteen years. Finally, the current classification of CKD is based on both eGFR and/or albuminuria, however, in our review, most of the included studies were based on eGFR, which could affect the generalizability of the findings. Therefore, clinical and policy applicaability of the finding should be consider those limitations.

Implication for Clinical Practice, Policy and Research

The results indicate significant clinical implications for enhancing the early detection and management of CKD in high-risk patients (such as hypertension, diabetes, or both). Routine follow-up care should always include easy-to-use diagnostic tools, such as serum creatinine with eGFR, as well as urine-based tests like albuminuria or dipsticks. This will help healthcare providers find kidney problems quickly. The common use of standardized eGFR thresholds, no matter which equation is used (MDRD, Cockcroft-Gault, or CKD-EPI), shows that it is possible to include CKD screening in primary care settings. Because the prevalence of CKD varies widely, healthcare providers should focus on targeted screening for patients who are most at risk. Overall, the evidence shows that systematic, regular CKD screening and strong management of modifiable risk factors in chronic disease care are necessary to slow the progression of the disease and its complications. From a policy point of view, the results highlight the imperative of standardizing screening protocols, advocating for the utilization of more precise eGFR equations such as CKD-EPI when possible, and guaranteeing access to essential diagnostic tests at primary healthcare levels. To lessen the growing burden of CKD, health systems should also make integrated chronic disease management a top priority, improve early detection strategies, and put more money into preventing and controlling key risk factors. For further research, the inconsistency in diagnostic specificity and the dependence on single-measure reports in certain studies underscore the need for longitudinal data to more accurately assess the burden of CKD.

Conclusions

Our systematic review findings imply that CKD screening during routine care for high-risk patients is low in SSA. During routine follow-up of high-risk patients, CKD screening was found to be efficient in early picking up of patients and early referral for nephrologist care. Most of the included studies conducted one-time screenings, which might not be reflective of actual CKD prevalence. It is recommended that confirmatory CKD screening should be conducted in line with the existing KDIGO guidelines to establish the prevalence of CKD among high-risk patients during routine follow-ups. Both eGFR and/or albuminuria screening tests should be integrated into routine healthcare to detect CKD early and refer for better treatment and slow progression of the disease. Finally, it is highly recommended that healthcare providers providing follow-up care for high-risk patients should give due emphasis to older age, female gender, longer disease duration, and concomitant hypertension and diabetes cases.

Supplemental Material

Supplemental material - Chronic Kidney Disease Screening Practice Among High-Risk Patients During Follow-Up in Sub-Saharan Africa: A Systematic Review

Supplemental material for Chronic Kidney Disease Screening Practice Among High-Risk Patients During Follow-Up in Sub-Saharan Africa: A Systematic Review by Habtamu Abera Areri, Yewondwossen Tadesse Mengistu, Rebecca Gary in Health Services Insights

Supplemental Material

Supplemental material - Chronic Kidney Disease Screening Practice Among High-Risk Patients During Follow-Up in Sub-Saharan Africa: A Systematic Review

Footnotes

Acknowledgments

We thank Addis Ababa and Emory University for library infrastructure. The review team also wants to acknowledge Emory University School of Nursing Global South Initiative for the capacity building provided for the primary author.

ORCID iD

Habtamu Abera Areri

Author Contributions

All authors conceived and designed the review. Habtamu Abera Areri searched for the articles. Yewondwossen Tadesse Mengistu and Gary Rebecca reviewed and approved the record identified. All authors are involved in screening, appraisal and result writing. Habtamu, drafted the manuscript. All authors have read and approved the final version of the manuscript.

Funding

The authors received no financial support for the review, authorship or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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