Comparison of the prevalence of kidney disease by proteinuria and decreased estimated glomerular filtration rate determined using three creatinine-based equations among patients admitted on medical wards of Masaka Regional Referral Hospital in Uganda: a prospective study

Abstract

Background: Despite estimated glomerular filtration rate (eGFR) being the best marker for kidney function, there are no studies in sub-Saharan Africa comparing the performance of various equations used to determine eGFR. We compared prevalence of kidney disease determined by proteinuria of ≥ + 1 and or kidney disease improving global outcomes (KDIGO) eGFR criteria of < 60 ml/minute/1.73m² determined using three creatinine-based equations among patients admitted on medical ward of Masaka Regional Referral Hospital.

Methods: This was a prospective study conducted among adult patients admitted on medical wards between September 2020 to March 2021. Spot urine samples were collected to assess for proteinuria and blood samples were collected to assess serum creatinine levels. Kidney disease was defined as proteinuria of ≥ 1 + on spot urine dipstick and or KDIGO eGFR criteria of < 60 ml/minute/1.73m². Estimated glomerular filtration rate was calculated using three creatinine-based equations: a) Full Age Spectrum equation (FAS), b) chronic kidney disease-Epidemiology collaboration (CKD-EPI) 2021 equation, c) CKD EPI 2009 (without and with race factor) equation. CKD was determined after followed up at 90 days post enrollment to determine the chronicity of proteinuria of ≥ + 1 and or KDIGO eGFR criteria of < 60mls /minute/1.73m². We also compared prevalence of CKD determined by KDIGO eGFR criteria of < 60mls /minute/1.73m² vs age adapted eGFR threshold criteria for defining CKD.

Results: Among the 357 patients enrolled in the study, KDIGO eGFR criteria of < 60mls / minute determined using FAS and CKD-EPI 2009 without race factor equations and or proteinuria of ≥ + 1 showed the highest overall prevalence of kidney disease at 27.2%. Prevalence of confirmed CKD at 90 days was highest with proteinuria ≥ + 1 and or KDIGO eGFR criteria of < 60mls/min determined using CKD EPI 2009 without race factor Equation (15.1%).

Conclusions: Use of KDIGO eGFR criteria of < 60mls / minute /1.73m² using FAS and CKD-EPI 2009 without race equations identifies the largest number of patients with CKD. Health care systems in sub-Saharan Africa should calculate eGFR using FAS equations or CKD-EPI 2009 without race equations during basic screening and management protocols.

Keywords: Comparison of prevalence of kidney disease; Estimated glomerular filtration rate equations; Kidney disease.

Fig. 1

Patient flow chart from enrollment to end of the study: Flow chart shows that 717 patients were screen, 360 excluded basing on exclusion criteria

Fig. 2

Comparison of prevalence of kidney disease basing on proteinuria ≥  + 1 and or KDIGO eGFR criteria of < 60 ml/min/1.73m² calculated by various eGFR creatinine-based equations. Bar chart shows that among the 357 patients enrolled in the study, both FAS and CKD EPI 2009 without race factor equations and or proteinuria of ≥  + 1 revealed the highest overall prevalence of kidney disease at 27.2% while CKD EPI 2009 with race factor and or proteinuria of ≥  + 1 showed the lowest overall prevalence of kidney disease at 23%. N = Number of patients enrolled in the study

Fig. 3

Comparison of prevalence of kidney disease using KDIGO eGFR criteria (< 60 ml/min/1.73m²) for defining CKD vs age adapted eGFR thresholds for CKD definition. Bar chart shows that KDIGO eGFR criteria of < 60 ml/min/1.73m² for defining CKD identifies 0.3–3% slightly more patients with kidney disease than age adapted eGFR thresholds for CKD definition while using all eGFR serum creatinine-based equations. N = Number of patients enrolled in the study

Fig. 4

Comparison of prevalence of CKD at ≥ 90 days determined by of proteinuria ≥ 1 + and or KDIGO eGFR criteria of < 60 ml/min/1.73m² using various eGFR serum creatinine-based equations. Bar chart shows that CKD confirmed by proteinuria ≥  + 1 and/or KDIGO eGFR criteria of < 60 ml/min/1.73m² determined by CKD EPI 2009 without race factor identified the highest number of patients with CKD at 15.1% while CKD EPI 2009 with race factor identified the least number of patients at 12.8%

Fig. 5

Comparison of prevalence of CKD after 90 days using KDIGO eGFR criteria of < 60mls/minute Vs age adapted eGFR thresholds to define CKD. Bar chart shows that KDIGO definition of CKD by eGFR < 60mls/minute/1.73m² identifies slightly more patients with CKD than age adapted eGFR thresholds for CKD across most eGFR serum creatinine-based equations: FAS 13.5% vs 12.3%, CKD EPI 2021 14.1% vs 13.4%, CKD EPI 2009 without race 14.9% vs 13% respectively