title: Why overestimate or underestimate chronic kidney disease when correct estimation is possible?
abstract: There is no doubt that the introduction of the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines 14 years ago, and their subsequent updates, have substantially contributed to the early detection of different stages of chronic kidney disease (CKD). Several recent studies from different parts of the world mention a CKD prevalence of 8-13%. However, some editorials and reviews have begun to describe the weaknesses of a substantial number of studies. Maremar (maladies rénales chroniques au Maroc) is a recently published prevalence study of CKD, hypertension, diabetes and obesity in a randomized, representative and high response rate (85%) sample of the adult population of Morocco that strictly applied the KDIGO guidelines. When adjusted to the actual adult population of Morocco (2015), a rather low prevalence of CKD (2.9%) was found. Several reasons for this low prevalence were identified; the tagine-like population pyramid of the Maremar population was a factor, but even more important were the confirmation of proteinuria found at first screening and the proof of chronicity of decreased estimated glomerular filtration rate (eGFR), eliminating false positive results. In addition, it was found that when an arbitrary single threshold of eGFR (<60 mL/min/1.73 m2) was used to classify CKD stages 3, 4 and 5, it lead to substantial 'overdiagnosis' (false positives) in the elderly (>55 years of age), particularly in those without proteinuria, haematuria or hypertension. It also resulted in a significant 'underdiagnosis' (false negatives) in younger individuals with an eGFR >60 mL/min/1.73 m2 and below the third percentile of their age-/gender-category. The use of the third percentile eGFR level as a cut-off, based on age-gender-specific reference values of eGFR, allows the detection of these false positives and negatives. There is an urgent need for additional quality studies of the prevalence of CKD using the recent KDIGO guidelines in the correct way, to avoid overestimation of the true disease state of CKD by ≥50% with potentially dramatic consequences.
authors.affiliation: Laboratory of Pathophysiology, University of Antwerp, Wilrijk, Belgium.
authors.forename: Marc E
authors.initials: ME
authors.lastname: De Broe
authors.affiliation: Faculty of Medicine and Pharmacy, University Hassan II, Casablanca, Morocco.
authors.forename: Mohamed Benghanem
authors.initials: MB
authors.lastname: Gharbi
authors.affiliation: Faculty of Medicine and Pharmacy, University Hassan II, Casablanca, Morocco.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Zamd
authors.affiliation: Department of Biostatistics, Center for Research and Innovation in Care, University of Antwerp, Wilrijk, Belgium.
authors.forename: Monique
authors.initials: M
authors.lastname: Elseviers
mesh_terms: D000328:Adult; D000368:Aged; D001530:Belgium / Q000453:epidemiology; D003951:Diagnostic Errors / Q000517:prevention & control*; D042241:Early Diagnosis; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D006973:Hypertension / Q000503:physiopathology; D007668:Kidney / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000503:physiopathology; D015995:Prevalence; D011507:Proteinuria / Q000453:epidemiology; D051436:Renal Insufficiency, Chronic / Q000145:classification* / Q000175:diagnosis / Q000453:epidemiology*; D009626:Terminology as Topic
keywords: CKD prevalence; eGFR percentile lines; false positives and negatives; single threshold for CKD