My SciELO
Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Cited by Google
- Similars in SciELO
- Similars in Google
Share
Enfermería Nefrológica
On-line version ISSN 2255-3517Print version ISSN 2254-2884
Abstract
GARCIA SERRANO, Cristina et al. Underdiagnosis identification of chronic kidney disease in primary care. Enferm Nefrol [online]. 2019, vol.22, n.3, pp.302-307. Epub Dec 23, 2019. ISSN 2255-3517. https://dx.doi.org/10.4321/s2254-28842019000300009.
Introduction
Chronic kidney disease affects 9.16% of the Spanish population. The high prevalence and underdiagnosis require interdisciplinary coordination to improve the prevention, diagnosis and treatment of this pathology. Thus, we propose to identify the real prevalence of chronic kidney disease in our Basic Health Area, to detect coding and diagnostic errors, and to increase detection.
Material and Method
Cross-sectional observational study in patients older than 14 years residing in the Basic Health Area of Balaguer. The diagnostic classification criteria were patients diagnosed with chronic kidney disease or not coded with renal impairment, measured by glomerular filtration rate, albumin/creatinine ratio or mild albuminuria. Loss of follow-up were considered deaths and patients with change in Basic Health Area. The variables studied were: diagnosis and stage of chronic kidney disease, mild albuminuria, albumin/creatinine ratio, glomerular filtration and analytical determinations. A coding was performed through the review of the medical history. The analysis was based on prevalence.
Results
The prevalence increased from an initial 3.98% to 6.00% after the review. Underdiagnosis figures were maintained, with a detection of two thirds of the expected. Adding the patients pending a second analytical determination and those suffering from mild albuminuria, the prevalence represented 80% of the expected (7.40%).
Conclusion
The existence of underdiagnosis is observed in the early detection of CKD. A review of the classification criteria helps to improve underdiagnosis data.
Keywords : chronic renal failure; prevalence; diagnostic errors; early diagnosis; primary health care.