What question did this study set out to answer?

This research seeks to evaluate the prevalence and recognition of chronic kidney disease (CKD) in primary care settings.

March 28, 2026Open Access

WCN26-8189 Laboratory-Based Identification of CKD in Primary Care—Prevalence, Recognition, and Care Gaps (2010–2022), Findings from The VISTAKID study

Key Points

This research seeks to evaluate the prevalence and recognition of chronic kidney disease (CKD) in primary care settings.
Analyzed data from the VISTAKID study covering 2010-2022.
Estimated Glomerular Filtration Rate (eGFR) using the 2021 CKD-EPI formula.
Conducted binary logistic regression for predictors of CKD and proteinuria.
5.6% of the population tested positive for dipstick-positive proteinuria.
Overall CKD prevalence was found to be 2.6%.
Diabetes mellitus was identified as the strongest predictor for proteinuria (OR=4.148).
Proteinuria was the most significant predictor of CKD (OR=2.940).
Obesity and underweight were associated with higher odds of proteinuria.

Abstract

estimated Glomerular Filtration Rate (eGFR) of less than 60 mL/min/ 1. 73 m2, calculated using the 2021 CKD-EPI formula. The primary variables analyzed were age, gender, hypertension, Body Mass Index (BMI), diabetes mellitus, and total cholesterol. Binary logistic regression was the main statistical method used to identify independent predictors. Results: The overall prevalence of dipstick-positive proteinuria was 5. 6%, and the overall prevalence of CKD was 2. 6%. Multivariate analysis identified diabetes mellitus as the strongest risk factor (OR=4. 148) for proteinuria. Other significant predictors for proteinuria included CKD (OR=3. 076), hypertension (OR=2. 146), advancing age (OR=1. 010per year), and male gender, which had approximately 1. 5 times higher odds than female gender (female OR=0. 667). A non-linear, U-shaped association was observed for BMI, with both obesity (BMI30 kg/m2, OR=1. 707) and underweight status (BMI<18. 5 kg/ m2, OR=1. 485) associated with significantly higher odds of proteinuria. The presence of proteinuria was the most powerful predictor (OR=2. 940) of CKD. Other significant predictors were advancing age (OR=1. 062per year) and hypertension (OR=1. 283). Male gender was associated with 49% lower odds of having CKD compared to females (OR=0. 510). Conclusion: This study reveals a significant prevalence of dipstickpositive proteinuria and reduced renal function within the asymptomatic, productive population undergoing routine MCU. Proteinuria emerged as the single most powerful independent predictor of reduced renal function, while diabetes mellitus was the most powerful predictor for proteinuria. As the first investigation within a large, productive Indonesian population, these findings emphasize the importance of routine screening for early detection and intervention of CKD. I have no potential conflict of interest to disclose. I did not use generative AI and AI-assisted technologies in the writing process.

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Cite This Study

Abedini et al. (Wed,) studied this question.

synapsesocial.com/papers/69c770418bbfbc51511e070f https://doi.org/https://doi.org/10.1016/j.ekir.2026.104920

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