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Chronic kidney disease risk prediction scores assessment and development in Mexican adult population

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Τίτλος: Chronic kidney disease risk prediction scores assessment and development in Mexican adult population
Συγγραφείς: Colli, Victor A., González-Rocha, Alejandra, Canales, David, Hernández-Alcáraz, Cesar, Pedroza, Andrea, Pérez-Chan, Manuel, Barquera, Simón, Denova-Gutierrez, Edgar
Συνεισφορές: Fundación Gonzalo Río Arronte
Πηγή: Frontiers in Medicine ; volume 9 ; ISSN 2296-858X
Στοιχεία εκδότη: Frontiers Media SA
Έτος έκδοσης: 2022
Συλλογή: Frontiers (Publisher - via CrossRef)
Περιγραφή: Background Chronic kidney disease (CKD) is a major public health problem, with considerable growth in prevalence and mortality in recent years. Screening of CKD at primary care is crucial for the implementation of prevention strategies. The aims of this study are to assess CKD risk prediction scores and to develop a risk prediction score for the Mexican adult population. Methods Data from the Mexican National Health and Nutrition Survey 2016 was utilized and 3463 participants ≥ 20 years old were included. Reduced renal function with Glomerular filtration rate and/or the presence of albuminuria was defined as CKD. Multiple logistic regression models were performed for the creation of a training and validation model. Additionally, several models were validated in our Mexican population. Results The developed training model included sex, age, body mass index, fast plasma glucose, systolic blood pressure, and triglycerides, as did the validation model. The area under the curve (AUC) was 0.78 (95% CI: 0.72, 0.79) for training model, and 0.76 (95% CI: 0.71, 0.80) in validation model for Mexican adult population. Age, female gender, presence of diabetes and hypertension, elevated systolic and diastolic blood pressure, serum and urinary creatinine, and higher HbA1c were significantly associated with the prevalent chronic kidney disease. Previous CKD risk predictive models were evaluated with a representative sample of the Mexican adult population, their AUC was between 0.61 and 0.78. Conclusion The designed CKD risk predictive model satisfactorily predicts using simple and common variables in primary medical care. This model could have multiple benefits; such as, the identification of the population at risk, and prevention of CKD.
Τύπος εγγράφου: article in journal/newspaper
Γλώσσα: unknown
DOI: 10.3389/fmed.2022.903090
DOI: 10.3389/fmed.2022.903090/full
Διαθεσιμότητα: https://doi.org/10.3389/fmed.2022.903090
https://www.frontiersin.org/articles/10.3389/fmed.2022.903090/full
Rights: https://creativecommons.org/licenses/by/4.0/
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  Data: Chronic kidney disease risk prediction scores assessment and development in Mexican adult population
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  Data: Fundación Gonzalo Río Arronte
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  Data: Frontiers in Medicine ; volume 9 ; ISSN 2296-858X
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  Data: Background Chronic kidney disease (CKD) is a major public health problem, with considerable growth in prevalence and mortality in recent years. Screening of CKD at primary care is crucial for the implementation of prevention strategies. The aims of this study are to assess CKD risk prediction scores and to develop a risk prediction score for the Mexican adult population. Methods Data from the Mexican National Health and Nutrition Survey 2016 was utilized and 3463 participants ≥ 20 years old were included. Reduced renal function with Glomerular filtration rate and/or the presence of albuminuria was defined as CKD. Multiple logistic regression models were performed for the creation of a training and validation model. Additionally, several models were validated in our Mexican population. Results The developed training model included sex, age, body mass index, fast plasma glucose, systolic blood pressure, and triglycerides, as did the validation model. The area under the curve (AUC) was 0.78 (95% CI: 0.72, 0.79) for training model, and 0.76 (95% CI: 0.71, 0.80) in validation model for Mexican adult population. Age, female gender, presence of diabetes and hypertension, elevated systolic and diastolic blood pressure, serum and urinary creatinine, and higher HbA1c were significantly associated with the prevalent chronic kidney disease. Previous CKD risk predictive models were evaluated with a representative sample of the Mexican adult population, their AUC was between 0.61 and 0.78. Conclusion The designed CKD risk predictive model satisfactorily predicts using simple and common variables in primary medical care. This model could have multiple benefits; such as, the identification of the population at risk, and prevention of CKD.
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