Nomogram to predict risk of incident chronic kidney disease in high-risk population of cardiovascular disease in China: community-based cohort study

Zhang, Qiuxia; Zhang, Jingyi; Li, Lei; Liang, Hongbin; Li, Yun; Lu, Junyan; Zhou, Shiyu; Li, Guodong; Zhang, Xinlu; Chen, Yaode; Pan, Jiazhi; Lu, Xiaoyong; Chen, Yejia; Lin, Xinxin; Li, Xiaobo; An, Shengli; Xiu, Jiancheng

doi:10.1136/bmjopen-2020-047774

Cited by 2 publications

(1 citation statement)

References 39 publications

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“…Data from this retrospective cohort study was derived from the Chinese National Basic Public Health Service project, which includes free general health check-ups annually for the elderly or those with chronic diseases ( 17 ). Generally, 9,846 elderly residents (aged ≥ 65 years) attending the annual health check-up at least two times were enrolled, which included 6,554 residents from 37 communities of Guangzhou who attended between January 2017 and July 2021 and 3,292 residents from communities of Foshan who attended between January 2017 and December 2019.…”

Section: Methodsmentioning

confidence: 99%

Association between triglyceride-glucose index and worsening renal function in the elderly

Liang

et al. 2022

Front. Nutr.

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BackgroundTriglyceride-glucose (TyG) index is a simple marker of insulin resistance. However, insufficient data is available on whether the TyG index is associated with worsening renal function (WRF) in the elderly. Therefore, this study was designed to explore the association between the TyG index and WRF based on a community elderly cohort.MethodsIn this study, 7,822 elderly (aged ≥ 65 years) adults from southern China were enrolled and divided into four groups according to the TyG index quartiles. The primary endpoint was incident chronic kidney disease (CKD), defined as incident estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2. Additional endpoints included a decline in eGFR of 30% and 40% during the follow-up period.ResultsDuring the median 2.04 year follow-up period, 1,541 (19.7%) participants developed CKD. After adjusting for confounding factors, multivariable Cox regression models revealed significant associations between TyG index and incident CKD (HR per SD increase, 1.21; 95% CI: 1.14–1.29), a decline in eGFR of 30% (HR per SD increase, 1.38; 95% CI: 1.26–1.50), and decline in eGFR of 40% (HR per SD increase, 1.42; 95% CI: 1.24–1.63). Furthermore, compared with those in Q1, participants in Q4 demonstrated a higher risk of developing CKD (HR, 1.59; 95% CI: 1.35–1.88). These positive associations remained consistent across different subgroup populations.ConclusionOur study suggests a positive and independent association between the TyG index and WRF in the elderly.

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Section: Methodsmentioning

confidence: 99%

Association between triglyceride-glucose index and worsening renal function in the elderly

Liang

et al. 2022

Front. Nutr.

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A machine learning driven nomogram for predicting chronic kidney disease stages 3–5

Ghosh,

Khandoker

2023

Sci Rep

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Chronic kidney disease (CKD) remains one of the most prominent global causes of mortality worldwide, necessitating accurate prediction models for early detection and prevention. In recent years, machine learning (ML) techniques have exhibited promising outcomes across various medical applications. This study introduces a novel ML-driven monogram approach for early identification of individuals at risk for developing CKD stages 3–5. This retrospective study employed a comprehensive dataset comprised of clinical and laboratory variables from a large cohort of diagnosed CKD patients. Advanced ML algorithms, including feature selection and regression models, were applied to build a predictive model. Among 467 participants, 11.56% developed CKD stages 3–5 over a 9-year follow-up. Several factors, such as age, gender, medical history, and laboratory results, independently exhibited significant associations with CKD (p < 0.05) and were utilized to create a risk function. The Linear regression (LR)-based model achieved an impressive R-score (coefficient of determination) of 0.954079, while the support vector machine (SVM) achieved a slightly lower value. An LR-based monogram was developed to facilitate the process of risk identification and management. The ML-driven nomogram demonstrated superior performance when compared to traditional prediction models, showcasing its potential as a valuable clinical tool for the early detection and prevention of CKD. Further studies should focus on refining the model and validating its performance in diverse populations.

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Nomogram to predict risk of incident chronic kidney disease in high-risk population of cardiovascular disease in China: community-based cohort study

Cited by 2 publications

References 39 publications

Association between triglyceride-glucose index and worsening renal function in the elderly

Association between triglyceride-glucose index and worsening renal function in the elderly

A machine learning driven nomogram for predicting chronic kidney disease stages 3–5

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