Nomogram Tool Can Predict Risk of CKD in Patients at High Risk of Developing Cardiovascular Disease


A tool utilizing 5 predictors was found to be reliable at identifying patients at a high risk of cardiovascular disease who were also at risk of developing chronic kidney disease (CKD), potentially allowing providers to implement prevention strategies sooner than ever before.

A nomogram tool utilizing 5 predictors was discovered to be a simple and reliable means for the stratification of chronic kidney disease (CKD) risk among high risk populations, according to a recent analysis of patients with a high risk of cardiovascular disease.

In the retrospective Chinese study, published in BMJ Open, the investigators claimed that the tool could enable physicians to identify individuals at a high risk of developing CKD so that they can implement precise prevention strategies earlier.

“Using the demographic, clinical and laboratory variables from electronic health records, our visualised nomogram with only five variables…demonstrated good discriminative power, which enables us to identify patients at high risk of incident CKD readily,” wrote the investigators.

CKD is challenging to treat as its often asymptomatic and diagnosed late. Along with hypertension and diabetes, CKD has been identified as an independent risk factor for cardiovascular disease (CVD) and all-cause mortality. Populations at high risk of CVD often take medicines for multiple comorbidities, such as blood pressure medications, antidiabetic drugs, antithrombotic agents, which can increase burden on the kidneys.

Risk prediction tools to identify individual risks for incident CKD could improve primary care for CKD. However, the primary health care system in China is often faced with not enough medical personnel, insufficient government funding, and high intensity work, suggesting that use of conventional data in the medical system in addition to improving chronic disease management methods are needed to build a CKD risk prediction model.

“The ability to identify the individuals at risk of incident CKD may decrease the incidence of CVD….For these persons, early identify the high-risk CKD individuals is of great significance to guide prevention and treatment,” noted the investigators.

The participants for the study were recruited from the National Basic Public Health Service Project of Guangzhou, China between January 2015 and December 2020. To participate, the patients had to be aged 65 years or older or at least 35 years old if they had diabetes or hypertension. The current analysis included patients with a 5-year cardiovascular risk score of 20% or greater.

In total, 5730 patients with a high CVD risk were categorized into the development cohort (n = 3820) and the validation cohort (n = 1910). The mean (SD) age of the entire cohort was 68.64 (6.49) years and the median eGFR was 92.95 mL/min/1.732.

Among the patients in the development cohort, those who developed CKD were often older, had a higher body mass index (BMI), and had a bigger waistline compared with those who were CKD-free. During laboratory examinations, patients who developed CKD had lower glomerular filtration rate (eGFR) and blood platelet counts as well as higher uric acid and triglyceride contents compared with patients who were CKD-free. Patients who developed CKD during the follow-up period were also more likely to have hypertension and diabetes and less likely to be smokers or drinkers.

During the median follow-up period of 4.22 years, incident CKD was present in 19.09% (n = 1094) of the entire, including 19.03% (n = 727) of the development cohort and 19.21% (n = 367) of the validation cohort. Death occurred in 23 (0.4%) patients during the follow-up period, of whom 7 died after developing CKD and 16 died without developing CKD.

Through a multivariable COX regression analysis and a backward stepwise approach age (HR, 1.07; 95% CI, 1.06-1.08), BMI (HR, 1.04; 95% CI, 1.02-1.06), an eGFR between 60-89 mL/min/1.732 (HR, 5.59; 95% CI, 4.70-6.65), diabetes (HR, 1.63; 95% CI, 1.38-1.91), and hypertension (HR, 1.40; 95% CI, 1.13-1.75) were selected as predictor of incident CKD.

In both groups, the nomogram developed by the investigators demonstrated a good discriminative power with C-index of 0.778 in the development cohort and 0.785 in the validation cohort. The areas under the curve (AUC) in the development cohort at 3 years, 4 years, and 5 years were 0.817, 0.814, and 0.834, respectively. The AUCs in the validation cohort was 0.830, 0.847, and 0.839 at 3 years, 4 years, and 5 years, respectively. The nomogram also showed to be able to distinguish patients at a high risk of CKD from those with a low risk at 3 years, 4 years, and 5 years.

The investigators noted the lack of albuminuria data for a majority of patients and concerns about the definition used for their eGFR endpoint as study limitations. Additionally, there was no external validation of the investigators’ model.

“More studies focusing on the clinical meaning of different decline of eGFR are in need,” they wrote.


Zhang Q, Zhang J, Lei L, et al. Nomogram to predict risk of incident chronic kidney disease in high-risk population of cardiovascular disease in China: community-based cohort study. BMJ Open. Published online November 12, 2021. Accessed December 1, 2021. doi:10.1136/bmjopen-2020-047774

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