A predictive model for progression of CKD

Chang, Hsueh-Lu; Wu, Chia‐Chao; Lee, Shu-Pei; Chen, Ying-Kai; Su, Weixu; Su, Sui-Lung

doi:10.1097/md.0000000000016186

Cited by 33 publications

(44 citation statements)

References 18 publications

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“…Chang et al retrospectively reviewed and analyzed 1549 CKD patients who participated in the “Public health insurance Pre-ESRD preventive program and patient health education program” to establish an optimal prediction model for CKD progression. They found that the influencing factors with the best explanatory power included age, serum creatinine (Cr), urea nitrogen, and comorbidity with diabetes [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Static and Dynamic Prediction of Chronic Renal Disease Progression Using Longitudinal Clinical Data from Taiwan’s National Prevention Programs

Chang

Liao

Wang

et al. 2021

JCM

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Kidney diseases can cause severe morbidity, mortality, and health burden. Determining the risk factors associated with kidney damage and deterioration has become a priority for the prevention and treatment of kidney disease. This study followed 1042 chronic kidney disease (CKD) patients with Stage 3–5 kidney disease who were treated at a public veteran’s hospital through the national prevention program. A total of 12.5 years of records of clinical measurements were collected and analyzed using dynamic and static Cox hazard models to predict the progression to dialysis treatment. The results showed that the statistical significance of several variables in patients with Stage 3–5 CKD was attenuated while the dynamic model was being used. The estimated glomerular filtration rate (eGFR) and urine protein to creatinine ratio (PCR) had the powerful ability to predict the progression of CKD patients with Stage 3a and Stage 3b–5 kidney disease, whereas serum calcium was also predictive for the progression of Stages 3b–5 CKD. Because these two sub-stages of Stage 3 CKD are often associated with differences in routine measurements and the risk analysis of renal dialysis, future research can use this predictive model as a reference while similar prevention programs are implemented.

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Section: Introductionmentioning

confidence: 99%

Static and Dynamic Prediction of Chronic Renal Disease Progression Using Longitudinal Clinical Data from Taiwan’s National Prevention Programs

Chang

Liao

Wang

et al. 2021

JCM

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“…However, the course of renal disease progression is heterogeneous and complex in T2DM, due to individual patient characteristics and disease‐specific conditions 12,13 . Although these studies had identified risk factors for the development of advanced kidney disease or a rapid decline in renal function in T2DM with CKD, the findings of these studies were limited due to small population sizes and short‐term follow‐up 9–13 . In addition, reported risk and protective factors for CKD progression among T2DM patients were conflicting 14–16 …”

Section: Introductionmentioning

confidence: 99%

Rate of kidney function decline and factors predicting progression of kidney disease in type 2 diabetes mellitus patients with reduced kidney function: A nationwide retrospective cohort study

et al. 2020

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Currently, the data on independent risk factors for the progression of kidney disease in type 2 diabetes mellitus (T2DM) patients with CKD are limited. This study aimed to investigate CKD progression in T2DM patients who have reduced kidney function with baseline estimated glomerular filtration rate (eGFRs) between 15 and 59 mL/min/1.73 m2. This study was composed of a nationwide retrospective cohort of adult T2DM patients from 831 public hospitals in Thailand during the year 2015. T2DM patients with CKD stages 3 and 4 were followed up, until development of CKD stage 5, requirement of chronic dialysis, loss to follow‐up, death, or 31 May 2018, whichever came first. Cox proportional hazard regression was utilized for analysis. A total of 8464 participants were included; 30.4% were male. The mean age was 69 ± 10 years. The mean eGFR was 45 ± 11 mL/min/1.73 m2. The incidence of CKD stage 5 or the need for chronic dialysis was 16.4 per 1000 person‐years. The annual rate of eGFR decline during a mean follow‐up of 29 months was −2.3 mL/min/1.73 m2; 14.4% had a rapid decline in eGFR. The risk factors associated with progression to CKD stage 5 or the need for chronic dialysis were diabetes duration, systolic blood pressure, serum uric acid, albuminuria, and baseline eGFR. Conversely, older age and the use of renin‐angiotensin aldosterone system blockade were associated with decreased risks for rapid CKD progression and incidence CKD stage 5 or dialysis. This study identifies multiple predictive risk factors that support a multifaceted approach to prevent progression of advanced CKD.

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“…Cr in the blood is mainly produced as a metabolite of muscle activity and is excreted daily by the kidney with urine. When renal function is impaired, Cr products cannot be completely excreted, resulting in elevated serum Cr concentration [23]. Bertille et al reported increased levels of Cr and CysC in males when compared with those in females, and they were higher in subjects over 55 years old [24].…”

Section: Discussionmentioning

confidence: 99%

Analysis of renal function in a Health Examination Population in Chengdu (2012-2018)

Bao

Yang

et al. 2020

Preprint

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Background Dysfunction of kidney correlates with multiple renal diseases, for instance, chronic kidney disease. However, monitoring the changes of indexes related to renal function may help to early find the potential patients with renal diseases. Methods A cohort of 14,716 participants (8,148 males and 6,568 females) was recruited from the Health Examination Center at West China Hospital, Sichuan University, and was followed up since 2012 to 2018. Four indexes related to renal function, including creatinine (Cr), uric acid (UA), cystatin C (CysC) and urea nitrogen (UN) were selected to monitor the kidney function. Results Levels of CysC, Cr were reduced, and expression of UA was increased in all the participants since 2012 to 2018 overall. In addition, levels of CysC, UA, Cr and UN were higher in males than those in females, and expression of the four indexes was up-regulated in the elderly population compared with those in the younger population since 2012 to 2018 overall. Conclusions The findings suggested that some preventive action may be adopted early and more attention can focus on the health-examination population.

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A predictive model for progression of CKD

Abstract: Supplemental Digital Content is available in the text

Cited by 33 publications

References 18 publications

Static and Dynamic Prediction of Chronic Renal Disease Progression Using Longitudinal Clinical Data from Taiwan’s National Prevention Programs

Static and Dynamic Prediction of Chronic Renal Disease Progression Using Longitudinal Clinical Data from Taiwan’s National Prevention Programs

Rate of kidney function decline and factors predicting progression of kidney disease in type 2 diabetes mellitus patients with reduced kidney function: A nationwide retrospective cohort study

Analysis of renal function in a Health Examination Population in Chengdu (2012-2018)

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