Self-management intervention aims to facilitate an individual’s ability to make lifestyle changes. The effectiveness of this intervention in non-dialysis patients with chronic kidney disease (CKD) is limited. In this study, we applied a systematic review and meta-analysis to investigate whether self-management intervention improves renoprotection for non-dialysis chronic kidney disease. We conducted a comprehensive search for randomized controlled trials addressing our objective. We searched for studies up to May 12, 2018. Two reviewers independently evaluated study quality and extracted characteristics and outcomes among patients with CKD within the intervention phase for each trial. Meta-regression and subgroup analyses were conducted to explore heterogeneity. We identified 19 studies with a total of 2540 CKD patients and a mean follow-up of 13.44 months. Compared with usual care, self-management intervention did not show a significant difference for risk of all-cause mortality (5 studies, 1662 participants; RR 1.13; 95% CI 0.68 to 1.86; I2 = 0%), risk of dialysis (5 studies, 1565 participants; RR 1.35; 95% CI 0.84 to 2.19; I2 = 0%), or change in eGFR (8 studies, 1315 participants; SMD -0.01; 95% CI -0.23 to 0.21; I2 = 64%). Moreover, self-management interventions were associated with a lower 24 h urinary protein excretion (4 studies, 905 participants; MD − 0.12 g/24 h; 95% CI -0.21 to − 0.02; I2 = 3%), a lower blood pressure level (SBP: 7 studies, 1201 participants; MD − 5.68 mmHg; 95%CI − 9.68 to − 1.67; I2 = 60%; DBP: 7 studies, 1201 participants; MD − 2.64 mmHg, 95% CI -3.78 to − 1.50; I2 = 0%), a lower C-reactive Protein (CRP) level (3 studies, 123 participants; SMD -2.8; 95% CI -2.90 to − 2.70; I2 = 0%) and a longer distance on the 6-min walk (3 studies, 277 participants; SMD 0.70; 95% CI 0.45 to 0.94; I2 = 0%) when compared with the control group. We observed that self-management intervention was beneficial for urine protein decline, blood pressure level, exercise capacity and CRP level, compared with the standard treatment, during a follow-up of 13.44 months in patients with CKD non-dialysis. However, it did not provide additional benefits for renal outcomes and all-cause mortality.

Objective: The self-reported scale is a widely used method to assess patients’ medication adherence in clinical practice, but there is still a lack of medicine adherence measurement scale for patients with Chronic Kidney Disease (CKD). Therefore, this study aimed to develop a medication adherence measurement scale of traditional Chinese medicine and Western medicine, providing a tool for evaluating medicine adherence of CKD patients. Methods: In the preliminary stage, we formed the prediction scale after three rounds Delphi method and it was filled by 20 patients, who were selected randomly. After pre-investigation and language adaption, we adjusted the prediction measurement scale which included 31 items based on Knowledge-Attitude-Belief Theory. Then, 222 CKD patients in Guangdong Hospital of traditional Chinese Medicine were investigated by this 31-item scale. We screened 31 items by Items analysis theory, including critical ratio, item correlation analysis, internal consistency analysis, principal component analysis and other methods. The left 26 items made up a formal scale. We collected and analyzed data of the 26-item scale and Chinese version of MGL scale, and took their scores correlation analysis as the criterion validity of the 26-item scale. At the same time, we evaluated content validity, Cronbach alpha coefficient and retest reliability of the 26-item scale. Results: We developed a scale with 26 items and 5 dimensions finally. In the validation analysis, the scale had good construct validity and content validity. The Pearson relation index between respective scores of the scale and Chinese version of MGL scale was 0.426, P<0.01. The scale also had good reliability as its 0.915 in Cronbach alpha, 0.753 in retest reliability and P<0.01. Conclusion: The scale revealed great reliability and validity, which could be used as a measurement tool to evaluate the medication adherence of patients with CKD.

Background: Kidney disease progression rates vary among patients. Rapid and accurate prediction of kidney disease outcomes is crucial for disease management. In recent years, various prediction models using Machine Learning (ML) algorithms have been established in nephrology. However, their accuracy have been inconsistent. Therefore, we conducted a systematic review and meta-analysis to investigate the diagnostic accuracy of ML algorithms for kidney disease progression. Methods: We searched PubMed, EMBASE, Cochrane Central Register of Controlled Trials, the Chinese Biomedicine Literature Database, Chinese National Knowledge Infrastructure, Wanfang Database, and the VIP Database for diagnostic studies on ML algorithms’ accuracy in predicting kidney disease prognosis, from the establishment of these databases until October 2020. Two investigators independently evaluate study quality by QUADAS-2 tool and extracted data from single ML algorithm for data synthesis using the bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model. Results: Fifteen studies were left after screening, only 6 studies were eligible for data synthesis. The sample size of these 6 studies was 12,534, and the kidney disease types could be divided into chronic kidney disease (CKD) and Immunoglobulin A Nephropathy, with 5 articles using end-stage renal diseases occurrence as the primary outcome. The main results indicated that the area under curve (AUC) of the HSROC was 0.87 (0.84–0.90) and ML algorithm exhibited a strong specificity, 95% confidence interval and heterogeneity (I²) of (0.87, 0.84–0.90, [I² 99.0%]) and a weak sensitivity of (0.68, 0.58–0.77, [I² 99.7%]) in predicting kidney disease deterioration. And the the results of subgroup analysis indicated that ML algorithm’s AUC for predicting CKD prognosis was 0.82 (0.79–0.85), with the pool sensitivity of (0.64, 0.49–0.77, [I² 99.20%]) and pool specificity of (0.84, 0.74–0.91, [I² 99.84%]). The ML algorithm’s AUC for predicting IgA nephropathy prognosis was 0.78 (0.74–0.81), with the pool sensitivity of (0.74, 0.71–0.77, [I² 7.10%]) and pool specificity of (0.93, 0.91–0.95, [I² 83.92%]). Conclusion: Taking advantage of big data, ML algorithm-based prediction models have high accuracy in predicting kidney disease progression, we recommend ML algorithms as an auxiliary tool for clinicians to determine proper treatment and disease management strategies.

Recent individual studies have indicated that ultra-processed food (UPF) consumption may be associated with the incidence of chronic kidney disease (CKD). We conducted a systematic review and meta-analysis based on those longitudinal studies evaluating the relationship between UPF consumption and the risk of incident CKD, and synthesizing the results. PubMed, Embase, The Cochrane Library, Web of Science, and Scopus were searched from inception through 22 March 2023. Any longitudinal studies evaluating the relationship between UPF consumption and the risk of incident CKD were included. Two researchers independently conducted the literature screening and data extraction. RR and its 95% CI were regarded as the effect size. The Newcastle-Ottawa Scale (NOS) was applied to assess the quality of the studies included, and the effect of UPF consumption on the risk of incident CKD was analyzed with STATA version 15.1. This study's protocol was registered in PROSPERO (CRD42023411951). Four cohort studies with a total of 219,132 participants were included after screening. The results of the meta-analysis suggested that the highest UPF intake was associated with an increased risk of incident CKD (RR = 1.25; 95% CI: 1.18-1.33). High-dose UPF intake was associated with an increased risk of incident CKD. However, the underlying mechanisms remain unknown. Thus, more standardized clinical studies and further exploration of the mechanisms are needed in the future.

Background: Chronic kidney disease (CKD) is a major global health problem. Short-term self-management has been considered to effect some renal and psychological endpoints. However, there are currently very few studies about self-management for CKD that a) have been scientifically designed by a theory-based framework and b) that evaluate the long-term effects and working mechanism. This study presents the rationale and design of a theory-based cohort study to explore how this self-management intervention works and its effectiveness on the Chinese CKD population. Methods: In this ambispective intervention cohort study,1,200 patients with CKD stages 1–5 will be recruited from July 2015 to July 2024 in 3 branches of Guangdong Provincial Hospital of Chinese Medicine (GPHCM) in Guangdong province, China. The patients in the self-management cohort will choose to receive an intervention that consists of education, nutrition/diet modification, lifestyle change recommendation, medication review, and psychology support based on Social Cognition Theory (SCT). The patients in the control cohort will do regular follow-ups based on the clinic rules. All the patients will be followed up for 5 years, or until the occurrence of a primary outcome. Detailed clinical, laboratory markers, nutritional status, psychological exposures and outcome questionaries will be collected semiannually in CKD stage 1–2 and trimonthly in stage 3–5 patients. The primary outcome is the occurrence of composite clinical endpoints (doubling of serum creatinine level, ESKD, loss of renal function (≥ 40% decline in GFR from baseline), death, major cardiovascular or cerebrovascular events). The main secondary outcomes include the absolute change and slope of eGFR, absolute changes of urinary protein creatinine ratio, 24-h urine proteinuria, intact parathyroid hormone level, and self-management adherence rate and quality of life from baseline to end of the study. The effectiveness of self-management will be analyzed and the association between longitudinal trajectories of self-management and renal outcomes will be evaluated. Discussion: This study aims to provide further evidence for the effectiveness of theory-based self-management in CKD patients and to improve the lives of patients with CKD by slowing progression, improving psychological well-being and overall quality of life. Trial registration: Chinese Clinical Trial Register (ChiCTR1900024633). 19 July, 2019. http://www.chictr.org.cn/showproj.aspx?proj=38378

Background: Time-restricted feeding (TRF) has become a popular weight loss method in recent years. It is widely used in the nutritional treatment of normal obese people and obese people with chronic diseases such as diabetes mellitus and hypertension, and has shown many benefits. However, most TRF studies have excluded chronic kidney disease (CKD) patients, resulting in a lack of sufficient evidence-based practice for the efficacy and safety of TRF therapy for CKD. Therefore, we explore the efficacy and safety of TRF in overweight and obese patients with moderate-to-severe stage CKD through this pilot study, and observe patient compliance to assess the feasibility of the therapy.Methods: This is a prospective, non-randomized controlled short-term clinical trial. We recruited overweight and obese patients with CKD stages 3-4 from an outpatient clinic and assigned them to either a TRF group or a control diet (CD) group according to their preferences. Changes in renal function, other biochemical data, anthropometric parameters, gut microbiota, and adverse events were measured before the intervention and after 12 weeks.Results: The change in estimated glomerular filtration rate (eGFR) before and after intervention in the TRF group (Δ = 3.1 ± 5.3 ml/min/1.73m²) showed significant improvement compared with the CD group (Δ = -0.8 ± 4.4 ml/min/1.73m²). Furthermore, the TRF group had a significant decrease in uric acid (Δ = -70.8 ± 124.2 μmol/L), but an increase in total protein (Δ = 1.7 ± 2.5 g/L), while the changes were inconsistent for inflammatory factors. In addition, the TRF group showed a significant decrease in body weight (Δ = -2.8 ± 2.9 kg) compared to the CD group, and body composition indicated the same decrease in body fat mass, fat free mass and body water. Additionally, TRF shifted the gut microbiota in a positive direction.Conclusion: Preliminary studies suggest that overweight and obese patients with moderate-to-severe CKD with weight loss needs, and who were under strict medical supervision by healthcare professionals, performed TRF with good compliance. They did so without apparent adverse events, and showed efficacy in protecting renal function. These results may be due to changes in body composition and alterations in gut microbiota.