Time-restricted feeding's effect on overweight and obese patients with chronic kidney disease stages 3-4: A prospective non-randomized control pilot study.

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.

An investigation of low-protein diets' qualification rates and an analysis of their short-term effects for patients with CKD stages 3-5: a single-center retrospective cohort study from China.

BACKGROUND: The feasibility and efficacy of low-protein diets (LPD) treatment in chronic kidney disease (CKD) is controversial. Based on the characteristics of the Chinese diet, we observe the qualification rates and short-term clinical effects of LPD for CKD patients in our center. METHODS: This is a retrospective cohort study. CKD stages 3-5 patients who were regularly followed up 5 times (over 2 years) and treated with LPD were included. We collected clinical data to observe the changes in LPD qualification rates and divided patients into LPD and non-LPD group according to the average dietary protein intake (DPI) of 5 follow-up time points and compared the changes in primary and secondary outcome measures between the two groups. RESULTS: We analyzed data from 161 eligible CKD stages 3-5 patients. From baseline to the 5th follow-up time point, the LPD qualification rates of all patients were 11.80%, 35.40%, 47.82%, 53.43% and 54.04%, respectively. For primary outcome measures, the urine protein/creatinine ratio (UPCR) decreased more in the LPD group than in the non-LPD group [Median (interquartile range, IQR) of the difference between the 5th follow-up time point and baseline: 0.19 (- 0.01-0.73) vs. 0.10 (- 0.08-0.27), P < 0.001]. We constructed three classes of mixed linear models (model I, II, III). The UPCR slopes were all negative in the LPD group and positive in the non-LPD group (P < 0.001). Meanwhile, in model I, the estimate glomerular filtration rate(eGFR) decline slope in the LPD group was lower than that in the non-LPD group [slope (standard error): - 1.32 (0.37) vs. - 2.35 (0.33), P = 0.036]. For secondary outcome measures, body mass index (BMI) triglycerides (TG), body weight, and fat free mass (FFM) showed stable statistical differences in the comparison of LPD and non-LPD groups, with greater declines in the former. CONCLUSION: The results of this study suggest that LPD treatment can reduce UPCR in patients with CKD stages 3-5, and may also delay the decline in eGFR. Meanwhile, it also reduces BMI, TG, body weight, and FFM, thus the need to prevent malnutrition in clinical implementation.

Machine learning algorithms' accuracy in predicting kidney disease progression: a systematic review and meta-analysis.

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.

Is E-Version Transition of the Medication Adherence Scale Feasible for CKD Management? A Pilot Study.

BACKGROUND: To transfer a paper-version Chinese and Western medication adherence scale for CKD into an electronic scale, and evaluate its validity, internal consistency and clinical implementation, and assess whether the transition is feasible in clinic. METHODS: We built an e-version Chinese and Western medication adherence scale based on the Wen-JuanXing platform. CKD subjects' responses were applied to test the scale's validity and internal consistency. We retested some of the participants two weeks later randomly. We also tested the clinical application. RESULTS: Of the 434 recruited patients, 228 responded. In exploratory factor analysis (EFA), the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy = 0.8 and Bartlett's approx. Chi-Square = 1340.0 (df = 105, p < 0.001). We extracted four common factors which could explain 61.47% of the variance. However, Item 15 "Have you changed a traditional Chinese medicine prescription yourself within the past month?" had factor loading = 0.3 and measure of sampling adequacy (MSA) = 0.5, meaning we could not enter it into the factor analysis. The internal consistency reliability for medication adherence was 0.9, with a Guttman split-half coefficient = 0.5 and a Spearman-Brown coefficient = 0.6. Cronbach's α was 0.9, 0.4 and 0.5 for the knowledge, belief and behavior domains, respectively. The correlation coefficient r of the test-retest reliability was -0.8 and was -0.8, 0.4, -0.3 in the knowledge, belief and behavior domains, respectively. Patients with comorbidities were more likely to respond. We detected no other significant differences in the clinical profiles between respondents and non-respondents. CONCLUSION: The e-version Chinese and Western medication adherence scales have undesirable construct validity and internal consistency. Thus, caution is needed in transitioning the paper-version scale into an e-version.

Refinement and Evaluation of a Chinese and Western Medication Adherence Scale for Patients with Chronic Kidney Disease: Item Response Theory Analyses.

PURPOSE: This study aimed to simplify the version-1 Chinese and Western medication adherence scale for patients with chronic kidney disease (CKD) to a version-2 scale using item response theory (IRT) analyses, and to further evaluate the performance of the version-2 scale. MATERIALS AND METHODS: Firstly, we refined the version-1 scale using IRT analyses to examine the discrimination parameter (a), difficulty parameter (b) and maximum information function peak (Imax). The final scale refinement from version-1 to version-2 scale was also decided upon clinical considerations. Secondly, we analyzed the reliability and validity of version-2 scale using classical test theory (CTT), as well as difficulty, discrimination and Imax of version-1 and version-2 scale using IRT in order to conduct scale evaluation. RESULTS: For scale refinement, the 26-item version-1 scale was reduced to a 15-item version-2 scale after IRT analyses. For scale evaluation using CTT, internal consistency reliability (total Cronbach α = 0.842) and test-rest reliability (r = 0.909) of version-2 scale were desirable. Content validity indicated 3 components of knowledge, belief and behaviors. We found meritorious construct validity with 3 detected components as the same construct of medication knowledge (items 1-9), medication behavior (items 13-15), and medication belief (items 10-12) based upon exploratory factor analysis. The correlation between the version-2 scale and Morisky, Green and Levine scale (MGL scale) was weak (Pearson coefficient = 0.349). For scale evaluation with IRT, the findings showed enhanced discrimination and decreased difficulty of most retained items (items 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15), decreased Imax of items 1, 2, 3, 4, 6, 11, 14, as well as increased Imax of items 5, 7, 8, 9, 10, 12, 13, 14, 15 in the version-2 scale than in the version-1 scale. CONCLUSION: The original Chinese and Western medication adherence scale was refined to a 15-item version-2 scale after IRT analyses. The scale evaluation using CTT and IRT showed the version-2 scale had the desirable reliability, validity, discrimination, difficulty, and information providedoverall. Therefore, the version-2 scale is clinically feasible to assess the medication adherence of CKD patients.

Intra-Rater and Inter-Rater Reliability of Tongue Coating Diagnosis in Traditional Chinese Medicine Using Smartphones: Quasi-Delphi Study.

BACKGROUND: There is a growing trend in the use of mobile health (mHealth) technologies in traditional Chinese medicine (TCM) and telemedicine, especially during the coronavirus disease (COVID-19) outbreak. Tongue diagnosis is an important component of TCM, but also plays a role in Western medicine, for example in dermatology. However, the procedure of obtaining tongue images has not been standardized and the reliability of tongue diagnosis by smartphone tongue images has yet to be evaluated. OBJECTIVE: The first objective of this study was to develop an operating classification scheme for tongue coating diagnosis. The second and main objective of this study was to determine the intra-rater and inter-rater reliability of tongue coating diagnosis using the operating classification scheme. METHODS: An operating classification scheme for tongue coating was developed using a stepwise approach and a quasi-Delphi method. First, tongue images (n=2023) were analyzed by 2 groups of assessors to develop the operating classification scheme for tongue coating diagnosis. Based on clinicians' (n=17) own interpretations as well as their use of the operating classification scheme, the results of tongue diagnosis on a representative tongue image set (n=24) were compared. After gathering consensus for the operating classification scheme, the clinicians were instructed to use the scheme to assess tongue features of their patients under direct visual inspection. At the same time, the clinicians took tongue images of the patients with smartphones and assessed tongue features observed in the smartphone image using the same classification scheme. The intra-rater agreements of these two assessments were calculated to determine which features of tongue coating were better retained by the image. Using the finalized operating classification scheme, clinicians in the study group assessed representative tongue images (n=24) that they had taken, and the intra-rater and inter-rater reliability of their assessments was evaluated. RESULTS: Intra-rater agreement between direct subject inspection and tongue image inspection was good to very good (Cohen κ range 0.69-1.0). Additionally, when comparing the assessment of tongue images on different days, intra-rater reliability was good to very good (κ range 0.7-1.0), except for the color of the tongue body (κ=0.22) and slippery tongue fur (κ=0.1). Inter-rater reliability was moderate for tongue coating (Gwet AC2 range 0.49-0.55), and fair for color and other features of the tongue body (Gwet AC2=0.34). CONCLUSIONS: Taken together, our study has shown that tongue images collected via smartphone contain some reliable features, including tongue coating, that can be used in mHealth analysis. Our findings thus support the use of smartphones in telemedicine for detecting changes in tongue coating.