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.

Developing and validating a prognostic prediction model for patients with chronic kidney disease stages 3-5 based on disease conditions and intervention methods: a retrospective cohort study in China.

OBJECTIVES: To develop and validate a nomogram model to predict chronic kidney disease (CKD) stages 3-5 prognosis. DESIGN: A retrospective cohort study. We used univariate and multivariate Cox regression analysis to select the relevant predictors. To select the best model, we evaluated the prediction models' accuracy by concordance index (C-index), calibration curve, net reclassification index (NRI) and integrated discrimination improvement (IDI). We evaluated the clinical utility by decision curve analysis. SETTING: Chronic Disease Management (CDM) Clinic in the Nephrology Department at the Guangdong Provincial Hospital of Chinese Medicine. PARTICIPANTS: Patients with CKD stages 3-5 in the derivation and validation cohorts were 459 and 326, respectively. PRIMARY OUTCOME MEASURE: Renal replacement therapy (haemodialysis, peritoneal dialysis, renal transplantation) or death. RESULTS: We built four models. Age, estimated glomerular filtration rate and urine protein constituted the most basic model A. Haemoglobin, serum uric acid, cardiovascular disease, primary disease, CDM adherence and predictors in model A constituted model B. Oral medications and predictors in model A constituted model C. All the predictors constituted model D. Model B performed well in both discrimination and calibration (C-index: derivation cohort: 0.881, validation cohort: 0.886). Compared with model A, model B showed significant improvement in the net reclassification and integrated discrimination (model A vs model B: NRI: 1 year: 0.339 (-0.011 to 0.672) and 2 years: 0.314 (0.079 to 0.574); IDI: 1 year: 0.066 (0.010 to 0.127), p<0.001 and 2 years: 0.063 (0.008 to 0.106), p<0.001). There was no significant improvement between NRI and IDI among models B, C and D. Therefore, we selected model B as the optimal model. CONCLUSIONS: We constructed a prediction model to predict the prognosis of patients with CKD stages 3-5 in the first and second year. Applying this model to clinical practice may guide clinical decision-making. Also, this model needs to be externally validated in the future. TRIAL REGISTRATION NUMBER: ChiCTR1900024633 (http://www.chictr.org.cn).

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.

Validity, reliability, and application of the electronic version of a chronic kidney disease patient awareness questionnaire: a pilot study.

OBJECTIVES: A questionnaire which provides desirable reliability and validity has been previously developed to assess the disease awareness of diagnosed chronic kidney disease (CKD) patients. However, conventional paper questionnaires often have disadvantages, including recall bias. To substantially improve this, we therefore aimed to explore the feasibility of developing a smartphone-based electronic version (e-version) based upon its original paper version and subsequently tested its validity, reliability, and applicability. METHODS: A pilot study was conducted at Guangdong Provincial Hospital of Chinese Medicine in Guangzhou, China, during August 2019. The e-version had identical content to the paper version and was adapted in terms of layout and assisted functions via the Wechat-incorporated Wen-Juan-Xing platform. Eligible patients with diagnosed CKD were invited to participate and were assigned the e-version. Randomly selected respondents received a test-retest of the same e-version 2 weeks after their first completion. In some instances, psychometric properties, including validity and reliability of the e-version, were examined. In others, its clinical application was also tested, which included comparisons among the clinical profiles of patients who had/had not responded to the questionnaire as well as patients with above or below average questionnaire scores. RESULTS: Of the 225 patients screened, 217 were enrolled to participate, with a response rate of 52.5%. Desirable reliability (Cronbachα = 0.962, ICC for total scores = 0.948), while good convergent validity (Cronbachα = 0.962) and low discriminant validity (one extracted component), of the e-version were detected. Performing inter-group comparisons highlighted statistical differences in terms of higher education level (z = -2.436, P = 0.015) and earlier CKD stages (z = -1.978, P = 0.048), with these patients often preferring to respond. No significant differences were detected in the clinical profiles between respondents who obtained an above or below average questionnaire score. CONCLUSION: The e-version is reliable but was not shown to be a valid approach. Audiences with higher education levels and less advanced disease condition may prefer to respond to the e-version. Adaptation of this e-questionnaire, from its original paper version, may not be a direct transition and meticulous modifications may be required during the transition process. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR1900024633).

The lattice reconstruction of Cs-introduced FAPbI1.80Br1.20 enables improved stability for perovskite solar cells.

Inorganic-organic hybrid perovskite solar cells (PSCs) have stirred up a new research spree in the field of photovoltaics due to its high photoelectric conversion efficiency and simple preparation process. In recent years, the research of inorganic-organic hybrid PSCs has been widely reported, among which FA+/Cs+ PSCs are especially outstanding. However, there are few reports explaining the lattice structural change mechanism of Cs x FA1-x PbI1.80Br1.20 PSCs from the view of chemical bonds. In this work, a facile method of 15% Cs+ cations partially substituting FA+ cations has been presented to enhance the structural stability and photovoltaic performances of FAPbI1.80Br1.20 PSCs. The partial incorporation of Cs+ in FAPbI1.80Br1.20 resulted in a more beneficial tolerance factor and inhibited the deep defect state of elemental Pb. More importantly, it inhibited the phase transition from the cubic black α-phase to the hexagonal yellow δ-phase of FAPbI1.80Br1.20. Moreover, the power conversion efficiency (PCE) of Cs0.15FA0.85PbI1.80Br1.20 PSCs achieved a substantial improvement. The stability also achieved a remarkable promotion, which was demonstrated by X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Nuclear Magnetic Resonance (NMR). These analyses indicate that 15% Cs+ can induce the lattice shrinkage, reduce the specific traps and inhibit the phase transition, thus improving the structural stabilities of Cs0.15FA0.85PbI1.80Br1.20 PSCs under atmosphere and calefaction. These results provide an effective way for fabricating stable and efficient inorganic-organic perovskite solar cells with promising properties.

α-CsPbI3 Nanocrystals by Ultraviolet Light-Driven Oriented Attachment.

Size and crystallinity of building units in the perovskite layer are of great significance to photovoltaic performance. Thus, to fabricate large-grain-size perovskite materials with the advantage of good crystallinity is quite necessary. The oriented attachment strategy has been proofed as an efficient method to control crystal growth. Herein, we reported on oriented attachment of α-CsPbI3 quantum dots (QDs) into a large-grain-size nanocrystal under moderate ultraviolet (UV) light. By virtue of atomic-resolution TEM and X-ray absorption fine structure (XAFS) spectroscopy, we observed the UV-directed structure-evolution and growth process. This is trigged by UV-light illumination (7 W, 365 nm), which drives the oriented assembly of QDs into a large nanoparticle along {110} facets. Moreover, we also visualized a damage process of the α-CsPbI3 QDs to photoinactive-δ-phase ones and finally into PbI2 under high-power UV-light (100 W, 365 nm) exposure. The findings provide a prototype for fabricating large-size perovskite nanostructures with promising properties.