Studies of evidence-based medicine have provided much important evidence, clarified problems, and guided the clinical practice in the treatment of renal diseases. As examples, several therapeutic problems in renal hypertension, renal anemia and low protein diet for the patients with chronic kidney disease are discussed in this paper.
ObjectiveTo observe whether proteinuria is relate to the decline of residual renal function (RRF) in peritoneal dialysis (PD) patients. MethodsThis is a prospective cohort study including 45 PD patients (underwent PD between January 2011 and January 2013) with a 12-month follow-up. All the patients were divided into 2 groups with respect to the initial proteinuria level: massive proteinuria group A (n=20) and non-massive proteinuria group B (n=25) at baseline. We established regression models to do univariate analysis and multivariate analysis of the relationship between the decline of RRF≥50% of baseline and the indices of age, sex, PD-associated peritonitis, baseliner residual glomerular filtration rate (rGFR), initial proteinuria, and use of ACEI/ARB. ResultsThe primary outcome (RRF>50% of baseline) at 12 months was 65% in group A, and 80% in group B (P<0.05). Based both on the results of univariate and multivariate Cox regression analysis, non-massive proteinuria and higher rGFR at baseline were factors to protect RRF from decline (P<0.05). ConclusionThe study demonstrates that massive proteinuria and lower rGFR at baseline may be associated with a rapid decline of RRF in PD patients. Treatment aimed at reducing albuminuria may lead to protect RRF and improve life quality of patients.
Objective To explore the hormone medication compliance in children with chronic kidney disease (CKD) and analyze its influencing factors. Methods Between May and December 2013, 96 children were investigated by questionnaires about medication compliance when they were out of the hospital. Then we analyzed the influencing factors for medication compliance. All the data were analyzed by SPSS 19.0 software. Results Of these 96 children, medication nonadherence accounted for 52% (50). The main guardian, educational level of the father, educational level of the mother, residence, duration of illness, time of hospitalization, and understanding of the treatment plan played significant roles in causing different medication compliance among these children (P＜0.05). Logistic regression analysis showed that duration of illness [OR=2.204, 95%CI (1.253, 3.875), P=0.006], residence [OR=2.615, 95%CI (1.0 23, 6.687), P=0.045] and the mother’s educational level [OR=0.147, 95%CI (0.028, 0.788), P=0.025] were the independent factors for medication compliance. Conclusions According to the survey, hormone medication compliance in children with chronic kidney disease is not satisfying. We should strengthen the health education in children and their parents, and adopt specific interventions to enhance the medication compliance so as to effectively control the disease and delay the progression.
The incidence of chronic kidney disease is increasing worldwide, which greatly increases the risk of end-stage renal disease. It is particularly important to find out the risk factors for the development and progression of chronic kidney disease. Whether gender is a risk factor for the progression of kidney disease remains controversial with inconsistent results in human cohort studies with diabetic or non-diabetic kidney disease. In most of the studies, women seem to exhibit certain gender advantages. Sex hormones, renal hemodynamics and lifestyle differences may play an important role. The underlying mechanism of gender affecting the progression of kidney disease deserves further exploration. This article reviews the gender differences and possible mechanisms in diabetic and non-diabetic chronic kidney disease, in order to provide reference for future research.
Objective To develop and validate a prediction model to assess the risk of depression in patients with chronic kidney disease (CKD) based on National Health and Nutrition Examination Survey (NHANES) database. Methods Data on patients with CKD were selected from the NHANES between 2005 and 2018. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio for model development and validation, respectively. Multivariable logistic regression was used in the training set to identify independent risk factors associated with depression in CKD patients, with stepwise selection applied to determine the final predictors. Model performance was assessed using receiver operating characteristic curve (ROC), calibration plots, and decision curve analysis (DCA). Internal validation was performed through bootstrap resampling, and a predictive model was ultimately established. Results A total of 4413 CKD patients were included, including 2112 males (47.86%) and 2301 females (52.14%). Among them, 3089 patients were assigned to the training set and 1324 to the validation set. In the training set, 332 patients (10.75%) presented with depressive symptoms, while 143 patients (10.80%) in the validation set had depressive symptoms. Multivariate logistic regression analysis showed that other hispanic, current smoking, and sleep disorders were risk factors (P＜0.05). Male, middle or high-income, high school grad/ged or above, married or widowed were protective factors (P＜0.05). Finally, 7 variables were included to construct a prediction model, including gender, poverty income ratio, education level, marital status, smoking status, body mass index, and sleep disorders. The ROC curve showed that the AUC=0.773 [95% confidence interval (0.747, 0.799)] in the training set, the internal validation was evaluated by 1000 Bootstrap resampling methods, and the corrected C-index=0.763. The validation set AUC=0.778 [95% confidence interval (0.740, 0.815)], showed good discrimination ability. The calibration curve showed that the model’s predicted probability was highly consistent with the actual occurrence. Decision curve analysis showed that the model provided a significant net benefit for clinical decision-making at a threshold probability of 20%～50%. Conclusions The prediction model constructed in this study can effectively predict the risk of depression in patients with CKD and can provide guidance for early screening and personalized intervention for high-risk groups. However, the external validation and localization of the model still needed further research.
Objective To evaluate the application effect of quality control circle (QCC) in improving the number of cases received in the follow-up management of chronic kidney disease (CKD). Methods The outpatient and inpatient CKD patients who were filed in the CKD follow-up management center of West China Hospital of Sichuan University from March 10 to October 10, 2020 were selected. We analyzed the reasons that affected CKD patients’ willingness to file by carrying out QCC, improved the case collection by establishing standardized processes, broadened the collection channels, established a collective team, strengthened training management and education of CKD patients and their families, so as to increase the number of cases received in CKD follow-up management. Then, we observed the score of active ability of QCC members before and after this activity. Results After the implementation of QCC activities, the number of follow-up cases increased from 8 per month to 15 per month. The target achievement rate was 140%, and the progress rate was 87.5%. The ability of all circle members in the evaluation indicators of team training has been improved. Conclusions QCC activity can effectively improve the number of cases received in CKD follow-up management. It is helpful for the medical staff to provide better disease management for CKD patients.
The number of clinical practice guidelines for traditional Chinese patent medicine has been increasing recently. However, the quality of guidelines was still low compared to international guidelines. Considering the characteristics of traditional Chinese patent medicine, we suggested the following items should be taken into account when developing traditional Chinese patent medicine guidelines: ensuring the standardized guidelines of traditional Chinese patent medicine research problem is scientific based on reliable evidence; identifying the common questions according to these research problems; understanding the strength of evidence and how to recommend correctly; inviting some experts in other fields to take part in the development of guidelines; paying more attention on the changes of disease burden and the impact of new methods and technologies when developing the guideline; paying more attention to the non-consensus opinions and evidence supporting these opinions; insisting on quality is the priority, while speed is secondary.
Chronic kidney disease (CKD) has become an important public health problem that seriously affects the physical and mental health of Chinese people. Nutritional therapy has become one of the important treatments for CKD. Domestic and international guidelines for CKD clinical nutrition therapy have been introduced, and the intake of various nutrients in CKD patients, especially protein intake, has been guided. In recent years, with the continuous development of nutrition assessment and treatment, the content of the guidelines has gradually improved, but some views are still controversial. This article explains the relevant guidelines for the treatment of CKD at home and abroad to provide reference for the clinical nutritional treatment of CKD patients.
Chronic kidney disease (CKD) has become a global public health problem because of its high prevalence, low awareness, poor prognosis, and high medical costs. Effective follow-up management can facilitate timely adjustment of the treatment of the CKD patients and delay the disease progression. The application of internet of things (IoT) technology in dynamic monitoring and telemedicine is helpful for the self-management of patients with chronic diseases, and can provide convenient, intelligent, and humanized medical and health services. In the future, with the rapid growth of demands of CKD management and innovations in information technology, new medical IoT industry will accelerate the intelligent development of CKD management. Multi-disciplinary and multi-industrial collaboration should be promoted to solve current challenges, such as evaluation of actual effectiveness, the system design and construction, and the accessibility of intelligent healthcare services, to ensure that IoT products can improve clinical outcomes, reduce medical expenditure, and lower disease burden.