[Validation of a hyperkalemia prediction model in chronic kidney disease]

Objective: To validate the accuracy and consistency of a previously established prediction model for the occurrence of hyperkalemia in non-dialytic chronic kidney disease (CKD) patients. Methods: All patients diagnosed with CKD from Outpatient Department of Shanghai Changzheng Hospital during the 4th quarter of 2020 were recruited. Demographic data, clinical characteristics and prediction model-related parameters of the patients were collected and analyzed. Receiver operating characteristic (ROC) curve was drawn to evaluate the effectiveness of the model, and the specificity and sensitivity were calculated based on the cut-off value of 4 obtained from the previous model. The improved Hanley method was used to compare the area under the curve (AUC) between the previously established model and current validation dataset. The calibration curve was drawn to verify the model calibration degree. Results: A total of 434 patients diagnosed with non-dialytic CKD were enrolled, among whom 233 were males and 201 were females, with an average age of (55±16) years. According to the measured serum potassium values, the prevalence of hyperkalemia was 7.6%. And 33 patients were allocated to the hyperkalemia group and 401 patients were to the normal potassium group. There was no significant difference in age and sex between the two groups (both P>0.05). A combination of hyperkalemia and heart failure (27.3% vs 3.7%, P<0.001), diabetes (42.4% vs 19.7%, P=0.002), and acidosis (51.5% vs 7.0%, P<0.001) were more frequently in the hyperkalemia group, compared with the normal serum potassium group. Patients in the hyperkalemia group were more likely to have a past history of serum potassium ≥5.0 mmol/L (48.5% vs 2.5%, P<0.001). For the drugs that could increase serum potassium levels, there was a significant correlation between Chinese herbal medicine and the occurrence of hyperkalemia, while renin-angiotensin-aldosterone system inhibitor (RAASi) and potassium supplementation showed no significant difference between the two groups. The results of ROC curve analysis showed that the AUC was 0.914, with the sensitivity of 84.8% and the specificity of 79.8% with the cut-off value of 4. The difference of AUC between the previously established risk assessment model of hyperkalemia in patients with non-dialytic CKD and current validation dataset was not statistically significant (Z=1.924, P=0.054), indicating the good accuracy and consistency of the prediction model. In the calibration curve, when the predicted risk of patients was below 0.4 or above 0.6, the prediction effect of the model was better. Conclusion: The previously-constructed hyperkalemia prediction model in non-dialytic CKD patients had good accuracy and consistency, and could be used to evaluate the risk of hyperkalemia in all stages of non-dialytic CKD patients.

[Development of a hyperkalemia risk assessment model for patients with chronic kidney disease]

Objective: To investigate risk factors for hyperkalemia among chronic kidney disease (CKD) patients and establish a risk assessment model for predicting hyperkalemia events. Methods: Clinical data of CKD patients (stage 3 to 5) hospitalized between May 2017 and June 2020 from 14 hospitals were retrospectively collected and divided into training dataset and validation dataset through balanced random sampling. Multivariate logistic regression analysis was used to analyze risk factors for hyperkalemia in CKD patients and the factors were scored. Receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. Meanwhile, the cut-off value with the best sensitivity and specificity were used to verify the accuracy of the model in validation dataset. Results: A total of 847 CKD patients were enrolled and further divided into training dataset (n=675) and validation dataset (n=172). There were 555 males and 292 females, with a mean age of (57.2±15.6) years. Multivariate logistic regression analysis showed that age, CKD stage, history of heart failure, history of serum potassium ≥5.0 mmol/L, diabetes, metabolic acidosis, and use of medications that increase serum potassium levels were risk factors for causing hyperkalemia in patients with CKD. Risk assessment model was established based on these risk factors. The AUC of the ROC curve was 0.809. Using 4 as the cut-off value, the sensitivity and specificity for predicting hyperkalemia events reached 87.1% and 57.0%, respectively. Conclusion: The model established in the current study can be used for predicting hyperkalemia events in clinical practices, which offers a new way to optimize serum potassium management in patients with CKD.

LncRNA TUG1 inhibits the proliferation and fibrosis of mesangial cells in diabetic nephropathy via inhibiting the PI3K/AKT pathway

OBJECTIVE

To elucidate the potential function of long non-coding RNA (lncRNA) TUG1 in the progression of diabetic nephropathy (DN) and the underlying mechanism.

MATERIALS AND METHODS

Rat diabetes mellitus (DM) model was established by streptozocin (STZ) administration. In vivo levels of TUG1 and relative genes in the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway in DM rats and control rats were determined by the quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Moreover, levels of kidney weight, 24 h-urine protein, blood urea nitrogen and serum creatinine in DM rats and controls were detected. Mesangial cells were subjected to induction of high-level glucose. Relative levels of TUG1 and relative genes in the PI3K/AKT pathway in mesangial cells were determined as well. Through Cell Counting Kit-8 (CCK-8) and 5-Ethynyl-2'-deoxyuridine (EdU) assay, the regulatory effect of TUG1 on the proliferative ability of mesangial cells induced with high-level glucose was evaluated. Finally, expression changes in the PI3K/AKT pathway and extracellular matrix (ECM)-related genes in mesangial cells were determined.

RESULTS

TUG1 was downregulated in DM rats and mesangial cells induced with high-level glucose. Compared with controls, DM rats presented higher levels of kidney weight, 24 h-urine protein, blood urea nitrogen and serum creatinine, which were markedly reduced after TUG1 overexpression in vivo. Moreover, overexpression of TUG1 downregulated TGF-β1, FN, and COL-IV, and inhibited the activation of the PI3K/AKT pathway.

CONCLUSIONS

TUG1 is downregulated in DN. The overexpression of TUG1 could suppress the proliferation and ECM accumulation of mesangial cells via inhibiting the PI3K/AKT pathway.

Urgent-start peritoneal dialysis and patient outcomes: a systematic review and meta-analysis

OBJECTIVE

The present study was aimed at illustrating short- or long-term patient outcome among individuals with urgent-start peritoneal dialysis (PD) compared with those with conventional PD.

MATERIALS AND METHODS

We searched the PubMed, EMBASE, Cochrane Controlled Trials Register and China National Knowledge Infrastructure databases. Cohort studies were investigated comparing the effects of urgent start of PD (<14 days after catheter insertion) to those of conventional start of PD (≥14 days after catheter insertion). Risks of bias across studies were evaluated using Newcastle-Ottawa Quality Assessment Scale. We calculated the pooled risk ratios and mean differences with 95% confidence intervals for dichotomous data and continuous data, respectively.

RESULTS

Six studies involving 1,242 patients were identified. Compared with conventional PD, urgent-start PD was not associated with a high mortality (RR: 1.25, 95% CI: 0.92 to 1.69; I2=0%, p=0.99) and a higher prevalence of overall mechanical complications (RR: 1.79, 95% CI: 0.85 to 3.78; p=0.12; I2=64%, p=0.02). However, urgent-start PD was associated with a higher prevalence of leakage (RR: 6.72, 95% CI: 2.11 to 21.32; I2=0%, p=0.60). In terms of infectious complications, data analysis of the fixed-effects model showed no difference between the two groups. (RR: 1.36, 95% CI: 0.90 to 2.05, p=0.14), regardless of peritonitis (RR: 1.36, 95% CI: 0.90 to 2.05, p=0.14; I2=0%, p=0.70) or other infections (RR: 1.15, 95% CI: 0.49 to 2.69, p=0.99; I2=0%, p=0.75).

CONCLUSIONS

Urgent-start PD was not associated with a higher risk of mortality and dialysis-related complications. However, compared with conventional PD, an urgent start of PD may increase the risk of a leak.

Induction treatment of proliferative lupus nephritis with leflunomide combined with prednisone: a prospective multi-centre observational study

To evaluate the efficacy and safety of leflunomide in the treatment of proliferative lupus nephritis, a prospective multi-centre observational study was conducted. Patients with biopsy proven proliferative lupus nephritis were assigned to receive either leflunomide or cyclophosphamide with concomitant prednisone. Leflunomide was given orally with a loading dose of 1 mg/kg/day for 3 days followed by 30 mg/day. Intravenous cyclophosphamide was administered monthly at a dose of 0.5 g/m2 of body-surface area. A total of 110 patients were enrolled, 70 in the leflunomide group and 40 in the cyclophosphamide group. The complete remission rate in the leflunomide group was 21% and partial remission rate 52%, as compared with 18% and 55%, respectively, in the cyclophosphamide group. Renal parameters and systemic lupus erythematosus disease activity index improved significantly and similarly in both groups. Serum creatinine decreased or stabilized in both treatment groups. No significant difference was noted with respect to clinical outcome between groups. Repeat biopsy also showed a significant reduction of active lesions in kidney pathology after 6 months of leflunomide treatment. Major adverse events, similar in both treatment groups, included infection, alopecia and hypertension. Leflunomide, compared with cyclophosphamide, in combination with prednisone was effective in the induction therapy of proliferative lupus nephritis and was generally well-tolerated.