To compare the impact of tunneled cuffed catheters (TCCs) and arteriovenous fistulas (AVFs) on outcomes in elderly hemodialysis (HD) patients. A retrospective matched cohort study was performed. Propensity score matching (PSM) was applied to balance the baseline conditions, and we compared all-cause mortality, major adverse cardiovascular and cerebrovascular events (MACCEs), hospitalization, and infection rates between AVF and TCC patients ≥70 years old. Cox survival analysis was used to analyze the risk factors for death. There were 2119 patients from our center in the Chinese National Renal Data System (CNRDS) between 1 January 2010 and 10 October 2023. Among these patients, 77 TCC patients were matched with 77 AVF patients. There was no significant difference in all-cause mortality between the TCC and AVF groups (30.1/100 vs. 33.3/100 patient-years, p = 0.124). Among the propensity score-matched cohorts, no significant differences in Kaplan-Meier curves were observed between the two groups (log-rank p = 0.242). The TCC group had higher rates of MACCEs, hospitalization, and infection than the AVF group (33.7/100 vs. 29.5/100 patient-years, 101.2/100 vs. 79.5/100 patient-years, and 30.1/100 vs. 14.1/100 patient-years, respectively). Multivariate analysis showed that high Charlson comorbidity index (CCI) score was a risk factor for death. There was no significant difference in all-cause mortality between elderly HD patients receiving TCCs and AVFs. Compared with those with a TCC, elderly HD patients with an AVF have a lower risk of MACCEs, hospitalization, and infection.

Background: Studies comparing the survival of hemodialysis (HD) and peritoneal dialysis (PD) patients are controversial. This study evaluated the impact of initial dialysis modality on the survival of patients with end-stage renal disease (ESRD) in a matched-pair cohort. Methods: A retrospective cohort study was performed on ESRD patients who initiated renal replacement treatment between January 1, 2010, and December 31, 2018. Propensity score matching was applied to balance the baseline conditions, and multivariate Cox regression analysis was applied to compare mortality between HD and PD patients and evaluate correlations between mortality and various baseline characteristics. Subgroup analysis was performed with respect to diabetes status. Results: There were 739 patients in our center in the Chinese National Renal Data System (CNRDS) between 2010 and 2018. Of these, 125 PD patients were matched with 125 HD patients. The 1-, 2-, and 3-year survival rates were 96.5%, 90.7%, and 82.5%, respectively, in the HD group and 99.5%, 97.8%, and 92.5%, respectively, in the PD group (log-rank P < 0.001). Among the propensity score-matched cohorts, no significant differences in Kaplan–Meier curves were observed between the two groups (log-rank P = 0.514). Age at dialysis initiation, CCI, congestive heart failure and cerebrovascular disease were risk factors in the multivariable-adjusted model. In subgroups defined by diabetes status, the Kaplan‒Meier survival curve showed that PD survival was significantly higher than that of HD (log-rank P = 0.022). Conclusions: HD and PD were not significantly different regarding the survival of patients with ESRD. PD was associated with better survival in diabetic ESRD patients.

Objective. To investigate the efficacy of Niao Du Kang (NDK) mixture in renal fibrosis of rats and to explore the mechanism underlying the effect of NDK on renal fibrosis. Methods. Unilateral ureteral obstruction (UUO) was used to replicate a rat renal interstitial fibrosis model. The drug‐administered groups were given 20 ml/kg (NDK‐H), 10 ml/kg (NDK‐M), and 5 ml/kg (NDK‐L) NDK mixture once a day for 21 days beginning 48 hours after surgery. The 24‐hour urine protein and serum creatinine (CR) levels in the sham group rats, UUO rats, and NDK mixture‐treated rats were measured after the last administration. The pathological changes of rat kidney tissue were observed by HE staining. The degree of fibrosis was observed by Masson’s staining and scored. The expression levels of TGF‐β, α‐SMA mRNA, and mir‐129‐5p in kidney were detected by qRT‐PCR. HK‐2 cells were treated with 5 ng/ml TGF‐β to induce HK‐2 cell fibrosis. The expression levels of TGF‐β, α‐SMA mRNA, and mir‐129‐5p in HK‐2 cells were detected by qRT‐PCR. TargetScan predicted the target gene of mir‐129‐5p, HK‐2 cells were transfected with mir‐129‐5p mimic, and an overexpressed mir‐129‐5p HK‐2 cell model was constructed. qRT‐PCR was used to detect the expression of PDPK1 mRNA. Western blot was used to detect the expression of PDPK1, AKT, and p‐AKT in HK‐2 cells induced by TGF‐β and in UUO rats. Results. NDK mixture significantly reduced the 24‐hour urine protein and CR levels of UUO rats. HE staining showed that the NDK mixture group exhibited a significantly reduced degree of renal interstitial fibrosis. NDK mixture also reduced the expression of TGF‐β and α‐SMA, and the middle‐dose group showed a better therapeutic effect. In vitro studies showed that NDK mixture‐containing serum increased the expression of mir‐129‐5p to reduce renal fibrosis. In addition, NDK mixture increased the expression of mir‐129‐5p in vivo. Further studies indicated that mir‐129‐5p could target PDPKl to reduce its expression. The NDK‐containing serum group also exhibited reduced expression of PDPK1. Conclusion. NDK mixture can significantly improve renal function and improve renal fibrosis in UUO model rats. Furthermore, NDK mixture can inhibit the expression of PDPK1 by upregulating the expression of mir‐129‐5p and then inhibiting the PI3K/AKT pathway to improve renal fibrosis.

The pursuit of clinical effectiveness in real-world settings is at the core of clinical practice progression. In this study, we address a long-term clinical efficacy evaluation decision-making problem with temporal correlation hybrid attribute characteristics. To address this problem, we propose a novel approach that combines a temporal correlation feature rough set model with machine learning techniques and nonadditive measures. Our proposed approach involves several steps. First, over the framework of granular computing, we construct a temporal correlation hybrid information system, the gradient method is employed to characterize the temporal attributes and the similarity between objects is measured using cosine similarity. Second, based on the similarity of gradient and cosine, we construct a composite binary relation of temporal correlation hybrid information, enabling effective classification of this information. Third, we develop a rough set decision model based on the Choquet integral, which describes temporal correlation decision process. We provide the ranking results of decision schemes with temporal correlation features. To demonstrate the practical applications of our approach, we conduct empirical research using an unlabeled dataset consisting of 3094 patients with chronic renal failure (CRF) and 80,139 EHRs from various clinical encounters. These findings offer valuable support for clinical decision-making. Two main innovations are obtained from this study. First, it establishes general theoretical principles and decision-making methods for temporal correlation and hybrid rough sets. Second, it integrates data-driven clinical decision paradigms with traditional medical research paradigms, laying the groundwork for exploring the feasibility of data-driven clinical decision-making in the field.