Previous studies have revealed that ankylosing spondylitis (AS), as the progenitor of axial spondyloarthritis (AxSpA), has been characterized by the insidiously progressive nature of sacroiliitis and spondylitis. Dual-energy computed tomography (DECT) has recently been used to analyse the deposition of monosodium urate (MSU) crystals with higher sensitivity and specificity. However, it remains unclear whether the existence of the MSU crystal deposition detected by DECT at the sacroiliac joint in patients with AxSpA also is associated with the existing structural damage. Here, we performed this study to show the DECT MSU crystal deposits in AxSpA patients without coexisting gout and to ascertain the relationship between the MSU crystal deposition and the structural joint damage of sacroiliac joints. One hundred and eighty-six AxSpA patients without coexisting gout were recruited. The plain radiographs of the sacroiliac joint were obtained, along with the DECT scans at the pelvis and the clinical variables. All statistics based on the left or right sacroiliac joint damage grading (0–4) were calculated independently. Bivariate analysis and ordinal logistic regression was performed between the clinical features and radiographic grades at the sacroiliac joint. At the pelvis, large quantities of MSU crystal deposition were found in patients with AxSpA. The average MSU crystal volume at the left sacroiliac joint, the right sacroiliac joint, and the pelvis were 0.902 ± 1.345, 1.074 ± 1.878, and 5.272 ± 9.044 cm3, values which were correlated with serum uric acid concentrations (r = 0.727, 0.740, 0.896; p < 0.001). In bivariate analysis, wide clinical variables were associated with the changes in sacroiliac joint damage. Further, the AxSpA duration, BASFI score, and the volume of MSU crystal at both sides of sacroiliac joint were associated with the progress of radiographic grade at the sacroiliac joints in the ordinal logistic models (left AOR = 1.180, 3.800, 1.920; right AOR = 1.190, 3.034, 1.418; p < 0.01). Large quantities of MSU crystal deposition detected by DECT were found at the pelvis in AxSpA patients without coexisting gout. In addition to AxSpA duration and BASFI score, the MSU crystal deposition at the sacroiliac joint is associated with the progress of radiographic grade at sacroiliac joints in those patients.

The Niaodukang mixture (NDK) is a preparation known for its ability to lower serum creatine levels in individuals with chronic kidney disease (CKD) and is commonly administered at medical facilities like the Zhongshan Hospital of Traditional Chinese Medicine. The initial use of NDK was mainly to treat CKD. Our hospital frequently utilizes NDK, which consists of Rheum officinaleBaill., Salvia miltiorrhiza Bunge., Astragalus aaronii(Eig) Zohary., Carthamus tinctorius L., and Sanguisorba officinalis L., for treating patients with CKD-MBD. It has the effects of eliminating dampness and turbidity and dredging kidney collaterals. However, The impact and process of NDK in chronic kidney disease remain unknown. To determine whether microRNA-146a (miR-146a) is associated with CKD micro-inflammationand whether NDK protects against CKD micro-inflammation by modulating the miR-146a/nuclear factor kappa-B (NF-κB) signaling pathway. (1) An adenine-induced rat model of chronic kidney disease was created through the use of materials and methods. The levels of miR-146a in exosomes from plasma and ileum were determined by RT-PCR. (2) Human cloned colon adenocarcinoma (Caco-2)cellswere stimulated with lipopolysaccharide (LPS)and transfected with miR-146a mimic and inhibitor. Following that, the western blot and RT-PCR techniques were used to measure the protein and mRNA quantities of Toll-like receptor 4 (TLR4), NF-κB, and TNF receptor-associated factor 6 (TRAF6).(3) Enzyme-linked immunosorbent assay (ELISA) was used to identify serum levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor α (TNF-α). (4) Plasma exosomes were extracted, and the exosomes in intestinal tissues were extracted via ultrahigh-speed centrifugation.Negative staining electron microscopy was used to analyze the morphology of exosomes and the ultrastructure of intestinal tissue and exosomes. The particle size of the exosomes was measured using nanoparticle tracking analysis. The pathological characteristics of CKD rats included those associated with systemic micro-inflammation, which may be associated with the release of exosomes in intestinal tissue. NDK suppressed the inflammatory response in Caco-2 cells and decreased the levels of IL-1β, IL-6, and TNF-α in rats with CKD. The expression of miR-146a, which regulates inflammation, differed between plasma-derived and enterogenous exosomes in CKD rats, which may be due to stimulation of ileal exosome release into the blood. NDK effectively reduced the levels of TRAF6, NF-κB, and TLR4 in the ileum tissue of CKD rats. NDK can effectively improve micro-inflammation in CKD ratsby enhancing the release of enterogenous exosomes, thereby enhancing the release of exosome-associated miR-146a and inhibiting micro-inflammation.

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.

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.

This paper focus on a kind of managerial decision-making problem with characteristics of interactive correlation and series relation from the realistic medical problems of traditional Chinese medicine (TCM) clinical diagnosis, and constructs a model based on the Choquet integral, multi-granulation fuzzy rough sets and graph. The decision-making method has the following processes: Firstly, construct a serial rough set model for interactively associated serial decision-making information. Secondly, using the graph model, each decision path of the decision group is described, and a multi-granularity fuzzy graph model based on serial rough set is constructed. Thirdly, Multi-granularity graph information is fused by Choquet integral, and then the distribution function is introduced to describe the distribution rule of uncertain vertex set in the graph. At last, using the data of 155 patients with rheumatoid arthritis (RA) in Guangdong Provincial Hospital of Chinese Medicine, the paper gives the application principle and algorithm steps of the proposed theoretical model, verifies the scientificity and applicability of the proposal, and provides auxiliary decision support for clinical decision-making.