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Gouty arthritis (GA) is an inflammatory disease, and renal impairment may occur to varying degrees with the progress of disease. The neutrophil-to-lymphocyte ratio (NLR) is an inflammatory marker. In this study, we aimed to explore the association between NLR and renal impairment in GA.The subjects comprised 499 patients with gouty arthritis (GA) (473 men, 26 women; age range, 39-61 years old) from our hospital. They were divided into a chronic kidney disease (CKD) group (n = 206) and non-CKD group (n = 293) according to the glomerular filtration rate. Blood samples were collected during the gout flares. The differences in NLR, general data, and laboratory indexes of patients with GA between the two groups were compared, such as serum uric acid (SUA), serum creatinine (SCREA), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), high-density lipoprotein (HDL), and low-density lipoprotein (LDL).NLR (3.38 vs. 2.38 (p 0.001)) was higher in the CKD group, compared to the non-CKD group. Similarly, both SUA (527 vs. 507 (p 0.05)) and SCREA (122 vs. 87 (p 0.001)) were higher in the CKD group than in the non-CKD group. Multivariate logistic regression analysis showed that NLR (OR = 1.122, p 0.05), age, hypertension, and SUA were risk factors for CKD in patients with GA, although HDL and HGB were protective factors. The receiver operating characteristic (ROC) curve analysis indicated that the area under the curve of NLR for predicting CKD in patients with GA was 0.646 (95% CI 0.597-0.694).Our data showed that NLR might be an important potential factor for evaluating renal impairment in GA during flares.

To the existing spectrum sharing schemes in wireless-powered cognitive wireless sensor networks, the protocols are limited to either separate the primary and the secondary transmission or allow the secondary user to transmit signals in a time slot when it forwards the primary signal. In order to address this limitation, a novel cooperative spectrum sharing scheme is proposed, where the secondary transmission is multiplexed with both the primary transmission and the relay transmission. Specifically, the process of transmission is on a three-phase time-switching relaying basis. In the first phase, a cognitive sensor node SU1 scavenges energy from the primary transmission. In the second phase, another sensor node SU2 and primary transmitter simultaneously transmit signals to the SU1. In the third phase, the node SU1 can assist the primary transmission to acquire the opportunity of spectrum sharing. Joint decoding and interference cancellation technique is adopted at the receivers to retrieve the desired signals. We further derive the closed-form expressions for the outage probabilities of both the primary and secondary systems. Moreover, we address optimization of energy harvesting duration and power allocation coefficient strategy under performance criteria. An effective algorithm is then presented to solve the optimization problem. Simulation results demonstrate that with the optimized solutions, the sensor nodes with the proposed cooperative spectrum sharing scheme can utilize the spectrum in a more efficient manner without deteriorating the performance of the primary transmission, as compared with the existing one-directional scheme in the literature.