Abstract:Our intent is to examine the predictive role of Charlson comorbidity index (CCI) on mortality of patients with type 2 diabetic nephropathy (DN). Based on the CCI score, the severity of comorbidity was categorized into three grades: mild, with CCI scores of 1-2; moderate, with CCI scores of 3-4; and severe, with CCI scores ≥5. Factors influencing mortality and differences between groups stratified by CCI were determined by logistical regression analysis and one-way analysis of variance (ANOVA). The impact of CCI on mortality was assessed by the KaplanMeier analysis. A total of 533 patients with type 2 DN were enrolled in this study, all of them had comorbidity (CCI score >1), and 44.7% (238/533) died. The mortality increased with CCI scores: 21.0% (50/238) patients with CCI scores of 1-2, 56.7% (135/238) patients with CCI scores of 3-4, and 22.3% (53/238) patients with CCI scores ≥5. Logistical regression analysis showed that CCI scores, hemoglobin, and serum albumin were the potential predictors of mortality (P<0.05). One-way ANOVA analysis showed that DN patients with higher CCI scores had lower levels of hemoglobulin, higher levels of serum creatinine, and higher mortality rates than those with lower CCI scores. The Kaplan-Meier curves showed that survival time decreased when the CCI scores and mortality rates went up. In conclusion, CCI provides a simple, readily applicable, and valid method for classifying comorbidities and predicting the mortality of type 2 DN. An increased awareness of the potential comorbidities in type 2 DN patients may provide insights into this complicated disease and improve the outcomes by identifying and treating patients earlier and more effectively.
Radio Frequency Identification (RFID) technology not only offers tracking capability to locate equipment, supplies and people in real time, but also provides efficient and accurate access to medical data for health professionals. However, the reality of RFID adoption in healthcare is far behind earlier expectation. This study reviews literature on the use of RFID in healthcare/hospitals following a formal innovation-decision framework. We aim to identify the common applications, potential benefits, barriers, and critical success factors. Our study facilitates quick assessment and provides guidance for researchers and practitioners in adopting RFID in medical arenas. Many earlier adopters in healthcare found RFID to be functional and useful in such areas as asset tracking and patient identification. Major barriers to adoption include technological limitations, interference concerns, prohibitive costs, lack of global standards and privacy concerns. Better designed RFID systems with low cost and privacy issues addressed are needed to increase acceptance of RFID in healthcare.
Although conventional cryptographic security mechanisms are essential to the overall problem of securing wireless networks, these techniques do not directly leverage the unique properties of the wireless domain to address security threats. The properties of the wireless medium are a powerful source of domain-specific information that can complement and enhance traditional security mechanisms. In this paper, we propose to utilize the fact that the radio channel decorrelates rapidly in space, time and frequency in order to to establish new forms of authentication and confidentiality that operate at the physical layer and can be used to facilitate cross-layer security paradigms. Specifically, for authentication services, we illustrate two channel probing techniques that can be used to verify the authenticity of a transmitter. Similarly, for confidentiality, we examine several strategies for establishing shared secrets/keys between two communicators using the wireless medium. These strategies range from extracting keys from channel state information, to utilizing the channel variability to secretly disseminate keys. We then validate the feasibility of using physical layer techniques for securing wireless systems by presenting results from experiments involving the USRP/GNURadio software defined radio platform.
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