Recently, there has been an increasing interest in the potential clinical use of several inflammatory indexes, namely, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic-immune-inflammation index (SII). This study aimed at assessing whether these markers could be early indicators of pulmonary hypertension (PH) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). A total of 185 patients were enrolled in our retrospective study from January 2017 to January 2019. Receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to evaluate the clinical significance of these biomarkers to predict PH in patients with AECOPD. According to the diagnostic criterion for PH by Doppler echocardiography, the patients were stratified into two groups. The study group consisted of 101 patients complicated with PH, and the control group had 84 patients. The NLR, PLR, and SII values of the PH group were significantly higher than those of the AECOPD one (p < 0.05). The blood biomarker levels were positively correlated with NT-proBNP levels, while they had no significant correlation with the estimated pulmonary arterial systolic pressure (PASP) other than PLR. NLR, PLR, and SII values were all associated with PH (p < 0.05) in the univariate analysis, but not in the multivariate analysis. The AUC of NLR used for predicting PH was 0.701 and was higher than PLR and SII. Using 4.659 as the cut-off value of NLR, the sensitivity was 81.2%, and the specificity was 59.5%. In conclusion, these simple markers may be useful in the prediction of PH in patients with AECOPD.
The smart substation communication network is the basis for information sharing of various devices in the substation. Its operation status has an important impact on the safe operation of the substation and even the power grid. Therefore, real-time status monitoring of the smart substation communication network is becoming more and more important. Aiming at the problems of single dimension, insufficient real-time performance and manual fault analysis in existing substation communication network state monitoring technology, this paper proposes a method of smart substation communication network state monitoring and fault prediction based on network communication quality. This paper uses switch ACL technology and coloring technology to obtain communication quality indexes such as bandwidth utilization, delay, and packet loss rate in real time; based on a multi-dimensional evaluation algorithm, a comprehensive evaluation model of network communication quality is constructed; the model of the relationship between abnormal network communication quality and failures is established. Finally, real-time monitoring of network communication quality and fault prediction are realized. The application analysis in a typical 110 kV substation shows that this method can effectively evaluate the network communication quality and accurately predict failures, and can guide operationer and maintenaner to quickly restore the normal operation of the communication network.
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