Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-05-04 Cooperative journals: 《中国全科医学》
Abstract： Background Early reperfusion therapy for acute myocardial infarction（AMI） is an effective approach to reduce mortality in AMI patients. Percutaneous coronary intervention（PCI） is one of the reperfusion therapy modalities，and contrast-induced acute kidney injury（CI-AKI） after PCI has become one of the common causes of AKI. Objective To investigate the risk factors for the development of CI-AKI in AMI patients after PCI，establish a risk prediction model for CI-AKI based on risk factors and evaluate its validity. Methods The clinical data of 1 274 patients who attended the Affiliated Hospital of Xuzhou Medical University diagnosed of AMI and treated with PCI were collected consecutively from 2019 to 2021. According to the chronological order of admission，the included patients were divided into the training group （January 2019 to March 2021，900 cases） and validation group（April 2021 to December 2021，374 cases） in a ratio of approximately 7：3；and divided into the CI-AKI and non-CI-AKI groups according to the diagnostic criteria of CI-AKI. Independent risk factors were screened using univariable Logistic regression analysis，Lasso regression，cross-validation，multivariable Logistic regression analysis，and a nomogram for predicting the risk of CI-AKI was plotted. Their discriminatory power，calibration ability，and clinical application value were evaluated by calculating concordance statistic（C-statistic），plotting calibration curve and decision curve. Results Among the 900 patients in the training group，109 patients（12.1%） developed CI-AKI after PCI；among the 374 patients in the validation group，27 patients（7.2%） developed CI-AKI. Multivariable Logistic regression analysis showed that LVEF〔OR=0.903，95%CI（0.873，0.934）〕，platelet distribution width〔OR=1.158，95%CI（1.053，1.274）〕，MPVLR〔OR=1.047，95%CI（1.016，1.079）〕，NHR〔OR=1.072，95%CI（1.021，1.124）〕，Scr〔OR=1.006，95%CI（1.002，1.011）〕，and diuretics〔OR=2.321，95%CI（1.452，3.709）〕 were independent influencing factors for CI-AKI after PCI in AMI patients（P<0.05）. A prediction model containing 6 risk factors of LVEF，platelet distribution width，MPVLR，NHR，Scr and diuretics was constructed and a nomogram for predicting the risk of CI-AKI was plotted. The C-statistic was 0.794〔95%CI（0.766，0.820）〕 for the training group and 0.799〔95%CI（0.774，0.855）〕 for the validation group，and the calibration plots showed good consistency between the predicted and actual results；the decision curve and clinical impact curve showed clinical application value of nomogram. Conclusion The CI-AKI risk prediction model including LVEF，platelet distribution width，MPVLR，NHR，Scr，and diuretics has good discrimination and accuracy，which can intuitively and independently screen high-risk population and has high predictive value for the development of CI-AKI after PCI in AMI patients.
Subjects: Dynamic and Electric Engineering >> Electrical Engineering submitted time 2022-10-11
Abstract： The temporary overvoltage (TOV) during fault recovery process of renewable energy system seriously restricts the development of renewable energy. However, the existing research lacks quantitative indicators of the TOV. Therefore, based on the mechanism of TOV, this paper proposes a method to quantify the TOV risk of multiple renewable energy station system (MRESS) considering the reactive power saturation characteristic. Firstly, based on the TOV mechanism of MRESS, the analysis model under different factors during fault recovery is established, and then the rationality of TOV assessment based on phasor model is demonstrated. After fully considering the saturation characteristics of converters after fault and the interaction between renewable energy generators, an evaluation method for TOV of MRESS is derived. Through analyzing the relationship between TOV of the system and short-circuit ratio, the temporary overvoltage short-circuit ratio (TOVSCR) of MRESS and its application method are proposed. Simulation results show that the proposed method can effectively evaluate the TOV risk and safety margin of the MRESS.
Peer Review Status:
Awaiting Review
Hits
Hits
Downloads
Comment