Objective Prognostic indicators in acute coronary syndrome (ACS) would aid in decision-making and identifying high-risk patients. The systemic immune-inflammation index (SII) has good prognostic value in many diseases; however, its use has not been reported for ACS. We aimed to determine the associations between the SII and outcomes in patients with ACS, with adjustment for confounders. Methods In this retrospective cohort study, we used the MIMIC-III (Multiparameter Intelligent Monitoring in Intensive Care) database and the eICU Collaborative Research Database. The primary outcome was 30-day mortality. Cox regression analysis was performed to determine the relationship between the SII and patient outcomes, and we conducted subgroup analysis and smooth curve fitting. Results We identified 4699 patients with ACS: 1741 women and 2949 men, mean age 82.8±29.7 years, and mean SII 72.58±12.9. For 30-day all-cause mortality, the unadjusted hazard ratio (HR) (95% confidence interval [CI]) of SII <69.4 and SII >88.8 were 1.25 (1.04, 1.50) and 1.38 (1.15, 1.65), respectively. With SII >88.8, this association remained significant after adjustment for numerous potential confounders: HR 1.27 (1.06, 1.52). A similar relationship was observed for 90-day and 1-year all-cause mortality. Conclusions SII is a promising prognostic indicator for unselected patients with ACS. This finding needs to be confirmed in prospective studies.
To meet the increasing need for clean combustion, improve the combustion efficiency of fuels, and reduce the pollutants produced in the combustion process, it is necessary to systematically study the combustion of hydrocarbon fuels. An accurate and detailed chemical kinetic model is an important prerequisite for understanding the combustion performance of hydrocarbon fuels and studying complex chemical reaction networks. Therefore, based on ReaxGen, new detailed mechanisms for the lowtemperature combustion of n-nonane are proposed and verified in detail in this study. Meanwhile, some international mainstream combustion models such as the LLNL model and the JetSurf 2.0 model are compared with ours, showing that the proposed new mechanisms can better predict the ignition delay combustion characteristics of n-nonane, and they also hold in a wide range of conditions. In addition, the numerical simulation results of the concentration curve calculated for the new mechanisms, especially Model v2, are in good agreement with the experimental data, and the mechanisms can reproduce the performance of the negative-temperaturecoefficient behavior toward n-nonane ignition. The numerical simulation results of the laminar flame propagation velocity varying with the equivalence ratio are also in good agreement with the available experimental data. Finally, the ignition delay sensitivity of nnonane is analyzed by the sensitivity analysis method; the key reactions affecting the ignition mechanism are investigated; and the reaction path analysis is conducted to better understand the models' predicted performance. In a word, the new mechanisms are helpful to understand the ignition properties of large hydrocarbon fuels for high-speed aircrafts.
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