Objective To analyze the situation of table tennis competitions in emergency public health events, find the possible weak links in the emergency rescue and care work, put forward the hospital in response to emergency public health emergency preparedness plan, health emergency drills and emergency rescue personnel training and so on targeted reference views. Methods A total of four public health emergencies such as traffic accident, mass food poisoning, fire and bird flu were selected as the theme of the competition to simulate the emergency rescue process after the emergency,the examination of each team is divided into pre-hospital disposal and hospital disposal links. Results The score of Crash in Batches was 225.13 ± 8.38, followed by Fire accident 222.78 ± 16.57, Avian Influenza 210.32 ± 11.19, Group Food poisoning 204.80 ± 6.77, the difference was statistically significant (F=8.706,P=0.000). The scores of pre-hospital treatment in all four subjects were109.04±4.80, 108.62±10.12, 98.24±6.95, 101.14± 8.85,lower than those in hospital, which were 116.09±4.79, 114.16±7.61, 106.56±5.31, 109.18±4.24, the difference was statistically significant (t=-6.130--2.338,P＜0.01 or 0.05). Conclusions On the different topics exposed in the desktop exercise competition and the differences between the pre-hospital treatment and the hospital disposal, the nursing managers should strengthen the training and practice of public health emergencies with different themes, and pay attention to the pre-hospital emergency public health emergencies training and rehearsal,the emergency response plans for public health emergencies were revised and improved through the health emergency drills.

Objective:To explore the application of effect of healthcare failure mode and effect analysis (HFMEA) in emergency waiting risk management.Methods:From May 2020 to April 2021, totally 87 902 emergency waiting patients from the First Affiliated Hospital of Anhui Medical University were assigned to control group by cluster sampling method. From May 2021 to April 2022, 80 594 emergency waiting patients were assigned to observed group. The patients in the control group received routine emergency waiting of itinerant management mode. In contrast, the patients in the observed group received emergency waiting risk management mode based on HFMEA. The process risk priority number (RPN) and waiting risk management index between two groups were compared.Results:The mean RPN of the observed group was (98.48 ± 8.27) points, significantly lower than that of the control group (251.27 ± 16.95) points. The nurses′ pre-identification rates of changes in the condition and adverse reaction in the observed group were 10.77%(8680/80 594) and 13.37%(10 775/80 594), which were higher than those in the control group, 5.77%(5072/87 902) and 8.12%(7134/87 902), the differences were statistically significant ( χ2 values were 1402.32 and 1221.66, all P<0.05). Conclusions:The application of HFMEA to optimize the emergency waiting management process can effectively reduce the risk of emergency waiting and improve the quality of emergency waiting management.

Objective: To evaluate the response of neoadjuvant chemotherapy on osteosarcoma by semi-quantitative parameters of dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI). Methods: Retrospectively analysis 25 cases of osteosarcoma confirmed by pathology.All cases received DCE-MRI scan before and after 4 cycles of neoadjuvant chemotherapy.The following semi-quantitative parameters were calculated by post-processing software: early dynamic enhancement wash-in slope (Slope), maximum signal intensity (SI_max), time to peak (TTP), signal enhanced extent (SEE), peak percent enhancement (PPE), wash out rate (WOR), enhancement rate (R). All cases were divided into good response group (tumor necrosis rate ≥90%, n=12) and non-response group (tumor necrosis rate <90%, n=13) according to the Huvos grading method. Semi-quantitative parameters of DCE-MRI before and after neoadjuvant chemotherapy between good response group and non-response group were compared by Mann-whitney U test. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the efficacy of different good response group and non-response group after neoadjuvant chemotherapy (NAC). Results: Slope, SI_max, TTP, SEE, PPE, WOR, R, TTP, WOR before and after NAC in good response group were significant different (P<0. 05), but only SI_max, SEE in non-response group. TTP, R were significant different between the above two groups before NAC, and Slope, SI_max, TTP, SEE, WOR, R were significant different after NAC (P<0.05). ROC was used to predict the diagnostic efficiency of various parameters for tumor necrosis rate after osteosarcoma NAC. It was found that the sensitivity and specificity of Slope, TTP and R parameters for predicting the response of osteosarcoma after chemotherapy were 83.3% and 92.3%, 91.7% and 69.2%, 84.6% and 75.0% respectively. The area under the curve (AUC) were 0.872 (95% CI: 0.716 to 1.027), 0.846 (95% CI: 0.685 to 1.007), 0.833 (95% CI: 0.662 to 1.004), the cut-off value were 0.032, 175 s, 5.441, Youden index were 0.756, 0.609, 0.596, respectively. Conclusions Slope, TTP, R were the most valuable semi-quantitative parameter of DCE-MRI to predict the response of NAC in osteosarcoma.