1.Application of SARIMA in predicting outbreaks of hospital-acquired infection in a tertiary psychiatric hospital
Mengwei ZHANG ; Hongwei WANG ; Mei GU ; Lunan XIAO
Chinese Journal of Nosocomiology 2025;35(16):2499-2503
OBJECTIVE To construct a Seasonal Autoregressive Integrated Moving Average(SARIMA)model based on the incidences of hospital-acquired infections(HAIs),and provide a reference for the prevention and control of HAI in such hospitals.METHODS The incidences of HAIs in a tertiary psychiatric hospital from Jan.2016 to Aug.2024 were collected by the Weining Hospital Infection Information Management software and paper-based HAI reporting cards.The incidence rates from 2016 to 2023 were analyzed and a SARIMA model was established.The incidence rates from Jan.to Aug.2024 were predicted,and the accuracy of the SARIMA model was evaluated based on the actual measured values.RESULTS From 2016 to 2023,a total of 98,075 patients were admitted,including 936 patients who developed HAIs,with an incidence rate of 0.95%ranged from 0.79%to 1.23%.The time series plot from 2016 to 2023 did not meet the requirements for sequence stability.After differ-entiating the original data,analyzing the correlation plot(ACF)and partial autocorrelation plot(PACF),and con-ducting multiple assessments and verifications,it was finally determined that SARIMA(1,1,1)(1,1,1)12,SA-RIM A(1,1,1)(1,1,0)12,ARIMA(1,1,1)(0,1,0)12,and SARIMA(1,1,1)(0,1,1)12 were the alterna-tive models.The Ljung-Box Q test was used to retain the models with P>0.05 that met the sequence with white noise and the minimum Bayesian Information Criterion(BIC)value was obtained,it was determined that SARIMA(1,1,1)(0,1,1)12 was the optimal model.When validated with Jan.to Aug.2024 HAI incidence data,the infection rates predicted by SARIMA(1,1,1)(0,1,1)12 model remained within the 95%confidence interval,indicating high prediction accuracy.CONCLUSION SARIMA model can effectively predict the monthly HAI incidences in a tertiary psychiatric hospital,and it plays an role in the decision-making of HAI prevention and control in psychiatric inpatients.
2.Application of SARIMA in predicting outbreaks of hospital-acquired infection in a tertiary psychiatric hospital
Mengwei ZHANG ; Hongwei WANG ; Mei GU ; Lunan XIAO
Chinese Journal of Nosocomiology 2025;35(16):2499-2503
OBJECTIVE To construct a Seasonal Autoregressive Integrated Moving Average(SARIMA)model based on the incidences of hospital-acquired infections(HAIs),and provide a reference for the prevention and control of HAI in such hospitals.METHODS The incidences of HAIs in a tertiary psychiatric hospital from Jan.2016 to Aug.2024 were collected by the Weining Hospital Infection Information Management software and paper-based HAI reporting cards.The incidence rates from 2016 to 2023 were analyzed and a SARIMA model was established.The incidence rates from Jan.to Aug.2024 were predicted,and the accuracy of the SARIMA model was evaluated based on the actual measured values.RESULTS From 2016 to 2023,a total of 98,075 patients were admitted,including 936 patients who developed HAIs,with an incidence rate of 0.95%ranged from 0.79%to 1.23%.The time series plot from 2016 to 2023 did not meet the requirements for sequence stability.After differ-entiating the original data,analyzing the correlation plot(ACF)and partial autocorrelation plot(PACF),and con-ducting multiple assessments and verifications,it was finally determined that SARIMA(1,1,1)(1,1,1)12,SA-RIM A(1,1,1)(1,1,0)12,ARIMA(1,1,1)(0,1,0)12,and SARIMA(1,1,1)(0,1,1)12 were the alterna-tive models.The Ljung-Box Q test was used to retain the models with P>0.05 that met the sequence with white noise and the minimum Bayesian Information Criterion(BIC)value was obtained,it was determined that SARIMA(1,1,1)(0,1,1)12 was the optimal model.When validated with Jan.to Aug.2024 HAI incidence data,the infection rates predicted by SARIMA(1,1,1)(0,1,1)12 model remained within the 95%confidence interval,indicating high prediction accuracy.CONCLUSION SARIMA model can effectively predict the monthly HAI incidences in a tertiary psychiatric hospital,and it plays an role in the decision-making of HAI prevention and control in psychiatric inpatients.
3.Preparation and Evaluation of Triptolide Self-microemulsifying Drug Delivery System
Jiawei CAO ; Jun FENG ; Xinjun CAI ; Jianjun NI ; Lunan GU ; Zhongyuan ZHOU
China Pharmacist 2017;20(4):638-642
Objective:To study the formula of triptolide (TRI) self-microemulsifying drug delivery system (SMEDDS) and evaluate the pharmaceutical properties.Methods:The formula and preparation process of triptolide self-microemulsion were screened by the solubility test and pseudo-ternary phase diagram.With the average particle size and self-microemulsifying time as the indices,the further formula optimization of triptolide self-microemulsion was carried out.The pharmaceutical properties of triptolide self-microemulsion were evaluated.Results:The optimal formula of TRI SMEDDS was as follows:the amount of medium chain triglycerides (MCT) was 20%,that of polyoxyethylene castor oil (EL-35) was 40%,and that of polyethylene glycol 400 (PEG-400) was 40% in the oil phase.The average particle size was 43.48 nm,and the time of self-microemulsification was less than 30 s.Conclusion:The average particle size and the appearance of triptolide self-microemulsion are accordance with the requirements of pharmaceutics.Triptolide self-microemulsion has good sustained-release effect,which lays foundation for the further study on pharmacodynamics.

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