Factors associated with red blood cell transfusion among hospitalized patients: a cross-sectional study / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

Red blood cell (RBC) transfusion is a clinically effective therapy in anemia, for example in patients with malignancies (Shander et al., 2020), bleeding (Odutayo et al., 2017), and preoperative anemia (Padmanabhan et al., 2019). The past few decades have witnessed a shortage of blood for transfusion due to limited health insurance coverage for blood use and the rapid expansion of hospitals (Chen et al., 2011; Shi et al., 2014). Blood donation levels may easily be affected by general changes in the environment, policy, major events such as disasters, and public sentiment (Hu et al., 2019). Meanwhile, the transfusion of allogeneic RBC is a double-edged sword, increasing the possibility of infectious and immunological complications, and also leading to higher morbidity and mortality after transfusion (Frank et al., 2012). Considering that the continual shortfall has been increasingly prominent, identifying the factors associated with RBC transfusion could help blood transfusion departments to improve their supply of blood products as well as their inventory management (O'Donnell et al., 2018).

Predictive study on school absences due to illness with seasonal exponential smoothing method / 中华疾病控制杂志

Objective To establish a suitable exponential smoothing prediction model for school absentees due to illness, to discuss its application value for predicting school absences due to illness, and to provide a basis for early warning of absence due to illness. Methods Numbers of schools absences by year and month due to illness in 30 primary schools from November 2015 to June 2017 were collected from symptom monitoring system of border county, southern Yunnan and Simple seasonal model, Winters addition model and Winters multiplication model were used to build simulation. The data of July 2017 to December 2017 were used for model validation. The three models were overall compared and evaluated through indicator analysis, statistical analysis and residual diagram analysis. The best model was selected to predict school absences due to illness from January 2018 to March 2018. Results Simple seasonal model, Winters addition model and Winters multiplication model were used to fit the variation trend of number of school absences due to illness in time series. The root mean square error (RMSE) of three models were 445.11, 420.99 and 258.75; R2adj were 0.72, 0.72 and 0.77; R2 were 0.92, 0.93 and 0.98; P values of Ljung-Box Q were 0.54, 0.43 and 0.21. As for prediction method linear trend, Alpha were 0.999, 1.000 and 0.298. The average relative error between predicted value and actual value was 9.62%, 21.90% and 7.52%. Conclusion Winters multiplication model has practical value to predict school absence due to illness and provide scientific basis for early identification of abnormal signals.

Trends of reported human brucellosis cases in mainland China from 2007 to 2017: an exponential smoothing time series analysis

BACKGROUND@#The main objective of this study was to describe the temporal distribution of monthly reported human brucellosis cases in mainland China and develop an appropriate time series model for short-term extrapolation forecast.@*METHODS@#Surveillance data of the monthly reported human brucellosis cases occurring from April 1, 2007, to March 31, 2017, in mainland China were obtained. The spectrum analysis was first adopted to find the cyclic and seasonal features, the existence of the seasonality and trend was determined by exponential smoothing method and the seasonal-trend decomposition. The candidate models of exponential smoothing included the additive model and multiplicative model; R was selected as the indicator for the selection of candidate model, and the stability of the model was verified by adjusting the training data and test data set. Finally, the extrapolations of monthly incident human brucellosis cases in 2017 were made.@*RESULTS@#From April 1, 2007, to March 31, 2017, a total of 435,108 cases of Brucellosis occurred in mainland China were reported, with an average of 3626 cases per month and a standard deviation of 1834 cases. The R of the exponential smoothing method that based on additive model increased steadily from 0.927 to 0.949 with the increase of the data volume. Ten of 12 actual values fell in the confidence interval of predicted value.@*CONCLUSIONS@#Human brucellosis cases peaked during the months from March to August in mainland China, with clear seasonality. The exponential smoothing based on the additive model method could be effectively used in the time series analysis of human brucellosis in China. Control methods, such as vaccination, quarantine, elimination of infected animals, and good hygiene within the production cycle, should be strengthened with paying more attention to the seasonality. Further research is warranted to explore the drivers behind the seasonality.

Factors Influencing the Risk of Death among Patients with Heart Failure.

The purpose of this study was to investigate the impact of risk factors on the death of patients with heart failure in a cohort of patients hospitalized with heart failure disease. In this paper we used chisquare tests with the aim of studying the relationship of each factor with survival. Generalized Additive Models (GAM), particularly Generalized Additive Logistic Regression Model, was used to examine the impact of risk factors on the death of patients with heart failure out of 263 patients considered in the analysis, 18.6% patients died of heart failure. A death proportion for female was 19.6% and that of male patients was 17.5%. From the GAM analysis the predictors: age, anemia, Tuberculosis, HIV status, renal inefficiency, diabetes, hypertension and sinus were found to significantly affect the death status of a patient. Being older age, anemic, renal inefficient, TB positive, HIV positive, diabetic, hypertensive and sinus positive increase the risk of death of a heart failure patient.

Estimation of Occurrence Peaks of Adverse Events Using Hazard Functions / 薬剤疫学

Objective : The incidence rate is used frequently in drug safety assessment. The incidence rate of adverse events is defined as the number of patients experiencing a certain adverse event divided by the number of patients administered a drug in spite of duration of administration (observation). In post-marketing surveillance, the duration of administration (observation) typically differs by patient and most of the analyses fail to take into account the differences in duration of administration (observation). Therefore, we investigated the usefulness of hazard functions in a drug safety assessment using the interim results from Clinical Experience Investigation of the oral anticancer drug, TS-1.<BR>Methods : About three thousand patients with gastric cancer were enrolled in this Clinical Experience Investigation. TS-1 was administrated orally twice daily. One course consisted of consecutive administration for 28 days and 14 days rest. Administration was repeated in two courses. Hematological measurements, stomatitis, anorexia, nausea/vomiting, diarrhea, malaise were analyzed. Adverse events were evaluated in accordance with the criteria of the Japan Society for Cancer Therapy, which were established based on criteria established by the WHO. Time to occurrence of an adverse event was calculated from the first day of administration until the adverse event was first observed. Hazard functions were estimated by smoothing methods using kernel functions.<BR>Results : The occurrence of adverse events using smoothed hazard functions had one peak around 10 days in the first course and decreased by administration rest. With the resumption of administration, the occurrence increased again. The occurrence in the second course were less than that of the first course.<BR>Conclusion : The occurrence peaks of adverse events were estimated graphically by smoothed hazard functions. We conclude that hazard functions are useful as an analytical tool in drug safety assessment.