目的通过对全国无偿献血者血费返还现状调查,分析全国无偿献血者用血费用返还总体发展趋势。方法对全国采供血机构血费返还标准、资金来源情况,献血者本人及亲属返还比例及金额进行调查分析。结果采供血机构全血返还标准主要集中在(200-...目的通过对全国无偿献血者血费返还现状调查,分析全国无偿献血者用血费用返还总体发展趋势。方法对全国采供血机构血费返还标准、资金来源情况,献血者本人及亲属返还比例及金额进行调查分析。结果采供血机构全血返还标准主要集中在(200-240)元/200 m L之间(94.65%),其中75%为220元/200 m L,而红细胞返还标准以(200-230)元/U之间最多(87.93%),机采血小板血费返还标准主要集中在1400元/治疗量(占61.28%),血浆返还标准主要集中在40元/100 m L(占50.44%)。全国采供血机构无偿献血者及其他亲属用血后的血费返还人次和返还金额均逐年递增。其中返还金额中80.74%为献血者亲属用血。血费返还金来源主要为机构自筹(56.81%)。结论随着无偿献血深入开展,享受用血返还政策的人数可能会持续增长,目前国内返还标准和政策差异较大,资金来源主要依靠机构自筹,血费返还主要用于亲属互助用血。展开更多
Objective This study aimed to explore the mortality prediction of patients with cerebrovascular diseases inthe intensive care unit(ICU)by examining the important signals during different periods of admission in theICU...Objective This study aimed to explore the mortality prediction of patients with cerebrovascular diseases inthe intensive care unit(ICU)by examining the important signals during different periods of admission in theICU,which is considered one of the new topics in the medical field.Several approaches have been proposed forprediction in this area.Each of these methods has been able to predict mortality somewhat,but many of thesetechniques require recording a large amount of data from the patients,where recording all data is not possiblein most cases;at the same time,this study focused only on heart rate variability(HRV)and systolic and diastolicblood pressure.Methods The ICU data used for the challenge were extracted from the Multiparameter Intelligent Monitoring inIntensive Care II(MIMIC-II)Clinical Database.The proposed algorithm was evaluated using data from 88 cerebrovascular ICU patients,48 men and 40 women,during their first 48 hours of ICU stay.The electrocardiogram(ECG)signals are related to lead II,and the sampling frequency is 125 Hz.The time of admission and time ofdeath are labeled in all data.In this study,the mortality prediction in patients with cerebral ischemia is evaluated using the features extracted from the return map generated by the signal of HRV and blood pressure.Topredict the patient’s future condition,the combination of features extracted from the return mapping generatedby the HRV signal,such as angle(𝛼),area(A),and various parameters generated by systolic and diastolic bloodpressure,including DBPMax−Min SBPSD have been used.Also,to select the best feature combination,the geneticalgorithm(GA)and mutual information(MI)methods were used.Paired sample t-test statistical analysis was usedto compare the results of two episodes(death and non-death episodes).The P-value for detecting the significancelevel was considered less than 0.005.Results The results indicate that the new approach presented in this paper can be compared with other methodsor leads to better results.The best combinatio展开更多
文摘目的通过对全国无偿献血者血费返还现状调查,分析全国无偿献血者用血费用返还总体发展趋势。方法对全国采供血机构血费返还标准、资金来源情况,献血者本人及亲属返还比例及金额进行调查分析。结果采供血机构全血返还标准主要集中在(200-240)元/200 m L之间(94.65%),其中75%为220元/200 m L,而红细胞返还标准以(200-230)元/U之间最多(87.93%),机采血小板血费返还标准主要集中在1400元/治疗量(占61.28%),血浆返还标准主要集中在40元/100 m L(占50.44%)。全国采供血机构无偿献血者及其他亲属用血后的血费返还人次和返还金额均逐年递增。其中返还金额中80.74%为献血者亲属用血。血费返还金来源主要为机构自筹(56.81%)。结论随着无偿献血深入开展,享受用血返还政策的人数可能会持续增长,目前国内返还标准和政策差异较大,资金来源主要依靠机构自筹,血费返还主要用于亲属互助用血。
文摘Objective This study aimed to explore the mortality prediction of patients with cerebrovascular diseases inthe intensive care unit(ICU)by examining the important signals during different periods of admission in theICU,which is considered one of the new topics in the medical field.Several approaches have been proposed forprediction in this area.Each of these methods has been able to predict mortality somewhat,but many of thesetechniques require recording a large amount of data from the patients,where recording all data is not possiblein most cases;at the same time,this study focused only on heart rate variability(HRV)and systolic and diastolicblood pressure.Methods The ICU data used for the challenge were extracted from the Multiparameter Intelligent Monitoring inIntensive Care II(MIMIC-II)Clinical Database.The proposed algorithm was evaluated using data from 88 cerebrovascular ICU patients,48 men and 40 women,during their first 48 hours of ICU stay.The electrocardiogram(ECG)signals are related to lead II,and the sampling frequency is 125 Hz.The time of admission and time ofdeath are labeled in all data.In this study,the mortality prediction in patients with cerebral ischemia is evaluated using the features extracted from the return map generated by the signal of HRV and blood pressure.Topredict the patient’s future condition,the combination of features extracted from the return mapping generatedby the HRV signal,such as angle(𝛼),area(A),and various parameters generated by systolic and diastolic bloodpressure,including DBPMax−Min SBPSD have been used.Also,to select the best feature combination,the geneticalgorithm(GA)and mutual information(MI)methods were used.Paired sample t-test statistical analysis was usedto compare the results of two episodes(death and non-death episodes).The P-value for detecting the significancelevel was considered less than 0.005.Results The results indicate that the new approach presented in this paper can be compared with other methodsor leads to better results.The best combinatio
