某医学中心药师对民众用药安全教育的经验交流

为推广正确用药知识,提升民众用药安全核心能力,使药品发挥治疗效果并避免药品使用不当产生不良后果,台湾地区某一大型综合医院药剂科药师通过成立"正确用药教育资源中心",联合各级药学会、学校、社区、公共平台等资源,让医院药师走出医院,走进校园、社区、公共场所等,借助活动、宣传、科普教育等方式,2014-2015年共举办114场,参与人数达到14 140人次,活动满意度达98.5%。藉此模式除提升民众正确用药的核心能力,同时可建构用药安全网,并充分发挥医院药师的工作价值。     

Decrease in bispectral index prior to cardiovascular collapse during Caesarean sections

We report a case of significant reduction in bispectral index (BIS) associated with suspected amniotic fluid embolism (AFE) that occurred prior to change in haemodynamic variables. The patient was a 29‐year‐old nulliparous, who was admitted for Caesarean section under general anaesthesia in the 33rd week of pregnancy. After the baby was born, the BIS value suddenly decreased to 0, with suppression ratio of 100. One minute later, saturation decreased abruptly to 85%, end‐tidal carbon dioxide (EtCO₂) decreased to 5 mmHg, peak inspiratory pressure increased to 35 cm H₂O, and non‐invasive blood pressure (BP) failed to obtain a reading. After administration of vasoactive drugs, the systolic BP was maintained at 100 mmHg or higher, the BIS value rose to 10–20, and the EtCO₂ increased to 24–33 mmHg. In this case, the BIS monitoring may provide an earlier warning of impending cardiovascular collapse in the case of AFE.     

POWER CALCULATION FOR A SCORE TEST IN THE DEPENDENT CENSORING MODEL

We propose a method for testing the assumption of independent censoring in right censored survival data. This method includes extra data collection by the subsequent follow-up of a subset of censored subjects. A score test statistic is derived within the framework of a Cox proportional hazards model with a time-dependent covariate. In this paper we focus on the power calculation for the score test under proportional hazards alternatives. Comparison of the observed with the theoretical power shows that the latter is somewhat lower than the former.     

TWO SAMPLE COMPARISON FOR LARGE GROUPS OF CORRELATED BINARY RESPONSES

Although there is much literature on testing the treatment effect in experiments with correlated binary outcomes, the existing methodologies only work well when the cluster size is small. In this paper, I propose a simple method to test the treatment effect in experiments with large groups of correlated binary outcomes. I use the weighted estimating equations approach to estimate the treatment effect. The proposal is appropriate under any correlation structure. Power comparisons show the advantage of the new procedure.