内蒙古自治区二级以上医疗机构实验室开展结核病相关检测项目的调查分析

了解并评价内蒙古自治区二级以上医疗机构实验室结核病相关检测开展情况。     

Performance of Hearing Aids with an Induction Loop Amplification System: Laboratory Versus Classroom Setting

This study was designed to investigate the acoustic response of ten body-type hearing aids when used with an induction loop amplification (ILA) system in the laboratory and in the actual classroom setting. Undesirable frequency response characteristics were discovered in the classroom ILA system used in this study. These consist of a slightly poorer low-frequency response and a deep notch at about 2 500 Hz. Had the frequency response of the classroom ILA system been flat, differences between laboratory and classroom measures would have been minimized. Findings of this study support the practicality of measurement in the classroom of the operating characteristics of ILA systems     

Genotoxicity studies of glycidol fatty acid ester (glycidol linoleate) and glycidol

Glycidol fatty acid esters (GEs) are found in refined edible oils. Safety concerns have been alleged due to the possible release of glycidol (G), an animal carcinogen.     

Internal quality control: Moving average algorithms outperform Westgard rules

IntroductionInternal quality control (IQC) is traditionally interpreted against predefined control limits using multi-rules or ‘Westgard rules’. These include the commonly used 1:3s and 2:2s rules. Either individually or in combination, these rules have limited sensitivity for detection of systematic errors. In this proof-of-concept study, we directly compare the performance of three moving average algorithms with Westgard rules for detection of systematic error.MethodsIn this simulation study, ‘error-free’ IQC data (control case) was generated. Westgard rules (1:3s and 2:2s) and three moving average algorithms (simple moving average (SMA), weighted moving average (WMA), exponentially weighted moving average (EWMA); all using ±3SD as control limits) were applied to examine the false positive rates. Following this, systematic errors were introduced to the baseline IQC data to evaluate the probability of error detection and average number of episodes for error detection (ANEed).ResultsFrom the power function graphs, in comparison to Westgard rules, all three moving average algorithms showed better probability of error detection. Additionally, they also had lower ANEed compared to Westgard rules. False positive rates were comparable between the moving average algorithms and Westgard rules (all <0.5%). The performance of the SMA algorithm was comparable to the weighted algorithms forms (i.e. WMA and EWMA).ConclusionApplication of an SMA algorithm on IQC data improves systematic error detection compared to Westgard rules. Application of SMA algorithms can simplify laboratories IQC strategy.