The teaching team of the Department of Laboratory Medicine, West China School of Medicine, Sichuan University takes scientific spirit, craftsmanship spirit, and medical humanities spirit as the goal, combines the core knowledge of clinical microbiology laboratory technology course with cases of coronavirus disease 2019 prevention and control, drug resistance monitoring, and scientists’ deeds, and adopts strategies such as hot debate and special report to achieve the integration of knowledge and value. The actual effectiveness of this model has been verified through the assessment of students’ abilities and values. This article introduces the course-based ideological and political education construction mentioned above, aiming to explore the integration path of course-based ideological and political education in the clinical microbiology laboratory technology, and construct a new teaching model that combines professional competence and value guidance.
Objective To seek the statistical solution in the comparison of different effects from multi-center randomized controlled trials （RCTs）. Methods The data collected from a multi-center RCT were used as the examples and processed by CMH test and meta-analysis. Results The result of CMH test indicated that the significant difference of the effect values existed among centers （P 〈0. 05 ）. While meta-analysis showed no significant difference （P 〉0.05 ） by heterogeneity test. However, when using fixed effect model, inter-group significant difference of merged effect values was observed （P 〈0.05 ）. Conclusions In the clinical research based on the method of multi-center RCT, met.a-analysis can be applied if the difference of inclination of the inter-group therapeutic effect is found among different centers. The proper mathematical model should be selected based on the result of heterogeneity test to merge and compare the effect values. The conclusions should be drawn from the results of both meta-analysis and CMH test.
Multilevel models are applicable to both the quantitative data and categorical variables. We used the methods, including the multilevel models, analysis of covariance and CMH chi-square test, to analyse different types of data, to explore the application of multilevel models in the analysis of the multicenter clinical trial center effect. The results showed that the analysis of covariance is more sensitive to find the center effect for quantitative data, while multilevel models are more sensitive to categorical variables. It can be seen that results with different analytical methods for center effect are not the same, and the most appropriate method should be selected in accordance with the characteristics of data, the objective of research, and the applicable conditions of the various methods in practical use.
With the dissemination and popularization of EBM around the world, the evidence-based laboratory medicine has boomed gradually. However, the substantial researches in tbe field are still inadequale now. Based on the facts of hospital laboratory medicine, this article discussed the feasibility that apply the rationale and methods to orient the laboratory quality control.
While proposing evidence-based medical decision, we analyzed the existing problems in laboratory medicine, discussed the necessity and probability and explored the practicing way of evidence-based laboratory medicine, in order to follow the latest developing of clinical medicine and provide the best clinical laboratory technique and clinical laboratory service for good patient care.
The conclusions of meta-analyses are susceptible to various of biases, and publication bias is one of such main bias. Therefore, Checking for evidence of publication bias should be undertaken routinely at the preliminary stage of a meta-analysis. Begg’s test, Egger’s test, and Macaskill’s test are usually used to objectively identify publication bias in meta-analyses. In order to conveniently use these methods, the SAS program of these three tests was designed in this paper. In order test practical data, the fact that the output of this program of SAS software was consisted with the output of STATA software was validated. So, this program is an alternative way to do such hypothesis tests to identify the publication bias in meta-analyses.
Objective To investigate an evaluation method of medical literature applicability to clinical work， and provide a convenient way for physicians to search for the best evidence. Methods Delphi method was used to choose appropriate evaluating indexes， analytic hierarchy process was performed to determine the weighing of each index， and the formula to calculate medical literature applicability was formed. The practicability of this formula was evaluated by consistency checking between the formula’s results and experts’ opinions on literature applicability. Results Five evaluating indexes were determined， including literature’s publishing year （X1）， whether the target questions were covered （X2）, sample size （X3）， trial category （X4）， and journal level （X5）. The formula to calculate medical literature applicability was Y=3.93 X1＋11.78 X2＋14.83 X3＋44.53 X4＋24.93 X5. The result of consistency checking showed that the formula’s results were highly consistent with experts’ opinions （Kappa=0.75， P＜0.001）. Conclusion The applicability formula is a valuable tool to evaluate medical literature applicability.
Objective To summarize the online practice teaching experience in laboratory medicine during the coronavirus disease 2019 (COVID-19) epidemic, and explore a new practice teaching mode of laboratory medicine which can provide a reference for improving the efficiency and quality of laboratory medicine education. Methods From June 8th, 2020 to June 30th, 2020, an online questionnaire survey was conducted in teachers and students who participated in online internship teaching and learning during the COVID-19 epidemic to evaluate the effect of online internship teaching and compare the advantages and disadvantages of online and offline internships. ResultsA total of 65 valid questionnaires were collected from 35 students and 30 teachers. There was no statistically significant difference in the satisfaction scores of intern students between online and offline internships [median (minimum, maximum): 100 (80, 100) vs. 100 (80, 100), P>0.05]. Among the teachers surveyed, 90.0% thought that the pre-teaching preparation for online internship teaching was more complicated and time-consuming, 60.0% thought that the online teaching was more difficult, and 63.3% thought that online internship could not achieve the expected results. Both the teachers and students believed that online and offline internships had their own advantages and disadvantages, and they could learn from each other. Conclusions The present online practice model cannot replace the traditional offline practice. A diversified practice model combining online and offline can help further develop and improve medical laboratory practice teaching.