Acute respiratory distress syndrome is a clinical syndrome caused by many reasons, which is characterized by intractable hypoxemia. Its etiology is complex and its mortality is high. Lung biopsy techniques can give accurate histopathological diagnosis to such patients to guide treatment and improve prognosis. At present, lung biopsy techniques include surgical lung biopsy, transbronchial lung cryobiopsy, transbronchial lung biopsy and percutaneous lung biopsy. The diagnostic rate of surgical lung biopsy is high, but it is traumatic and difficult to implement. The diagnostic rate of transbronchial cryobiopsy is relatively high, and the complications are acceptable. Transbronchial lung biopsy is minimally invasive but the diagnostic rate is low. The diagnostic rate of percutaneous lung biopsy is relatively high, and the complications are relatively few. For patients with acute respiratory distress syndrome who need lung biopsy, it is very important to choose different surgical procedures according to their effectiveness, safety and applicability.
Randomized controlled trials (RCTs) are often limited because of ethical or operational reasons. Quasi-experimental studies could be an alternative to RCTs to make causal inferences without randomization by controlling the confounding effects of the study. This paper introduced the general statistical analysis methods of quasi-experimental design through basic ideas, characteristics, limitations and applications in medicine, including difference-in-difference models, instrumental variables, regression discontinuity design, interrupted time series, and so on, and to provide references for future research.
Objective To elaborate on the statistical analysis methods for evaluating the accuracy of imaging diagnostic tests in a multiple-reader multiple-case (MRMC) design through formula derivation and real cases. Methods This study consisted of two parts: theoretical derivation and a real case study. The theoretical part discussed in detail the principles and procedures of MRMC statistical analysis methods, particularly the Obuchowski-Rockette (OR) and Dorfman-Berbaum-Metz (DBM) methods. The real case included 100 subjects, of whom 67 had disease. Four readers interpreted all the cases based on both traditional film imaging methods and digital imaging methods. OR and DBM methods were employed for data analysis. Results The real case showed that the OR and DBM methods had a high degree of consistency, with only slight differences in the confidence intervals. Conclusion It is recommended to use the OR and DBM methods for the statistical analysis of imaging diagnostic test accuracy, ensuring that the impact of reader factors on the evaluation results is fully considered. The results from the OR and DBM methods are relatively similar; when applying these methods in practice, one should consider the specific characteristics of the data and the research design to choose the appropriate analysis method. Besides, there are still challenges when applying the OR and DBM methods, such as software implementation and missing data handling, which require further exploration.
ObjectiveTo explore two methods of sample size estimation in multi-reader multi-case study of radiological diagnostic test and realize them by software. MethodsDemonstration programs were conducted in R software using the Van Dyke dataset, calculating combinations of readers and cases using the OR and DBM methods. These serve as pilot test results for multi-reader multi-case studies, providing a reference for parameter settings in subsequent formal experiments. ResultsWhen the effect size was 0.044, 6 readers and 247 cases could yield 0.80 power, while with an effect size of 0.088, only 6 readers and 44 cases were needed to reach 80.5% power. The sample sizes calculated using the OR method and the DBM method were consistent, and the same sample size calculation results could be obtained through conversion between the two methods. ConclusionFor the estimation of sample size in multi-reader multi-case studies, R software provides a convenient and mature software package for sample size estimation using multi-reader multi-case designs in radiological diagnostic tests, thereby offering a reference for selecting appropriate sample size estimation and statistical analysis methods in radiological diagnostic tests.
ObjectiveTo understand the distribution characteristics and nosocomial infection of carbapenem-resistant Enterobacteriaceae (CRE) in a general hospital of traditional Chinese medicine, so as to provide the evidence for control and management of multidrug-resistant bacteria.MethodsData of CRE in the first Affiliated Hospital of Anhui University of Traditional Chinese Medicine were analyzed retrospectively from 2014 to 2018.ResultsThe total detection rate of CRE was 10.76%, 5.58%, 15.42%, 12.94% and 16.18% from 2014 to 2018, respectively. The detection rate of CRE showed a gradual upward trend (χ2=29.940, P<0.001). The highest number of CRE isolated from clinical specimens was sputum (355 strains, 63.39%), and the next were urine (98 strains, 17.50%) and secretions (38 strains, 6.79%). CRE isolated from different clinical departments were mainly in Neurosurgery Department (172 stains, 30.71%), Intensive Care Unit (Internal Medicine) (145 strains, 25.89%), Intensive Care Unit (Surgery)(106 strains,18.93%), and other internal medical departments (83 strains, 14.82%). A total of 179 patients developed CRE nosocomial infection in the past 5 years, who were mainly male, and with advanced age, long hospital stay, basic diseases, abnormal immune function and invasive operation. The incidence of hospital infection with CRE from 2014 to 2018 were 0.31‰, 0.38‰, 0.89‰, 0.80‰ and 1.14‰, respectively, which also showed a gradual upward trend (χ2=25.111, P<0.001).ConclusionWith the increasing number of clinically isolated CRE strains and the increasing incidence of nosocomial infection of CRE, effective intervention measures should be taken to prevent and control CRE.
