Objective To evaluate the diagnostic value of all diagnostic tests detecting the ethambutol resistance in Mycobacterium tuberculosis. Methods PubMed, EMbase, Chinese Biomedical Database (CBM), Chinese Scientific Journals Full-Text Database (CSJD), and Chinese Journal Full-text Database (CJFD) were searched, and QUADAS items were used to evaluate the quality of included studies. Meta-disc software was used to handle data from included studies. Such index as sensitivity, specificity, and SROC were applied to assess the diagnostic value of individual diagnostic test. Results Nine studies were included. The results of meta-analyses showed that compared with proportion method, the summary sensitivity, summary specificity, positive likelihood ratio, negative likelihood ratio, and SROC area under curve of a nitrate reductase assay were 92%, 99%, 30.50, 0.13, and 0.975 2, respectively, while compared with BACTEC 460 TB, the above mentioned indexes of BACTEC MGIT 960 System were 92%, 99%, 6.27, 0.11, and 0.9, respectively. Bacteriophage biological amplification method revealed relative good analysis effectiveness on MB/BacT. Conclusion According to the results, it is recommended that nitrate reductase assay can replace proportion method as screening test of ethambutol resistance in Mycobacterium tuberculosis, and BACTEC MGIT 960 System can replace BACTEC 460 as final diagnostic test of ethambutol resistance in Mycobacterium tuberculosis.
Extraction and analysis of electroencephalogram (EEG) signal characteristics of patients with autism spectrum disorder (ASD) is of great significance for the diagnosis and treatment of the disease. Based on recurrence quantitative analysis (RQA)method, this study explored the differences in the nonlinear characteristics of EEG signals between ASD children and children with typical development (TD). In the experiment, RQA method was used to extract nonlinear features such as recurrence rate (RR), determinism (DET) and length of average diagonal line (LADL) of EEG signals in different brain regions of subjects, and support vector machine was combined to classify children with ASD and TD. The research results show that for the whole brain area (including parietal lobe, frontal lobe, occipital lobe and temporal lobe), when the three feature combinations of RR, DET and LADL are selected, the maximum classification accuracy rate is 84%, the sensitivity is 76%, the specificity is 92%, and the corresponding area under the curve (AUC) value is 0.875. For parietal lobe and frontal lobe (including parietal lobe, frontal lobe), when the three features of RR, DET and LADL are combined, the maximum classification accuracy rate is 82%, the sensitivity is 72%, and the specificity is 92%, which corresponds to an AUC value of 0.781. The research in this paper shows that the nonlinear characteristics of EEG signals extracted based on RQA method can become an objective indicator to distinguish children with ASD and TD, and combined with machine learning methods, the method can provide auxiliary evaluation indicators for clinical diagnosis. At the same time, the difference in the nonlinear characteristics of EEG signals between ASD children and TD children is statistically significant in the parietal-frontal lobe. This study analyzes the clinical characteristics of children with ASD based on the functions of the brain regions, and provides help for future diagnosis and treatment.
Postoperative gastrointestinal disorder (POGD) is a common complication after surgery under anesthesia. Strategies in combination with traditional Chinese medicine and Western medicine have shown some distinct effects but standardized clinical practice guidelines are not available. Thus, a multidisciplinary expert team from various professional bodies including the Perioperative and Anesthesia Professional Committees of the Chinese Association of Integrative Medicine (CAIM), jointly with Gansu Province Clinical Research Center of Integrative Anesthesiology/Anesthesia and Pain Medical Center of Gansu Provincial Hospital of Traditional Chinese Medicine and WHO Collaborating Center for Guideline Implementation and Knowledge Translation/Chinese Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) Center /Gansu Provincial Center for Medical Guideline Industry Technology/Evidence-based Medicine Center of Lanzhou University was established to develop evidence-based guidelines. Clinical questions (7 background and 12 clinical questions) were identified through literature reviews and expert consensus meetings. Based on systematic reviews/meta-analyses, evidence quality was analyzed and the advantages and disadvantages of interventional measures were weighed with input from patients’ preferences. Finally, 20 recommendations were developed through the Delphi-based consensus meetings. These recommendations include disease definitions, etiologies, pathogenesis, syndrome differentiation, diagnosis, and perioperative prevention and treatment.