Objective To assess the quality of diagnostic studies on detecting the tuberculosis antibody to diagnose tuberculosis.Methods CBM (1978 to 2006) and VIP (1994 to 2006) were searched; any author-claimed diagnostic studies which used the dot immunogold filtration assay (DIGFA) to detect the tuberculosis antibody and to diagnose tuberculosis were included. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) was used to assess the quality of included diagnostic studies by two reviewers independently.Results Thirty-eight papers were included and assessed. We found that most of the quality items were not met with QUADAS. Most papers adopted the retrospective diagnostic case-control design. Thirty-one papers did not describe the selection criteria clearly, 18 did not describe whether all the included patients were verified by using a reference standard of diagnosis, 36 did not describe whether the index test results were interpreted without knowledge of the results of the reference standard, 37 did not report the uninterpretable/intermediate test results, and 34 did not report the withdrawals from the study.Conclusion There are few high quality studies on using DIGFA to detect tuberculosis antibody to diagnose tuberculosis.
Objective To survey and analyze the quality assessment of the included studies in the Overviews of reviews (Overviews), so as to provide methodology references for Overviews authors. Methods A computerized search was performed for collecting Overviews in The Cochrane Library (Issue 1, 2010), PubMed, EMBASE, and CBM, and the search time ended by December, 2009. Then the relevant data, such as assessment standard etc, were extracted, and the staple standards were analyzed. Results A total of 43 typical Overviews were included. Thirty-two (74.4%) of them assessed the methodology quality of the included systematic reviews with different standards, including OQAQ (34.9%/15), AMSTAR (9.1%/3), Checklist from DARE (4.6%/2), Assendelft scale (4.6%/2), Effective Public Health Practice Project standards (2.3%/1), self-formulated standards (14.0%/ 6), syntaxic standards (2.3%/1), and other standards (4.6%/2). Ten Overviews (23.6%) assessed the quality of evidence, including eight (18.6%) applied the GRADE system. Only 7 studies (16.3%) assessed the quality of evidence and applied the GRADE system as well. Conclusion The quality assessment in Overviews includes the assessment of both methodological quality and evidence quality. But most Overviews do not assess comprehensively. The methodological quality standards applied in current Overviews are numerous and no standard is acknowledged. Yet, the OQAQ and AMSTAR are applied widely and recommended because they are comprehensive and easy to be conducted. It suggests that Overviews authors should choose appropriate methodological quality assessment standards according to concrete conditions. The GRADE system is much more comprehensive and systematic than other systems, so it is recommended that Overviews authors should apply GRADE to assess the quality of evidence in their studies in order to make the study results more comprehensive and easier for clinical application.
In order to promote the effective development of hospital day surgery mode, a construction method of information management platform that meets the characteristics of day surgery mode is presented. By analyzing the business process of the day surgery mode, the system architecture of the information platform is given; according to the difficulty of the surgical scheduling, the two-stage surgical scheduling algorithm based on the ranking theory is given; by analyzing the day surgery data statistically, a multi-angle surgical index analysis module is provided. The information management of the day surgery mode has been realized, and the work efficiency has been improved. A reasonable day surgery information platform construction can help to optimize the daytime surgical procedure and promote the smooth development of day surgery.
With the change of medical diagnosis and treatment mode, the quality of medical image directly affects the diagnosis and treatment of the disease for doctors. Therefore, realization of intelligent image quality control by computer will have a greater auxiliary effect on the radiographer’s filming work. In this paper, the research methods and applications of image segmentation model and image classification model in the field of deep learning and traditional image processing algorithm applied to medical image quality evaluation are described. The results demonstrate that deep learning algorithm is more accurate and efficient than the traditional image processing algorithm in the effective training of medical image big data, which explains the broad application prospect of deep learning in the medical field. This paper developed a set of intelligent quality control system for auxiliary filming, and successfully applied it to the Radiology Department of West China Hospital and other city and county hospitals, which effectively verified the feasibility and stability of the quality control system.
ObjectiveWe constructed a real-world evidence evaluation system to provide reference for obtaining high-quality evidence in evidence-based medicine.MethodsThrough the investigation and analysis of the key factors influencing the real-world research evidence, combined with domestic and foreign literature and evaluation tools, we preliminarily constructed the indicators of the real-world evidence evaluation system, then consulted experts in related fields by the Delphi method, modified and determined the final evaluation indicators. ResultsThe indicators of the final real-world evidence evaluation system included 40 items. The recovery efficiencies of the two rounds of expert consultation were 88.2% and 100%; The expert coordination coefficients were 0.174 (P<0.001) and 0.189 (P<0.001). After the second round of consultation, the mean of Likert scale in the range of 3.73~4.93, and the coefficient of variation varied in the range of 0.05~0.21. ConclusionThe real-world evidence evaluation system constructed in this study has certain reliability and scientificity, which can provide a basis and help for the transformation of real-world research into high-quality evidence.
AMSTAR (Assessment of Multiple Systematic Reviews) is currently developed as a measurement tool with extensive application to assess the methodological quality of systematic review/meta-analysis. It has good reliability, validity, and responsibility, and has been widely applied. This paper introduces AMSTAR to researchers and users in China, in view of development procedure, assessment items, and application status.
ObjectivesTo assess the methodological quality of clinical practice guidelines of cervical cancer in China published from 2014 to 2018.MethodsCNKI, WanFang Data, CBM, VIP, Medlive.cn, the National Guideline Clearinghouse, PubMed, The Cochrane Library and EMbase were searched for cervical cancer clinical practice guidelines published in China from January 1st, 2014 to December 31st, 2018. Four reviewers searched and selected the literature independently according to the inclusion and exclusion criteria and assessed the methodological quality of the included guidelines by using AGREE Ⅱ.ResultsA total of 9 guidelines were included. The average score for each area was: scope and purpose 75.47%, stakeholders’ involvement 35.09%, the rigor of development 43.70%, clarity of presentation 87.74%, applicability 80.76%, and editorial independence 0%.ConclusionsThe quality of cervical cancer clinical practice guidelines in China requires further improvement.
Objective To evaluate the quality of Chinese literatures on the methodology of D-dimer diagnostic test. Method We searched CNKI (1994 to 2006) and CBM (1978 to 2006) for articles involving the diagnostic tests of D-dimer for coagulation disorders. Result A total of 63 relevant articles were retrieved and 7 were included in our review. Only one of these provided useful data on two two table for the evaluation of diagnostic accuracy. Conclusions Few studies on the diagnostic tests of D-dimer have been performed and publ ished in China, all of poor quality. Further studies should focus on clinical diagnostic sensitivity and specificity, so as to provide more valuable information for readers.
Focusing on research quality is a crucial aspect of modern evidence-based medical practice, providing substantial evidence to underpin clinical decision-making. The increase in real-world studies in recent years has presented challenges, with varying quality stemming from issues such as data integrity and researchers’ expertise levels. Although systematic reviews and meta-analyses are essential references for clinical decisions, their reliability is contingent upon the quality of the primary studies. Making clinical decisions based on inadequate research poses inherent risks. With the lack of a specialized tool for evaluating the quality of real-world studies within systematic reviews and meta-analyses, the Gebrye team has introduced a new assessment tool - QATSM-RWS. Comprising 5 modules and 14 items, this tool aims to improve real-world research evaluation. This article aims to elaborate on the tool’s development process and content, using this tool to evaluate a published real-world study as an example and providing valuable guidance for domestic researchers utilizing this innovative tool.
Objective To investigate the benefits of using a stapler tractor in the treatment of segmental bronchus during lung segmentectomy through detailed video replay analysis of surgical procedures. Methods We collected data from patients who underwent segmentectomy performed by the same surgical team in the Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, from November 2020 to August 2023. After excluding data that lacked analysis parameters, the remaining patients were divided into four groups based on the methods used for dissociating segmental bronchus: a stapler tractor group (group A), a stapler with bronchial stretching group (group B), a stapler only group (group C), and a silk ligature group (group D). Then, we compared baseline data and videotaped surgical details across all groups. Surgical details included the success rate of one-time segmental bronchus dissociation and severance, the time taken for successful one-time dissociation and severance of the segmental bronchus, the incidence of bleeding during bronchus dissociation, the conversion rate to thoracotomy during surgery, and surgical outcomes such as total operative time, postoperative hospitalization days, postoperative thoracic drainage volume, and pulmonary air leakage rate. Results The study included 325 patients (203 in the group A, 62 in the group B, 29 in the group C, and 31 in the group D). There was no statistically significant difference in baseline data among the four groups. However, significant differences were found in terms of total operation time, postoperative hospitalization days, intraoperative blood loss, segmental bronchial stump length, postoperative air leakage rate, hemorrhage rate during segmental bronchial dissociation, and conversion to thoracotomy rate among the four groups (P<0.05). ConclusionUsing a stapler tractor for dissociating segmental bronchus in lung segmentectomy results in shorter operative time, less risk of intraoperative bleeding, and less surgical complications. This study provides valuable evaluation methodologies through the analysis of video replay surgical details, contributing to the improvement of lung segmentectomy quality.