Objective To investigate evidence retrieval, appraisal, and reevaluation during evidence-based clinical decision making in China. Also, to analyze the related factors, so as to find the problems in the course of evidence-based clinical decision making and put forward corresponding solutions. Methods We searched Chinese Biomedical Literature Disc (CBM) and China Journal Full-text Database (Medical sciences) of the China National Knowledge Infrastructure (CNKI) to collect clinical evidence-based case reports. Relevant information was extracted from these reports by a selfdesigned investigation form.Then statistical analyses were performed. Results The search tools used in the course of evidence-based clinical decision making varied. The most frequently used were MEDLINE/PubMed (82.08%) and The Cochrane Library (60.38%). 30.63% of evidence-based case reports described the search strategy in detail, and 9.01% described how they modified their search strategy. All doctors evaluated the association between evidence and disease, but few of them integrated patient factors and relevant external factors when evaluating evidence. The scientific nature and validity of the evidence was evaluated in 74 evidence-based case reports (66.67%), and such evaluation was mainly based on the criteria of evidence grading (50.00%). Reevaluation was mentioned in 85.59% of evidence-based case reports. Conclusion In China, the application of evidence-based decision making varied in different clinical departments. Problems existed in the course of evidence retrieval, appraisal, and reevaluation. This revealed the low information diathesis level of doctors and their lack of evidence-based medicine knowledge. It is suggested that information education and evidence-based medicine education should be strengthened to improve doctors’ ability to use evidence-based clinical decision making. It is also recommended that the search tools, relevant search strategy, the modification of search strategy, and reevaluation on practice results of each case should be mentioned in evidence-based case reports.
Evidence-based dentistry has been established for more than a decade, and described as ‘the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients＇. However, Orthodontic clinicians in China still tend to base their treatment protocols on the ‘it works in my hands＇evidence provided by their peers, mainly due to their weak experience in searching and applying clinical evidences. In this article, authors are willing to share their experience with their Chinese peers, and to promote the dissemination and application of evidence-based orthodontics in clinical practice.
After the completion of a clinical trial, its conclusion generally depends on the results of statistical analysis of the main outcome, that is, whether the P-value in the hypothesis test is less than the α level of the hypothesis test, usually α=0.05. The size of the P-value indicates the sufficient degree of reason for making the hypothesis judgment, and can be interpreted as to determine whether a conclusion is statistically significant but does not involve the difference in the degree of drug effects or other effects. Fragility index, which is, the minimum number of patients required to change the occurrence of a target outcome event to a non-target outcome event from a statistically significant outcome to a non-significant outcome, can be used to assist in understanding of clinical trial statistical inference results and assisting in clinical decision making This paper discusses the concept, calculation method and clinical application of the fragility index, and recommends that the fragility index be routinely reported in all future randomized controlled trials to help patient clinicians and policymakers make appropriate and optimal decisions.
Artificial intelligence (AI) is reshaping evidence-based clinical decision-making. From the perspective of clinical decision-making, this paper explores the collaborative value of AI in life-cycle health management. While AI can enhance early disease screening efficiency (e.g., medical image analysis) and assist clinical decision-making through personalized health recommendations, its reliance on non-specialized data necessitates the development of dedicated AI systems grounded in high-quality, specialty-specific evidence. AI should serve as an auxiliary tool to evidence-based clinical decision-making, with physicians’ comprehensive judgment and humanistic care remaining central to medical decision-making. Clinicians must improve the reliability of decision making through refining prompt design and cross-validating AI outputs, while actively participate in AI tool optimization and ethical standard development. Future efforts should focus on creating specialty-specific AI tools based on high-quality evidence, establishing dynamic guideline update systems, and formulating medical ethical standards to position AI as a collaborative partner for physicians in implementing life-cycle health management.
ObjectiveBased on the clinical data of patients with foot and ankle deformities in the QIN Sihe Orthopaedic Surgery Database, to analyze the characteristics and treatment strategies of foot and ankle deformities, and provide a basis for clinical decision-making. Methods A total of 22 062 patients with foot and ankle deformities who received orthopedic surgery between May 25, 1978 and December 31, 2020 were searched in the QIN Sihe Orthopedic Surgery Database. The gender, age at operation, regional distribution, etiology, type of deformity, operation method, postoperative fixation method, and other information were collected. Results Among the 22 062 patients, there were 13 046 males (59.13%) and 9 016 females (40.87%); the age at operation ranged from 1 to 77 years, with a median of 17 years, and 20 026 cases (90.77%) were aged 5 to 40 years. The patients came from 32 provinces, municipalities, and autonomous regions across the China and 5 countries including India and the United States, et al. The etiology and diseases type covered 154 kinds (of which sequelae of poliomyelitis, cerebral palsy, spina bifida and tethered spinal cord, congenital equinovarus foot, post-traumatic foot and ankle deformity, and Charcot-Marie-Tooth disease accounted for the highest proportion). The types of deformities included varus foot, equinus foot, valgus foot, talipes calcaneus, equinocavus, high arched foot, claw toe, and flail foot. Surgical methods included tendon lengthening, soft tissue release, tendon transposition, osteotomy orthopedics, and ankle arthrodesis. The 36 620 operations were performed, including 11 561 cases of hip, knee, and lower leg operations to correct the foot and ankle deformities. Postoperative fixation methods included Ilizarov external fixator in 2 709 cases (12.28%), combined external fixator in 3 966 cases (17.98%), and plaster or brace fixation in 15 387 cases (69.74%). ConclusionMale patients with foot and ankle deformities account for a large proportion, and the population distribution is mainly adolescents, with a wide distribution of regions, causes and diseases, and talipes equinovarus and varus foot are the main types of deformities. Foot and ankle deformities are often combined with deformities of other parts of the lower limb, which requires a holistic treatment concept. The application of foot soft tissue and bone surgery combined with Ilizarov external fixator and combined external fixators provides a guarantee for the correction of complex foot and ankle deformities.
The analysis of big data in medical field cannot be isolated from the high quality clinical database, and the construction of first aid database in our country is still in the early stage of exploration. This paper introduces the idea and key technology of the construction of multi-parameter first aid database. By combining emergency business flow with information flow, an emergency data integration model was designed with reference to the architecture of the Medical Information Mart for Intensive Care III (MIMIC-III), created by Computational Physiology Laboratory of Massachusetts Institute of Technology (MIT), and a high-quality first-aid database was built. The database currently covers 22 941 medical records for 19 814 different patients from May 2015 to October 2017, including relatively complete information on physiology, biochemistry, treatment, examination, nursing, etc. And based on the database, the first First-Aid Big Data Datathon event, which 13 teams from all over the country participated in, was launched. The First-Aid database provides a reference for the construction and application of clinical database in China. And it could provide powerful data support for scientific research, clinical decision making and the improvement of medical quality, which will further promote secondary analysis of clinical data in our country.