３ 整体流程图……
Objective To apply the method of evidence-based medicine to identify the best therapy option for an emergency patient with upper gastrointestinal hemorrhage. Methods According to time and logical sequence of clinical events, a complete decision tree was built after the following steps to find the best treatment: clear decision-making, drawing decision tree graphics, listing the outcome probability, giving appropriate values to the final outcome, calculating and determining the best strategies. Results The performance of endoscopic therapy for the patient with upper gastrointestinal hemorrhage within the first six hours had little effect on the prognosis. Interventional therapy after the failure of endoscopic therapy had less mortality than direct surgical exploration. Conclusion Making clinical decision analyses via drawing the decision tree can help doctors clarify their ideas, get comprehensive views of clinical problems, and ultimately choose the best treatment strategy for patients.
1背景早在1987年英国爱丁堡皇家医院就开始着手研究快速的治疗流程分类系统给心肌梗塞的患者所带来的时间经济效益，就此对快速流程的研究正式拉开了序幕。到了20世纪90年代初，欧洲部分医院的急诊科首先从科室角度开始迅速推广快速流程； 同时涉及麻醉方面的流程效率改革和创新逐步兴起。20世纪90年代末麻醉专业从门诊麻醉模式、手术及麻醉前干预上，开始逐步提升快速流程的综合管理能力。正是在20世纪90年代末，快速流程的理念被正式提出，在当时它还有一个名称叫做多模式康复流程。这种理念随之在欧美国家流行起来，大量的临床实践不断在进行。1994年，美国Engelman等就提出了冠状动脉旁路“fast-track recovery”的概念，并建立了一套相应的快速康复程序，通过实践发现其的确能够加快患者的术后康复、缩短住院时间。至此快速流程作为一项高效的临床运作模式被正式纳入临床具体病种的应用中。从2001年至今，心脏外科及结直肠外科的快速流程已趋于成熟，并已成功地渗透到外科领域的多个环节……
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.
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.
Guideline implementation with decision support checklist (GUIDES) aims to assist the self-reflection of evidence-based clinical decision support system (CDSS) related professionals to enhance the process monitor and continuous improvement of evidence-based CDSS. This paper interpreted the development process, target user, and assessment method of GUIDES, analyzed the practical value of GUIDES through a typical example, and then reflected on the GUIDES and current studies on evidence-based CDSS in China. It is expected to provide references for future studies.
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.
ObjectivesTo provide an overview of whether the clinical decision support system (CDSS) was effective in reducing medication error and improving medication safety and to assess the quality of available scientific evidence.MethodsPubMed, EMbase, The Cochrane Library, CBM, WanFang Data, VIP and CNKI databases were electronically searched to collect systematic reviews (SRs) on application of clinical decision support system in the medication error and safety from January, 1996 to November, 2018. Two reviewers independently screened literature, extracted data and then evaluated methodological quality of included SRs by using AMSTAR tool.g AMSTAR tool.ResultsA total of 20 SRs including 256 980 healthcare practitioners and 1 683 675 patients were included. Specifically, 16 studies demonstrated moderate quality and 4 demonstrated high quality. 19 SRs evaluated multiple process of care outcome: 9 were sufficient evidence, 6 were limited evidence, and 7 were insufficient evidence which proved that CDSS had a positive effect on process outcome. 13 SRs evaluated reported patient outcomes: 1 with sufficient evidence, 3 with limited evidence, and 9 without sufficient evidence.ConclusionsCDSS reduces medication error by inconsistently improving process of care measures and seldom improving patient outcomes. Larger samples and longer-term studies are required to ensure a larger and more reliable evidence base on the effects of CDSS intervention on patient outcomes.
Objective To summarize the classic and latest treatment techniques for localized knee cartilage lesions in clinical practice and create a new comprehensive clinical decision-making process. Methods The advantages and limitations of various treatment methods for localized knee cartilage lesions were summarized by extensive review of relevant literature at home and abroad in recent years. Results Currently, there are various surgical methods for treating localized knee cartilage injuries in clinical practice, each with its own pros and cons. For patients with cartilage injuries less than 2 cm2 and 2-4 cm2 with bone loss are recommended to undergo osteochondral autograft (OAT) and osteochondral allograft (OCA) surgeries. For patients with cartilage injuries less than 2 cm2 and 2-4 cm2 without bone loss had treatment options including bone marrow-based techniques (micro-fracture and ogous matrix induced chondrogenesis), autologous chondrocyte implantation (ACI)/matrix-induced ACI, particulated juvenile allograft cartilage (PJAC), OAT, and OCA. For patients with cartilage injuries larger than 4 cm2 with bone loss were recommended to undergo OCA. For patients with cartilage injuries larger than 4 cm2 without bone loss, treatment options included ACI/matrix-induced ACI, OAT, and PJAC. Conclusion There are many treatment techniques available for localized knee cartilage lesions. Treatment strategy selection should be based on the size and location of the lesion, the extent of involvement of the subchondral bone, and the level of evidence supporting each technique in the literature.