Regional cerebral oxygen saturation cerebral oxygen saturation(rScO2) monitoring by using near-infrared spectroscopy(NIRS) is a simple, sensitive, continuous and noninvasive method, which can detect the change in oxygen supply and demand. It has already draw attentions and applications during perioperative in recent years. The technique was firstly used in cardiac surgery, thereafter some studies found thoracic surgery which mostly used one-lung ventilation also was necessary to monitor rScO2. A series of studies confirmed there were correlations among perioperative adverse events and rScO2. In this paper, we reviewed the basic principle of rScO2, summarized the applications of rScO2 in cardiac and thoracic surgery, discussed the existing problems.
Objective To evaluate the effects of low-dose epinephrine on cerebral oxygen saturation (rScO2) and awakening time during one-lung ventilation (OLV) for thoracic surgery. Methods Thirty consecutive patients undergoing lobectomy from March to July 2016 in our hospital were randomly divided into an epinephrine group (n=15, 8 males and 7 females at an average age of 58.70±11.40 years) or a saline group (n=15, 7 males and 8 females at an average age of 57.00±11.40 years). They were continuously infused with 0.01 μg/(kg·min) epinephrine or saline after general induction. Hemodynamics was maintained ±20% of the baseline value. All patients were ventilated by a pressure control mode during OLV with tidal volume of 5-8 ml/kg and end-tidal carbon dioxide tension (EtCO2) of 35-45 mm Hg. Regional cerebral oxygen saturation (rScO2) was monitored using near-infrared spectroscopy (NIRS) continuously. Results Compared with the saline group, the epinephrine group had a high rScO2 during OLV, with a statisitical significance at OLV 40 min and 50 min (67.76%±4.64% vs. 64.08%±3.07%, P=0.016; 67.25%±4.34% vs. 64.20%±3.37%, P=0.040). In addition, the awakening time of patients in the epinephrine group was shorter than that of the saline group (P=0.004), and the awakening time was associated with the duration of low-dose rScO2 (r=0.374). Conclusion Continuous infusion of 0.01 μg/(kg·min) could improve the rScO2 during OLV and shorten awakening time in thoracic surgery.
With the rapid development of information technology, medical reforms in various countries are moving towards informatization, and internet medical projects have been carried out gradually. Internet hospitals, as one of the manifestations of internet medical projects, have the advantages of improving the efficiency of medical services, revitalizing and effectively sinking high-quality medical resources, and therefore has become the focus of China’s next stage of medical reform. However, internet hospitals are innovative and local products of China, leading its practices lack of domestic and foreign theoretical research, as well as experience, which results in government policies and hospital management strategies are both moving forward in groping, and the construction outcomes vary. Therefore, this article aims to analyze the comprehensive dilemmas currently confronted by internet hospitals in China in different stages of construction, operation and management based on PDCA cycle, and thus, puts forward corresponding construction thinking and analysis in a targeted manner, and proposes guidance for the further development of internet hospitals.
ObjectiveTo systematically review the qualitative research on the obstacles and promoting factors of artificial intelligence implementation in the real perioperative world. MethodsComputer searches were conducted on PubMed, CINAHL, Scopus, Web of Science, ACM Digital Library, Cochrane Library, CNKI, WanFang Data, and VIP databases to collect perioperative studies related to the clinical application of artificial intelligence. The search period was from database establishment until December 31, 2023. Based on the SPIDER model, the quality of the included literature was evaluated using the JBI Epidemiological Scale. The NASSS framework was used to integrate and analyze the qualitative factors discovered during the implementation of the perioperative artificial intelligence system, and a problem item pool was established. ResultsA total of 22 articles were included, and perioperative stakeholders mainly focused on perioperative artificial intelligence technology users such as anesthesiologists, anesthesiologists, and surgeons. The field of perioperative artificial intelligence services mainly focused on robot surgery. The JBI evaluation score was 4-8 points. The NASSS implementation factor framework consisted of 7 core themes and 27 secondary items. ConclusionIt is undeniable that perioperative artificial intelligence has a positive impact on the prognosis, medical quality, and efficiency of surgical patients. However, its clinical application will face influences from adopters, organizational structures, social culture, and other aspects, which will ultimately affect its implementation effect. The existing qualitative research on the influencing factors of perioperative artificial intelligence systems in clinical implementation has problems such as limited quantity, moderate quality, and lack of scientific research based on a systematic implementation factor framework. Conducting scientific and standardized application research will have a guiding effect on the future use of perioperative artificial intelligence and is expected to improve its final service effectiveness.
With the fast advancement of information technology and artificial intelligence, the conventional medical service model has been presented with new growth potential. Internet-based health care has become one of the unavoidable future delivery methods for diagnostic and therapeutic services. Internet-based hospitals are being deployed in medical facilities throughout. The extension of offline to online diagnosis and treatment will need new standards for the personal competency of physicians as well as new requirements for medical education and staff training. In the context of universal Internet diagnosis and treatment, research on the full-cycle training of medical talent will play a clear guiding role in the development of physicians’ skills. By evaluating the relevant literature on competence model and interviewing the behavior events of working physicians in e-hospitals, together with the real situation of current medical students and doctor training barriers, this article aims to improve the quality of remote healthcare via provide related path for enhancing the periodic medical education based on the competency variables.
This article combines researches and experiments of mild cognitive impairment (MCI) from 2005 to 2018. It makes a conclusion among psychological evaluation, imaging studies, nerve electrophysiology, neural circuit and mental models, and concludes the changes of patients with MCI, which helps to make a definite diagnosis of MCI in clinical practice. Due to the research above we can find the suitable way to improve the sensitivity and specificity of discovery of MCI, improve the predictive power of its development, and intervene potential Alzheimer’s disease effectively.