Couinaud first proposed the naming of S9 segment of liver in 1994, and Liu Yunyi further promoted this naming in his work “Applied Anatomy of Hepatectomy and Liver Transplantation” in 2016. However, it has not been widely recognized and supported in the field of liver surgery for a long time. In recent years, due to the promotion and gradual maturity of endoscopic technology, there has been a more detailed understanding and demand for anatomy of liver and bile duct. Therefore, this article further explores the clinical value and significance of S9 segment of liver.
Objective To undertake a preliminary study of the concept and approach of patient value and preference and to learn how to understand and elicit patient preference in the light of evidence-based medicine so as to promote evidence-based practice and improve the relationship between clinicians and patients. Methods The searching key words were developed and pertinent data were retrospectively retrieved for the years of 1992-2002. MEDLINE and CBMdisc were searched along with handsearching 9 Chinese medical journals and 4 evidence-based medicine books. Data were scanned and analyzed. Results A total of 2 646 related articles were identified, most of which were found in MEDLINE (2 403), followed by CBMdisc (185) and the journals (58). Currently there is no original article to study in this field from a point of view of evidence-based medicine in China. Conclusion Patient value and preference have been emphasized in the approach of evidence-based medicine and it is a worthwhile topic for us to explore.
Lung cancer ranks among the most prevalent and lethal malignancies globally. Its prognostic outcomes are not only contingent upon tumor characteristics and therapeutic interventions but also intricately linked to the nutritional and immune profiles of patients. This article conducts a thorough review of both domestic and international research, providing a comprehensive synthesis of the prognostic value of widely investigated nutritional and immune indicators in the context of lung cancer. The primary objective is to identify optimal prognostic markers in clinical practice, offering guidance for precise post-treatment assessment and early intervention for lung cancer patients.
Blockchain is a modern technological model for concatenating transaction records (also called blocks) by means of cryptography to concatenate and protect the contents. The core of blockchain technology lies in the demand of reducing cost, improving efficiency and optimizing the industry credit environment. The role of blockchain is mainly manifested in the value increment brought by application in industrial scenarios. This paper introduces the application of blockchain technology in medical records information preservation and sharing, regional medical complex construction, protection of sensitive information of patients, improvement of industry transparency, drug authenticity tracing, improvement of medical work mode, and effective improvement of medical cost safety accounting efficiency and discusses the existing problems in the application of blockchain technology in medical care industry, aiming to provide a reference for better application of blockchain technology in medical care industry in the future.
The establishment of brain metabolic network is based on 18fluoro-deoxyglucose positron emission computed tomography (18F-FDG PET) analysis, which reflect the brain functional network connectivity in normal physiological state or disease state. It is now applied to basic and clinical brain functional network research. In this paper, we constructed a metabolic network for the cerebral cortex firstly according to 18F-FDG PET image data from patients with temporal lobe epilepsy (TLE).Then, a statistical analysis to the network properties of patients with left or right TLE and controls was performed. It is shown that the connectivity of the brain metabolic network is weakened in patients with TLE, the topology of the network is changed and the transmission efficiency of the network is reduced, which means the brain metabolic network connectivity is extensively impaired in patients with TLE. It is confirmed that the brain metabolic network analysis based on 18F-FDG PET can provide a new perspective for the diagnose and therapy of epilepsy by utilizing PET images.
M+N theory can be used as a method to improve the prediction accuracy in spectral analysis. The measured component, M kinds of non-measurement component, and N kinds of outside interference are induced into the entire measuring system, with the impact of "M" factors and "N" factors on the measurement accuracy considered systematically and comprehensively. Our human experiment system testing blood oxygen saturation based on "M+N" theory has been established. Dynamic spectrum method was used to eliminate the effects of different persons and different measuring parts which belonged to the system error of "N" factors. And then the D-value estimation was used to eliminate the effects of motion pseudo signal which belonged to the random error of "M" factors. Sixty two groups of valid data were obtained. The prediction model of blood oxygen saturation was built based on partial least squares regression method. The correlation coefficient and relative error were 0.796 8 and ±0.026 6, while the result of oximeter was 0.595 7 and relative error was ±0.076 0, respectively. The results show that the prediction accuracy of the measurement method based on the "M+N" theory is much higher than that of the oximeter.
Objective To evaluate the diagnosis of blue-on-yellow perimetry and macular threshold perimetry in early primary glaucoma. Methods Humphrey II 750 automatic perimetry was used to test 60 eyes of 60 cases in normal control group and 63 eyes of 63 cases in early primary glaucoma group with white-on-white perimetry (W/W), blue-on-yellow perimetry (B/Y)，and macular threshold perimetry (M TP). The results of the visual field defects detected by the three perimetries were compared and analyzed.Results The differences of mean sensibility of W/W, B/Y and MTP between the two groups had statistical significance［t=-3 .01, P=0.0054 (W/W); t=-2.95, P=0.006 3 (B/Y); t=-2.59,P=0. 0150 (MTP)］. In the diagnosis of early primary glaucoma, the sensitivity of MTP was the highest (83%), B/Y was the second (65%), and W/W was the lowest (48%). When B/Y and MTP were combined, the sensitivity was improved to 94% using parallel testing, and the specificity was improved to 87% using serial testing.Conclusions B/Y and MTP are valuable in diagnosis of early primary glaucoma, and the sensitivity and specificity of the diagnosis can be improved when B/Y and MTP are combined. (Chin J Ocul Fundus Dis，2003，19：102-105)
Serum marker Golgi protein 73 (GP73) is a type Ⅱ integral membrane protein located in cellular Golgi apparatus. GP73 not only processes proteins, but also participates in cell differentiation, intercellular signaling, and apoptosis. With the development of proteomics technology, GP73 has been used as a novel serum marker for detecting liver diseases. This article reviews the research progress of GP73 in the clinical diagnosis value and prognosis prediction of chronic hepatitis B in recent years, in order to provide new ideas for the diagnosis and treatment of patients with chronic hepatitis B.
Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.
Randomized double-blind controlled trials (RCTs) conduct researches in carefully selected populations to ensure results of RCTs are unaffected by external disturbances and provide evidence of safety and efficacy. Real-world researches further help to understand the real world effects of new technologies in different medical environments after-market authorization. RCTs are the evidence foundation of real-world researches, and real-world researches provide valuable complement to RCTs. Medical insurance database is one of the most important database in real-world researches. Now, China's national medical insurance is entering a new era and transits from passive payment and compensation into a value-based strategic purchase mechanism for its insured population to buy the most cost-effective services. It is necessary to establish a mature, well-organized and value-based mechanism. The core of such mechanism is values, which is the price/performance ratio of innovative medicines and technologies rather than looking at the price solely. Demonstrating innovative drug value is an essential part of health care assessment. The authors argue that the assessment of the overall value of innovative technologies or medicines should include and based on the following four dimensions: clinical value, economic value, patient value and society value.