Objective To investigate the differences in the topology of functional brain networks between populations with good spatial navigation ability and those with poor spatial navigation ability. Methods From September 2020 to September 2021, 100 college students from PLA Army Border and Coastal Defense Academy were selected to test the spatial navigation ability. The 25 students with the highest spatial navigation ability were selected as the GN group, and the 25 with the lowest spatial navigation ability were selected as the PN group, and their resting-state functional MRI and 3D T1-weighted structural image data of the brain were collected. Graph theory analysis was applied to study the topology of the brain network, including global and local topological properties. Results The variations in the clustering coefficient, characteristic path length, and local efficiency between the GN and PN groups were not statistically significant within the threshold range (P>0.05). The brain functional connectivity networks of the GN and PN groups met the standardized clustering coefficient (γ)>1, the standardized characteristic path length (λ)≈1, and the small-world property (σ)>1, being consistent with small-world network property. The areas under curve (AUCs) for global efficiency (0.22±0.01 vs. 0.21±0.01), γ value (0.97±0.18 vs. 0.81±0.18) and σ value (0.75±0.13 vs. 0.64±0.13) of the GN group were higher than those of the PN group, and the differences were statistically significant (P<0.05); the between-group difference in AUC for λ value was not statistically significant (P>0.05). The results of the nodal level analysis showed that the AUCs for nodal clustering coefficients in the left superior frontal gyrus of orbital region (0.29±0.05 vs. 0.23±0.07), the right rectus gyrus (0.29±0.05 vs. 0.23±0.09), the middle left cingulate gyrus and its lateral surround (0.22±0.02 vs. 0.25±0.02), the left inferior occipital gyrus (0.32±0.05 vs. 0.35±0.05), the right cerebellar area 3 (0.24±0.04 vs. 0.26±0.03), and the right cerebellar area 9 (0.22±0.09 vs. 0.13±0.13) were statistically different between the two groups (P<0.05). The differences in AUCs for degree centrality and nodal efficiency between the two groups were not statistically significant (P>0.05). Conclusions Compared with people with good spatial navigation ability, the topological properties of the brains of the ones with poor spatial navigation ability still conformed to the small-world network properties, but the connectivity between brain regions reduces compared with the good spatial navigation ability group, with a tendency to convert to random networks and a reduced or increased nodal clustering coefficient in some brain regions. Differences in functional brain network connectivity exist among people with different spatial navigation abilities.
ObjectiveTo compare the effectiveness of haemocoagulase agkistrodon and tranexamic acid and sodium chloride in the prevention and treatment of perioperative bleeding in a real world setting. MethodsA research database was constructed based on the records of inpatient visits using haemocoagulase agkistrodon and tranexamic acid and sodium chloride according to the SuValue® database from January 1, 2016 to December 31, 2020. The patients were divided into two groups according to the different interventions. After matching with a 1∶1 propensity score, the effectiveness of two groups was compared. ResultsA total of 858 patients were included in each of the two groups, and there was no statistically significant difference in baseline characteristics between the two groups (P>0.05). Research results showed that patients using haemocoagulase agkistrodon had significantly reduced length of hospital stay, decrease in hematocrit, average estimated surgical bleeding, and decrease in hemoglobin (P<0.01). ConclusionHaemocoagulase agkistrodon has better effectiveness than tranexamic acid and sodium chloride for reducing perioperative blood loss based on current real world evidence.
ObjectivesTo analyze the active areas of real world studies on traditional Chinese medicine in China.MethodsCBM, CNKI, WanFang Data, PubMed and EMbase databases were electronically searched to collect real world studies on traditional Chinese medicine in China from inception to 26th April, 2018. The main research contents (research direction, data sources, and research methods) by Excel were extracted, together with the primary information by BICOMS-2 software and production of the network figures by NetDraw 2.084 software.ResultsEventually, 373 real world studies in traditional Chinese medicine were included, in which the initial one was punished in 2008. The top three ranking of authors involved in real world studies on traditional Chinese were Xie Yanming, Zhuang Yan, Yang Wei, and the top three ranking of institutions were Institute of Basic Research in Clinical Medicine of China Academy of Chinese Medical Sciences, School of Statistics of Renmin University of China, and the PLA Navy General Hospital. The amount of related studies in Beijing accounted for 74.26%. It was found that the active areas involve real world, hospital information system, real world study, drug combination, and propensity score method. In terms of the main studied contents on the use of traditional Chinese medicine in the real world, in which the top three were Fufang Kushen injection, Dengzhanxixin injection, and Shuxuetong injection. Digestive system disease, nervous system disease and cardiovascular disease received the highest attention rate, specifically stroke, coronary heart disease, virus hepatitis and hypertension. 58.18% studies were retrospective studies, 49.60% of the information were from the hospital information system, and 56.30% studies used data mining to carry out statistical analysis.ConclusionsMost real world studies on traditional Chinese medicine are based on HIS, and use data mining to study Chinese medicine preparations. The research attention on Chinese medicine is higher than that of the method of diagnosis and treatment, similarly the Chinese medicine preparations is higher than traditional Chinese medicine. In future, attention should be paid to traditional Chinese medicine, prescription and traditional methods of diagnosis and treatment, such as moxibustion and scraping.
We applied resting-state functional magnetic resonance imaging (rfMRI) combined with graph theory to analyze 90 regions of the infantile small world neural network of the whole brain. We tried to get the following two points clear:① whether the parameters of the node property of the infantile small world neural network are correlated with the level of infantile intelligence development; ② whether the parameters of the infantile small world neural network are correlated with the children's baseline parameters, i.e., the demographic parameters such as gender, age, parents' education level, etc. Twelve cases of healthy infants were included in the investigation (9 males and 3 females with the average age of 33.42±8.42 months.) We then evaluated the level of infantile intelligence of all the cases and graded by Gesell Development Scale Test. We used a Siemens 3.0T Trio imaging system to perform resting-state (rs) EPI scans, and collected the BOLD functional Magnetic Resonance Imaging (fMRI) data. We performed the data processing with Statistical Parametric Mapping 5(SPM5) based on Matlab environment. Furthermore, we got the attributes of the whole brain small world and node attributes of 90 encephalic regions of templates of Anatomatic Automatic Labeling (ALL). At last, we carried out correlation study between the above-mentioned attitudes, intelligence scale parameters and demographic data. The results showed that many node attributes of small world neural network were closely correlated with intelligence scale parameters. Betweeness was mainly centered in thalamus, superior frontal gyrus, and occipital lobe (negative correlation). The r value of superior occipital gyrus associated with the individual and social intelligent scale was -0.729 (P=0.007); degree was mainly centered in amygdaloid nucleus, superior frontal gyrus, and inferior parietal gyrus (positive correlation). The r value of inferior parietal gyrus associated with the gross motor intelligent scale was 0.725 (P=0.008); efficiency was mainly centered in inferior frontal gyrus, inferior parietal gyrus, and insular lobe (positive correlation). The r value of inferior parietal gyrus associated with the language intelligent scale was 0.738 (P=0.006); Anoda cluster coefficient (anodalCp) was centered in frontal lobe, inferior parietal gyrus, and paracentral lobule (positive correlation); Node shortest path length (nlp) was centered in frontal lobe, inferior parietal gyrus, and insular lobe. The distribution of the encephalic regions in the left and right brain was different. However, no statistical significance was found between the correlation of monolithic attributes of small world and intelligence scale. The encephalic regions, in which node attributes of small world were related to other demographic indices, were mainly centered in temporal lobe, cuneus, cingulated gyrus, angular gyrus, and paracentral lobule areas. Most of them belong to the default mode network (DMN). The node attributes of small world neural network are widely related to infantile intelligence level, moreover the distribution is characteristic in different encephalic regions. The distribution of dominant encephalic is in accordance the related functions. The existing correlations reflect the ever changing small world nervous network during infantile development.
The research on brain functional mechanism and cognitive status based on brain network has the vital significance. According to a time–frequency method, partial directed coherence (PDC), for measuring directional interactions over time and frequency from scalp-recorded electroencephalogram (EEG) signals, this paper proposed dynamic PDC (dPDC) method to model the brain network for motor imagery. The parameters attributes (out-degree, in-degree, clustering coefficient and eccentricity) of effective network for 9 subjects were calculated based on dataset from BCI competitions IV in 2008, and then the interaction between different locations for the network character and significance of motor imagery was analyzed. The clustering coefficients for both groups were higher than those of the random network and the path length was close to that of random network. These experimental results show that the effective network has a small world property. The analysis of the network parameter attributes for the left and right hands verified that there was a significant difference on ROI2 (P = 0.007) and ROI3 (P = 0.002) regions for out-degree. The information flows of effective network based dPDC algorithm among different brain regions illustrated the active regions for motor imagery mainly located in fronto-central regions (ROI2 and ROI3) and parieto-occipital regions (ROI5 and ROI6). Therefore, the effective network based dPDC algorithm can be effective to reflect the change of imagery motor, and can be used as a practical index to research neural mechanisms.
Retrospective chart review (RCR) is a type of research that answers specific research questions based on the existing patient medical records or related databases through a series of research processes including data extraction, data collation, statistical analysis, etc. Relying on the development of medical big data, as well as the relatively simple implementation process and low cost of information acquisition, RCR is increasingly used in the medical research field. In this paper, we conducted the visual analysis of high-quality RCR published in the past five years, and explored and summarized the current research status and hotspots by analyzing the characteristics of the number of publications, national/regional and institutional cooperation networks, author cooperation networks, keyword co-occurrence and clustering networks. We further systematically combed the methodological core of this kind of research from eight aspects: research question and hypothesis, applicability of chart, study design, data collecting, statistical analysis, interpretation of results, and reporting specification. By summarizing the shortcomings, unique advantages and application prospects of RCR, providing guidance and suggestions for the standardized application of RCR in the medical research field 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.
ObjectiveTo study the clinical characteristics of patients with partial and transitional atrioventricular septal defects (P/TAVSDs) in our hospital, and to evaluate the early follow-up outcomes from a real-world research perspective.MethodsThe clinical data of all patients diagnosed with P/TAVSDs from January 1, 2018 to July 12, 2020, in our hospital were collected, and all patients' examination results were used as the real-world follow-up data, univariable Cox risk proportional model was used to analyze the outcomes. A total of 93 patients were finally included in the analysis, 72 with partial and 21 with transitional AVSD. There were 38 males and 55 females at age of 182.0 months (20.0 d to 779.5 months).ResultsUnivariable Cox proportional risk model suggested that at least one cardiac malformation (HR=15.00, 95%CI 3.00 to 75.00, P=0.001), preoperative moderate or greater mitral regurgitation (HR=6.60, 95%CI 1.70 to 26.00, P=0.007), and preoperative moderate or greater tricuspid regurgitation (HR=13.00, 95%CI 3.10 to 51.00, P<0.0001) were risk factors for moderate or greater postoperative atrioventricular valve regurgitation.ConclusionChildren with coarctation of the aorta or partial pulmonary vein connection, moderate or greater preoperative mitral regurgitation, and moderate or greater preoperative tricuspid regurgitation need to be alerted to the risk of moderate or greater postoperative atrioventricular valve regurgitation. Real-world data, with relaxed statistical P values and combined expertise, can suggest clinical conclusions that are close to those of high-quality retrospective studies.
Traditional randomized controlled trial and real-world study have different advantages in internal validity and external extensibility, respectively. With the development of evidence-based health decisions, randomized controlled trial was no longer the only golden standard of interventional study, the research evidence of the real world was gradually involved in health decisions. This study mainly analyzed the requirements of evidence and actual application of evidence in the evaluation of the effectiveness of NICE in the UK. It was found that NICE still used the results of randomized controlled trials as a primary basis. Although real-world research has developed rapidly in recent years, it was limited used in health decision because of its bias by design and other factors. However, in recent years, real-world evidence has played a significant role in the field of innovative drugs or diseases that lack therapeutic drugs. With the improvement of real-world research in experimental design and data analysis, it is expected that it will play a more important role in health decision-making.
ObjectiveTo analyze the limitations and challenges for the use of real-world data in the decision making of drug reimbursement through literature review and provide standard process and guideline for the real-world study supporting drug reimbursement. MethodsBy summarizing the relevant policies, regulations, and guiding principles of major drug regulatory agencies worldwide, the study analyzed the applicable conditions, framework, and reimbursement mode for using real-world evidence in the decision making of drug reimbursement. ResultsThe study found that the health technology assessment departments of major developed countries and Asian countries have used real -world evidence to evaluate the drug efficacy and safety. The application scope of real-world data for reimbursement decision included describing the treatment process of the disease, assessing economic burden, verifying economic models, and evaluating the efficacy and safety of drugs. Some developed countries including the United Kingdom and the United States had released guidelines or frameworks of the real-world study for reimbursement decision. The process and framework of using real-world data in reimbursement decision could be divided into three models: coverage with evidence development, outcome-based contract, and re-assessment. ConclusionReal-world data has been widely used in the process of health technology assessment. To adapt to the development of the pharmaceutical industry and to meet the needs of clinical patients, it is urgent to standardize the process of collecting real-world data and formulate the scope and process of using real-world data in the reimbursement process.