ObjectiveTo learn the distribution pattern and characteristics of autoimmune pancreatitis research literature, and its worldwide research trend. MethodsPublished data between September 22, 2004 and September 21, 2014 were searched by using the keyword autoimmune pancreatitis in the database of Pubmed. Publication year, journals, authors and research topics were bibliometrically analyzed. The analysis software Bibliographic Item Co-occurrence Matrix Builder was used for cluster analysis on high-frequency keywords. ResultsA total of 1 518 articles on autoimmune pancreatitis were acquired. The amount of published literature rose rapidly in the past 10 years, reaching its peak in the year of 2012. Most of the articles were published by several leading authors in the leading journals. There were 26 keywords with a frequency of more than 30 times, and 4 categories were classified through cluster analysis of these keywords. They were pathology and immunology, imaging, diagnosis and treatment. ConclusionsAttention on autoimmune pancreatitis has been increasing in the recent 10 years. Japanese researchers have been taking the lead. Current research focus is the diagnosis of autoimmune pancreatitis.
ObjectiveTo research on the influence of cluster management on the nutritional intervention for nasopharynx cancer patients undergoing intensity modulated radiation therapy (IMRT), in order to discuss effective and feasible nutrition management method. MethodEighty-three nasopharynx cancer patients undergoing IMRT between June 2013 and December 2014 were selected as the study subjects. They were divided into two groups randomly. Regular health education and nutritional guidance were carried out for the 41 patients in the control group, while nutritional risk screening (NRS)-2002 nutrition screening, nutrition assessment and nutritional intervention were carried out for the 42 patients in the intervention group. Nutrition risk, nutritional status and side-reaction were recorded and evaluated for both groups of patients. ResultsAfter treatment, NRS-2002 score of the intervention group was lower than the control group (P<0.05). Body weight, constitutional index, skinfold thickness of triceps brachii muscle, mid-arm circumference and mid-arm muscle circumference of the intervention group were better than the control group (P<0.05). Total serum protein, serum albumin, serum transferrin were better and the rate of levelⅢ-Ⅳ radiation-induced oral mucositis was lower in the intervention group than that in the control group (P<0.05). ConclusionsThe application of cluster management model in nutritional intervention is a way to promote patients' rehabilitation, which can effectively improve the whole body situation of nasopharynx cancer patients, and reduce malnutrition rate and side-reaction.
Objective To investigate the hot topics of research on evidence-based medicine in 2002. Method To search MEDLINE for papers on evidence-based medicine published in 2002, identify high-frequency subject headings related to research on evidence-based medicine, and cluster the high-frequency subject headings according to rates they appeared in common papers. Results 545 papers, 1 554 subject headings, 30 high-frequency subject headings on evidence-based medicine, and nine clustering categories of high-frequency subject headings were identified through search. Conclusions Both high-frequency subject headings and their clustering categories suggested that “evidence-based practice guidelines and their innovation”, “evidence-based health research and health policy”, “methodology on systematic reviews and randomized clinical trials”, “method of evidence-based decision making and its application in various subjects”, were the hot topics of evidence-based medicine. They provided useful references for Chinese medical professionals to practice evidence-based medicine.
When a clustered coronavirus disease 2019 epidemic occurs, how to prevent and control hospital infection is a challenge faced by each medical institution. Under the normalization situation, building an effective prevention and control system is the premise and foundation for medical institutions to effectively prevent and control infection when dealing with clustered epidemics. According to the principles of control theory, medical institutions should quickly switch to an emergency state, and effectively deal with the external and internal infection risks brought by clustered epidemics by strengthening source control measures, engineering control measures, management control measures and personal protection measures. This article summarizes the experience of handling clustered outbreaks in medical institutions in the prevention and control of coronavirus disease 2019, and aims to provide a reference for medical institutions to take effective prevention and control measures when dealing with clustered outbreaks.
Epilepsy is a neurological disease with disordered brain network connectivity. It is important to analyze the brain network mechanism of epileptic seizure from the perspective of directed functional connectivity. In this paper, causal brain networks were constructed for different sub-bands of epileptic electroencephalogram (EEG) signals in interictal, preictal and ictal phases by directional transfer function method, and the information transmission pathway and dynamic change process of brain network under different conditions were analyzed. Finally, the dynamic changes of characteristic attributes of brain networks with different rhythms were analyzed. The results show that the topology of brain network changes from stochastic network to rule network during the three stage and the node connections of the whole brain network show a trend of gradual decline. The number of pathway connections between internal nodes of frontal, temporal and occipital regions increase. There are a lot of hub nodes with information outflow in the lesion region. The global efficiency in ictal stage of α, β and γ waves are significantly higher than in the interictal and the preictal stage. The clustering coefficients in preictal stage are higher than in the ictal stage and the clustering coefficients in ictal stage are higher than in the interictal stage. The clustering coefficients of frontal, temporal and parietal lobes are significantly increased. The results of this study indicate that the topological structure and characteristic properties of epileptic causal brain network can reflect the dynamic process of epileptic seizures. In the future, this study has important research value in the localization of epileptic focus and prediction of epileptic seizure.
Objective To set up healthcare device-technology deployment assessment model and procedures through establishing the assessment parameter system between the functions of the clinical technical requirements and devices. Methods The bidirectional assessment parameter system developed by the literature review and Delphi, then combination weighting calculated by the combination weighting method, and the proposals for function deployment performed on the cluster analysis. Results The positive coefficients of twice Delphi were 75.56% and 87.50%, respectively. The effective recovery rates of the questionnaire were higher. The structure of the bidirectional assessment parameter system acquired according to the data mining and review, Delphi and integrated analysis. We calculated the weighting for the required functions and the deployed functions of the ventilator in the ICU, ER and RR. We listed the absolute importance and rank. The proposals for the function deployment of the ventilator which met different needs in fields of the critical care medicine were produced by the cluster analysis, ranking absolute importance and the calibration of weighting based on the investigation for actual function utilized rate. Conclusion It studies healthcare device-technology deployment assessment model by sequential integrated methods and sets up bidirectional assessment parameter system based on clinical technical function requirement, and the result is effective.
ObjectiveTo investigate the gene expression spectrum of retina and optic nerve after partial injury of optic nerve.MethodsSixty SD rats were randomly divided into 4 groups. The optic nerves of the right eyes were clipped for 6 seconds with a pair of crossaction forceps. The retinae and optic nerves in the operation eye and contralateral sham operation eye were removed 3, 7, 14, and 21 days after the injury to detect gene expression patterns with high-density DNA microarrays.ResultsChanges of a mass of gene expressions were found after the optic nerve injury, and the positive rate of gene expression was 2.35%, 6.48%, 3.82% and 4.09% after 3, 7, 14, 21 days, respectively, and the total positive rate was 11.77%. The functions of positive expression of the gene involved cell survival, cytoskeleton, extracellular matrix and cell adhesion, free radicals and oxidative damage, energy and metabolism, inflammation, neurotransmission and ion transport, signal transduction, structural protein, transcription and translation. Up-or down-regulation of repaired genes was the main part of the changes of gene expression, while the alteredexpression destroy genes was the minor part in the whole gene expression spectrum, in which the up- and down-regulation of expression of repaired genes accounted for 13.98% and 24.73% respectively 7 days after the injury, and the downregulation of expression of repaired genes accounted for 17.20% 14 days after the injury.ConclusionsA mass of gene expression changes occurs after the optic nerve injury, and the comprehensive view on the gene expression pattern following the optic nerve injury is crucial to discover the mechanism of post-injury reaction and regeneration.(Chin J Ocul Fundus Dis, 2005,21:163-166)
ObjectiveTo analyze the current situation and international research focuses on the study of medical device risk management. MethodsTo retrieve medical device risk management literature information cited from 2002 to 2011 in PubMed such as high-frequency MeSH; analyze current situation and research focuses of medical device risk management by using bibliometrics, bibliographic item co-occurrence matrix builder (BICOMB), and graphical clustering toolkit (gCluto) for quantitative analysis, high-frequency MeSH term papers cluster visualization analysis. ResultsA total of 7 073 published studies were retrieved, basically suggesting a gradually increasing trend of the number of published papers. The top 3 numbers of first authors' papers referred to three countries: the United States, Britain and Germany, while China ranked twelfth. The top 3 numbers of journal articles referred to the United States, Britain and Holland, while China ranked twenty-second. Twenty journals published more than 50 papers, and all these journals were clinical journals. Thirty-three authors published no less than 5 papers, with the maximum of 18 articles. Totally, there were 124 highfrequency MeSHs. The high-frequency MeSHs were classified into 6 categories by using double cluster analysis: kinds 0 to 4 included risk report, risk analysis, risk assessment and methodology of heart valve prosthesis, coronary stents, peripheral vascular stents, implantable defibrillators and other life support device, surgical repair surgical flaps and minimal invasion surgical device such as laparoscopy; kind 5 focused on safety management, risk control, organization and implementation and other related research based on prevention and control of medical device adverse reaction, medical errors, occupation exposure, and equipment failure. ConclusionThe analysis on international literature on medical device risk management basically shows a gradually increasing trend; most studies published in the clinical medicine journals; research focus on risk assessment, safety management and quality improvement in the application such as angioplasty, artificial prosthesis replacement, plastic surgery, minimally invasive surgery and critical care medicine, and radiology diagnosis and treatment; implantable, life-supported invasive and radiological devices as the main research subject; and characteristics include closely combination between medical device risk management and the application of safe and effective, quality improvement systems for clinical diagnosis and treatment.
ObjectiveWhen using multi-center data to construct clinical prediction models, the independence assumption of data will be violated, and there is an obvious clustering effect among research objects. In order to fully consider the clustering effect, this study intends to compare the model performance of the random intercept logistic regression model (RI) and the fixed effects model (FEM) considering the clustering effect with the standard logistic regression model (SLR) and the random forest algorithm (RF) without considering the clustering effect under different scenarios. MethodsIn the process of forecasting model establishment, the prediction performance of different models at the center level was simulated when there were different degrees of clustering effects, including the difference of discrimination and calibration in different scenarios, and the change trend of this difference at different event rates was compared. ResultsAt the center level, different models, except RF, showed little difference in the discrimination of different scenarios under the clustering effect, and the mean of their C-index changed very little. When using multi-center highly clustered data for forecasting, the marginal forecasts (M.RI, SLR and RF) had calibrated intercepts slightly less than 0 compared with the conditional forecasts, which overestimated the average probability of prediction. RF performed well in intercept calibration under the condition of multi-center and large samples, which also reflected the advantage of machine learning algorithm for processing large sample data. When there were few multiple patients in the center, the FEM made conditional predictions, the calibrated intercept was greater than 0, and the predicted mean probability was underestimated. In addition, when the multi-center large sample data were used to develop the prediction model, the slopes of the three conditional forecasts (FEM, A.RI, C.RI) were well calibrated, while the calibrated slopes of the marginal forecasts (M.RI and SLR) were greater than 1, which led to the problem of underfitting, and the underfitting problem became more prominent with the increase in the central aggregation effect. In particular, when there were few centers and few patients, overfitting of the data could mask the difference in calibration performance between marginal and conditional forecasts. Finally, the lower the event rate the central clustering effect at the central level had a more pronounced impact on the forecasting performance of the different models. ConclusionThe highly clustered multi-center data are used to construct the model and apply it to the prediction in a specific environment. RI and FEM can be selected for conditional prediction when the number of centers is small or the difference between centers is large due to different incidence rates. When the number of hearts is large and the sample size is large, RI can be selected for conditional prediction or RF for edge prediction.
The risk of bias assessment tool 2.0 (RoB 2.0) for analyzing cluster randomized trials and crossover trials (revised version 2021) has been updated. The current paper briefly delineates the history of the RoB 2.0 tool and includes an explanation and interpretation of the updated contents and software operation process for use with cluster randomized trials and crossover trials. Compared with the previous versions, the updated RoB 2.0 tool (revised version 2021) has the advantage of precise language and is easily understood. Thus, the updated RoB 2.0 tool merits popularization and further general application.