Objective To learn the distribution pattern and worldwide research tendency of vitrectomy literatures. Methods Articles were searched from American Institute of Scientific Information (ISI) online database of web of science (WOS) database as a data source, to analyze the age distribution, national and regional, funding agency and citation of the vitrectomy literatures included during the year of 1971 -2011. The analysis software BibExcel and SPSS 19.0 were used to cluster highfrequency of them. Results Totally 8540 literatures were included, the numbers of them were gradually increased since 1971, significantly after 1991. The literatures were mainly in English, the literatures of our country capacity ranked 6th; funded institutions in all article, the National Natural Science Foundation of China ranked No. 5. Citation gradually increased since 1991, increased significantly after 2004. There were 50 highfrequency subjects, and hot topics were clustered into 6 categories which including vitrectomy for diseases of macula lutea, new techniques and complication of vitrectomy, medical treatment and surgical therapy of diabetic retinopathy, cataract, vitrectomy for endophthalmitis caused by intraocular injection and eye injury. Conclusions There is a growing trend on the research of vitrectomy. The hot topics include vitrectomy for diseases of macula lutea, new techniques and complication of vitrectomy. It may provide references for the scholars in scientific research and clinical studies.
Cluster randomized trial (CRT) is one of the most common design for complex intervention. This paper mainly introduced:the definition of CRT, two designs of CRT including the completely randomization and the restricted randomization (such as stratified randomization and matching randomization), and the statistical analysis methods (such as the general statistical analysis and mixed effect model/multi-level model). This paper also introduced how to estimate the sample size of a CRT, how to report a CRT, and how to apply it into a clinical or community study.
ObjectiveTo explore the effect of the cluster intervention in new nurses in the Department of Neurosurgery in occupation training, so as to provide reference for the clinical training of new nurses. MethodsEight nurses who entered the Department of Neurosurgery in January 2013 were set as control group and the 8 new nurses entering in January 2014 as the observation group. The control group was adopted the traditional training methods, while the observation group underwent used extra cluster intervention. The differences in the results of theory, technology, operation and the 360-degree evaluation between the two groups were analyzed at the end of year. ResultsIn the observation group, the median theory examination score was 91.50, median operation assessment grades was 95.00, which were higher than those in the control group (82.00 and 83.00). The average scores of 360-degree evaluation in the observation group were higher than those in the control group with a significant difference (P < 0.01). ConclusionsIntensive intervention should be used for new nurses' training. It helps to improve the training effect and new nurses' ability.
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.
ObjectiveTo explore the preventive role of maintaining constant pressure of the endotracheal catheter cuff on ventilator-associated pneumonia (VAP). MethodsFrom January to December 2015, 96 patients of type Ⅱ respiratory failure were selected as the trial group who underwent intubation and mechanical ventilation more than 48 hours in the Intensive Care Unit (ICU). We used pressure gauges to measure the endotracheal catheter cuff pressure regularly and maintained a constant pressure in addition to the application of artificial airway cluster management. We recorded the initial pressure value which was estimated by pinching with finger and set initial pressure to 30 cm H2O (1 cm H2O=0.098 kPa). We measured endotracheal catheter cuff pressure and recorded it during different intervals. We reviewed 88 patients with the same disease as the control group who only accepted artificial airway cluster management between January and December 2014. Mechanical ventilation time, VAP occurrence time, ICU admission time, the incidence of VAP were recorded and analyzed for both the two groups of patients. ResultsIn the trial group, the initial pressure of endotracheal catheter cuff which was estimated by pinching with finger showed that only 11.46% of pressure was between 25 and 30 cm H2O and 82.29% of the pressure was higher than 30 cm H2O. We collected endotracheal catheter cuff pressure values during different interval time by using pressure gauges to maintain a constant management. The ratio at the pressure between 25 and 30 cm H2O was respectively 41.32%, 43.75%, 64.20%, 76.54%, 91.13%, and 91.85%. ICU admission time, mechanical ventilation time in patients of the trial group decreased more, compared with the control group, and the differences were statistically significant (t=4.171, P<0.001; t=4.061, P<0.001). The VAP occurrence time in patients of the trial group was later than the control group (t=2.247, P<0.001). ConclusionThe endotracheal catheter cuff pressure estimated by pinching with finger has errors. We recommend using pressure gauges to detect pressure every four hours, which utilizes minimal time to maintain effective pressure. The method of artificial airway of cluster management combined with the pattern of maintaining constant endotracheal catheter cuff pressure can shorten ICU admission time, mechanical ventilation time and delay the occurrence of VAP.
Objective To analyze the hot spot and future application trend of artificial intelligence technology in the field of intensive care medicine. Methods The CNKI, WanFang Data, VIP and Web of Science core collection databases were electronically searched to collect the related literature about the application of artificial intelligence in the field of critical medicine from January 1, 2013 to December 31, 2022. Bibliometrics was used to visually analyze the author, country, research institution, co-cited literature and key words. Results A total of 986 Chinese articles and 4 016 English articles were included. The number of articles published had increased year by year in the past decade, and the top three countries in English literature were China, the United States and Germany. The predictive model and machine learning were the most frequent key words in Chinese and English literature, respectively. Predicting disease progression, mortality and prognosis were the research focus of artificial intelligence in the field of critical medicine. ConclusionThe application of artificial intelligence in the field of critical medicine is on the rise, and the research hotspots are mainly related to monitoring, predicting disease progression, mortality, disease prognosis and the classification of disease phenotypes or subtypes.
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.
Objective To analyze and reveal the domestic and abroad studies on polypoidal choroidal vasculopathy (PCV) by bibliometric. Methods Foreign articles were searched from American Institute of Scientific Information online database of web of science (WOS) database, Chinese articles were searched from China National Knowledge Infrastructure (CNKI) database. The age distribution, national and regional, funding agency and citation of the PCV literatures published before December 31 2012 were analyzed by software Bibexcel and SPSS 17.0. Results Totally 696 literatures were analyzed, including 440 foreign literatures and 256 Chinese literatures. The numbers of foreign literatures were gradually increased since 2000, significantly after 2007, reached the maximum at 2011. The literatures were mainly in English, the number of the literatures of China ranked 4th of all countries. The National Natural Science Foundation of China ranked No.5 of funding agency. Citations gradually increased since 2000, increased significantly after 2008; there were 30 highfrequency subjects, and hot topics were clustered into 5 categories: treatment of PCV, genetics studies of PCV, detection, diagnosis and epidemiology of PCV, relationships between PCV and macular degeneration, related cytokine of PCV. Chinese literatures increased since 2000, significantly after 2006, and reached the maximum at 2010; there were 15 literatures supported by National Natural Science Foundation of China; Citation of Chinese literatures gradually increased since 2001, and reached the maximum at 2012. There were 30 highfrequency subjects, and hot topics were clustered into 5 categories: genetics and cytokine studies of PCV, detection and diagnosis of PCV, treatment of PCV, PCV and macular diseases, PCV and vitreous hemorrhage. Conclusions Literatures of PCV were gradually increased since 2000, abroad and domestic literatures of PCV reached maximum at 2011 and 2010 respectively. The abroad research of PCV focuses on 5 categories: treatment of PCV, genetics studies of PCV, detection, diagnosis and epidemiology of PCV, relationships between PCV and macular degeneration, related cytokine of PCV. The domestic research focuses on genetics and cytokine studies of PCV, detection and diagnosis of PCV, treatment of PCV, PCV and macular diseases, PCV and vitreous hemorrhage.
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.