Network plots can clearly present the relationships among the direct comparisons of various interventions in a network meta-analysis. Currently, there are some methods of drawing network plots. However, the information provided by a network plot and the interface-friendly degree to a user differ in the kinds of software. This article briefly introduces how to draw network plots using the network package and gemtc package that base on R Software, Stata software, and ADDIS software, and it also compares the similarities and differences among them.
The WinBUGS software can be called from either R (provided R2WinBUGS as an R package) or Stata software for network meta-analysis. Unlike R, Stata software needs to create relevant ADO scripts at first which simplify operation process greatly. Similar with R, Stata software also needs to load another package when drawing network plots. This article briefly introduces how to implement network meta-analysis using Stata software by calling WinBUGS software.
This paper systematically compares the common integrated elderly care and medical services models and related elements in China, analyzes the six major elements of system dynamics order flow, capital flow, equipment flow, personnel flow, information flow and material flow under the health care integration service model, compares the current situation of the application of system dynamics in the operation mechanism of the integrated elderly care and medical services model, supporting policies, cooperation and collaboration model, effect evaluation and industrial prediction simulation of key elements, summarizes the shortcomings of the existing application research and proposes research outlook, and provides a theoretical basis for the optimization research of the integrated elderly care and medical services model.
ObjectiveTo systematically review the clinical and genetic features of permanent neonatal diabetes mellitus (PNDM) case reports. MethodsThe PubMed, Embase, Scopus, SinoMed, Web of Science, CINAHL, Medrxiv, VIP, CNKI and WanFang Data databases were electronically searched to collect PNDM case reports from inception to June 2023. Two reviewers independently screened literature, extracted data and assessed the reporting quality of the included studies. Descriptive analysis was performed. ResultsA total of 105 case reports were finally included. Typical clinical manifestations of PNDM were early onset of persistent hyperglycemia, developmental delay and low birth weight. The results of genetic testing showed that mutations in the KCNJ11, INS, EIF2AK3, GCK, ABCC8, PTF1A, GATA6, IER3IP1, SLC19A2, NEUROG3, PDX1, and 6q24 genes were closely associated with the development of PNDM. In addition, there may be different clinical manifestations and prognosis of PNDM in different genotypes. ConclusionThis study reveales the clinical characteristics and genetic pattern of PNDM, and provides a direction for further research on the mechanism of PNDM.
Objective To investigate the correlation between smoking, alcohol, chronic diseases, fasting plasma glucose levels, uric acid and the incidence of urolithiasis. Methods A 1∶1 pair-wise matching design was used in case-control study. We randomly selected 150 samples from 459 patients with urolithiasis in Zhongnan Hospital of Wuhan University from May 2015 to November 2015. Patient with intact information were identified as case group. The control group were patients who hospitalized in the same period without urolithiasis matched by gender, ethnic, and marital status. Univariate ANOVA and multivariate conditional logistic regression were used to test the differences between the two groups. Results A total of 125 patients in case group and 125 patients in control group were included. The peak age of urolithiasis was 50 to 70 years old, male patients accounted for 70.75% of the population, and one side urolithiasis accounted for 62.24% of the stone types. The results of multivariate conditional logistic regression showed that hyperuricemia was the related factor of urolithiasis (OR=5.19, 95%CI 2.27 to 11.91, P<0.01). Conclusions Hyperuricemia is a high risk factor for urolithiasis.
Due to the competition of new drug research and clinical requirement, speeding up drug development and marketing requires faster and more flexible clinical trial design that meets the ethical requirements. Different adaptive designs have emerged in clinical trials of different stages and purposes, for trial efficiency improvement. Adaptive design is more widely used in the field of oncology. Compared with traditional design, adaptive design is more complicated and requires higher level of methodology from researchers. Therefore, implementing adaptive design requires careful consideration and adequate preparation. This paper aims to summarize the design of adaptive methods used in different trial stages so as to provide reference for clinical research designers and implementers.
Objective To explore the matching relationship between the supply and demand of different types of integrated elderly care and medical service for the elderly population in the region, and achieve the simulation purpose of coordinated allocation and balanced development of supply and demand of integrated elderly care and medical service. Methods Combining literature, interviews, and expert consultation to sort out the main factors and system element relationships between the supply and demand of integrated elderly care and medical service in the region, the Vensim software was used to clarify the relationships and operation mechanisms between the subsystems of supply and demand of integrated elderly care and medical service. The data of the construction base for the integrated elderly care and medical service project in Suzhou city, Jiangsu province from January 1, 2010 to December 31, 2022 were selected. Results Combined with the accessibility and completeness of data, the main variables and indicators of the five subsystems were screened, and the causality diagram and flow diagram of the system dynamics were drawn to clarify the main variables and flow direction of the subsystems, and the constructed model was more stable in simulation operation. The simulation model results showed that the supply-demand ratio of home-based elderly care and community elderly care decreased relatively before 2012, and the institutional elderly care model gradually emerged and developed from 2013 to 2018. From 2019 to 2022, the supply-demand ratio of medical care with elderly care and elderly care with medical care decreased. Conclusions Based on the theoretical foundation of system dynamics, the supply and demand the integrated elderly care and medical service in the region are regarded as a complex system. Through the analysis of the system elements among the subsystems and the sorting out of the mechanisms, it can provide certain theoretical support for constructing and improving the system dynamics model for matching the supply and demand of integrated elderly care and medical service in the region.
ObjectiveTo evaluate the robustness of pediatrics Clinical evidence-based evidence using fragility index and to explore the factors influencing fragility index. MethodsWe searched the PubMed, Embase, and Scopus databases to collect relevant literature on systematic reviews and meta-analyses in the field of pediatrics, and calculated the fragility index. The rank sum test was used to compare differences between groups with different outcome types, different levels of statistical significance, and different sample sizes. Spearman correlation analysis was used to explore the association between the fragility index and sample size, as well as the year of publication. ResultsA total of 152 systematic reviews, including 573 meta-analyses, were included, with a median fragility index of 6 (3, 10). Most meta-analyses chose the risk ratio (RR) as the effect measure (387/573, 67.5%), the Mantel-Haenszel method (412/573, 71.9%) as the synthesis method, and the fixed-effect model (300/573, 57.4%) as the assumed model. The Mann-Whitney test showed no statistically significant difference in the fragility index between meta-analyses with safety outcomes and those with efficacy outcomes (P=0.397), and no statistically significant difference between meta-analyses with significant results and those with non-significant results (P=0.520). The Kruskal-Wallis test found a statistically significant difference in sample size among groups with different fragility indices (P<0.001). Spearman correlation analysis found a positive correlation between the fragility index and sample size (ρ=0.39, P<0.001), but no statistically significant correlation with the year of publication (P=0.235). ConclusionThe fragility index of clinical evidence-based evidence published in pediatrics journals is generally low, and the robustness of the results is not high, so it is necessary to be cautious when making evidence-based decisions. Furthermore, the larger the sample size included in the meta-analysis, the higher the fragility index, and incorporating more trials and populations can facilitate the increase in the robustness of the meta-analysis results.
Dose-response meta-analysis is being increasingly applied in evidence production and clinical decision. The research method, synthesizing certain dose-specific effects across studies with the same target question by a certain types of weighting schedule to get a mean dose-response effect, is to reflect the dose-response relationship between certain exposure and outcome. Currently, the most popular method for dose-response meta-analysis is based on the classical "two-stage approach", with the advantage that it allows fixed- or random-effect model, according to the amount of heterogeneity in the model. There are two types of random-effect model available for dose-response meta-analysis, that is, the generally model and the coefficient-correlation-adjusted model. In this article, we briefly introduce two models and illustrate how they are applied in Stata software, which is expected to provide theoretical foundation for evidence-based practice.
Dose-response meta-analysis serves an important role in investigating the dose-response relationship between independent variables (e.g. dosage) and disease outcomes. Traditional dose-response meta-analysis model is based on one independent variable to consider its own dose-specific effect on the outcome. However, for drug clinical trials, it generally involves two-dimensions of the treatment, such as dosage and course of treatment. These two-dimensions tend to be associated with each other. When neglecting their correlations, the results may be at risk of bias. Moreover, taking account of the "combined effect” of dosage and time on outcome has more clinical value. Therefore, in this article, based on traditional dose-response meta-analysis model, we propose a three-dimension model for dose-response meta-analysis which considers both the effect of dosage and time, to provide a solution for the above-mentioned problems in a traditional model.