Dose-response meta-analysis, an important tool in investigating the relationship between a certain exposure and risk of disease, has been increasingly applied. Traditionally, the dose-response meta-analysis was only modelled as linearity. However, since the proposal of more powerful function models, which contains both linear, quadratic, cubic or more higher order term within the regression model, the non-linearity model of dose-response relationship is also available. The packages suit for R are available now. In this article, we introduced how to conduct a dose-response meta-analysis using dosresmeta and mvmeta packages in R.
ObjectiveThyroid nodules are an exceptionally common thyroid disorder. Past studies suggested a possible link between thyroid diseases and breast neoplasms. However, few studies have delved into the causal relationship between thyroid nodules and breast neoplasms. This study conducted a Mendelian randomization (MR) analysis to further investigate the causal relationship between them. MethodsThis study was conducted using data sourced from genome-wide association study (GWAS) summary datasets. The study focused on thyroid nodules, benign breast tumors, and malignant breast cancers as the research objects, and relevant single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs). The inverse-variance weighted (IVW) was primarily used to assess the causal relationship between thyroid nodules and breast neoplasms. Cochran’s Q test was employed to detect heterogeneity, while MR-Egger intercept and MR-PRESSO were used to test for pleiotropy. Sensitivity analysis was conducted using the leave-one-out method. ResultsThere was a significant causal relationship between thyroid nodules and malignant neoplasm of breast (OR=0.88, 95%CI 0.83 to 0.95, P<0.01), with no evidence of reverse causality between them (OR=1.01, 95%CI 0.99 to 1.03, P=0.16). No causal relationship was found between thyroid nodules and benign neoplasm of breast, as indicated by both forward MR analysis (OR=0.97, 95%CI 0.89 to 1.06, P=0.51) and reverse MR analysis (OR=0.97, 95%CI 0.92 to 1.04, P=0.40). Sensitivity analyses suggested that the study findings were accurate and reliable. ConclusionThe present study identifies thyroid nodules as a potential protective factor for malignant neoplasm of breast.
The medical literature contains a wealth of valuable medical knowledge. At present, the research on extraction of entity relationship in medical literature has made great progress, but with the exponential increase in the number of medical literature, the annotation of medical text has become a big problem. In order to solve the problem of manual annotation time such as consuming and heavy workload, a remote monitoring annotation method is proposed, but this method will introduce a lot of noise. In this paper, a novel neural network structure based on convolutional neural network is proposed, which can solve a large number of noise problems. The model can use the multi-window convolutional neural network to automatically extract sentence features. After the sentence vectors are obtained, the sentences that are effective to the real relationship are selected through the attention mechanism. In particular, an entity type (ET) embedding method is proposed for relationship classification by adding entity type characteristics. The attention mechanism at sentence level is proposed for relation extraction in allusion to the unavoidable labeling errors in training texts. We conducted an experiment using 968 medical references on diabetes, and the results showed that compared with the baseline model, the present model achieved good results in the medical literature, and F1-score reached 93.15%. Finally, the extracted 11 types of relationships were stored as triples, and these triples were used to create a medical map of complex relationships with 33 347 nodes and 43 686 relationship edges. Experimental results show that the algorithm used in this paper is superior to the optimal reference system for relationship extraction.
The increasing deteriorative trend of doctor-patient relationship (DPR) have destroyed patient safety, doctor safety and social stability in China. DPR is a complicated social problem related to multidisciplinary and multi-factor interactions. A series of researches providing different views on how to improve DPR in China have been published in recently years. Evidence-based medicine (EBM) aims to deal with massive information by producing, synthesizing and disseminating evidence from complex interventions. We tried to explore the trait of DPR by EBM methods. We provided evidence on research trends, topics and methods by systematic database retrieval, classification by screening, and quality assessment. Through dissection, attribution, and visualization of interactions and relationships between factors, we provided an evidence-supported framework for improvement of DPR. We identified gaps, defects or deficiencies in existing research, and promoted further research. We continued to follow up the research and faced a challenge: Reflection and frustration in the process of establishing the quality evaluation system of qualitative research. We found that the study of complex humanities and social sciences by reference to evidence-based methodology might be: providing a structured, panoramic perspective for complex social problems on " de-fragmentation”, providing a framework for social governance through classification and hierarchy, and calling for a more tolerant attitude and more comprehensive application of methodologies.
We introduced the current doctor-patient relationship and analyzed its opposition and unification based on present medical practice. We suggested that evidence-based medicine should be an important in improving doctor-patient relationship in clinical practice. We urged health care professionals to learn and apply initiatively evidence-based medicine, so as to improve the patient-professional relationship.
It is essential to improve the practice of community healthcare service for the resolution of the problem of inadequate and overly expensive medical services, to promote the harmonization of doctor-patient relationship. From the aspects of the introduction of community healthcare service and the necessity of its standard management, the civil legal relation of community healthcare and its major problems, as well as the rights and duties of community doctors, the authors discussed the importance and necessity of scientific management, right protection by law as well as sound and orderly development of community healthcare service.
To analyze the current doctor-patient relationship and explore its underlying reasons. Evidence-based medicine may provide scientific evidence for the deepening of healthcare reforms as well as the improvement of social security system; provide abundant information for both sides of the doctor-patient relationship; improve medical quality and reduce medical costs, so as to establish a harmonious patient-oriented doctor-patient relationship .
ObjectiveTo investigate the causal relationship between gut microbiota and cholelithiasis using a two-sample Mendelian randomization method. MethodsThe genome-wide association studies (GWAS) data of gut microbiota from the MiBioGen study and the GWAS data of cholelithiasis from the FinnGen Biobank were utilized. Genetic variants significantly associated with the relative abundance of gut microbiota were identified as instrumental variables (IVs) based on a specified threshold. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with results assessed based on the odds ratio (OR) and 95% confidence interval (CI). The robustness and reliability of the findings were ensured through quality control measures, including sensitivity analysis, assessment of heterogeneity, and evaluation for horizontal gene pleiotropy. ResultsClostridiumsensustricto1 [OR=1.160, 95%CI (1.023, 1.314), P=0.020], Coprococcus3 [OR=1.136, 95%CI (1.014, 1.272), P=0.028] and Peptococcus [OR=1.074, 95%CI (1.023, 1.128) , P=0.004] increased the risk of cholelithiasis. Bacilli [OR=0.897, 95%CI (0.818, 0.984), P=0.022], Family Ⅹ ⅢAD3011group [OR=0.908, 95%CI (0.830, 0.992), P=0.033] and Lactobacillales [OR=0.884, 95%CI (0.802, 0.974), P=0.013] were protective factors for cholelithiasis. ConclusionThe study has identified 6 kinds of specific gut microbiota that are causally linked to the development of cholelithiasis, providing new ideas for the diagnosis and treatment of cholelithiasis.
Objective To explore the factors which affect shared decision-making and develop strategies to get patients actively involved in clinical decision-making. Methods We conducted a survey on 566 patients of a Class A Hospital in Sichuan with group random sampling method. The data were collected by the use of anonymous selfadministered questionnaires. We used SPSS 10.0 to analyse the data. Results A total of 600 questionnaires were distributed at random, of which 565 were completed. There were 68% patients who had some knowledge of the disease, and 93% who were willing to participate in clinical decision-making. The patients’ biggest concerns were: treatment effect, cost and doctors’ skills. The biggest difficulties that patients worried about were: long-time waiting in out-patient departments and limited time to communicate with doctors. Conclusion As more and more patients would like to involve in shared decision-making, doctors need to provide patients with more choices and help them make a right decision in their treatment.