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.
Objective To explore the factors which influence the doctor-patient relationship and to provide evidence to help decision makers improve hospital management and construct a harmonious doctor-patient relationship. Methods Discharged patients of West China Hospital from 2003-2006 were randomly selected and asked to complete a specially designed questionnaire. Results In total, 8 000 questionnaires were distributed and 2 526 were returned. The retrieval rate was 31.57%. The responses showed that non-medical factors have became the main factors affecting the doctor-patient relationship (91.8%). Other important factors included medical cost (21.5%) and doctor-patient communication (11.51%). Conclusion We should boost hospital management level, train non-medical staff, save costs and improve doctor-patient communication.
Objective To analyze the causal relationship between cerebrospinal fluid (CSF) metabolites and tic disorder (TD) based on two-sample Mendelian randomization (MR). Methods CSF metabolites data from humans were downloaded from genome-wide association study databases, and CSF metabolites were selected as exposure factors. single nucleotide polymorphisms (SNPs) strongly associated with the exposure factors and independent of each other were selected as instrumental variables. The TD dataset from the Finngen database was downloaded, including 365 cases of TD and 411 816 controls. Analysis was conducted using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode. Sensitivity analysis was conducted using leave-one-out, and multiple-effects testing was conducted using MR-Egger and MR-PRESSO. Heterogeneity was detected using Cochran’s Q. Results A total of 9 CSF metabolites were found to have a causal relationship with the occurrence and development of TD (P<0.05), with a total of 394 SNPs included in the analysis. Inverse variance weighting results showed that N-acetylneuraminic acid [odds ratio (OR)=2.715, 95% confidence interval (CI) (1.102, 6.961), P=0.030], γ-glutamylglutamine [OR=1.402, 95%CI (1.053, 1.868), P=0.021], lysine [OR=2.816, 95%CI (1.084, 7.319), P=0.034] could increase the risk of TD. Cysteinylglycine disulfide [OR=0.437, 95%CI (0.216, 0.885), P=0.021], propionylcarnitine [OR=0.762, 95%CI (0.616, 0.941), P=0.012], pantothenate [OR=0.706, 95%CI (0.523, 0.952), P=0.023], gulareic acid [OR=0.758, 95%CI (0.579, 0.992), P=0.044], and cysteine-glycine [OR=0.799, 95%CI (0.684, 0.934), P=0.005] could reduce the risk of TD. The results of leave-one-out sensitivity analysis were stable, and no horizontal pleiotropy or heterogeneity was observed. Conclusions N-acetylneuraminic acid, γ-glutamylglutamine, and lysine can increase the risk of TD, but cysteinylglycine disulfide, propionylcarnitine, pantothenate, gulagic acid and cysteine-glycine can reduce the risk of TD. However, the mechanism of their effects on TD still needs to be further explored.
This paper explores the relationship between the cardiac volume and time, which is applied to control dynamic heart phantom. We selected 50 patients to collect their cardiac computed tomography angiography (CTA) images, which have 20 points in time series CTA images using retrospective electrocardiograph gating, and measure the volume of four chamber in 20-time points with cardiac function analysis software. Then we grouped patients by gender, age, weight, height, heartbeat, and utilize repeated measurement design to conduct statistical analyses. We proposed structured sparse learning to estimate the mathematic expression of cardiac volume variation. The research indicates that all patients’ groups are statistically significant in time factor (P = 0.000); there are interactive effects between time and gender groups in left ventricle (F = 8.597, P = 0.006) while no interactive effects in other chambers with the remaining groups; and the different weight groups’ volume is statistically significant in right ventricle (F = 9.004, P = 0.005) while no statistical significance in other chambers with remaining groups. The accuracy of cardiac volume and time relationship utilizing structured sparse learning is close to the least square method, but the former’s expression is more concise and more robust. The number of nonzero basic function of the structured sparse model is just 2.2 percent of that of least square model. Hence, the work provides more the accurate and concise expression of the cardiac for cardiac motion simulation.
ObjectiveTo systematically review the dose-response relationship between body mass index (BMI) and all-cause mortality in the elderly with frailty.MethodsPubMed, EMbase, Web of Science, CNKI, VIP, WanFang Data, and CBM databases were electronically searched to collect cohort studies on the association of BMI and mortality in frail adults from inception to November 2019. Two reviewers independently screened literature, extracted data and assessed risk bias of included studies; Stata 15.0 software was then used to analyze the dose-response analysis of BMI and mortality by restricted cubic spline function and generalized least squares method.ResultsA total of 4 cohort studies involving 12 861 frail adults were included. Meta-analysis results showed that compared with normal BMI, the frail elderly who were overweight (HR=0.80, 95%CI 0.74 to 0.88, P<0.001) and obese (HR=0.89, 95%CI 0.79 to 1.00, P=0.047) had lower all-cause mortality. The results of dose-response meta-analysis showed that there was a non-linear relationship between BMI and all-cause mortality in the elderly with frailty (P value for nonlinearity was 0.035), for which the elderly with frailty had a BMI nadir of 27.5-31.9 kg/m2. For linear trends, and when BMI was less than 27.5 kg/m2, the risk of all-cause death was reduced by 4% for every 1 kg/m2 increase in BMI (RR=0.96, 95%CI 0.90 to 1.03, P=0.320), when BMI was greater than 27.5 kg/m2, the risk of all-cause death increased by 4% for every 1 kg/m2 increase in BMI (RR=1.04, 95%CI 1.03 to 1.05, P<0.001).ConclusionsThere is a paradox of obesity and a significant nonlinear relationship between BMI and all-cause mortality in the frailty elderly, with the lowest all-cause mortality in the frailty elderly at BMI 27.5-31.9 kg/m2. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusions.
ObjectiveTo systematically evaluate the dose-response relationship between coffee consumption and liver cancer risk. MethodsThe PubMed, Web of Science, Cochrane Library, EMbase, CNKI, VIP, WanFang Data, and CBM databases were searched from inception to December 2022. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. Meta-analysis was then performed by using Stata 17.0 software. ResultsFifteen studies (11 cohort studies and 4 case-control studies) involving 557 259 participants were included. The results of meta-analysis showed that coffee consumption was significantly negatively associated with the risk of liver cancer (RR=0.39, 95%CI 0.27 to 0.57, P<0.01). The dose-response meta-analysis showed a non-linear dose-response relationship between coffee consumption and the risk of liver cancer (P<0.01). Compared with people who did not drink coffee, people who drank 1 cup of coffee a day had a 25% lower risk of liver cancer (RR=0.75, 95%CI 0.67 to 0.83), and people who drank 2 cups of coffee a day had a 38% lower risk of liver cancer (RR=0.62, 95%CI 0.56 to 0.70). The risk of liver cancer decreased by 45% (RR=0.55, 95%CI 0.48 to 0.62) for 3 cups of coffee and by 51% (RR=0.49, 95%CI 0.43 to 0.56) for 4 cups of coffee. ConclusionCurrent evidence suggests that there is a nonlinear dose-response relationship between coffee consumption and the risk of liver cancer. These results indicate that habitual coffee consumption is a protective factor for liver cancer. Due to the limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusion.
This article briefly introduces the status and problems of research and application on medical professionalism in China; proposes the concept of translational medicine and the challenges of introduction of translational medicine to physician professionalism research and translation. Some measurements or approaches to promote research translation on medical professionalisms are proposed to shorten the distance from research outcomes to practical application, in order to carry out evidence-based construction of modern medical professionalism of Chinese characteristics and build a harmonious doctor-patient relationship.
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.
The β-secretase is one of prospective targets against Alzheimer's disease (AD). A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of Hydroethylamines (HEAs) as β-secretase inhibitors was established using Topomer CoMFA. The multiple correlation coefficient of fitting, cross validation and external validation were r2=0.928, qloo2=0.605 and rpred2=0.626, respectively. The 3D-QSAR model was used to search R groups from ZINC database as the source of structural fragments. As a result, a series of R groups with relatively high activity contribution was obtained to design a total of 15 new compounds, with higher activity than that of the template molecule. The molecular docking was employed to study the interaction mode between the new compounds as ligands and β-secretase as receptors, displaying that hydrogen bond and hydrophobicity played important roles in the binding affinity between the new compounds and β-secretase. The results showed that Topomer CoMFA and Topomer Search could be effectively used to screen and design new molecules of HEAs as β-secretase inhibitors, and the designed compounds could provide new candidates for drug design targeting AD.
The relationship between doctors and patients becomes a public hot topic recently, which becomes more prominent during the reforming and transition of the health care system. The emergence of evidence-based medicine corresponds to the requirement of the clinical practice brought by the transition of the health care system. It will play an important role in improving the relationship between doctors and patients. The promotion of evidence-based practice will be helpful to alleviate the conflict between doctors and patients and to increase the quality of health care.