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The quality evaluation of the blind method is to evaluate the clinical blind data obtained from clinical trials adopting the blind method and judge the effectiveness of the blind method by investigating the blind effect of different blind objects. A successful blind method can avoid the influence of subjective factors on the test results of subjects and researchers to a certain extent. The quality evaluation of the blind method can reflect not only the effectiveness of the blind method but also the accuracy and credibility of clinical trial results. In recent years, randomized controlled trials have been widely used in the evaluation of the clinical efficacy of traditional Chinese medicine (TCM), but the quality of the implementation of blind methods is uneven, and the evaluation criteria have not yet been formed. In this paper, the data collection methods, calculation principles, advantages, and disadvantages of two quantitative quality evaluation methods of blind methods, namely James Blinding Index (JBI) and Bang Blinding Index (BBI), were introduced. The two indexes were analyzed in a randomized controlled trial of acupuncture and moxibustion to relieve postoperative oral pain. The calculation process of the results was demonstrated by R software and visualized by forest map. At the same time, a tool table was designed to facilitate the collection of evaluation data of blind methods in TCM clinical trials at different stages. Finally, the necessity and feasibility of quality evaluation of blind method in TCM research were discussed to provide a basis for evaluating and improving the quality of blind method implementation in TCM clinical trials.
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Trials within cohorts (TwiCs) are design methods derived from randomized controlled trials (RCTS). They have been widely used in chronic disease areas such as tumors and cardiovascular diseases. The basis of the TwiCs design is a prospective cohort of specific diseases. When RCTS need to be implemented, some patients meeting the inclusion and exclusion criteria are randomly sampled from the cohort to receive "trial interventions", while the remaining patients in the cohort who meet the inclusion and exclusion criteria continue to receive conventional treatment as control groups. By comparing the efficacy differences between the intervention measures of the trial group and the control group, the efficacy of intervention measures was evaluated. Within the cohort, the same process could be repeated to carry out multiple RCTS, so as to evaluate different intervention measures or compare the efficacy of different doses or timing of interventions. Compared with classical RCTS, TwiCs make it easier to recruit patients from the cohort and have higher external validity, providing a new research paradigm for improving the efficiency and applicability of RCTS in clinical practice. However, TwiCs may also face the challenge of poor compliance of patients in the cohort. Researchers need to take effective measures to control these patients in the design and operation of TwiCs. This article focused on the methodological key points during the implementation of TwiCs, including multi-stage informed consent (patients are informed of consent at three stages: entering the cohort, entering the trial group, and after the trial), randomization procedures (only random sampling of patients from the cohort to receive "trial interventions"), sample size calculation, and statistical analysis methods. The article also compared the differences between TwiCs and traditional RCTS and illustrated TwiCs research design and analysis with examples, so as to provide new research ideas and methods for clinical researchers.
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Target trial emulation, using observational data to emulate a target trial, applies the study design principles of randomized controlled trials to observational studies that aim to estimate the effect of an intervention. The advantage of target trial emulation is that observational data is used to emulate a target trial when it is not appropriate to conduct randomized controlled trials. Target trial emulation can control bias caused by the design of observational studies, and improve the effectiveness of causal inference from observational data. This paper introduced the methodological framework and key points in terms of eligibility criteria, treatment strategies, assignment procedures, grace period, outcomes, follow-up period, effect contrasts, and statistical plan for implementing target trial emulation. This article elucidated the feasibility and necessity of applying target trail emulation in the realm of traditional Chinese medicine researches, and highlighted the challenges encountered in its implementation, such as the need for specialized personnel, data collection and integration, and the control of confounding factors.
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Objective To analyze the risk factors associated with periprosthetic femoral fracture following hemiarthroplasty (HA) for displaced femoral neck fracture in aged patients.Methods From January 2013 to June 2016,120 patients over 80 years old were treated by HA for displaced femoral neck fractures.They were 45 males and 75 females,with an average age of 85.2 years (from 80 to 97 years).Their fractures were Garden type Ⅲ (72 cases) and Garden type Ⅳ (48 cases).The time from injury to operation averaged 5.1 days.The patients were divided into a fracture group and a non-fracture group according to the presence or absence of the periprosthetic fracture.The general data of the 2 groups were compared;multivariate logistic regression analyses were done to indentify the influencing factors associated with periprosthetic femoral fracture.Results The 120 patients obtained a mean follow-up of 26.1 months (from 13 to 48 months).Periprosthetic femoral fracture occurred in 11 cases,giving an overall incidence of 9.2% (11/120).Compared with the non-fracture group,the average age was significantly older,the incidence of past fractures was significantly higher,significantly more types of uncemented stem were used,and American Society of Anesthesiologists (ASA) grading was significantly more severe for the fracture group (P < 0.05).There were no significant differences between the 2 groups concerning the general data (P > 0.05).Multivariate Logistic regression analyses revealed that age [OR =1.268,95% CI (1.059,1.517),P =0.010] and type ofuncemented stem [OR =0.072,95% CI (0.008,0.625),P =0.017] were independent risk factors for periprosthetic fracture.Conclusions The incidence of periprosthetic femoral fracture in the elderly patients may be high following HA for femoral neck fractures.Since age and uncemented stem may be independent risk factors for periprosthetic femoral fracture,surgeons should pay enough attention to them in clinic.
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Objective To study the influence factors for HBV reinfection following liver transplantation.Methods 92 cases of liver transplantation were enrolled for open non-randomized clinical study.Given conventional OLTx and immunosuppressive agents and antibiotics to prevent infection etc,patients are divided into lamivudine alone and HBIG combined with lamivudine group.Observation of postoperative liver function,HBV serum markers,HBV DNA in PBMC,YMDD and HBV S gene mutation,liver tissue IH etc.Results In 92 cases of liver transplantation with HBV-related liver disease,hepatitis B recurrence rate was 4.35%(4/92).In lamivudine group the HBV infection rate was 35%(7/20);In combined therapy group the HBV infection rate was 6.94%(5/72).With preoperatively negative HBV DNA negative the hepatitis B recurrence rate was 0;With preoperatively positive HBV DNA,the postoperative HBV infection rate was 17.39%(12/69),which had cases with S gene or YMDD mutation.In patients with negative HBV DNA before and after operation,the HBV re-infection rate was 11.11%(1/9);In 5 cases with preoperative HBV DNA positive,the HBV infection rate was 4/5 after LTx;before and after operation HBV DNA are positive,the HBV infection rate was 100%(3/3);the preoperative HBV DNA positive and postoperative HBV DNA negative,the HBV infection rate was 50%(1/2).Conclusion To prevent HBV infection after LTx,lamivudine group easily leads to HBV re-infection than HBIG combined with lamivudine group.Preoperative serum HBV DNA positive,preoperative and postoperative HBV YMDD and S gene mutation are the primary factors affecting the HBV re-infection after operation.HBV DNA positive in PBMC is the source of HBV re-infection,but also the factor of recurrence of hepatitis B.