As one of the standard electrophysiological signals in the human body, the photoplethysmography contains detailed information about the blood microcirculation and has been commonly used in various medical scenarios, where the accurate detection of the pulse waveform and quantification of its morphological characteristics are essential steps. In this paper, a modular pulse wave preprocessing and analysis system is developed based on the principles of design patterns. The system designs each part of the preprocessing and analysis process as independent functional modules to be compatible and reusable. In addition, the detection process of the pulse waveform is improved, and a new waveform detection algorithm composed of screening-checking-deciding is proposed. It is verified that the algorithm has a practical design for each module, high accuracy of waveform recognition and high anti-interference capability. The modular pulse wave preprocessing and analysis software system developed in this paper can meet the individual preprocessing requirements for various pulse wave application studies under different platforms. The proposed novel algorithm with high accuracy also provides a new idea for the pulse wave analysis process.
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.
N-of-1 trial design offers a methodologically sound approach to determining optimum treatment for an individual patient and solves some limitations of randomized controlled trials. This design could offer an efficient method of reaching a personal treatment regime tailored to suit individual needs and preferences. The paper introduces practical application, objects and the implementation process of N-of-1 trial, to explore its design points and implementation.
Compared with traditional medical devices, artificial intelligence medical devices face greater challenges in the process of clinical trials due to their related characteristics of artificial intelligence technology. This paper focused on the challenges and risks in each stage of clinical trials on artificial intelligence medical devices for assisted diagnosis, and put forward corresponding coping strategies, with the aim to provide references for the performance of high-quality clinical trials on artificial intelligence medical devices and shorten the research period in China.
ObjectiveTo establish a reasonable risk evaluation tool in order to guide the clinical prevention of accidental extubation.
MethodsWe collected all the tube types in our hospital, and according to the extubation consequence severity and risks, we designed the extubation risk factor items and formed the professional tables for scoring. Sixteen medical experts and 16 nursing experts were chosen to determine the scores for two rounds following the "Delphi" method. Five patients that had extubation accidentally were selected for evaluation, and 56 clinical cases provided feedbacks after evaluation. Then, the risk was set into 3 ranks:light (≤ 8 points), medium (9-12 points) and high (≥ 13 points). Finally, literature review and collection of the prevention measures were carried out, and the final "Accidental Extubation Risk Evaluation Table" was completed.
ResultsAltogether, 283 patients were evaluated using the table in 23 departments of the hospital, among whom 121 were at mild risk, 76 were at medium risk and 86 were at high risk. Measures were taken accordingly, and no accidental extubation occurred.
ConclusionThe evaluation table is reasonable, with which accidental extubation risk evaluation is standardized, and the safety of catheter nursing is enhanced.
ObjectiveTo explore the technique of preoperative evaluation of video electroencephalography (VEEG) electrode fixation method.MethodsThe electrode fixation method was modified using a simple and easy-to-manufacture 3M decompression sticker designed by ourselves.ResultsUsing the modified electrode fixation method, compared with the traditional fixation method, the electrode displacement, shedding rate and pain score of the children were significantly lower (P<0.05). The incidence of skin pressure sore by traditional fixation method was 7.03%. The rate of improvement after release was 3.37%. Although it was not statistically significant, the incidence of pressure ulcers were reduced.ConclusionsEffectively reduce the adverse reactions such as electrode displacement, shedding, pain and skin pressure sore caused by wearing the electrode for a long time. It has the advantages of being simple, fast, safe, stable and humanized, and it is worthy of clinical promotion.
Simulation-based medical education is becoming increasingly common. In this paper, the status and goal of SBME development is analyzed after a brief introduction of SBME. Secondly, the essentiality and possibility of bringing SBME to a situated paradigm are clarified, because there are rich implications for situated cognition as the theory foundation of SBME. As a main discussion point, eight practical situated designing principles for SBME in theoretical and practical contexts are then expounded. Finally, a specific attitude toward the relationship between theory and practice for the SBME teachers is also elucidated.
The data collection form is a bridge in-between the original studies and the final systematic reviews. It’s the basis for data analyses, directly related to the results and conclusions of systematic reviews, and plays an important role in systematic reviews. There are strict requirements of data collection forms in making Cochrane systematic reviews. In this article, the authors introduce their experiences regarding to the design of data collection form.
Objective To systematically review the prevalence of depression and anxiety among health care workers in designated hospitals during the COVID-19 pandemic. Methods The Cochrane Library, PubMed, EMbase, Web of Science, CNKI, WanFang Data, VIP, and CBM databases were electronically searched to collect cross-sectional studies on the prevalence of depression and anxiety among health care workers from December 2019 to April 2021. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 14.0 software. Results A total of 21 cross-sectional studies were included, involving 38 372 participants. Meta-analysis results showed that during the COVID-19 epidemic, the prevalence of depression and anxiety among health care workers in designated hospitals were 31.00% (95%CI 0.25 to 0.37) and 44.00% (95%CI 0.34 to 0.53). The results of subgroup analysis showed that individuals of female, married, bachelor degree or above, nurses, junior professional titles, and non-first-line medical staff had higher prevalence of depression and anxiety. Conclusions During the COVID-19 pandemic, the incidence of depression and anxiety among health care workers in designated hospitals remain high. Therefore, more attention should be paid to the mental health of health care workers in designated hospitals. Due to the limited quantity and quality of included studies, more high-quality studies are needed to verify the above conclusions.
With the encouragement of national policy on drug and medical device innovation, multi-center clinical trials and multi-regional clinical trials are facing an unprecedented opportunity in China. Trials with a multi-center design are far more common at present than before. However, it should be recognized there still exists shortcomings in current multi-center trials. In this paper, we summarize the problems and challenges and provide corresponding resolutions with the aim to reduce heterogeneity between study centers and avoid excessive center effects in treatment. It is urgent to develop design, implementation and reporting guidelines to improve the overall quality of multi-center clinical trials.
