Objectives To explore the quality of the reporting of randomized controlled trials (RCTs) of traditional Chinese medicine (TCM) for chronic fatigue syndrome (CFS).Methods We searched the Cochrane Central Register of Controlled Clinical Trials (CENTRAL) (The Cochrane Library, Issue 4, 2006), PubMed, EMbase, the Chinese Biomedical Database (CBMdisc), VIP Information, and China National Knowledge Infrastructure (CNKI) (from establishment to February 2007). We also checked the reference lists of included studies. The quality of the reporting of RCTs was assessed using the 22-item checklist of the CONSORT Statement and other self-established criteria. Results Thirty-eight RCTs were included. The word “randomization” was not present in any of the trials, and only 17 reports used a structured abstract. All trials did not report the scientific background and the rational for the trial, the estimation of the necessary sample size, the methods of allocation concealment and blinding, participant flow chart, ITT analysis, and ancillary analyses. Some authors misunderstood the diagnostic criteria and inclusion criteria, some selected inappropriate control interventions, and some did not clearly describe their statistical methods or used incorrect methods. All 38 trials reported positive outcomes, few reported adverse effects. No report included a general interpretation of the new trial’s results in the context of current evidence in their discussion section, and none mentioned the limitations of the study, the clinical and research implications or the external validity of the trial findings. Conclusion The overall reporting quality of RCTs of TCM for CFS is poor. Defects are found in each section of the reports. Researchers and journal editors should learn and use the principles and methods of evidence-based medicine—especially the use of a transparent prospective clinical trial register and the CONSORT Statement—to improve the design, conduct and report TCM trials.
The pace of modern life is accelerating, the pressure of life is gradually increasing, and the long-term accumulation of mental fatigue poses a threat to health. By analyzing physiological signals and parameters, this paper proposes a method that can identify the state of mental fatigue, which helps to maintain a healthy life. The method proposed in this paper is a new recognition method of psychological fatigue state of electrocardiogram signals based on convolutional neural network and long short-term memory. Firstly, the convolution layer of one-dimensional convolutional neural network model is used to extract local features, the key information is extracted through pooling layer, and some redundant data is removed. Then, the extracted features are used as input to the long short-term memory model to further fuse the ECG features. Finally, by integrating the key information through the full connection layer, the accurate recognition of mental fatigue state is successfully realized. The results show that compared with traditional machine learning algorithms, the proposed method significantly improves the accuracy of mental fatigue recognition to 96.3%, which provides a reliable basis for the early warning and evaluation of mental fatigue.
Mental fatigue is the subjective state of people after excessive consumption of information resources. Its impact on cognitive activities is mainly manifested as decreased alertness, poor memory and inattention, which is highly related to the performance after impaired working memory. In this paper, the partial directional coherence method was used to calculate the coherence coefficient of scalp electroencephalogram (EEG) of each electrode. The analysis of brain network and its attribute parameters was used to explore the changes of information resource allocation of working memory under mental fatigue. Mental fatigue was quickly induced by the experimental paradigm of adaptive N-back working memory. Twenty-five healthy college students were randomly recruited as subjects, including 14 males and 11 females, aged from 20 to 27 years old, all right-handed. The behavioral data and resting scalp EEG data were collected simultaneously. The results showed that the main information transmission pathway of the brain changed under mental fatigue, mainly in the frontal lobe and parietal lobe. The significant changes in brain network parameters indicated that the information transmission path of the brain decreased and the efficiency of information transmission decreased significantly. In the causal flow of each electrode and the information flow of each brain region, the inflow of information resources in the frontal lobe decreased under mental fatigue. Although the parietal lobe region and occipital lobe region became the main functional connection areas in the fatigue state, the inflow of information resources in these two regions was still reduced as a whole. These results indicated that mental fatigue affected the information resources allocation of working memory, especially in the frontal and parietal regions which were closely related to working memory.
Objective To identify, describe, and evaluate the evidence of traditional Chinese medicine (TCM) interventions for cancer-related fatigue (CRF) using an evidence mapping approach. Methods The CNKI, WanFang Data, VIP, SinoMed, PubMed, Web of Science and Embase databases were electronically searched to collect studies on TCM interventions for CRF from inception to June 4, 2024. Evidence mapping was employed to present the characteristics of study populations, interventions, studies included in systematic review/meta-analysis (SR/MA), and conclusions. Results A total of 94 randomized controlled trials (RCT) and 17 SR/MA/network MA were included. The number of publications has shown an overall fluctuating upward trend in the past 15 years. The RCT included literature with a high focus on mixed cancers, involving a total of 51 TCM therapeutic measures, including 40 herbal treatments, 5 external TCM treatments, and 5 TCM integrative therapies. The outcome indicators were classified into 14 categories, with the most frequent ones being CRF scores, TCM syndrome scores, clinical efficacy, quality of life scores, immune function indicators, adverse event rates, and serum indicators. The SR/MA included 7-81 original studies with sample sizes of 551-7 547 cases, involving 5 intervention measures: herbal medicine (9 studies), moxibustion (3 studies), TCM injection (2 studies), moxibustion (2 studies), and acupuncture (1 study). The quality of RCT and SR/MA was generally low, and the evidence quality was low. Most studies showed that TCM interventions for CRF had potential efficacy, but there was still a lack of definitive clinical evidence. Conclusion The results suggest that TCM interventions for CRF have advantages but also problems. There is still a lack of high-quality research. More large-sample, multicenter RCT and high-quality SR/MA are needed to further explore the advantages of TCM interventions for CRF and provide strong support for the effectiveness and safety of TCM interventions for CRF.
Objective To explore the current situation and influencing factors of self-regulatory fatigue in maintenance hemodialysis (MHD) patients, so as to provide good dialysis treatment for MHD patients, reduce their level of self-regulated fatigue and improve their quality of life. Methods The convenient sampling method was used to select the MHD patients in the Wenjiang Hemodialysis Center of West China Hospital of Sichuan University between April 12 and April 30, 2022. The patients were investigated by self-made basic information scale and self-regulatory fatigue scale. Results A total of 131 patients were included. The average score of self-regulatory fatigue was 53.47±6.45, cognitive dimension was 20.21±2.39, emotional dimension was 20.85±2.85, behavioral dimension was 12.40±3.63. The results of multiple linear stepwise regression analysis showed that age, duration of dialysis and educational background could inversely predict the score of self-regulatory fatigue (P<0.05). Conclusions MHD patients have a high level of self-regulatory fatigue. Clinical nurses can make individual dialysis programs according to the actual situation of MHD patients, improve their self-regulated level and physical and mental health, and improve the quality of life of MHD patients.
ObjectiveTo investigate the methodological and reporting quality of clinical trials involving Xiaoyao San for chronic fatigue syndrome.
MethodsWe searched PubMed, CBM, CNKI, VIP and WanFang Data to identify randomized controlled trials (RCTs) about Xiaoyao San for chronic fatigue syndrome. The methodological and reporting quality of included RCTs was respectively evaluated according to the assessment tool of risk of bias of the Cochrane Handbook 5.1.0 and the CONSORT 2010 statement, combined with complementary assessment by the characteristic indicators of traditional Chinese medicine (TCM). The methodological and reporting quality of included case series study was respectively assessed by the methods recommended by the Britain's National Institute for Clinical Excellence (NICE) and the STROBE statement.
ResultsA total of 27 clinical trials were included, involving 11 RCTs and 16 case series studies. According to the assessment tool of risk of bias of the Cochrane Handbook, 54.5% of the RCTs performed proper random method, 9.1% conducted allocation concealment and blinding, 72.7% selected intention-to-treat (ITT) analysis without the report of loss to follow-up, and no RCT existed selective reports. Corresponding to the characteristic indicators of TCM, 54.5% of the RCTs did not conduct TCM syndrome diagnosis, the curative effect standard of TCM syndrome was discrepant, and no RCT was multi-center study. The CONSORT 2010 statement indicated that no RCT explained sample size estimation, implementation details of randomization, flow diagram of participant, use of ITT and clinical trial registration. According to the items recommended by Britain's NICE, 6.25% of the case series studies were multi-center, 81.25% did not report clear inclusion and exclusion criteria, and no case series study performed continuous patient recruitment and stratification analysis of outcome. The STROBE statement indicated that no case series study reported research design, sample size, flow chart, bias, limitations and generalizability.
ConclusionThe quality of clinical trials about Xiaoyao San for chronic fatigue syndrome is still low in methodological and reporting aspects. It is suggested that the future clinical trials should be conducted with references of CONSORT statement and STROBE statement, to propel the modernization and internationalization of TCM.
The purpose of this study is to compare the differences among neck muscle fatigue evaluation algorithms and to find a more effective algorithm which can provide a human factor quantitative evaluation method for neck muscle fatigue during bending over the desk. We collected surface electromyography signal of sternocleidomastoid muscle of 15 subjects using wireless physiotherapy Bio-Radio when they bent over the desk using memory pillows for 12 minutes. Five algorithms including mean power frequency, spectral moments ratio, discrete wavelet transform, fuzzy approximation entropy and the complexity algorithms were used to calculate the corresponding muscle fatigue index. The least squares method was used to calculate the corresponding coefficient of determination R2 and slope k of the linear regression of the muscle fatigue metric. The coefficient of determination R2 evaluates anti-interference ability of algorithms. The maximum vertical distance Lmax which is obtained by the Kolmogorov-Smirnov test for the slopes k evaluates the ability to distinguish fatigue of algorithms. The results indicate that in the aspect of anti-interference ability, the fuzzy approximation entropy has the largest R2 when using memory pillows with different heights. When the fuzzy approximate entropy is compared with average power frequency or the discrete wavelet transform, the differences are significant (P < 0.05). In terms of distinguishing the degree of fatigue, the approximate entropy is still the largest, with a maximum of 0.496 7. Fuzzy approximation entropy is superior to other algorithms in ability of anti-interference and distinguishing fatigue. Therefore, fuzzy approximation entropy can be used as a better evaluation algorithm in the evaluation of cervical muscle fatigue.
The mechanical properties of nitinol iliac vein stent (NIVS) have been studied by many scholars at home and abroad, but the study on the mechanical properties of iliac vein stent under different release scales has not been reported yet. Based on the finite element analysis method, the mechanical properties of three self-developed NIVS were studied to reveal the influence of stent diameters (12, 14, 16 mm) and different release scales (80%, 90%) on its strength, fatigue life and vein wall biomechanical properties. With an increases in the release scales, the equivalent elastic strain, fatigue strength safety factors, and vessel wall equivalent stress exhibited a downward trend, while the most stressed cross-section coincided with the arc of stent-connecting rods. Through 30, 60 and 90 days’ animal test, a narrowed vascular model was established in the iliac veins of 12 pigs, and the developed iliac vein stents were implanted to comprehensively evaluate the safety and effectiveness of the stent, and at the same time the mechanical properties of stents were verified to provide important reference for the type inspection and clinical trials of follow-up products.
In the present paper, the contribution of the largest principal component and the number of principal component needed for accumulative contribution 95% are selected as indices of electroencephalogram (EEG) in mental fatigue state in order to investigate the relationship between these parameters and mental fatigue. The experimental results showed that the contribution of the largest principal component of EEG signals increased in the prefrontal, frontal and central areas, while the number of principal component needed for accumulative contribution decreased by 95% with the increasing mental fatigue level. The parameters of singular system of EEG signals can be regarded as useful features for the estimation of mental fatigue and have larger application value in the study of mental fatigue.
The objective of this study is to combine troponin and indicators of cardiac acoustics for synthetically evaluating cardiac fatigue of rabbits, analyzing exercise-induced cardiac fatigue (EICF) and exercise-induced cardiac damage (EICD). New Zealand white rabbits were used to conduct a multi-step swimming experiments with load, reaching an exhaustive state for evaluating if the amplitude ratio of the first to second heart sound (S1/S2) and heart rate (HR) during the exhaustive exercise would decrease or not and if they would be recovered 24-48 h after exhaustive exercise. The experimental end point was to complete 3 times of exhaustions or death from exhaustion. Circulating troponin I (cTnI) were detected from all of the experimental rabbits at rest [(0.02±0.01) ng/mL], which, in general, indicated that there existed a physiological release of troponin. After the first exhaustive swim, cTnI of the rabbits increased. However, with 24-hour rest, S1/S2, HR, and cTnI of the tested rabbits all returned toward baseline levels, which meant that the experimental rabbits experienced a cardiac fatigue process. After repeated exhaustion, overloading phenomena were observed, which led to death in 3 out of 11 rabbits, indicating their cardiac damage; the troponin elevation under this condition could be interpreted by pathological release. Evaluation of myocardial damage can not be based on the troponin levels alone, but can only be based on a comprehensive analysis.
