With the implementation of “Good Clinical Practice”, the quality of clinical trials in China has increased constantly and more importance has been attached to the protection of the subject. Large scale clinical trials are primarily featured by long-term intervention, large sample size, many participant organizations, different levels of investigators, long test periods, and lots of adverse events. Consequently, the protection of subject is full of extensive complexities and difficulties and currently there is little experience to refer to. Hence, the article introduces the subject’s protection method adopted in the National Program Subject of Secondary Prevention Clinical Trial about Effect of Qi Shen Tonifying Qi on Myocardial Infarction (MISPS-TCM).
Objective To observe the serumlevel of neuron-specific enolase( NSE) in patients with pulmonary encephalopathy and its changes after treatment with mechanical ventilation. Methods Twentyone patients with pulmonary encephalopathy were enrolled. Glasgow coma scale( GCS) , serumNSE level, and arterial blood gas were evaluated at three time-points: before mechanical ventilation, after 12 hours mechanical ventilation, and the moment of consciousness. Results 18 patients recovered consciousness, and 3 patients remained in persistent coma and died. GCS and arterial blood gas improved obviously after 12 hours mechanical ventilation. Meanwhile, the serumNSE concentration decreased significantly after 12 hours mechanical ventilation [ ( 24. 54 ±6. 65) μg/L] and at the moment of consciousness [ ( 14. 19 ±2. 91) μg/L] compared with before mechanical ventilation( P lt; 0. 05, P lt; 0. 01) . Conclusion Dynamic measurment of serumNSE may be a useful biomarker for assessing the severity of cerebral injury and predicting prognosis.
Objective To develop a behavioral assessment scale for medication management plans in women of childbearing age with epilepsy and to test its reliability and validity. Methods Based on the Theory of Planned Behavior, a pool of questionnaire items was initially drafted through literature review and focus group discussions. A two-round Delphi expert consultation was conducted with 15 experts to form a test version of the behavioral assessment scale for medication management plans in women of childbearing age with epilepsy (including 27 items and 5 dimensions). Convenience sampling was used to conduct surveys among women of childbearing age with epilepsy in some tertiary hospitals in Chuxiong, Shenzhen and Wuhan from February to May 2024 (the first time) and from June to October 2024 (the second time). ResultsThe effective recovery rates of the two rounds of questionnaires were 95.5% and 94.6%, respectively. The final scale included 24 items and 5 dimensions, with good reliability and validity: the content validity index (S-CVI) was 0.934, Cronbach's α coefficient was 0.876, split-half reliability was 0.819, and test-retest reliability was 0.901; exploratory factor analysis extracted 5 factors (cumulative variance explained rate 73.97%, item load 0.42~0.85), and confirmatory factor analysis showed that the model had good fit (χ2/df=1.849, RMSEA=0.075, CFI, GFI, AGFI, IFI, TLI all>0.85). Conclusion The scale meets the reliability and validity standards and can be used to assess the medication management plans and behaviors of women of childbearing age with epilepsy.
Non-rigid registration plays an important role in medical image analysis. U-Net has been proven to be a hot research topic in medical image analysis and is widely used in medical image registration. However, existing registration models based on U-Net and its variants lack sufficient learning ability when dealing with complex deformations, and do not fully utilize multi-scale contextual information, resulting insufficient registration accuracy. To address this issue, a non-rigid registration algorithm for X-ray images based on deformable convolution and multi-scale feature focusing module was proposed. First, it used residual deformable convolution to replace the standard convolution of the original U-Net to enhance the expression ability of registration network for image geometric deformations. Then, stride convolution was used to replace the pooling operation of the downsampling operation to alleviate feature loss caused by continuous pooling. In addition, a multi-scale feature focusing module was introduced to the bridging layer in the encoding and decoding structure to improve the network model’s ability of integrating global contextual information. Theoretical analysis and experimental results both showed that the proposed registration algorithm could focus on multi-scale contextual information, handle medical images with complex deformations, and improve the registration accuracy. It is suitable for non-rigid registration of chest X-ray images.
ObjectiveThis study aimed to revise the perioperative recovery scale for integrative medicine (PRSIM) based on item response theory (IRT). MethodsUnder the guidance of IRT, a total of 349 patient data collected during the development of the original version of PRSIM at Guangdong Provincial Hospital of Chinese Medicine were used. Principal component analysis was performed using SPSS 18.0 software to test the unidimensionality. The R language was utilized for parameter estimation, including discrimination coefficient, difficulty parameters and information content, as well as drawing item characteristic curves to assess item quality and estimate item functioning differences. A comprehensive screening process was carried out by combining expert consultations, patient evaluations, and discussions within a core group. ResultsThe degree of discrimination of all items ranged from ?0.535 to 2.195. The difficulty coefficient ranged from ?10.343 to 5.461, and the average information content of all items ranged from 0.043 to 1.075. Based on the criteria for parameter selection, nine items were retained. The results of expert consultations indicated the removal of 5 items and the modification of 7 items. After discussion within the core group, a final decision was made to remove 5 items. ConclusionBased on a synthesis of IRT and expert consultation feedback, and following discussions within the core group, a revised version comprising 15 items is retained and modified from the original 20 items.
Objective To evaluate the reliability and validity of IBS-QOL scale in irritable bowel syndrome (IBS) patients. Methods IBS-QOL scale was applied to survey the quality of life of 123 IBS patients. The split-half and internal consistency method were used to evaluate the reliability, and with the construct method to evaluate the validity. Results The split-half reliability was 0.86. Cronbach’s α-coefficient of all domains was between 0.71 and 0.89 except body image and food avoidance; In the correlation analysis, the correlations between items and its subscale structure were above 0.60 (except interference with activity), but there were no correlations between items and other subscale structure. Eight components from factorial analysis were in accordance with theoretical structure.The cumulative contribution rate was 72.7%. Conclusions The reliability and validity of IBS-QOL scale are acceptable. It might be useful for us to assess the QOL of IBS patients in China.
ObjectiveTo explore the feasibility to use pain scale and arterial oxygen partial pressure(PaO2)as screening internal fixation indications for patients with multiple rib fractures. MethodsClinical data of 48 patients with multiple rib fractures who were admitted to Shanghai Pudong Hospital from September 2010 to February 2013 were retrospectively analyzed. Visual analogue scale (VAS) was used for pain assessment. Twenty-four patients whose VAS was greater than or equal to 6 and PaO2 was less than 60 mm Hg 3 days after injury were chosen as the experimental group, including 16 males and 8 females with their age of 49.29±15.73 years. Another 24 patients whose VAS was less than or equal to 5 and PaO2 was greater than 60 mm Hg 3 days after injury were chosen as the control group, including 19 males and 5 females with their age of 48.63±13.49 years. Patients in both groups received rib internal fixation with steel plates. Three days and 1 week after surgery respectively, VAS and PaO2 were compared between the 2 groups. ResultsIn the experimental group, VAS 3 days after surgery was significantly lower than preoperative VAS (4.09±0.93 vs. 8.21±1.18, P < 0.05), and VAS 1 week after surgery was significantly lower than preoperative VAS (3.20±0.98 vs. 8.21±1.18, P < 0.05). In the control group, there was no statistical difference between VAS 3 days after surgery and preoperative VAS (P > 0.05), and there was no statistical difference between VAS 1 week after surgery and preoperative VAS (P > 0.05). Three days after surgery, PaO2 of the experimental group was significantly higher than preoperative PaO2 (61.00±3.47 mm Hg vs. 53.00±3.97 mm Hg, P < 0.05). There was no statistical difference between PaO2 3 days after surgery and preoperative PaO2 in the control group (66.71±5.15 mm Hg vs. 66.00±5.00 mm Hg, P > 0.05). Three days after surgery, pneumonia occurred in 4 patients in the experimental group and 2 patients in the control group (χ2=0.762, P > 0.05). Three days after surgery, pain scale reduction of the experimental group was significantly higher than that of the control group (4.13±1.45 vs. 0.00±0.42, P < 0.05). One week after surgery, pain scale reduction of the experimental group was significantly higher than that of the control group (5.04±1.23 vs. 0.08±0.28, P < 0.05). Three days after surgery, PaO2 increase of the experimental group was significantly higher than that of the control group (7.42±3.59 mm Hg vs. 0.21±0.98 mmHg, P < 0.05). ConclusionIt's reasonable and feasible to use pain scale greater than or equal to 6 and PaO2 less than 60 mm Hg as internal fixation indications for patients with multiple rib fractures.
By analyzing the physiological structure and motion characteristics of human ankle joint, a four degree of freedom generalized spherical parallel mechanism is proposed to meet the needs of ankle rehabilitation. Using the spiral theory to analyze the motion characteristics of the mechanism and based on the method of describing the position with spherical coordinates and the posture with Euler Angle, the inverse solution of the closed vector equation of mechanism position is established. The workspace of mechanism is analyzed according to the constraint conditions of inverse solution. The workspace of the moving spherical center of the mechanism is used to match the movement space of the tibiotalar joint, and the workspace of the dynamic platform is used to match the movement space of subtalar joint. Genetic algorithm is used to optimize the key scale parameters of the mechanism. The results show that the workspace of the generalized spherical parallel mechanism can satisfy the actual movement space of human ankle joint rehabilitation. The results of this paper can provide theoretical basis and experimental reference for the design of ankle joint rehabilitation robot with high matching degree.
ObjectiveTo investigate the effects of pulmonary rehabilitation on the exercise capacity and quality of life in patients with stable chronic obstructive pulmonary disease (COPD) for a optimal strategy for pulmonary rehabilitation. MethodsOne hundred and six patients with COPD in stable stage were divided into group B (n=37), group C (n=36), and group D(n=33) based on GOLD 2011.Each group of patients were randomly subdivided into a control group(usual care), a pulmonary rehabilitation strategy group 1 (breathing training), and a pulmonary rehabilitation strategy group 2 (breathing training and exercise training), and they were intervened for 24 weeks.Pulmonary function(FEV1%pred), COPD Assessment Test (CAT), modified British Medical Research Council dyspnea scale(mMRC), BODE index and 6-minute walking distance(6MWD) were compared before and after intervention. ResultsAfter pulmonary rehabilitation intervening for 24 weeks, in group B and group C, pulmonary rehabilitation strategy group 2 showed the best effect, CAT, mMRC, BODE index, and 6MWD were proved significantly different before and after pulmonary rehabilitation (P < 0.05).In group D, all indexes had no significant difference between pulmonary rehabilitation strategy group 1 and group 2 before and after pulmonary rehabilitation (P > 0.05), but they were better than those of the control group.Correlation analysis showed that CAT score had significant correlation with FEV1 % pred, mMRC, BODE index and 6MWD (P < 0.01). ConclusionPatients with different subgroup of COPD based on GOLD 2011 may take different pulmonary rehabilitation strategies to achieve the optimal effect.
The deep learning-based automatic detection of epilepsy electroencephalogram (EEG), which can avoid the artificial influence, has attracted much attention, and its effectiveness mainly depends on the deep neural network model. In this paper, an attention-based multi-scale residual network (AMSRN) was proposed in consideration of the multiscale, spatio-temporal characteristics of epilepsy EEG and the information flow among channels, and it was combined with multiscale principal component analysis (MSPCA) to realize the automatic epilepsy detection. Firstly, MSPCA was used for noise reduction and feature enhancement of original epilepsy EEG. Then, we designed the structure and parameters of AMSRN. Among them, the attention module (AM), multiscale convolutional module (MCM), spatio-temporal feature extraction module (STFEM) and classification module (CM) were applied successively to signal reexpression with attention weighted mechanism as well as extraction, fusion and classification for multiscale and spatio-temporal features. Based on the Children’s Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) public dataset, the AMSRN model achieved good results in sensitivity (98.56%), F1 score (98.35%), accuracy (98.41%) and precision (98.43%). The results show that AMSRN can make good use of brain network information flow caused by seizures to enhance the difference among channels, and effectively capture the multiscale and spatio-temporal features of EEG to improve the performance of epilepsy detection.