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.
Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.
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.
The judgment of the type of arrhythmia is the key to the prevention and diagnosis of early cardiovascular disease. Therefore, electrocardiogram (ECG) analysis has been widely used as an important basis for doctors to diagnose. However, due to the large differences in ECG signal morphology among different patients and the unbalanced distribution of categories, the existing automatic detection algorithms for arrhythmias have certain difficulties in the identification process. This paper designs a variable scale fusion network model for automatic recognition of heart rhythm types. In this study, a variable-scale fusion network model was proposed for automatic identification of heart rhythm types. The improved ECG generation network (EGAN) module was used to solve the imbalance of ECG data, and the ECG signal was reproduced in two dimensions in the form of gray recurrence plot (GRP) and spectrogram. Combined with the branching structure of the model, the automatic classification of variable-length heart beats was realized. The results of the study were verified by the Massachusetts institute of technology and Beth Israel hospital (MIT-BIH) arrhythmia database, which distinguished eight heart rhythm types. The average accuracy rate reached 99.36%, and the sensitivity and specificity were 96.11% and 99.84%, respectively. In conclusion, it is expected that this method can be used for clinical auxiliary diagnosis and smart wearable devices in the future.
Sleep stage classification is essential for clinical disease diagnosis and sleep quality assessment. Most of the existing methods for sleep stage classification are based on single-channel or single-modal signal, and extract features using a single-branch, deep convolutional network, which not only hinders the capture of the diversity features related to sleep and increase the computational cost, but also has a certain impact on the accuracy of sleep stage classification. To solve this problem, this paper proposes an end-to-end multi-modal physiological time-frequency feature extraction network (MTFF-Net) for accurate sleep stage classification. First, multi-modal physiological signal containing electroencephalogram (EEG), electrocardiogram (ECG), electrooculogram (EOG) and electromyogram (EMG) are converted into two-dimensional time-frequency images containing time-frequency features by using short time Fourier transform (STFT). Then, the time-frequency feature extraction network combining multi-scale EEG compact convolution network (Ms-EEGNet) and bidirectional gated recurrent units (Bi-GRU) network is used to obtain multi-scale spectral features related to sleep feature waveforms and time series features related to sleep stage transition. According to the American Academy of Sleep Medicine (AASM) EEG sleep stage classification criterion, the model achieved 84.3% accuracy in the five-classification task on the third subgroup of the Institute of Systems and Robotics of the University of Coimbra Sleep Dataset (ISRUC-S3), with 83.1% macro F1 score value and 79.8% Cohen’s Kappa coefficient. The experimental results show that the proposed model achieves higher classification accuracy and promotes the application of deep learning algorithms in assisting clinical decision-making.
According to the characteristics of the diversified employment system of general hospitals, we have independently developed a set of personnel information platforms suitable for our hospital's operating model and work-flow which achieved establishing a novel big data management model for big personnel. After a year of trial operation, the big data management of personnel has completely covered the target management and requirements of the hospital, covering basic quality, public services, teaching work, medical work, scientific research, and other dimensions of information, which helped the hospital constructed a systematically networked and full-coveraged, personnel information system with strong early warning functions and incentives, enabling the reasonable utilization rate of human capital and continuous improvement of the quality of talent training.
ObjectiveTo study the preservation effect of true bone ceramics (TBC) prepared by high-temperature calcination of bovine bone on alveolar ridge of canine extraction socket.MethodsSix healthy Beagle dogs (aged 1.5-2 years) were selected to extract the second and fourth premolars of both mandibles and the second premolars of the maxilla. The left extraction socket was implanted with TBC as the experimental group, and the right side was implanted with the calcined bovine bone (CBB) as the control group, to observe the alveolar ridge preservation effect. Three dogs were euthanized after general observation at 1 and 6 months after operation respectively. After separating the maxilla and mandible, cone beam CT (CBCT) was performed to measure the average gray value of the graft site and the adjacent reference area (the area between the roots of the adjacent third premolar) and calculate the gray scale ratio between the bone graft site and the reference area. Histological observation was made on the bone graft site to evaluate the new bone formation.ResultsGeneral observation showed that the wounds of both groups were basically healed at 2 weeks after operation, and the bone graft materials were not exposed. The wounds healed well at 1 and 6 months after operation without swelling. The results of CBCT showed that the residual material was found in both groups at 1 month after operation, and no significant residual material was found in both groups at 6 months after operation, and the alveolar ridge height of the bone graft area was not significantly reduced. There was no significant difference in the bone mineral density between the experimental group and the control group. The gray scale ratios of the experimental group at 1 month and 6 months after operation were 0.97±0.14 and 0.93±0.06, respectively, and were 0.99±0.16 and 0.94±0.05 in control group, showing no significant difference between the two groups (t=?1.030, P=0.333; t=?0.770, P=0.466). HE staining observation showed that a large number of bone graft materials did not degrade and new bone formed around the grafts in both groups at 1 month after operation; the bone graft materials were absorbed and a large number of new bones were formed in both groups at 6 months after operation.ConclusionTBC can maintain bone mineral density and have good osteoconductivity in the alveolar ridge site preservation experiment of dogs, and can be used for alveolar ridge site preservation.
Taking advantages of the sparsity or compressibility inherent in real world signals, compressed sensing (CS) can collect compressed data at the sampling rate much lower than that needed in Shannon’s theorem. The combination of CS and low rank modeling is used to medical imaging techniques to increase the scanning speed of cardiac magnetic resonance (CMR), alleviate the patients’ suffering and improve the images quality. The alternating direction method of multipliers (ADMM) algorithm is proposed for multiscale low rank matrix decomposition of CMR images. The algorithm performance is evaluated quantitatively by the peak signal to noise ratio (PSNR) and relative l2 norm error (RLNE), with the human visual system and the local region magnification as the qualitative comparison. Compared to L + S, kt FOCUSS, k-t SPARSE SENSE algorithms, experimental results demonstrate that the proposed algorithm can achieve the best performance indices, and maintain the most detail features and edge contours. The proposed algorithm can encourage the development of fast imaging techniques, and improve the diagnoses values of CMR in clinical applications.
ObjectiveTo evaluate the applicability of SF-36 scale on assessment of quality of life in patient with breast cancer. MethodsThree hundreds and seventy-one patients with breast cancer in Department of Breast of First Affiliated Hospital of Xinjiang Medical University from June 2011 to January 2014 were treated and then surveyed with SF-36 scale, evaluating the feasibility, reliability, validity, ceiling effect, and floor effect. Results①The feasibility evaluation:Completion time of SF-36 scale was (12.1±3.2) min, finishing rate was 100%. ②The reliability evaluation:All the split-half reliability coefficients and the Cronbach's α were all above 0.8. All the internal consistency coefficients were all above 0.6. ③The validity analysis:All the Pearson coefficients were all above 0.7. Tow principal component were extracted by factor analysis, which accounted for 63.22% of total variance. After the maximum variance rotation, two common factors were generated, which was almost the same with the theory structure assumption of scale. ④Ceiling effect and floor effect:There was remarkable ceiling effect on bodily pain, which was 77.35%; there was obvious floor effect on role physical and mental health, which was 20.32% and 24.88%, respectively. ConclusionThe SF-36 scale is an useful scale for the evaluation of the quality of life among the patients with breast cancer, but individual items need to be further perfected according to the actual situation.
Objective To compare the quality of life after laparoscopic and open surgery for gastric stromal tumor patients. Methods We collected the data of the patients undergoing the gastric stromal tumor surgery from May 2011 to August 2016 in West China Hospital of Sichuan University, and compared the basic data, complications, micturition time, hospital stay time, bleeding volume and hospitalization expenses. SF-36 scale was used to evaluate the quality of life. Then, SPSS 19.0 software was used for data analysis. Results Eighty nine patients involving 31 laparoscopic patients and 58 open surgery patients were included. There was no statistical significance in basic line between two groups. The laparoscopic group had shorter micturition time and hospital stay time, less intraoperative bleeding and lower hospitalization costs, the differences between two groups were statistically significant (P<0.05). But there were no significant differences between two groups in the operation time and postoperative complication rate. The SF-36 quality of life scale of laparoscopic group and open surgery group were 737.7±68.3 and 665.1±138.1, respectively. The laparoscopic surgery group had higher scores in validity (VT), social function (SF) and mental health (MH) than those in open surgery group with significant differences (P<0.05). Conclusion Laparoscopic surgery is safe and effective for the patients with stromal tumor. Patients in laparoscopic group have shorter recovery time and higher quality of life than open surgery group. Due to the limited of study design, more high quality studies are needed to verify above conclusion.