ObjectiveTo compare the biomechanical characteristics of self-made nickel-titanium shape memory alloy stepped plate with calcaneal plate and cannulated compression screws in fixing calcaneal osteotomy.MethodsCalcaneal osteotomy was operated on 6 fresh-frozen lower limbs collected from donors. Then three kinds of fixation materials were applied in random, including the self-made nickel-titanium shape memory alloy stepped plate (group A), calcaneal plate (group B), and cannulated compression screws (group C). Immediately after fixation, axial loading of 20-600 N and 20 N/s in speed was introduced to record the biomechanical data including maximum displacement, elastic displacement, and maximum load. Then fatigue test was performed (5 Hz in frequency and repeat 3 000 times) and the same axial loading was introduced to collect the biomechanical data. Finally, the axial compression stiffness before and after fatigue test were calculated.ResultsThere was no significant difference in the axial compression stiffness between pre- and post-fatigue test in each group (P>0.05). However, the axial compression stiffness was significant higher in group A than that in groups B and C both before and after fatigue test (P<0.05). No significant difference was found between group B and group C (P>0.05).ConclusionSelf-made nickel-titanium shape memory alloy stepped plate is better than calcaneal plate and cannulated compression screws in axial load stiffness after being used to fix calcaneal osteotomy.
Objective To evaluate initial experience with shape memory alloy stent as an alterative to colostomy in patients with intestinal obstruction of rectal cancer. Methods Twenty-one patients with acute and chronic rectal obstructions from malignant causes underwent stent placement. After rectal stent was slenderized in ice water, it was inserted into the strictured rectum by hand or sigmoidoscope. Nitinol mesh stent were deployed in hot water. Results Eighteen patients who had underwent rectal stent placement achieved clinical decompression within 5 hours. Colostomy underwent in 3 patients due to stent failure. Eighteen patients with stent were followed-up, 14 cases died in 56-720 days and 4 other cases were still alive without intestinal obstruction in 2-15 months. Conclusion Nitinol mesh stent may be useful in the management of terminal or high-risk surgical patients for palliative purposes shuning colostomy. Palliation of stent combined with chemotherapy and immunotherapy can be performed to improve survival.
Electrocardiogram (ECG) can visually reflect the physiological electrical activity of human heart, which is important in the field of arrhythmia detection and classification. To address the negative effect of label imbalance in ECG data on arrhythmia classification, this paper proposes a nested long short-term memory network (NLSTM) model for unbalanced ECG signal classification. The NLSTM is built to learn and memorize the temporal characteristics in complex signals, and the focal loss function is used to reduce the weights of easily identifiable samples. Then the residual attention mechanism is used to modify the assigned weights according to the importance of sample characteristic to solve the sample imbalance problem. Then the synthetic minority over-sampling technique is used to perform a simple manual oversampling process on the Massachusetts institute of technology and Beth Israel hospital arrhythmia (MIT-BIH-AR) database to further increase the classification accuracy of the model. Finally, the MIT-BIH arrhythmia database is applied to experimentally verify the above algorithms. The experimental results show that the proposed method can effectively solve the issues of imbalanced samples and unremarkable features in ECG signals, and the overall accuracy of the model reaches 98.34%. It also significantly improves the recognition and classification of minority samples and has provided a new feasible method for ECG-assisted diagnosis, which has practical application significance.
Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was proposed. Based on the idea of transfer learning, the algorithm leverages the correlation between diseases to transfer information of different disease prognostic models, constructs the effictive model of target disease of small samples with the aid of large data of related diseases, hence improves the prediction performance and reduces the requirement for target training sample quantity. The transLSTM algorithm firstly uses the related disease samples to pretrain partial model parameters, and then further adjusts the whole network with the target training samples. The testing results on MIMIC-Ⅲ database showed that compared with traditional LSTM classification algorithm, the transLSTM algorithm had 0.02-0.07 higher AUROC and 0.05-0.14 larger AUPRC, while its number of training iterations was only 39%-64% of the traditional algorithm. The results of application on sepsis revealed that the transLSTM model of only 100 training samples had comparable mortality prediction performance to the traditional model of 250 training samples. In small sample situations, the transLSTM algorithm has significant advantages with higher prediciton accuracy and faster training speed. It realizes the application of transfer learning in the prognostic model of critical disease with small samples.
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.
Glaucoma stands as the leading irreversible cause of blindness worldwide. Regular visual field examinations play a crucial role in both diagnosing and treating glaucoma. Predicting future visual field changes can assist clinicians in making timely interventions to manage the progression of this disease. To integrate temporal and spatial features from past visual field examination results and enhance visual field prediction, a convolutional long short-term memory (ConvLSTM) network was employed to construct a predictive model. The predictive performance of the ConvLSTM model was validated and compared with other methods using a dataset of perimetry tests from the Humphrey field analyzer at the University of Washington (UWHVF). Compared to traditional methods, the ConvLSTM model demonstrated higher prediction accuracy. Additionally, the relationship between visual field series length and prediction performance was investigated. In predicting the visual field using the previous three visual field results of past 1.5~6.0 years, it was found that the ConvLSTM model performed better, achieving a mean absolute error of 2.255 dB, a root mean squared error of 3.457 dB, and a coefficient of determination of 0.960. The experimental results show that the proposed method effectively utilizes existing visual field examination results to achieve more accurate visual field prediction for the next 0.5~2.0 years. This approach holds promise in assisting clinicians in diagnosing and treating visual field progression in glaucoma patients.
Objective To investigate the effectiveness of nickel-titanium shape memory staples in treating multiple metatarsal fractures. MethodsThe clinical data of 27 patients with multiple metatarsal fractures who were treated between January 2022 and June 2023 and met the selection criteria were retrospectively analysed. The cohort consisted of 16 males and 11 females, aged 33-65 years (mean, 47.44 years). The causes of injury included heavy object impact in 11 cases, traffic accidents in 9 cases, and crush in 7 cases. Simultaneous fractures of 2, 3, 4, and 5 bones occurred in 6, 6, 4, and 8 cases, respectively, with tarsometatarsal joint injury in 3 cases. Fixation was performed using staples for 16, 22, and 9 fractures in the metatarsal neck, shaft, and the base, respectively, and 5 tarsometatarsal joint injuries. Preoperative soft tissue injuries were identified in 8 cases and classified according to the Tscherne-Oestern closed soft tissue injury classification as type Ⅰ in 5 cases and type Ⅱ in 3 cases. One case of type Ⅱexhibited preoperative skin necrosis. The patients were treated with fixation using nickel-titanium shape memory staples. Complications and fracture healing were documented. At last follow-up, the American Orthopaedic Foot and Ankle Society (AOFAS) forefoot score was used to evaluate the function, and the visual analogue scale (VAS) score was used to evaluate the pain. Results The 27 patients were followed up 9-19 months (mean, 12.4 months). Postoperative X-ray films revealed no loss of fracture reduction, and all fractures achieved bony union. No internal fixator loosening, breakage, or other mechanical failures was observed. The mean fracture healing time was 3.13 months (range, 3-4 months). Postoperatively, 4 cases (2 of Tscherne-Oestern type Ⅰ, 2 of type Ⅱ) developed superficial skin necrosis, which resolved with dressing changes. No infection was observed in the remaining patients, and all wounds healed. At last follow-up, the AOFAS forefoot score ranged from 70 to 95, with an average of 86.6, of which 19 cases were excellent, 6 cases were good, and 2 cases were fair, with an excellent and good rate of 92.6%; the VAS score ranged from 0 to 3, with an average of 0.9, of which 24 cases were excellent, and 3 cases were good, with an excellent and good rate of 100%. Conclusion The use of nickel-titanium shape memory staples in the treatment of multiple metatarsal fractures can effectively protect local skin and soft tissues and minimize secondary damage associated with internal fixator insertion. It is a viable surgical option for management of multiple metatarsal fractures.
As one of the stimulus-response polymeric intelligent materials, shape memory polymers have been widely applied in biomedicine due to their better biocompatibility, higher controllability, stronger deformation restorability and biodegradability compared with shape memory alloys and shape memory ceramics. This review will introduce the structural principles of shape memory polymers and summarize their applications in the treatment of vascular diseases, especially in endovascular therapy. At the same time, the related technical problems and the future of shape memory polymers are prospected. With the continuous development of processing technology and materials, it can be predicted that shape memory polymers will be more widely used in the medical field.
ObjectiveTo evaluate the effects of sevoflurane and propofol on preoperative implicit and explicit memories in general anaesthesia patients of elective surgery. MethodsThe surgical inpatients in Sichuan Provincial People's Hospital were enrolled from December 2013 to May 2014, and were randomly divided into three groups (S, P, M). In Group S, anesthesia was induced and maintained with sevoflurane. In Group P, anesthesia was induced and maintained with propofol. Midazolam was not utilized throughout the whole anaesthesia for the above groups. Patients in Group S and Group P were given a list of test materials to remember and listen before the anesthesia. Within 12 to 36 hours after operation, memory was assessed, based on the Buchner's model applied on the process dissociation procedure (PDP) using a phrases task. The Group M was given the same test materials, and received test with the PDP in 12 to 36 hours before surgery. Value A and value R were used to represent the implicit memory score and the explicit memory score, respectively. ResultsA total of 150 patients were included, and 50 cases were included in each group. During testing, 2 cases were excluded, 3 cases were loss to follow-up, so finally 49 cases were included in the Group S, 47 cases in the Group P and 49 cases in the Group M. The results showed that there were significant differences in the implicit memory score (A) and the explicit memory score (R) among the three groups (all P values <0.05). The explicit memory score (R) of the Group M was higher than those of the Group P and Group S (all P values <0.05), the implicit memory score (A) in the Group M was higher than those of the Group S and Group P (all P values <0.05), and the implicit memory score (A) in the Group S was higher than that of the Group P (P<0.05). ConclusionPropofol and sevoflurane can decrease the score of explicit memory after anesthesia within 12 to 36 hours, and there are no significant differences in explicit memory between the two drugs. Both propofol and sevoflurane can decrease the score of implicit memory, but the influence of sevoflurane on the implicit memory is less than propofol within 12 to 36 hours.