ObjectiveTo investigate the establishment of a risk nomogram model for predicting vagus excitatory response in patients with functional epilepsy after radiofrequency thermocoagulation.MethodsA total of 106 patients with epilepsy admitted to the neurosurgery department of our hospital from January 2016 to June 2020 were selected and divided into the Vagus excitatory response (VER) group and the non-VER group according to their occurrence or absence. Logistic regression analysis was used to screen out the risk factors of VER during SEEG-guided Percutaneous radiofrequency thermocoagulation (PRFT) in patients with functional epilepsy, and R software was used to establish a histogram model affecting VER in SEEG-guided PRFT. Bootstrap method was used for internal verification. C-index, correction curve and ROC curve were used to evaluate the prediction ability of the model.ResultsLogistic regression analysis showed that age [OR=0.235, 95%CI (0.564, 3.076)], preoperative fugl-meyer score [OR=4.356, 95%CI (1.537, 6.621)], depression [OR=0.995, 95%CI (1.068, 7.404)], and lesion range [OR=1.512, 95%CI (0.073, 3.453)] were independent risk factors for the occurrence of VER in PRFT under the guidance of SEEG (P<0.05), and were highly correlated with the occurrence of VER in PRFT. Based on the above six indicators, a SEEG-guided colograph model of VER risk in PRFT was established, and the model was validated internally. The results showed that the C-index of the modeling set and validation set were 0.779 [95%CI (0.689, 0.869)] and 0.782 [95%CI (0.692, 0.872)], respectively. The calibration curves of the two groups fit well with the standard curves. The areas under the ROC curve (AUC) of the two groups were 0.779 and 0.782 respectively, which proved that the model had good prediction accuracy.ConclusionFor patients with functional epilepsy requiring seeg-guided PRFT therapy, age, preoperative Fugl-meyer score, depression and lesion range should be taken into full consideration to comprehensively assess the incidence of VER, and early intervention measures should be taken to reduce and reduce the incidence, which has good clinical application value.
Objective To establish a purified model of rat retinal ganglion cells （RGCs） cultured by serum-free medium，and provide a good cell model to investigate the damage of RGCs in glaucoma，retinal ischemia，and degenerative retinopathy. Methods Two monoclonal antibodies，anti-rat SIRP（OX-41）against rat macrophage and antibody against rat Thy-1（OX-7），were used to purify and characterize RGCs from 1-3-day old Sprague-Dawley（SD）rats by means of two-step filtration.Purified RGCs were cultured in serum-free neurobasal medium containing B27 and ciliary neurotrophic factor（CNTF） meeting the neuronal cellrsquo;s special requirements.Photomicrographs illustration，immunfluorescence staining of Thy-1，calcein-acetoxymethyl ester（calcein-AM）fluorescence images were used to observe and identify cultured retinal cells and purified RGCs. Results Among the primary cultured rat retinal cells，91% were retinal neurons.Protuberances of RGCs were seen after cultured for 24 hours.At the4th to 8th day，many cells had uniform configuration，large body，and long protuberances. At the 14th day，over 60% cells maintained viability.Immunoflurescence staining of Thy-1 showed the purity of RGCs was about 90%. The results of calcein-AM staining，which stained the living cells only，showed large cell body of RGCs and most of RGCs had a protuberance whose length was twice longer than the diameter of the cells. Conclusion RGCs cultured by serum-free medium has uniform size，good configuration，and high purity，which is adapt to the research of damage of RGCs caused by various factors and to evaluate the protective effects of neuroprotective agents. (Chin J Ocul Fundus Dis, 2006, 22: 200-203)
Electrocardiogram (ECG) is a noninvasive, inexpensive, and convenient test for diagnosing cardiovascular diseases and assessing the risk of cardiovascular events. Although there are clear standardized operations and procedures for ECG examination, the interpretation of ECG by even trained physicians can be biased due to differences in diagnostic experience. In recent years, artificial intelligence has become a powerful tool to automatically analyze medical data by building deep neural network models, and has been widely used in the field of medical image diagnosis such as CT, MRI, ultrasound and ECG. This article mainly introduces the application progress of deep neural network models in ECG diagnosis and prediction of cardiovascular diseases, and discusses its limitations and application prospects.
ObjectiveTo understand patients’ cognition of third-party mediation model for medical disputes, analyze the factors influencing the trust of patients on third-party mediation, and propose recommendations for building third-party mediation mechanisms. MethodsFrom November 2013 to April 2014, we referred past literature to design a relevant questionnaire on the cognition of third-party mediation for medical disputes. Patients who had reached the end of the treatment were surveyed by random cluster sampling. The raw data were put into the computer for statistical analysis by SPSS 18.0. ResultsAfter giving out 500 questionnaires, we acquired 486 effective questionnaires. The result showed that 61.52% of the patients knew of third-party mediation; 55.35% of the patients considered that thirdparty mediation should be set in and supervised by the court or judicial administrative department; if the mediation failed, 57.41% of the patients chose to resolve the dispute through legal channels, and 67.90% of the patients tended to confirm the force of mediation conclusion by arbitration; 70.58% of the patients considered that mediators should have professional background of medicine and law; 73.05% of the patients tended to take conclusions of forensic identification as the basis for mediation; 64.81% of the patients were biased to take Tort Liability Act as the basis for determining the compensation; 53.70% of the patients believed that financial allocations could solve the fund problems of third-party mediation, while 38.48% of the patients thought the funds should be provided by insurance companies; 91.15% of the patients thought the medical institutions should purchase medical liability insurance, and 54.32% of the patients thought insurance companies should not intervene the process of meditation. Conclusions Government should provide financial allocations to ensure the funds of third-party mediation. Besides, medical insurance should be brought in as a supplement. Medical institutions should purchase medical liability insurance to solve problems caused by medical disputes. Third-party mediation should be set in and supervised by the court or the judicial administrative department. Mediators should have professional background of medicine and law. Conclusions of forensic identification should be the basis for third-party mediation.
Objective To explore the application effect of 3D printed heart models in the training of young cardiac surgeons, and evaluate their application value in surgical simulation and skill improvement. MethodsEight young cardiac surgeons were selected form West China Hospital as the trainees. Before training, the Hands-On Surgical Training-Congenital Heart Surgery (HOST-CHS) operation scores of the 8 cardiac surgeons were obtained after operating on 2 pig heart models of ventricular septal defect (VSD). Subsequently, simulation training was conducted on a 3D printed peri-membrane VSD heart model for 6 weeks, once a week. After the training, all trainees completed 2 pig heart VSD repair surgeries. The improvement of doctors’ skills was evaluated through survey questionnaires, HOST-CHS scores, and operation time after training. ResultsBefore the training, the average HOST-CHS score of the 8 trainees was 52.2±6.3 points, and the average time for VSD repair was 54.7±7.1 min. During the 6-week simulation training using 3D printed models, the total score of HOST-CHS for the 8 trainees gradually increased (P<0.001), and the time required to complete VSD repair was shortened (P<0.001). The trainees had the most significant improvement in scores of surgical cognition and protective awareness. The survey results showed that trainees were generally very satisfied with the effectiveness of 3D model simulation training. Conclusion The 3D printed VSD model demonstrates significant application advantages in the training of young cardiac surgeons. By providing highly realistic anatomical structures, 3D models can effectively enhance surgeons’ surgical skills. It is suggested to further promote the application of 3D printing technology in medical education, providing strong support for cultivating high-quality cardiac surgeons.
Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. ResultsTaking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.
ObjectiveTo systematically review mortality risk prediction models for acute type A aortic dissection (AAAD). MethodsPubMed, EMbase, Web of Science, CNKI, WanFang Data, VIP and CBM databases were electronically searched to collect studies of mortality risk prediction models for AAAD from inception to July 31th, 2021. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Systematic review was then performed. ResultsA total of 19 studies were included, of which 15 developed prediction models. The performance of prediction models varied substantially (AUC were 0.56 to 0.92). Only 6 studies reported calibration statistics, and all models had high risk of bias. ConclusionsCurrent prediction models for mortality and prognosis of AAAD patients are suboptimal, and the performance of the models varies significantly. It is still essential to establish novel prediction models based on more comprehensive and accurate statistical methods, and to conduct internal and a large number of external validations.
The present paper is to analyze the trend of sinus heart rate RR interphase sequence after a single ventricular premature beat and to compare it with the two parameters, turbulence onset (TO) and turbulence slope (TS). Based on the acquisition of sinus rhythm concussion sample, we in this paper use a piecewise linearization method to extract its linear characteristics, following which we describe shock form with natural language through cloud model. In the process of acquisition, we use the exponential smoothing method to forecast the position where QRS wave may appear to assist QRS wave detection, and use template to judge whether current cardiac is sinus rhythm. And we choose some signals from MIT-BIH Arrhythmia Database to detect whether the algorithm is effective in Matlab. The results show that our method can correctly detect the changing trend of sinus heart rate. The proposed method can achieve real-time detection of sinus rhythm shocks, which is simple and easily implemented, so that it is effective as a supplementary method.
Objective To detect expression of NF-κB in the inner retina and in vestigate the inhibitoryeffect of pyrrolidine dithiocarbamate on retinal neovascularization in rats. Methods The rat models with retinopathy were set up un der the hypoxia condition, and fluorescein fundus angiography (FFA) was used to observe the retinal neovascularization. The expressions of NF-κB in the inner retina in rats with and without neovascularization were detected by immunohisto chemical method. PDTC was intraperitoneally injected in rats with neovascularization to observe the expression of NF-κB in the inner retina and the effect on retinal neovascularization. Results Hypoxia induced NF-κB activation in the retinal glial cells and endothelial cells. But immuno-staining intensity for NF-κB and adhesion molecules were reduced by PDTC intraperitoneal injection. Retin al angiogenesis in rats were suppressed effectively (P＜0.05). Conclusions NF-κB activation correlates with retinal neovascularization closely. PDTC may inhibit the NF-κB activation and prove beneficial in the treatment of ischemic neovascularization. (Chin J Ocul Fundus Dis，2003，19：201-268)
Complete three-dimensional (3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography (CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs,i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete 3D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.