Objective To investigate the effects of children’s crawling-promotion-training-robot on gross motor function and cognitive function in children with global developmental delay (GDD). Methods A total of 40 children with GDD admitted to the Department of Rehabilitation Medicine, Children’s Hospital of Nanjing Medical University were selected as the research subjects. By envelope method, the children were randomly and equally divided into experimental group and control group, with 20 cases in each group. The experimental group received children’s crawling-promotion-training-robot combined with conventional rehabilitation therapy, while the control group received manual crawling training combined with conventional rehabilitation therapy. Before and after treatment, the scores of Gross Motor Function Measure Scale-88 (GMFM-88) and Gesell Developmental Scale (GDS) were respectively used to evaluate gross motor function and cognitive function. Results There was no significant difference in gender (χ2=0.100, P=0.752) and age (t=0.053, P=0.962) between the two groups. Before treatment, there was no significant difference in GMFM-88 and GDS scores between the two groups (P>0.05). After treatment, there were statistically significant differences in GMFM-88 and GDS scores between the two groups (P<0.05). The comparison within the group showed that there were statistically significant differences in GMFM-88 and GDS scores between the two groups before and after treatment. Conclusion Children’s crawling-promotion-training-robot is more effective than manual crawling training in improving gross motor function and cognitive function in children with GDD.
Epilepsy is a neurological disease with disordered brain network connectivity. It is important to analyze the brain network mechanism of epileptic seizure from the perspective of directed functional connectivity. In this paper, causal brain networks were constructed for different sub-bands of epileptic electroencephalogram (EEG) signals in interictal, preictal and ictal phases by directional transfer function method, and the information transmission pathway and dynamic change process of brain network under different conditions were analyzed. Finally, the dynamic changes of characteristic attributes of brain networks with different rhythms were analyzed. The results show that the topology of brain network changes from stochastic network to rule network during the three stage and the node connections of the whole brain network show a trend of gradual decline. The number of pathway connections between internal nodes of frontal, temporal and occipital regions increase. There are a lot of hub nodes with information outflow in the lesion region. The global efficiency in ictal stage of α, β and γ waves are significantly higher than in the interictal and the preictal stage. The clustering coefficients in preictal stage are higher than in the ictal stage and the clustering coefficients in ictal stage are higher than in the interictal stage. The clustering coefficients of frontal, temporal and parietal lobes are significantly increased. The results of this study indicate that the topological structure and characteristic properties of epileptic causal brain network can reflect the dynamic process of epileptic seizures. In the future, this study has important research value in the localization of epileptic focus and prediction of epileptic seizure.
ObjectiveTo assesse the effectiveness of anterior cervical discectomy and fusion with Cage alone in treating multi-level cervical degenerative disease. MethodsBetween August 2010 and August 2012, 62 eligible patients with multi-level cervical degenerative disease were treated, and the clinical data were reviewed. Of 62 patients, 32 underwent anterior cervical discectomy and fusion with Cage alone (group A), and 30 underwent anterior cervical discectomy and fusion with plate fixation (group B). Both groups showed no significant difference in gender, age, disease duration, lesion types, and affected segments (P>0.05), it had comparability. Clinical outcomes were assessed using Japanese Orthopedic Association (JOA) score and visual analogue scale (VAS) score; the fused segment height, subsidence rates of Cages, global cervical lordosis, and fusion rates were also compared. ResultsThe operation time of group B[(109.7±11.2) minutes] was significantly more than group A[(87.8±6.9) minutes] (t=-2.259, P=0.037). Primary healing of incisions was obtained in all patients of 2 groups. All patients were followed up; the follow-up period ranged from 8 to 27 months (mean, 15.8 months) in group A, and from 9 to 28 months (mean, 16.4 months) in group B. There was no complication and internal fixation failure. The JOA score and VAS score were significantly improved at last follow-up when compared with preoperative scores in 2 groups (P<0.05). According to Robinson standard for axial symptom severity, the results were excellent in 20 cases, good in 9, fair in 2, and poor in 1, with an excellent and good rate of 90.63% in group A; the results were excellent in 19 cases, good in 7, fair in 3, and poor in 1, with an excellent and good rate of 86.67% in group B; and no significant difference was found between 2 groups (χ2=0.765, P=0.382). The fused segment height at immediate after operation and at last follow-up and global cervical lordosis at last follow-up were significantly improved when compared with preoperative ones in 2 groups (P<0.05). There was no significant difference (P>0.05) between groups A and B in the Cage subsidence height[(1.4±0.9) mm vs. (1.2±1.6) mm], Cage subsidence rate[9.52% (8/84) vs. 7.59% (6/79)], and fusion rate[95.24% (80/84) vs. 96.20% (76/79)]. ConclusionAnterior cervical discectomy and fusion with Cage alone can obtain good clinical results and radiologic indexes, avoid plate-related complications and reduce operation time. It is a safe and effective surgical option in the treatment of multi-level cervical degenerative disease.
Objective The aim of this study was to describe the trends in the burden of breast cancer in women of all ages in China from 1990 to 2021, compare it with the global burden of breast cancer in women, and predict the burden of disease in the next 15 years. Methods Based on the open data of the Global Burden of Disease (GBD) in 2021, the incidence, prevalence, mortality and disability-adjusted life years (DALYs) of breast cancer among women in China and the world were analyzed. Joinpoint was used to calculate annual percentage change (APC) and average annual percentage change (AAPC) to reflect the changing trend of disease burden. An autoregressive composite moving average (ARIMA) model was used to predict the disease burden of breast cancer in women from 2022 to 2036. Results From 1990 to 2021, the age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR) of female breast cancer in China showed an increasing trend, with an average annual increase of 2.400 7% and 2.334 8%, respectively, and the age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) showed a decreasing trend. The average annual decline was 0.290 0% and 0.198 3%, respectively. Meanwhile, ASIR and ASPR of global female breast cancer also showed an increasing trend, with an average annual increase of 0.474 9% and 0.3445 2% respectively, while ASMR and ASDR showed a decreasing trend, with an average annual decrease of 0.425 2% and 0.321 8% respectively. Among them, there were differences in the impact of age on the burden of female breast cancer. The peak of ASIR and ASPR appeared in the age group of 50 to 69 years old, and generally increased with the increase of age, and then decreased when reaching the peak. ASMR and ASDR increased with age. In the following 15 years, the prevalence of breast cancer in women in China and globally showed an increasing trend, while the mortality rate showed a decreasing trend. Conclusion From the analysis of the disease burden from 1990 to 2021, breast cancer has a huge harm to women, and the incidence of young and middle-aged women is high, the death rate of middle-aged and elderly women is high, and the disease time is long, which brings a heavy psychological and economic burden to patients and society. From the trend forecast for the next 15 years, the prevalence of breast cancer in women in China and the world will increase, while the mortality rate will decrease slightly, but the decrease is not large, which will bring huge public health challenges and put higher requirements on the prevention and control of the disease. To reduce the disease burden of breast cancer, comprehensive strategies for disease control are needed, including prevention of risk factors at the primary care level, screening of at-risk populations, and quality medical services.
Objective To analyze the spatiotemporal trends in hepatitis B-related mortality and disability-adjusted life years (DALYs) attributable to high body mass index (BMI) at the global, regional, and national levels. Methods We extracted data on hepatitis B-related mortality numbers, DALYs, age-standardised mortality rates (ASMR), and age-standardised DALY rates (ASDR) attributed to high BMI from the GBD 2021 database for the period 1990-2021, stratified by gender, age, country, and social demographic index (SDI). Time trends were assessed using estimated annual percentage change (EAPC), and decomposition analysis and frontier analysis were employed to identify the drivers of burden changes and leading countries. Inequality indicators (inequality slope index SII and concentration index CI) were used to measure health disparities across SDI levels, and the Bayesian age period cohort model (BAPC) was applied to predict disease trends up to 2050. Results The global burden of hepatitis B disease attributable to high BMI continues to rise. In 2021, the number of DALYs reached 499 900 (four times that of 1990), and the number of deaths was five times that of 1990. The burden and rate of increase were most pronounced in Asia: in 2021, East Asia recorded 7 919.70 deaths (95%UI 2 984.05 to 14 386.39) and 257 954.31 DALYs (95%UI 97 807.17 to 482 232.54), ranked highest among the 21 GBD regions; From 1990 to 2021, South Asia recorded the fastest increase in ASMR (EAPC=4.99, 95%CI 4.83 to 5.16) and the highest growth rate in ASDR (EAPC=4.92, 95%CI 4.74 to 5.10); at the national level, China and the United States had the heaviest burden. Countries with medium SDI had the highest burden, peaking at an SDI of 0.65. Global and regional decomposition analyses indicated that epidemiological changes were the primary drivers of the increased burden. The CI and SII values derived from inequality analyses of ASDR and ASMR had both increased, indicating worsening health inequalities. Frontier analysis further confirmed that certain countries, such as Tonga and Mongolia, bear a significantly higher burden than expected for their developmental level, demonstrating marked disparities in disease burden across nations. The BAPC model predicts that the burden attributable to high BMI will continue to rise in the absence of interventions. Conclusion High BMI has become an important risk factor for hepatitis B-related diseases globally, with the burden particularly pronounced in Asian regions and middle-income countries. Health inequalities must not be overlooked. Precise interventions should be implemented based on regional, gender, and age differences.
Heart sounds are critical for early detection of cardiovascular diseases, yet existing studies mostly focus on traditional signal segmentation, feature extraction, and shallow classifiers, which often fail to sufficiently capture the dynamic and nonlinear characteristics of heart sounds, limit recognition of complex heart sound patterns, and are sensitive to data imbalance, resulting in poor classification performance. To address these limitations, this study proposes a novel heart sound classification method that integrates improved Mel-frequency cepstral coefficients (MFCC) for feature extraction with a convolutional neural network (CNN) and a deep Transformer model. In the preprocessing stage, a Butterworth filter is applied for denoising, and continuous heart sound signals are directly processed without segmenting the cardiac cycles, allowing the improved MFCC features to better capture dynamic characteristics. These features are then fed into a CNN for feature learning, followed by global average pooling (GAP) to reduce model complexity and mitigate overfitting. Lastly, a deep Transformer module is employed to further extract and fuse features, completing the heart sound classification. To handle data imbalance, the model uses focal loss as the objective function. Experiments on two public datasets demonstrate that the proposed method performs effectively in both binary and multi-class classification tasks. This approach enables efficient classification of continuous heart sound signals, provides a reference methodology for future heart sound research for disease classification, and supports the development of wearable devices and home monitoring systems.
In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.
Objective To assess the prevalence of malnutrition in patients with advanced non-small cell lung cancer (NSCLC) using the Global Leadership Initiative on Malnutrition (GLIM) criteria, analyze its associated factors, and explore the adverse effects of malnutrition on advanced NSCLC patients in multiple aspects. Methods Patients with NSCLC who were hospitalized for the first time in the Department of Oncology, Shangjin Hospital, West China Hospital, Sichuan University between January and December 2021 were retrospectively selected as the study objects. Malnutrition assessment was carried out in all patients according to GLIM criteria, and the current situation and related factors of malnutrition were analyzed. The Barthel index scale was used to compare the daily activity ability between the malnourished group and the non-malnourished group, the Quality-of-Life Questionnaire-Core 30 scale was used to compare the quality of life between the two groups, and the adverse reactions of the two groups were compared by the hospital information system course records. Results According to GLIM diagnostic criteria, 134 of 285 patients (47.0%) were diagnosed with malnutrition. The results of binary multiple logistic regression analysis showed that age [60-69 vs. <60 years old: odds ratio (OR)=2.323, 95% confidence interval (CI) (1.277, 4.397); ≥70 vs. <60 years old: OR=10.816, 95%CI (4.185, 27.959)], previous medical history [OR=2.740, 95%CI (1.313, 5.717)], and albumin level [OR=0.905, 95%CI (0.848, 0.965)] were associated with malnutrition in patients with advanced NSCLC (P<0.05). The daily activity ability and quality of life in the malnourished group were significantly worse than those in the non-malnourished group (87.57±12.48 vs. 91.82±6.77, P<0.05; 76.22±11.52 vs. 83.96±9.75, P<0.05), and the incidence of adverse reactions in the malnourished group was higher than that of the non-malnourished group (50.7% vs. 31.8%, P<0.05). Conclusions The prevalence of malnutrition in patients with advanced NSCLC is high, and advanced age, previous medical history and albumin are related factors of malnutrition in patients with advanced NSCLC. Combined malnutrition may have adverse effects on mobility, quality of life and adverse effects of anti-tumor therapy in advanced NSCLC patients.
Objective To evaluate the effects of knowledge about malaria after the implementation of Global Fund Malaria Project in Chongqing for future prevention and treatment of malaria. Methods Four counties were selected from the counties of Global Fund Malaria Project of Chongqing. Three towns were randomly selected in each selected county; one primary school and one high school were investigated in each selected town; one class was randomly selected in each selected school; and 30 students in each selected class were randomly selected. Then, three villages were randomly selected in each selected county; one group of villagers were randomly selected in each selected village; and 200 local residents were randomly investigated in each selected villager group. Before and after implementation of Global Fund Malaria Project, their awareness of malaria was investigated using a questionnaire. Results After implementation of the project, the pupils’ average awareness rate of knowledge about malaria rose from 58.94% to 89.96% (χ2=179.48, Plt;0.01) with average increase of 31.02%; the middle school students’ average awareness rate of rose from 52.83% to 86.06% (χ2=196.64, Plt;0.01) with average increase of 33.23%; the local residents’ average awareness rate of knowledge about malaria rose from 56.74% to 83.89% (χ2=1 281.70, Plt;0.01) with average increase of 27.15%. The accuracies of all respondents after project implement was higher than before. After the implementation, the accuracies of malaria transmission route, main clinical symptoms, and seeing doctor while malaria occurring were all above 80%, but the accuracy of the index of best preventive methods was less than 50%. Conclusion The implementation of Global Fund Malaria Project in Chongqing increase the awareness rate of malaria knowledge but the relevant education should be strengthened, so as to promote general population’s awareness of malaria prevention.
ObjectiveTo investigate the clinical significance of cardiac function index (CFI) and global ejection fraction (GEF), derived from single-indicator transpulmonary thermodilution technique, in assessment of cardiac function in critically ill patients. MethodsA prospective clinical observational study was conducted in the Intensive Care Unit of the First Affiliated Hospital of Guangzhou Medical University. Between January 2012 and December 2012, 39 patients who underwent PiCCO monitoring were recruited, including 18 cases with left ventricular systolic dysfunction and 21 cases without left ventricular systolic dysfunction. Both groups underwent transpulmonary thermodilution measurements and transthoracic cardiac ultrasonography. Pearson correlation analysis was conduced to assess the correlation between left ventricular ejection fraction (LVEF) and CFI and GEF. ROC curve was established to calculate the predicted threshold of CFI and GEF for diagnosing cardiac insufficiency. ResultsLVEF was significantly correlated with CFI and GEF (r=0.553, P < 0.005; r=0.468, P < 0.005). The area under ROC curve of CFI, GEF and LVEF for diagnosing cardiac insufficiency was 0.885, 0.862 and 0.903, respectively (P > 0.05 for comparison). The cut-off value of CFI for predicting cardiac insufficiency was 4.25/min, with a sensitivity of 77.8% and a specificity of 88.9%. The cut-off value of GEF for predicting cardiac dysfunction was 19.5/min, with a sensitivity of 88.9% and a specificity of 66.7%. ConclusionCFI and GEF measured by transpulmonary thermodilution correlate well with LVEF assessed by transthoracic echocardiography, both can be used for assessment of left ventricular systolic function.