Objective: To investigate the relationship between physical development indicators and the onset and progression of myopia among children and adolescents, so as to provide theoretical support for coordinated vision and physical health management. Methods: A prospective cohort study was conducted. In September 2022, 3 102 students from grade one in primary school to grade three in junior high school (five year primary school and four year junior high school) from six schools in Huantai County, Shandong Province, were selected using multistage cluster random sampling method to participate in an epidemiological survey on myopia, with follow up completed in September 2023. Follow up value minus baseline value( d ) was used to assess changes in physical development and vision indicators. Multivariate Logistic regression analysis was used to examine the relationship between physical development indicators and the incidence of myopia. Generalized linear models were established to analyze the relationship between physical development indicators and changes in d spherical equivalent (SE) and d axial length (AL) . Results: Multivariate Logistic regression analysis showed that, after adjusting for factors such as gender, age, and baseline body mass index, the third ( Q 3)and fourth ( Q 4)quartiles of d height showed increased risks of myopia onset within one year compared to the first quartile( Q 1) ( OR =1.85,95% CI =1.18-2.88; OR =1.74,95% CI =1.09-2.78,both P ＜0.05). Results from the generalized linear model indicated that, after adjusting for confounding factors such as gender, age, and baseline SE, d SE was negatively correlated with d height and d weight in children and adolescents ( β =-0.024, 95% CI =-0.031 to -0.018; β =-0.006, 95% CI =-0.011 to -0.001), d AL was positively correlated with d height and d weight in children and adolescents ( β =0.011, 95% CI =0.008-0.013; β =0.005, 95% CI =0.003-0.007) (all P ＜0.05). Conclusions Physical development indicators in children and adolescents were associated with the onset and progression of myopia. Dynamic monitoring and early intervention of myopia should be strengthened for children and adolescents with rapid height and weight gain to achieve coordinated management of myopia and physical development.

Objective:To establish daily quality assurance workflow based on self-developed phantom to ensure MR-linac performance such as beam accuracy, MR image guidance accuracy, and the clinical treatment workflow to enhance the efficiency of daily quality assurance (QA).Methods:The self-developed phantom was made by 3D printer and used in conjunction with Daily QA-MR detector array. After CT-sim scanning, a treatment plan was designed and transmitted to the accelerator, tests were performed such as image guidance accuracy, beam output and beam quality, the differences in daily QA results between the self-developed phantom and standard phantom recommended by the manufacturer were analyzed by using paired t-test. Results:A total of 24 sets results were collected, the image guide accuracy in the X, Y and Z directions between standard and self-made phantom were (0.1±0.4), (-0.14±0.16), (0.07±0.05) mm and (0±0.02), (-0.02±0.02), (0.02±0.01) mm, respectively, and the differences were statistically significant ( P<0.001, =0.001 and <0.001). Daily QA-MR detector array beam measurement results including output, symmetry, beam quality and field size were -0.11%±0.20%, -0.10%±0.19%, -0.01%±0.08%, (0.4±0.1) mm and (0.2±0.1) mm, respectively. The new process saved 25% (approximately 9 min) of the time compared to the standard process. Conclusions:The new daily QA process for MR-linac is performed based on self-developed phantom and Daily QA-MR detector array. The accuracy and sensitivity meet the requirements and can improve the QA efficiency.

Objective:This study investigated the expression of C-X-C motif chemokine receptor 3 (CXCR3) on CD45RO? T cells in the peripheral blood of patients with Alzheimer′s disease (AD) and its association with clinical features.Methods:A total of 41 AD patients and 30 age-and sex-matched healthy controls (HCs) were recruited from the Department of Neurology at the Medical Division of PLA General Hospital between September 2022 and March 2024. Flow cytometry was used to quantify CXCR3 expression on CD45RO? T cell subsets in peripheral blood. Dementia severity in AD patients was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Spearman correlation analysis examined the relationship between CD45RO?CXCR3? T cell levels and cognitive function in the AD group. Receiver operating characteristic (ROC) curve analysis determined the predictive utility of CD45RO?CXCR3? T cells for AD, quantified by the area under the curve (AUC).Results:Compared to healthy controls, AD patients exhibited significantly elevated levels of CD8?CD45RO?CXCR3? T cells [17.8% (7.2%, 40.3%) vs. 8.2% (5.1%, 12.3%), Z=-2.59, P<0.05]. However, no significant differences were observed for CD4?CD45RO?CXCR3? T cells, CD4?CD45RO?CXCR3? T cells, or CD8?CD45RO?CXCR3? T cells ( P>0.05). Spearman correlation analysis revealed a negative correlation between CD8?CD45RO?CXCR3? T cell levels and cognitive scores (MMSE: r=-0.72, P<0.05; MoCA: r=-0.70, P<0.05). ROC analysis demonstrated an AUC of 0.81 for CD8?CD45RO?CXCR3? T cells in predicting AD, with a sensitivity of 59.0% and specificity of 93.3%. Conclusions:CXCR3 expression is significantly upregulated on CD8?CD45RO? T cells in AD patients, and its levels correlate with cognitive impairment severity. These findings suggest that CD8?CD45RO?CXCR3? T cells may serve as a potential biomarker for AD diagnosis and progression monitoring.

Objective:To observe any relationships among the nutritional status, the social abilities, and the eating and drinking ability of children with severe cerebral palsy.Methods:A total of 334 children with cerebral palsy, classified as level IV or V according to the gross motor function classification system, were enrolled. Their social ability, and their eating and drinking performance were assessed using the eating and drinking ability classification system (EDACS) or the mini-EDACS classification, and their nutritional status was also evaluated. Logistic regressions were evaluated seeking any useful inter-relationships.Results:The incidence of nutritional deficiency among the children was estimated at 71.5%, with 4.5% overweight or obese. 80.5% of the children exhibited mild to profound impairment in their social abilities, with another 15.0% on the borderline. The eating and drinking ability of 57.5% was rated as mildly to moderately dysfunction, with another 13.5% of severe dysfunction. The boys had a higher rate of nutritional deficiency and excess compared to the girls ( OR=2.41, P≤0.05). And eating and drinking ability was observed to improve with age ( OR=2.41, P≤0.05), while the average standard score for social ability improved ( OR=1.21, P≤0.05). Those nutritionally deficient or in excess had a significantly higher rate of impaired social ability compared to healthy children ( OR=1.38, P≤0.05). A higher standard score for social living ability was associated with a lower risk of severe eating and drinking dysfunction ( OR=0.45, P≤0.05). Conclusions:Malnutrition, impaired social ability, and impaired eating and drinking ability are common in children with severe cerebral palsy, and these three factors are inter-related. Boys have a significantly higher rate of nutritional deficiency or excess compared to girls. However, eating and drinking ability improves with age.

OBJECTIVES: To evaluate the impact of HBV infection on pre- and postpartum health-related quality of life (HRQoL) in pregnant women. METHODS: A prospective matched cohort consisting of 70 HBV-infected and 70 healthy pregnant women was recruited from the Fifth Affiliated Hospital of Guangzhou Medical University between April 17 and September 25, 2023. HRQoL of the participants was assessed at 16-24 weeks of gestation, between 32 weeks and delivery, and 5-13 weeks postpartum. Mixed linear models were used for evaluating temporal trends of HRQoL changes, and univariate ANOVA with multiple linear regression was used to identify the predictors of HRQoL. RESULTS: Compared with healthy pregnant women, HBV-infected pregnant women had consistently lower total HRQoL scores across all the 3 intervals, with the lowest scores observed between 32 weeks of gestation and delivery, during which these women had significantly reduced mental component scores (74.27±13.43 vs 80.21±12.9, P=0.009) and postpartum mental (76.52±16.19 vs 85.02±6.51, P<0.001) and physical component scale scores (77.17±14.71 vs 83.09±10.1, P=0.009). HBV infection was identified as an independent risk factor affecting HRQoL during late pregnancy and postpartum periods. Additional independent risk factors for postpartum HRQoL reduction included self-pay medical expenses, spouse's neutral attitude toward the current pregnancy, and preexisting comorbidities (all P<0.05). CONCLUSIONS HRQoL of pregnant women deteriorates progressively in late pregnancy, and HBV infection exacerbates reductions of physical function and role emotion in late pregnancy and after delivery, suggesting the importance of targeted interventions for financial burdens, partner support and comorbid conditions to improve HRQoL of pregnant women with HBV infection.
Humans ; Female ; Pregnancy ; Quality of Life ; Prospective Studies ; Postpartum Period ; Hepatitis B, Chronic/psychology* ; Adult ; Pregnancy Trimester, Third ; Pregnancy Trimester, Second ; Pregnancy Complications, Infectious

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal inflammatory disease, which not only affects the digestive tract, but also involves extraintestinal organs and tissues such as joints and eyes, and ultimately endangers human health and affects the quality of life of patients. With the development of information technology, there is an increasing application of digital therapeutics in the management of IBD. This article aims to comprehensively analyze the characteristics, use, and challenges of digital therapeutics in the management of IBD, and explore its potential to improve treatment adherence, disease surveillance, and improve patients' quality of life.

Objective:To analyze the correlation between near work, screen time, outdoor time and myopia in children based on objective monitoring technology and to explore the influencing factors related to myopia in children.Methods:A cross-sectional study was conducted.From October 2022 to March 2023, the purposive sampling method was used to select 596 children in Grade 2 and Grade 3 from two primary schools in Shandong Province as study subjects.Eye-Monitor technology of eye-use behavior based on artificial intelligence was used to quantify parameters of near work, screen time and outdoor time.The eye-use behavior parameters were compared within each subject and between non-myopic and myopic children on weekdays and weekends.A multivariate binary logistic regression model was constructed to analyze the influencing factors related to myopia.The study protocol was approved by the Medical Ethics Committee of the Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine (No.HEC-HY-2022023KY).Written informed consent was obtained from the legal guardian of each subject.Results:For each subject, the proportion of near work time on weekdays was greater than on weekends, the proportion of time spent looking at cell phones, computer screens, and outdoor activities was smaller, the duration of single continuous near eye use was longer, the tilt angle of the head in sitting position was greater, and the light intensity was stronger, showing statistically significant differences ( t=19.427, -9.964, -5.916, -10.470, 2.211, 2.898, 15.061; all P<0.05).During weekdays, compared with the non-myopia group, the myopia group had longer total near work duration, longer single continuous near eye use duration, shorter outdoor activity duration, closer eye use distance, larger proportion of near work time, and smaller proportion of outdoor activity time, showing statistically significant differences (all P<0.05).During weekends, compared with the non-myopia group, the myopia group had longer time spent looking at cell phones and computer screens, shorter outdoor activity time, greater proportion of time spent looking at cell phones and computer screens, and smaller proportion of outdoor activity time, with statistically significant differences (all P<0.05).During weekdays, after adjusting for confounding factors, longer single continuous near eye use duration ( OR=1.138, 95% CI: 1.086-1.192, P<0.001) was the risk factor for myopia, and longer working distance ( OR=0.906, 95% CI: 0.847-0.970, P=0.004) and longer outdoor activity time ( OR=0.127, 95% CI: 0.023-0.703, P=0.018) were protective factors for myopia.During weekends, after adjusting for confounding factors, longer time spent on looking at cell phone screens ( OR=2.437, 95% CI: 1.460-4.068, P<0.001) and longer time spent on looking at computer screens ( OR=2.260, 95% CI: 1.283-3.979, P=0.005) were risk factors for myopia, and longer outdoor activity time ( OR=0.624, 95% CI: 0.416-0.934, P=0.022) was the protective factor for myopia. Conclusions:The eyes with continuous near work, prolonged use of smartphone and computer screens, closer eye use distance, and less time spent outdoors have been confirmed to be significantly correlated with myopia based on objective monitoring data.When formulating intervention measures for myopia prevention and control in children, it is advocated to further pay attention to control the distance and duration of near work on weekdays and strengthen screen time management on weekends.

Objective:To understand the current situation of the specialized nursing alliance team after training, and to provide countermeasures for the further construction of the specialized nurse linkage team in medical institutions.Methods:From April to July in 2024, the descriptive qualitative research method was used, 25 community nursing professionals were interviewed by the objective sampling, and the contents were analyzed and refined by the Colaizzi 7-step analysis method.Results:A total of 25 community specialist nurses were all females, aged 31 - 47 years old. Four themes and 15 sub-themes were extracted: internal benefits after the linkage of the specialized nursing alliance team, external benefits after the linkage of the specialized nursing alliance team, existing difficulties in the construction of the specialized nursing alliance team, and future needs of the specialized nursing alliance team construction. Based on this analysis, the present situation of the team construction of specialized nursing alliance is made.Conclusions:Under the background of medical union, the team construction of specialized nursing alliance meets the needs of patients and policy trends, and has achieved phased results. In the future, it is still necessary to further improve the professional ability of community specialized nurses and strengthen multi-channel sustainable cooperation, including reshaping the structure of medical resources, strengthening capital investment, improving the utilization rate of information technology and strengthening the assessment mechanism to promote the improvement of the specialized nursing alliance team.

Objective:To analyze the correlation between near work, screen time, outdoor time and myopia in children based on objective monitoring technology and to explore the influencing factors related to myopia in children.Methods:A cross-sectional study was conducted.From October 2022 to March 2023, the purposive sampling method was used to select 596 children in Grade 2 and Grade 3 from two primary schools in Shandong Province as study subjects.Eye-Monitor technology of eye-use behavior based on artificial intelligence was used to quantify parameters of near work, screen time and outdoor time.The eye-use behavior parameters were compared within each subject and between non-myopic and myopic children on weekdays and weekends.A multivariate binary logistic regression model was constructed to analyze the influencing factors related to myopia.The study protocol was approved by the Medical Ethics Committee of the Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine (No.HEC-HY-2022023KY).Written informed consent was obtained from the legal guardian of each subject.Results:For each subject, the proportion of near work time on weekdays was greater than on weekends, the proportion of time spent looking at cell phones, computer screens, and outdoor activities was smaller, the duration of single continuous near eye use was longer, the tilt angle of the head in sitting position was greater, and the light intensity was stronger, showing statistically significant differences ( t=19.427, -9.964, -5.916, -10.470, 2.211, 2.898, 15.061; all P<0.05).During weekdays, compared with the non-myopia group, the myopia group had longer total near work duration, longer single continuous near eye use duration, shorter outdoor activity duration, closer eye use distance, larger proportion of near work time, and smaller proportion of outdoor activity time, showing statistically significant differences (all P<0.05).During weekends, compared with the non-myopia group, the myopia group had longer time spent looking at cell phones and computer screens, shorter outdoor activity time, greater proportion of time spent looking at cell phones and computer screens, and smaller proportion of outdoor activity time, with statistically significant differences (all P<0.05).During weekdays, after adjusting for confounding factors, longer single continuous near eye use duration ( OR=1.138, 95% CI: 1.086-1.192, P<0.001) was the risk factor for myopia, and longer working distance ( OR=0.906, 95% CI: 0.847-0.970, P=0.004) and longer outdoor activity time ( OR=0.127, 95% CI: 0.023-0.703, P=0.018) were protective factors for myopia.During weekends, after adjusting for confounding factors, longer time spent on looking at cell phone screens ( OR=2.437, 95% CI: 1.460-4.068, P<0.001) and longer time spent on looking at computer screens ( OR=2.260, 95% CI: 1.283-3.979, P=0.005) were risk factors for myopia, and longer outdoor activity time ( OR=0.624, 95% CI: 0.416-0.934, P=0.022) was the protective factor for myopia. Conclusions:The eyes with continuous near work, prolonged use of smartphone and computer screens, closer eye use distance, and less time spent outdoors have been confirmed to be significantly correlated with myopia based on objective monitoring data.When formulating intervention measures for myopia prevention and control in children, it is advocated to further pay attention to control the distance and duration of near work on weekdays and strengthen screen time management on weekends.