Objective To explore the clinical characteristics of organ donors in the intensive care unit (ICU), analyze the impact of comprehensive ICU treatment on organ function maintenance and donation efficiency, and provide data support for optimizing organ donation management strategies. Methods A retrospective analysis was conducted on the data of 263 donors who underwent organ donation after ineffective active treatment in the ICU of Sun Yat-sen Memorial Hospital of Sun Yat-sen University from January 2020 to January 2024. The clinical characteristics, main therapeutic measures in the ICU, and organ donation situations were analyzed. Results The 263 organ donors had an out-of-hospital hospitalization duration of 2 (1, 5) days and an in-hospital hospitalization duration of 4 (3, 6) d. The acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score at admission was (21±5). Among them, 16.7% had a history of cardiopulmonary resuscitation, 30.4% had a history of hypertension, and 48.7% had a history of cranial surgery. The duration of enteral nutrition provided in the ICU was 18 (8, 32) h, with daily energy provision of 160 (0, 320) kcal, parenteral nutrition provided non-protein energy of 877 (710, 1 058) kcal daily. Fiberoptic bronchoscopy was performed 0.25 (0, 0.50) times a day. Continuous renal replacement therapy (CRRT) was performed in 90.1% of the cases, with an average daily duration of 10 (6, 16) h. The daily dosage of human albumin was 40 (30, 50) g, and the daily dosage of methylprednisolone was 120 (80, 160) mg. The most commonly used empirical anti-infection regimens included cefoperazone-sulbactam in 59 cases (22.4%), meropenem combined with vancomycin in 31 cases (11.8%), and piperacillin-tazobactam in 29 cases (11.0%). The most commonly used goal-directed anti-infection adjustment regimen was meropenem combined with vancomycin in 21 cases (8.0%). After comprehensive treatment in the ICU, cardiac function, some liver functions, some coagulation functions, renal function, electrolytes, and infection indicators improved. A total of 981 organs were donated by the 263 organ donors, with 23 organs discarded. The average organ yield rate was 3.64, and the organ utilization rate was 97.7%. Conclusions Comprehensive ICU treatment may significantly improve the cardiac function, some liver functions, coagulation functions, and infection indicators of organ donors, enhance the effect of organ function maintenance, and provide an effective guarantee for optimizing organ donation management in the ICU and improving organ utilization rates.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective To review the occurrence of allergic reactions during therapeutic plasma exchange(TPE)and to explore the risk factors of TPE allergic reactions.Methods The clinical data of 929 patients treated with TPE using plasma components by the Department of Transfusion Medicine in our medical center from 2018 to 2023 were collected.The influen-cing factors of allergic reactions were analyzed by univariate analysis,and the independent risk factors of allergic reactions were analyzed by logistic multivariate regression analysis.Results A total of 4 071 TPEs were performed in 929 patients.A-mong them,198 patients(21.31%)experienced 349 times(8.57%)of allergic reactions,with the incidence of gradeⅠ,Ⅱ and Ⅲ allergic reactions of 16.33%,81.38%and 2.29%,respectively,and no deaths.The univariate analysis showed that the patient′s age,allergy history,diagnosis of immune-related diseases,ICU admission,plasma consumption,total blood volume,maximum blood flow rate and combined use of albumin were related to the occurrence of allergic reactions(P＜0.05).Multivariate regression analysis showed that young patients,a history of allergy,immune-related diseases and non-ICU patients were prone to allergic reactions in TPE,but the treatment options of TPE such as substitute fluid category,plasma consumption and blood flow rate were not related to the occurrence of allergic reactions.Conclusion There are sig-nificant individual differences in the occurrence of allergic reactions for TPE,and young age,history of allergies,immune-related diseases and non-ICU patients are risk factors for allergic reactions in TPE.Identifying patients with risk factors be-fore TPE treatment and giving corresponding preventive measures can reduce the incidence of allergic reactions.

Objective:To establish a scoring system for preoperative prediction of the malignant potential of gastric stromal tumors based on gastroscopic and endoscopic ultrasound features, along with validation.Methods:A total of 286 patients who were treated in Jiangsu Province Hospital of Chinese Medicine from January 1, 2017 to December 31, 2023 and diagnosed as having gastric stromal tumors by postoperative pathology were enrolled in the modeling group. According to National Institutes of Health classification system, 227 very-low/low-risk patients were classified into the low malignant potential (LMP) group, and the 59 intermediate/high-risk patients into the high malignant potential (HMP) group. LASSO regression analysis was performed to identify predictive factors for HMP gastric stromal tumors, and a nomogram prediction model was developed. Internal validation using the Bootstrap method was performed on the modeling group, and external validation was performed on data from 85 patients who were treated and diagnosed as having gastric stromal tumors by postoperative pathology in Taizhou People's Hospital from January 1, 2021 to December 31, 2023. The receiver operator characteristic (ROC) curves, calibration curves, and decision curve analyses were employed in both the modeling and external validation groups.Results:Tumor size (coef=0.755), tumor shape (coef=0.015), tumor location (coef=0.008), growth pattern (coef=-0.026), cystic change (coef=0.685), and surface unceration change (coef=-0.545) were the independent predictive factors for HMP gastric stromal tumors. The nomogram-based prediction model constructed using these factors achieved an area under the ROC curve of 0.959 (95% CI: 0.898-0.903) in the modeling group and 0.959 (95% CI: 0.857-1.000) in the external validation group. The model demonstrated good accuracy (0.917) and a Kappa value of 0.737 in internal validation. Calibration curve and decision curve analyses indicated strong calibration and high net benefit in both the modeling and the external validation groups. Conclusion:Tumor size, tumor shape, tumor location, growth pattern, cystic change, and surface ulceration change are independent predictive factors for HMP gastric stromal tumors. The nomogram model developed based on these factors offers effective and convenient visualization for clinicians to predict the malignant potential of gastric stromal tumors preoperatively.

Objective:To investigate the clinical effect of Alirocumab in reducing low density lipoprotein cholesterol(LDL-C)in patients with coronary heart disease(CHD)and substandard blood lipids and its effect on atheroscle-rotic plaque.Methods:A total of 127 CHD patients with substandard blood lipids who were treated in Shenzhen Longhua District People's Hospital between September 2017 and March 2021 were selected.According to patients re-ceived Alirocumab therapy or not,they were divided into control group(n=81)and combined group(n=46).The control group remained original statin therapeutic regimen,while combined group received additional PCSK9 inhibi-tor Alirocumab injection based on original statin therapeutic regimen,75mg subcutaneously,once every 2 weeks.Both groups were treated for 3 months,then followed up for 12 months.Levels of total cholesterol(TC)and LDL-C,plaque fiber cap thickness,lipid plaque radian,lipid plaque length and minimum lumen cross-sectional area before and after 12-month follow-up,and incidence of adverse reactions and clinical endpoint events were com-pared between two groups.Results:After 12-month follow-up,compared with control group,combined group had significant lower plasma levels of TC[(3.48±1.04)mmol/L vs.(2.29±0.76)mmol/L],LDL-C[(2.08±0.53)mmol/L vs.(1.27±0.41)mmol/L],lipid plaque radian[(107.22±13.29)° vs.(92.65±11.81)°]and lipid plaque length[(5.45±0.89)mm vs.(4.84±0.82)mm],and significant higher plaque fiber cap thickness[(123.60±14.87)μm vs.(131.46±14.29)μm]and minimum lumen cross-sectional area[(2.51±0.37)mm2 vs.(2.69±0.33)mm2](P＜0.01 all).There was no significant difference in incidence rates of adverse reactions(x2=0.428,P=0.513)and clinical endpoint events(x2=0.253,P=0.615)between two groups.Conclusion:Alirocumab can significantly reduce LDL-C level,increase the plaque fiber cap thickness and lumen cross-section-al area,reduce the internal lipid load of plaque and improve the stability of plaque with good safety in CHD patients with substandard blood lipids.