Objective To investigate the impact of red blood cell suspension infusion across various perioperative periods on patients with valvular heart disease. Methods The patients with valvular heart disease admitted to Tianjin Chest Hospital from 2018 to 2020 were selected. Based on the timing of perioperative red cell suspension infusion, patients were categorized into three groups: a group 1 receiving intraoperative red cell suspension infusion, a group 2 receiving red cell suspension infusion within 24 hours after entering the ICU, and a group 3 receiving red cell suspension infusion at both time points. The laboratory results, perioperative blood component infusion volume, and other relevant parameters were retrospectively analyzed. After propensity score matching, the differences in different variables among the three groups were compared. Results After propensity score matching, 102 patients were enrolled, including 52 males and 50 females, with an average age of (61.74±10.58) years. There were 34 patients in each group. The preoperative hemoglobin (Hb) value of the group 2 was significantly higher than that of the group 1 and the group 3, and the amount of red cell suspension and autoblood transfusion was the lowest (P<0.05). Group 1 had the highest postoperative Hb, as well as the highest Hb and hematocrit (HCT) levels within 24 hours post-surgery (P<0.05). The group 1 had the lowest plasma, platelet and cryoprecipitate infusion volumes, and the shortest cardiopulmonary bypass time, aortic occlusion time, postoperative ICU stay and hospital stay, and the least blood loss and total drainage volume (P<0.05). The difference between postoperative and preoperative Hb (△Hb1) was highest in group 1 (P<0.05). Conclusion For patients with valvular heart disease, intraoperative-only infusion of red blood cell suspension is associated with a better prognosis at discharge and during follow-up.

Objective To analyze the difference of psoas major muscle morphology and pain degree in patients with different types of lumbar disc herniation ( LDH ) by quantitative CT, and to further explore the relationship between psoas major muscle morphology and pain degree. Methods A total of 120 patients with LDH admitted to our hospital from January to December 2025 were enrolled as study subjects. Based on clinical symptoms and lesion location, they were divided into a simple lower extremity pain group and a lumbar and leg pain group. All patients underwent lumbar CT examination. The psoas major muscle index was used as a CT quantitative parameter, which was calculated as the mean of the maximum cross-sectional areas of both psoas major muscles divided by the cross-sectional area of the L5 vertebral body. This index was measured to reflect psoas major muscle morphology. Pain severity was assessed using the visual analogue scale (VAS). Differences in psoas major muscle morphology and pain severity between the two groups were compared. A Pearson correlation analysis was used to examine the relationship between the psoas major muscle index and pain severity. A linear regression model was used to analyze the independent risk factors affecting pain severity. Results There were no statistically significant differences in sex, age, or body mass index between the two groups (P>0.05). The disease duration was longer and the incidence of anxiety and depression was higher in the lumbar and leg pain group than those in the simple lower extremity pain group (P<0.05). Compared with the simple lower extremity pain group, the lumbar and leg pain group showed lower psoas major muscle index [(0.53 ± 0.05) vs. (0.61 ± 0.07)] and higher VAS score [(4.67 ± 1.10) vs. (3.02 ± 0.89)], and the differences were statistically significant (P<0.05). Pearson correlation analysis revealed a negative correlation between the psoas major muscle index and the VAS score (r=−0.288, P<0.05). Linear regression model analysis indicated that the independent risk factors affecting the VAS score were age, disease duration, LDH type, and the psoas major muscle index. Conclusion Compared with LDH patients with simple lower extremity pain, those with lumbar and leg pain demonstrate a longer disease duration, a higher incidence of anxiety and depression, and a higher severity of psoas major muscle atrophy and pain. The severity of pain is associated with not only advanced age and prolonged disease duration but also the LDH type and psoas major muscle atrophy.

Objective To analyze the difference of psoas major muscle morphology and pain degree in patients with different types of lumbar disc herniation ( LDH ) by quantitative CT, and to further explore the relationship between psoas major muscle morphology and pain degree. Methods A total of 120 patients with LDH admitted to our hospital from January to December 2025 were enrolled as study subjects. Based on clinical symptoms and lesion location, they were divided into a simple lower extremity pain group and a lumbar and leg pain group. All patients underwent lumbar CT examination. The psoas major muscle index was used as a CT quantitative parameter, which was calculated as the mean of the maximum cross-sectional areas of both psoas major muscles divided by the cross-sectional area of the L5 vertebral body. This index was measured to reflect psoas major muscle morphology. Pain severity was assessed using the visual analogue scale (VAS). Differences in psoas major muscle morphology and pain severity between the two groups were compared. A Pearson correlation analysis was used to examine the relationship between the psoas major muscle index and pain severity. A linear regression model was used to analyze the independent risk factors affecting pain severity. Results There were no statistically significant differences in sex, age, or body mass index between the two groups (P>0.05). The disease duration was longer and the incidence of anxiety and depression was higher in the lumbar and leg pain group than those in the simple lower extremity pain group (P<0.05). Compared with the simple lower extremity pain group, the lumbar and leg pain group showed lower psoas major muscle index [(0.53 ± 0.05) vs. (0.61 ± 0.07)] and higher VAS score [(4.67 ± 1.10) vs. (3.02 ± 0.89)], and the differences were statistically significant (P<0.05). Pearson correlation analysis revealed a negative correlation between the psoas major muscle index and the VAS score (r=−0.288, P<0.05). Linear regression model analysis indicated that the independent risk factors affecting the VAS score were age, disease duration, LDH type, and the psoas major muscle index. Conclusion Compared with LDH patients with simple lower extremity pain, those with lumbar and leg pain demonstrate a longer disease duration, a higher incidence of anxiety and depression, and a higher severity of psoas major muscle atrophy and pain. The severity of pain is associated with not only advanced age and prolonged disease duration but also the LDH type and psoas major muscle atrophy.

Objective To analyze the difference of psoas major muscle morphology and pain degree in patients with different types of lumbar disc herniation ( LDH ) by quantitative CT, and to further explore the relationship between psoas major muscle morphology and pain degree. Methods A total of 120 patients with LDH admitted to our hospital from January to December 2025 were enrolled as study subjects. Based on clinical symptoms and lesion location, they were divided into a simple lower extremity pain group and a lumbar and leg pain group. All patients underwent lumbar CT examination. The psoas major muscle index was used as a CT quantitative parameter, which was calculated as the mean of the maximum cross-sectional areas of both psoas major muscles divided by the cross-sectional area of the L5 vertebral body. This index was measured to reflect psoas major muscle morphology. Pain severity was assessed using the visual analogue scale (VAS). Differences in psoas major muscle morphology and pain severity between the two groups were compared. A Pearson correlation analysis was used to examine the relationship between the psoas major muscle index and pain severity. A linear regression model was used to analyze the independent risk factors affecting pain severity. Results There were no statistically significant differences in sex, age, or body mass index between the two groups (P>0.05). The disease duration was longer and the incidence of anxiety and depression was higher in the lumbar and leg pain group than those in the simple lower extremity pain group (P<0.05). Compared with the simple lower extremity pain group, the lumbar and leg pain group showed lower psoas major muscle index [(0.53 ± 0.05) vs. (0.61 ± 0.07)] and higher VAS score [(4.67 ± 1.10) vs. (3.02 ± 0.89)], and the differences were statistically significant (P<0.05). Pearson correlation analysis revealed a negative correlation between the psoas major muscle index and the VAS score (r=−0.288, P<0.05). Linear regression model analysis indicated that the independent risk factors affecting the VAS score were age, disease duration, LDH type, and the psoas major muscle index. Conclusion Compared with LDH patients with simple lower extremity pain, those with lumbar and leg pain demonstrate a longer disease duration, a higher incidence of anxiety and depression, and a higher severity of psoas major muscle atrophy and pain. The severity of pain is associated with not only advanced age and prolonged disease duration but also the LDH type and psoas major muscle atrophy.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

OBJECTIVE To investigate the prognostic factors of chondrosarcoma of the larynx,deeply analyze its clinical data,and provide a theoretical basis for better treatment of chondrosarcoma of the larynx.METHODS A retrospective analysis was conducted on the complete clinical data of patients with primary chondrosarcoma of the larynx admitted to the Department of Otolaryngology Head and Neck Surgery,Beijing Tongren Hospital,Capital Medical University from January 2010 to December 2024.RESULTS A total of 15 patients were included,including 11 males and 4 females,with a gender ratio of 11∶4.The average age of onset was 57.3 years,and the average clinical symptom duration was 12.2 months.The tumors were mainly located in the cricoid cartilage in 11 patients,in the arytenoid cartilage in 2 patients,and in the thyroid cartilage in 2 patients.Tumor grading showed that 7 patients were grade I and 8 were grade II.Four patients underwent transoral laser minimally invasive surgery,2 patients underwent partial laryngectomy+tracheotomy,and 9 patients underwent total laryngectomy/cervical lymph node dissection+tracheostomy.The 5-year overall survival rate was 85.7%,the 5-year disease-specific survival rate was 100%,and the 5-year local-regional control rate was 90.9%.Gender,tumor location,tumor grade,Ki-67,tumor size,and whether larynx preservation surgery was performed did not affect the local-regional control rate or disease-specific survival rate.CONCLUSION Laryngeal chondrosarcoma generally has a longer disease history and is difficult to detect.The pathological type is mostly well-differentiated.Regional or distant metastasis is rare,and the long-term survival rate is good.Surgical resection is the preferred treatment option.On the basis of not reducing the tumor control rate,surgery that prioritizes preserving laryngeal function should be given priority,while comprehensive treatment is generally not recommended.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

Objective:To compare the value of different quantification methods for intraoperative hypotension in predicting postoperative acute kidney injury (AKI) in patients undergoing off-pump coronary artery bypass grafting (OPCABG).Methods:The medical records of American Society of Anesthesiologists Physical Status classification Ⅲ-Ⅳ patients of either sex, aged 18-80 yr, with a body mass index of 18-30 kg/m 2, scheduled for elective OPCABG, were retrospectively collected at Tianjin Chest Hospital from September 2021 to October 2023. Intraoperative hypotension was quantified using the methods such as the number of occurrence, average decrease in magnitude, duration, and the area under the threshold (mean arterial pressure <65 mmHg, 1 mmHg = 0.133 kPa). Patients were divided into AKI group and non-AKI group based on the occurrence of AKI within 7 days postoperatively. The extended logistic regression model was used to adjust for confounding factors, and the receiver operating characteristic curves were plotted to compare the accuracy of different methods for intraoperative hypotension in predicting postoperative AKI. Results:The results of multivariate logistic regression analysis showed that the frequency of hypotension ( OR=1.03, 95% confidence interval [ CI] 1.01-1.05, P=0.010), duration of hypotension ( OR=1.04, 95% CI 1.01-1.08, P=0.007), and area under the threshold ( OR=1.03, 95% CI 1.01-1.06, P=0.023) were risk factors for postoperative AKI. The areas under the curve for the quantification methods predicting the occurrence of postoperative AKI within 7 days, including the duration of hypotension, area under the threshold, frequency of hypotension, and mean decrease in blood pressure, were 0.751, 0.652, 0.647 and 0.513, respectively. Conclusions:The duration of hypotension, area under the threshold and frequency of hypotension are independent risk factors for postoperative AKI in patients undergoing OPCABG. The duration of hypotension has a higher accuracy in predicting the occurrence of postoperative AKI.

Objective:To explore an effective measurement method for the output power of high-frequency electrosurgical equipment,so as to provide a basis for improving the accuracy of measurement results of output power of this kind of equipment.Methods:Adopt a combined measurement method of voltage method and current method to verify the impedance characteristics of high-frequency resistors of the AJ-60 high-frequency surgical system at 4.2 MHz and 13.56 MHz.Through resistor modification,explore the measurement methods of output power under the two working modes of the system:monopolar pencil vaporization cutting(PV)and bipolar cutting(BC).Measure the power of the two working modes using both voltage method and current method,and analyze the influencing factors of their measurement accuracy.Results:The results of relative deviation between voltage method and current method for the measured power were significantly reduced through refit and comparison experiments.PV mode reduced from 40.58%to 1.11%,and BC mode reduced from 29.48%to 5.37%.In practical operation,the factors included limitation of prober's bandwidth,and mismatch of inputted impedance were important factors that affected the accuracy of measurement.Conclusions:In order to ensure accurate measurement for equipment's output power when operating frequencies exceed 4 MHz,it is essential to use non-inductive load resistance that is accurately calibrated at the specific operating frequency.It has great significance for enhancing the measured accuracy and reliability of output power of electrosurgical equipment with high-frequency.

Objective:To evaluate the effects of the Chinese visceral adiposity index(CVAI)and the Triglyceride-Glucose(TyG)index on the risk of hypertension among the elderly in the Zhengxiangbai Banner community of Inner Mongolia.Methods:This study selected elderly individuals who underwent physical examinations at the community health service center in Zhengxiangbai Banner, Inner Mongolia, from January 2024 to July 2024 as the study population.Based on the diagnostic criteria for hypertension, participants were divided into hypertensive and non-hypertensive groups.Data on demographics, body mass index(BMI), waist circumference(WC), fasting blood glucose(FSG), and blood lipids were collected.The CVAI, TyG, Triglyceride Glucose-Body Waist Circumference(TyG-WC), and Triglyceride Glucose-Body Mass Index(TyG-BMI)were calculated.Subjects were categorized into quartiles(1st to 4th)based on CVAI, TyG, TyG-WC, and TyG-BMI.Multivariate logistic regression analysis was employed to explore the relationship between these indicators and the risk of hypertension in the elderly.Results:This study included a total of 3, 319 elderly subjects, comprising 1, 743 individuals in the hypertensive group and 1, 576 in the non-hypertensive group.Multivariate logistic regression analysis indicated that the fourth quartile of the CVAI was a risk factor for hypertension when compared to the first quartile.Additionally, the second, third, and fourth quartiles of the TyG-BMI were identified as risk factors for hypertension relative to the first quartile.The analysis of the correlation strength between various obesity indexes and hypertension revealed that CVAI, TyG-WC, and TyG-BMI were independently correlated with the risk of hypertension.Notably, TyG-BMI exhibited a stronger association with hypertension( OR=1.006, 95% CI: 1.004-1.008).ROC curve analysis demonstrated that TyG-BMI possessed superior predictive ability for hypertension, with an AUC of 0.587(95% CI: 0.568-0.607).Furthermore, Decision Curve Analysis(DCA)also indicated that TyG-BMI had enhanced predictive capability.Further stratification by gender revealed that TyG-BMI in elderly men was independently correlated with the risk of hypertension( P<0.001), while CVAI in elderly women was independently correlated with the risk of hypertension( P<0.05).ROC curve analysis indicated that TyG-BMI in elderly men had better predictive ability for hypertension(AUC=0.582, 95% CI: 0.554~0.610).The difference in AUC compared to CVAI was statistically significant( P<0.01).DCA analysis further confirmed that TyG-BMI exhibited superior predictive ability. Conclusions:Our findings suggest that both CVAI and TyG-BMI exhibit superior predictive value for hypertension, with TyG-BMI demonstrating a particularly strong predictive capability in elderly men.