Heart failure （HF） is the end stage of various cardiovascular diseases， manifested as ventricular filling or impaired left ventricular ejection fraction （LVEF）. Type 2 diabetes mellitus （T2DM） is a metabolic disorder， mainly caused by insufficient insulin secretion and insulin resistance. The incidence rates of the two common clinical diseases are increasing year by year. HF and T2DM are mutually causal chronic diseases， and their mutual deterioration can form a HF-T2DM comorbidity. The comorbidity status significantly increases the mortality and readmission risk of patients， and seriously affects the quality of life of patients. At present， western medicine treatment mainly involves the use of anti HF drugs and hypoglycemic drugs， which can significantly alleviate the clinical symptoms of patients. However， these two categories of drugs are numerous in variety and differ in their mechanisms， and blind combination may produce adverse reactions. With its unique theoretical system， traditional Chinese medicine exhibits the advantages of multiple components， multiple targets， and high safety through traditional Chinese medicine monomers， Chinese patent medicine， traditional Chinese medicine compounds， and acupuncture， which significantly delays the development of HF-T2DM and shows great potential in clinical treatment. A large number of clinical studies have shown that the integrated traditional Chinese and western medicine in the treatment of HF-T2DM has a significant effect in improving cardiac function， controlling blood glucose levels， and improving the quality of life of patients. Based on relevant research at home and abroad， this paper reviewed the HF-T2DM pathogenesis， pharmacological effects， research status of traditional Chinese and western medicine， and early prevention strategies， and discussed current problems and future research directions， in order to provide new ideas and useful references for clinical prevention and treatment of HF-T2DM.

Heart failure （HF） is the end stage of various cardiovascular diseases， manifested as ventricular filling or impaired left ventricular ejection fraction （LVEF）. Type 2 diabetes mellitus （T2DM） is a metabolic disorder， mainly caused by insufficient insulin secretion and insulin resistance. The incidence rates of the two common clinical diseases are increasing year by year. HF and T2DM are mutually causal chronic diseases， and their mutual deterioration can form a HF-T2DM comorbidity. The comorbidity status significantly increases the mortality and readmission risk of patients， and seriously affects the quality of life of patients. At present， western medicine treatment mainly involves the use of anti HF drugs and hypoglycemic drugs， which can significantly alleviate the clinical symptoms of patients. However， these two categories of drugs are numerous in variety and differ in their mechanisms， and blind combination may produce adverse reactions. With its unique theoretical system， traditional Chinese medicine exhibits the advantages of multiple components， multiple targets， and high safety through traditional Chinese medicine monomers， Chinese patent medicine， traditional Chinese medicine compounds， and acupuncture， which significantly delays the development of HF-T2DM and shows great potential in clinical treatment. A large number of clinical studies have shown that the integrated traditional Chinese and western medicine in the treatment of HF-T2DM has a significant effect in improving cardiac function， controlling blood glucose levels， and improving the quality of life of patients. Based on relevant research at home and abroad， this paper reviewed the HF-T2DM pathogenesis， pharmacological effects， research status of traditional Chinese and western medicine， and early prevention strategies， and discussed current problems and future research directions， in order to provide new ideas and useful references for clinical prevention and treatment of HF-T2DM.

Objective:To develop and validate CT radiomics models based on machine learning for predicting recurrence of chronic subdural hematoma (cSDH) after endoscopic treatment.Methods:A retrospective study was performed; 252 patients with cSDH who underwent endoscopic treatment in Department of Neurosurgery, the Second Affiliated Hospital of Soochow University from October 2016 to October 2024 were selected. The clinical and imaging data of these patients were collected, and these patients were divided into a training set ( n=176) and a validation set ( n=76) at a ratio of 7:3. Patients in both sets were further sub-divided into a recurrence group and a non-recurrence group based on whether they had recurrence within 3 months of discharge. (1) Radiomics features of cSDH on initial non-enhanced CT images were extracted using 3D-Slicer software. Optimal features were selected through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis; based on these optimal features, 3 machine learning algorithms (Logistic, support vector machine [SVM], and K-nearest neighbor [KNN]) were used to construct CT radiomics models. Differences in predictive performance of different radiomics models were compared by analyzing indicators such as sensitivity, specificity, and area under receiver operating characteristic (ROC) curve (AUC), and the best model was selected. (2) Based on the initial non-enhanced CT images, cSDH was classified into homogeneous type, laminar type, septated type, and trabecular type according to Nakaguchi classification system; combined these cSDH typing with clinical features (clinical Markwalder's grade and bilateral hematoma), univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors for cSDH recurrence. Based on these factors, the 3 machine learning algorithms (Logistic, SVM, KNN) were used to construct hematoma typing-clinical feature models; differences in predictive performance of different hematoma typing-clinical feature models were compared by analyzing indicators such as sensitivity, specificity, and AUC, and the best model was selected. (3) DeLong's test was used to compare the ROC curve differences between the CT radiomics model and hematoma typing-clinical feature model. Decision curve analysis was used to compare the effective scope of the CT radiomics model and hematoma typing-clinical feature model. Results:(1) Seven optimal CT radiomics features based on wavelet transform were obtained after univariate analysis and LASSO regression: one gray-level dependence matrix feature, one first-order energy feature, two gray-level co-occurrence matrix features, two gray level size zone matrix features, and one gray-level run-length matrix feature. The KNN model constructed based on these 7 optimal features had the best performance in predicting cSDH recurrence, with an AUC of 0.845, a sensitivity of 0.833, a specificity of 0.857, a recall rate of 0.833, and an F1 score of 0.476 in patients from the validation set. (2) Three independent risk factors for cSDH recurrence were screened out through univariate analysis and multivariate Logistic regression analysis: hematoma Nakaguchi classification, Markwalder's grade, and bilateral hematoma. Logistic model constructed based on these 3 factors had the best performance in predicting cSDH recurrence, with an AUC of 0.675, a sensitivity of 0.609, a specificity of 0.654, a recall rate of 0.609, and an F1 score of 0.311 in patients from the validation set. (3) DeLong's test showed that the AUC of the CT radiomics model was significantly greater than that of the hematoma typing-clinical feature model in patients from the training set and validation set ( P=0.027 and P=0.035). Decision curve analysis showed that in the CT radiomics model, the net benefit of the model was >0 when the risk threshold was 0.05-0.95; in the hematoma typing-clinical feature model, the net benefit of the model was >0 when the risk threshold was 0.05-0.55. Conclusion:The KNN model based on 7 CT radiomics features in this study can effectively predict the cSDH recurrence in patients after endoscopic treatment, and its performance is obviously better than that of hematoma typing-clinical feature model constructed in this study.

Objective:To develop and validate CT radiomics models based on machine learning for predicting recurrence of chronic subdural hematoma (cSDH) after endoscopic treatment.Methods:A retrospective study was performed; 252 patients with cSDH who underwent endoscopic treatment in Department of Neurosurgery, the Second Affiliated Hospital of Soochow University from October 2016 to October 2024 were selected. The clinical and imaging data of these patients were collected, and these patients were divided into a training set ( n=176) and a validation set ( n=76) at a ratio of 7:3. Patients in both sets were further sub-divided into a recurrence group and a non-recurrence group based on whether they had recurrence within 3 months of discharge. (1) Radiomics features of cSDH on initial non-enhanced CT images were extracted using 3D-Slicer software. Optimal features were selected through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis; based on these optimal features, 3 machine learning algorithms (Logistic, support vector machine [SVM], and K-nearest neighbor [KNN]) were used to construct CT radiomics models. Differences in predictive performance of different radiomics models were compared by analyzing indicators such as sensitivity, specificity, and area under receiver operating characteristic (ROC) curve (AUC), and the best model was selected. (2) Based on the initial non-enhanced CT images, cSDH was classified into homogeneous type, laminar type, septated type, and trabecular type according to Nakaguchi classification system; combined these cSDH typing with clinical features (clinical Markwalder's grade and bilateral hematoma), univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors for cSDH recurrence. Based on these factors, the 3 machine learning algorithms (Logistic, SVM, KNN) were used to construct hematoma typing-clinical feature models; differences in predictive performance of different hematoma typing-clinical feature models were compared by analyzing indicators such as sensitivity, specificity, and AUC, and the best model was selected. (3) DeLong's test was used to compare the ROC curve differences between the CT radiomics model and hematoma typing-clinical feature model. Decision curve analysis was used to compare the effective scope of the CT radiomics model and hematoma typing-clinical feature model. Results:(1) Seven optimal CT radiomics features based on wavelet transform were obtained after univariate analysis and LASSO regression: one gray-level dependence matrix feature, one first-order energy feature, two gray-level co-occurrence matrix features, two gray level size zone matrix features, and one gray-level run-length matrix feature. The KNN model constructed based on these 7 optimal features had the best performance in predicting cSDH recurrence, with an AUC of 0.845, a sensitivity of 0.833, a specificity of 0.857, a recall rate of 0.833, and an F1 score of 0.476 in patients from the validation set. (2) Three independent risk factors for cSDH recurrence were screened out through univariate analysis and multivariate Logistic regression analysis: hematoma Nakaguchi classification, Markwalder's grade, and bilateral hematoma. Logistic model constructed based on these 3 factors had the best performance in predicting cSDH recurrence, with an AUC of 0.675, a sensitivity of 0.609, a specificity of 0.654, a recall rate of 0.609, and an F1 score of 0.311 in patients from the validation set. (3) DeLong's test showed that the AUC of the CT radiomics model was significantly greater than that of the hematoma typing-clinical feature model in patients from the training set and validation set ( P=0.027 and P=0.035). Decision curve analysis showed that in the CT radiomics model, the net benefit of the model was >0 when the risk threshold was 0.05-0.95; in the hematoma typing-clinical feature model, the net benefit of the model was >0 when the risk threshold was 0.05-0.55. Conclusion:The KNN model based on 7 CT radiomics features in this study can effectively predict the cSDH recurrence in patients after endoscopic treatment, and its performance is obviously better than that of hematoma typing-clinical feature model constructed in this study.

OBJECTIVE To analyze the impact of hospital-acquired infections on medical resource consumption un-der the diagnosis-related group(DRG)payment method.METHOD Medical record information and settlement lists of all discharged patients from Zhejiang Provincial People's Hospital from 2022 to 2023 were selected.Based on the Zhejiang Provincial Medical Insurance Bureau's diagnosis-related groups(ZJ-DRG)Edition 1.0,indicators such as time consumption index,cost consumption index,length of stay,total hospitalization costs and detailed cost breakdowns were used to analyze cases in the hospital-acquired infection group and the non-hospital-ac-quired infection group.RESULTS Among the 268 278 cases included in the study,2 186 were infected,with an in-fection rate of 0.81％.The infection rates for medical DRG disease group,surgical DRG disease group,and proce-dural DRG disease group were 0.86％(917/105 916),0.82％(1 069/131 112),and 0.64％(200/31 250),re-spectively.The time consumption index and cost consumption index were higher in the hospital-acquired infection group than in the non-hospital-acquired infection group(P＜0.05).In the RW21 group,the length of stay,total hospitalization costs and detailed cost breakdowns were all higher in the hospital-acquired infection group than in the non-hospital-acquired infection group(P＜0.05).Similarly,in the BB21 and GK11 groups,the hospital-ac-quired infection group had high length of stay,total hospitalization costs,medicine fees,treatment fees,material fees,laboratory fees,examination fees and other fees compared to the non-hospital-acquired infection group(P＜0.05).Bone(joint)infections,respiratory infections,and infectious fever had a significant impact on the time consumption index,while respiratory infections,bone(joint)infections and urinary tract infections had a relative-ly great impact on the cost consumption index.CONCLUSIONS Hospital-acquired infections result in additional consumption of medical resources.By analyzing the consumption of medical resources related to DRG disease groups,key monitoring disease groups for nosocomial infection control can be identified,which can aid relevant departments and clinical departments in taking early intervention measures,strengthen key prevention efforts,re-duce the incidence of nosocomial infections,and shorten the length of stay.

OBJECTIVE To analyze the impact of hospital-acquired infections on medical resource consumption un-der the diagnosis-related group(DRG)payment method.METHOD Medical record information and settlement lists of all discharged patients from Zhejiang Provincial People's Hospital from 2022 to 2023 were selected.Based on the Zhejiang Provincial Medical Insurance Bureau's diagnosis-related groups(ZJ-DRG)Edition 1.0,indicators such as time consumption index,cost consumption index,length of stay,total hospitalization costs and detailed cost breakdowns were used to analyze cases in the hospital-acquired infection group and the non-hospital-ac-quired infection group.RESULTS Among the 268 278 cases included in the study,2 186 were infected,with an in-fection rate of 0.81％.The infection rates for medical DRG disease group,surgical DRG disease group,and proce-dural DRG disease group were 0.86％(917/105 916),0.82％(1 069/131 112),and 0.64％(200/31 250),re-spectively.The time consumption index and cost consumption index were higher in the hospital-acquired infection group than in the non-hospital-acquired infection group(P＜0.05).In the RW21 group,the length of stay,total hospitalization costs and detailed cost breakdowns were all higher in the hospital-acquired infection group than in the non-hospital-acquired infection group(P＜0.05).Similarly,in the BB21 and GK11 groups,the hospital-ac-quired infection group had high length of stay,total hospitalization costs,medicine fees,treatment fees,material fees,laboratory fees,examination fees and other fees compared to the non-hospital-acquired infection group(P＜0.05).Bone(joint)infections,respiratory infections,and infectious fever had a significant impact on the time consumption index,while respiratory infections,bone(joint)infections and urinary tract infections had a relative-ly great impact on the cost consumption index.CONCLUSIONS Hospital-acquired infections result in additional consumption of medical resources.By analyzing the consumption of medical resources related to DRG disease groups,key monitoring disease groups for nosocomial infection control can be identified,which can aid relevant departments and clinical departments in taking early intervention measures,strengthen key prevention efforts,re-duce the incidence of nosocomial infections,and shorten the length of stay.

AIM:To investigate the effect of hydrogen sulfide(H2S)on ferroptosis and functional impairment induced by oxidized high-density lipoprotein(ox-HDL)in human umbilical vein endothelial cells(HUVECs),and to ex-plore its mechanisms.METHODS:The HUVECs were cultured in vitro and exposed to 200 mg/L ox-HDL,ferroptosis in-hibitor ferrostatin-1(Fer-1),protein kinase B(PKB/Akt)inhibitor MK-2206 2HCl(MK),Akt agonist SC79,and/or H2S for 24 h.Western blot was used to identify the relevant proteins.Intracellular levels of reactive oxygen species(ROS)were analyzed by flow cytometry and immunofluorescence staining.Intracellular iron was measured using an iron detection kit.The number of monocytes adhering to endothelial cells was counted using the monocyte adhesion assay.RESULTS:Compared with control group,acyl-CoA synthetase long-chain family member 4(ACSL4)protein expression in ox-HDL group was elevated by 1.45-fold(P<0.01),glutathione peroxidase 4(GPX4)protein expression was decreased by 29.79%(P<0.05),and ROS levels and iron ion content were elevated by 4.81-fold and 1.40-fold,respectively(P<0.01).The ratios of p-PI3K/PI3K and p-Akt/Akt were decreased by 45.65%and 41.68%,respectively(P<0.01),endo-thelial cell function-related protein IL-6,ICAM-1 and TNF-α expression was elevated 1.18-fold,1.24-fold and 1.41-fold(P<0.05),respectively,eNOS protein expression was decreased by 35.24%(P<0.01),and monocyte adhesion was ele-vated 3.43-fold(P<0.01).Compared with ox-HDL group,the endothelial cell iron death-related protein ACSL4 was de-creased by 22.32%(P<0.05),GPX4 was increased by 1.27-fold(P<0.01),and the p-Akt/Akt ratio was increased by 1.52-fold(P<0.01)in ox-HDL+H2S group.The fluorescence microscopy results showed that the ROS was decreased by 50.35%(P<0.01).The IL-6,ICAM-1 and TNF-α protein expression was decreased by 13.34%,9.83%and 13.46%(P<0.05),respectively,eNOS was elevated by 1.22-fold(P<0.01),and the number of monocyte adhesion was de-creased by 59.05%(P<0.01).Compared with ox-HDL group,GPX4 protein expression in ox-HDL+SC79 group was ele-vated by 1.49-fold(P<0.01),ACSL4 expression was decreased by 20.72%(P<0.05),and ROS and iron ions were de-creased by 59.31%and 23.85%(P<0.05),respectively.Compared with ox-HDL+H2S group,GPX4 protein expression was decreased by 21.28%,and ACSL4 protein expression was increased by 1.16-fold in ox-HDL+H2S+MK group(P<0.05).CONCLUSION:H2S activates Akt to inhibit ox-HDL-induced ferroptosis in HUVECs and alleviate their func-tional damage.

Objective:To observe the efficacy of Long’s bone setting manipulation combined with hyperbaric oxygen（HBO）in the treatment of vertigo caused by cervical spondylosis of the vertebral artery type（CSA）.Methods:A total of 143 patients with CSA and vertigo treated in the Department of Rehabilitation Medicine of the Second Hospital of Shanxi Medical University from April 2019 to July 2020 were prospectively included as the research subjects by a random number table. The patients were divided into control group（72 cases）and observation group（71 cases）. The control group was treated with Long’s bone setting manipulation，while the observation group was treated with Long’s bone setting manipulation combined with HBO. The overall curative effect of the two groups was evaluated and compared by Traditional Chinese Medicine Syndrome Score Scale（TCMSSS）. The vertigo symptom of the two groups was evaluated by Dizziness Handicap Inventory（DHI）. The hemodynamic indexes of vertebral artery，including left vertebral artery（LVA），right vertebral artery（RVA）and basilar artery（BA），were detected and compared between the two groups by Doppler ultrasound.Results:After treatment，the overall curative effect of the observation group was better than that of the control group，with statistically significant difference（ P < 0.05）. No statistically significant difference in DHI scores or vertebral artery hemodynamic indexes between the two groups was observed before treatment（ P > 0.05）. After treatment，the observation group had lower DHI scores while higher indexes of LVA，RVA and BA compared with those in the control group（ P < 0.05）. Conclusion:Long’s bone setting manipulation combined with HBO has better efficacy than Long’s bone setting manipulation alone in the treatment of vertigo caused by CSA，which is more conducive to reducing vertigo symptoms and improving vertebral artery hemodynamics.

Objective:To evaluate the effectiveness of digital orthognathic surgery in the surgical treatment of patients with hemifacial microsomia (HFM) and patients’ satisfaction.Methods:The clinical data of HFM patients admitted to the Department of Orthognathic & Cleft Lip and Palate Plastic Surgery, Hospital of Stomatology, Wuhan University, from January 2017 to May 2020 were retrospectively analyzed. The digital orthognathic surgery was used to design surgical protocols before surgery. The intermediate wafer and terminal wafer by three-dimensional printing were applied to determine the position of maxillary and mandible bone blocks. The distance change between landmarks in maxillary and chin and the reference planes was measured. The skull CT and face photographs were taken 5 days after surgery to compare the distance between the actual position and the designed position. Data were expressed as the Mean±SD and analyzed by the pairing t-test with P<0.05 considered statistically. The patients’ satisfaction was investigated by interval scale method on day 7 and 6 months after operation. Results:There were 9 HFM patients in this study, included 5 men and 4 women, and the average age was 25.8±3.8 years old. 6 patients were affected on the left side and 3 patients was affected on the right side. All the operations were processed successfully. The wafers were in good position that the maxillary and mandible blocks were moved precisely according to the digital design. There were no accidental fractures of the jaw during the operation. The post-operative photographs and CT showed the stomatognathic system recovered well without serious postoperative complications. The errors between postoperative situation and preoperative designed situation in maxillary and chin were no statistically difference ( P>0.05). The maximum movement error of the maxillary bone block was the mark point of the first molar on the left, with an average error of (0.92 ± 0.34) mm. The patients’ satisfaction scores were averaged 83.2±2.7 points on day 7 after surgery, while the score dropped to 73.8±2.5 points after 6 months. Conclusions:The digital orthognathic surgery technology can satisfy the accuracy requirement of the surgical plan design for HFM patients in correcting the deflect of dental middle line, occlusal plane and chin point. High postoperative satisfaction can be achieved, which may decrease slightly 6 months after operation.

Objective:To evaluate the effectiveness of digital orthognathic surgery in the surgical treatment of patients with hemifacial microsomia (HFM) and patients’ satisfaction.Methods:The clinical data of HFM patients admitted to the Department of Orthognathic & Cleft Lip and Palate Plastic Surgery, Hospital of Stomatology, Wuhan University, from January 2017 to May 2020 were retrospectively analyzed. The digital orthognathic surgery was used to design surgical protocols before surgery. The intermediate wafer and terminal wafer by three-dimensional printing were applied to determine the position of maxillary and mandible bone blocks. The distance change between landmarks in maxillary and chin and the reference planes was measured. The skull CT and face photographs were taken 5 days after surgery to compare the distance between the actual position and the designed position. Data were expressed as the Mean±SD and analyzed by the pairing t-test with P<0.05 considered statistically. The patients’ satisfaction was investigated by interval scale method on day 7 and 6 months after operation. Results:There were 9 HFM patients in this study, included 5 men and 4 women, and the average age was 25.8±3.8 years old. 6 patients were affected on the left side and 3 patients was affected on the right side. All the operations were processed successfully. The wafers were in good position that the maxillary and mandible blocks were moved precisely according to the digital design. There were no accidental fractures of the jaw during the operation. The post-operative photographs and CT showed the stomatognathic system recovered well without serious postoperative complications. The errors between postoperative situation and preoperative designed situation in maxillary and chin were no statistically difference ( P>0.05). The maximum movement error of the maxillary bone block was the mark point of the first molar on the left, with an average error of (0.92 ± 0.34) mm. The patients’ satisfaction scores were averaged 83.2±2.7 points on day 7 after surgery, while the score dropped to 73.8±2.5 points after 6 months. Conclusions:The digital orthognathic surgery technology can satisfy the accuracy requirement of the surgical plan design for HFM patients in correcting the deflect of dental middle line, occlusal plane and chin point. High postoperative satisfaction can be achieved, which may decrease slightly 6 months after operation.