Objective To investigate the clinical characteristics of patients with chronic abacterial pros-tafitis(CAP),the CAP related factors were analyzed,and a risk prediction model for CAP were constructed and validated.Methods The clinical dataes of 252 suspected CAP patients admitted to the hospital from June 2022 to December 2024 were collected,the patients were divided into modeling set(ni=177)and validation set(n=75)by 7∶3 ratio.Based on the modeling set dataes,the Lasso was used to screen CAP related predictive factors,a logistic multiple factor model was used to analyze the independent influence factors of CAP and a risk prediction model was constructed.The validation set patient dataes were used to plot ROC and DCA and validate the predic-tion model.Results There were 86 cases of CAP in the modeling set,accounting for 48.59％;32 cases of CAP in the validation set,accounting for 42.67％.The Logistic multiple regression analysis showed that BMI,waist to hip ratio,abnormal elevation of IL-8,COX-2,and PGE2 in prostate fluid were independent influence factors of CAP(P＜0.05),a Nomogram column chart based on this was established.The ROC analysis showed that the sensitivity of the model for detecting CAP in the modeling and validation sets were 0.814 and 0.802,respectively,and the specificity were 0.673 and 0.703,respectively.The DCA analysis showed that the net benefit thresholds for model-ing and validation sets by column charts are 0.1～0.9 and 0.2～1.0,respectively.Conclusions The occurrence of CAP is related to the patient's BMI,waist to hip ratio,the levels of IL-8,COX-2,and PGE2 in prostate fluid.The predictive model established based on this is highly accurate and it can help for CAP screening.

Objective:To explore the value of lumbar volumetric bone mineral density (vBMD) measured by quantitative computed tomography (QCT) in predicting coronary artery calcification (CAC).Methods:This retrospective, cross-sectional study included a total of 991 patients (504 male and 487 female) who underwent coronary artery CT angiography (CTA) and chest, abdomen, or lumbar spine CT examinations at Taihe County People′s Hospital from January 2023 to June 2024. Lumbar vBMD was measured by QCT. The coronary artery calcification score (CACS) was calculated using an artificial intelligence-assisted diagnostic system. Patients were categorized into a low calcification group (CACS≤100, 592 cases) and a moderate-to-severe calcification group (CACS>100, 399 cases). Independent-sample t-tests, Mann-Whitney U tests, or χ2 tests were employed to analyze the differences in clinical data and lumbar vBMD between the two groups. Binary logistic regression was employed to control confounding factors and analyze the correlation between lumbar vBMD and moderate-to-severe CAC. Multivariate binary logistic regression was used to identify independent predictors of moderate-to-severe CAC and construct a combined prediction model. The receiver operating characteristic curve was used to evaluate the efficacy of lumbar vBMD and the combined model in predicting moderate-to-severe CAC. The comparison of the area under the curve (AUC) was conducted using the DeLong test. Results:The age, incidence of diabetes, hypertension, and osteoporosis were significantly higher in the moderate-to-severe calcification group than in the low calcification group, while lumbar vBMD was significantly lower in the former group (all P<0.05). The body mass index, smoking history, and hyperlipidemia had no statistical differences between the two groups (all P>0.05). Following adjustment for potential confounding variables, the results of binary logistic regression analysis revealed that lumbar vBMD was not significantly associated with the presence of moderate-to-severe CAC in the overall study population or in male ( OR=0.998, 95% CI 0.993-1.003, P=0.379; OR=1.000, 95% CI 0.993-1.006, P=0.918). However, lumbar vBMD was a statistically significant predictor in females ( OR=0.992, 95% CI 0.985-0.999, P=0.032). Multivariate binary logistic regression analysis further demonstrated that age ( OR=1.048, 95% CI 1.019-1.077, P=0.001), hypertension ( OR=2.649, 95% CI 1.719-4.082, P<0.001), and lumbar vBMD ( OR=0.992, 95% CI 0.984-0.999, P=0.022) were independent predictors of moderate-to-severe CAC in women. The AUC of lumbar vBMD for predicting moderate-to-severe CAC in female patients was 0.684 (95% CI 0.641-0.725), and the AUC of the combined model was 0.746 (95% CI 0.705-0.784), with a statistically significant difference ( Z=3.26, P=0.001). Conclusions:Lumbar vBMD measured by QCT is an independent predictor of moderate-to-severe CAC in women and demonstrates moderate predictive value. The predictive performance can be enhanced by integrating age and hypertension into a combined predictive model.

Objective:To explore the value of lumbar volumetric bone mineral density (vBMD) measured by quantitative computed tomography (QCT) in predicting coronary artery calcification (CAC).Methods:This retrospective, cross-sectional study included a total of 991 patients (504 male and 487 female) who underwent coronary artery CT angiography (CTA) and chest, abdomen, or lumbar spine CT examinations at Taihe County People′s Hospital from January 2023 to June 2024. Lumbar vBMD was measured by QCT. The coronary artery calcification score (CACS) was calculated using an artificial intelligence-assisted diagnostic system. Patients were categorized into a low calcification group (CACS≤100, 592 cases) and a moderate-to-severe calcification group (CACS>100, 399 cases). Independent-sample t-tests, Mann-Whitney U tests, or χ2 tests were employed to analyze the differences in clinical data and lumbar vBMD between the two groups. Binary logistic regression was employed to control confounding factors and analyze the correlation between lumbar vBMD and moderate-to-severe CAC. Multivariate binary logistic regression was used to identify independent predictors of moderate-to-severe CAC and construct a combined prediction model. The receiver operating characteristic curve was used to evaluate the efficacy of lumbar vBMD and the combined model in predicting moderate-to-severe CAC. The comparison of the area under the curve (AUC) was conducted using the DeLong test. Results:The age, incidence of diabetes, hypertension, and osteoporosis were significantly higher in the moderate-to-severe calcification group than in the low calcification group, while lumbar vBMD was significantly lower in the former group (all P<0.05). The body mass index, smoking history, and hyperlipidemia had no statistical differences between the two groups (all P>0.05). Following adjustment for potential confounding variables, the results of binary logistic regression analysis revealed that lumbar vBMD was not significantly associated with the presence of moderate-to-severe CAC in the overall study population or in male ( OR=0.998, 95% CI 0.993-1.003, P=0.379; OR=1.000, 95% CI 0.993-1.006, P=0.918). However, lumbar vBMD was a statistically significant predictor in females ( OR=0.992, 95% CI 0.985-0.999, P=0.032). Multivariate binary logistic regression analysis further demonstrated that age ( OR=1.048, 95% CI 1.019-1.077, P=0.001), hypertension ( OR=2.649, 95% CI 1.719-4.082, P<0.001), and lumbar vBMD ( OR=0.992, 95% CI 0.984-0.999, P=0.022) were independent predictors of moderate-to-severe CAC in women. The AUC of lumbar vBMD for predicting moderate-to-severe CAC in female patients was 0.684 (95% CI 0.641-0.725), and the AUC of the combined model was 0.746 (95% CI 0.705-0.784), with a statistically significant difference ( Z=3.26, P=0.001). Conclusions:Lumbar vBMD measured by QCT is an independent predictor of moderate-to-severe CAC in women and demonstrates moderate predictive value. The predictive performance can be enhanced by integrating age and hypertension into a combined predictive model.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

Objective To investigate the predictive role of transcranial Doppler(TCD)ultrasound combined with invasive intracranial pressure(ICP)monitoring in the early outcomes for patients with moderate-to-severe traumatic brain injury(msTBI)after ICP probe insertion surgery.Methods A retrospective case-control analysis was conducted on the clinical data of 65 msTBI patients who underwent invasive ICP probe insertion surgery within 24 h after injury and routine TCD examination postoperatively in No.904 Hospital of Joint Logistic Support Force of Chinese PLA between January 2021 and March 2025.Based on whether disease progression met the indications for craniotomy,they were divided into a failed conservative treatm ent group(n=28)and a successful conservative treatment group(n=37).Baseline clinical data,and parameters of TCD and ICP monitoring were collected in both groups.Univariate analysis was used for comparing differences in various parameters between the groups.The variables related to ICP and TCD were denoted as Model 1,and variables that significantly affected the outcome were incorporated as potential confounding factors into Model 2 based on clinical experience.Multivariate logistic regression analysis was performed to screen for independent predictors of conservative treatment failure.Receiver operating characteristic(ROC)curves were plotted to evaluate the diagnostic efficacy of each predictive factor.Results Statistical differences were observed between the 2 groups in terms of Glasgow Coma Scale(GCS)score at admission,postoperative mean intracranial pressure(ICPm),postoperative mean cerebral perfusion pressure(CPPm),and pulsatility index(PI)of the ipsilateral internal carotid artery extracranial segment(ICAt),and mean flow velocity(Vm)and pulsatility index(PI)of the ipsilateral middle cerebral artery(MCA)(all P<0.01).After adjusting for age,GCS score at admission,hematoma volum,and mean postoperative brain temperature,multivariate logistic regression analysis revealed that ICPm(OR=1.248,95%CI:1.044～1.491,P=0.015),ipsilateral MCA.Vm(OR=0.964,95%CI:0.933～0.997,P=0.034),and ipsilateral MCA.PI(OR=1.612,95%CI:1.026～2.533,P=0.038)were independent predictors of failure in conservative treatment in msTBI patients.After adjustment,ROC curve analysis demonstrated that the combined model of ipsilateral MCA.PI,ipsilateral MCA.Vm,and ICPm achieved a predictive efficacy of 0.931(95%CI:0.873～0.988),which was obviously higher than that of the single model of ICPm(0.875,95%CI:0.791～0.959).Conclusion Combined monitoring of TCD and ICP can provide a more accurate prediction of the early outcomes for msTBI patients after ICP probe insertion,providing a more effective assessment for clinical diagnosis and treatment.

Objective: To analyze the association between dietary diversity and cognitive function among the elderly using group-based trajectory model, so as to provide the basis for formulating dietary intervention strategies to prevent cognitive impairment. Methods: Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) project, demographic information, lifestyle behaviors, psychological well-being, and activities of daily living of elderly individuals aged ≥65 years from 2008 to 2018 were collected. Dietary diversity was assessed using a food frequency questionnaire, with a score of <7 points defined as low dietary diversity. Cognitive function was evaluated using the Chinese version of the Mini-Mental State Examination (MMSE). A group-based trajectory model was established based on cognitive function scores from 2008 to 2018 to analyze the trajectories of cognitive function change. The association between dietary diversity and cognitive function was analyzed using a multinomial logistic regression model. Results: A total of 1 613 individuals were collected, with a median age was 72.00 (interquartile range, 10.00) years. There were 810 males (50.22%) and 803 females (49.78%). The group-based trajectory model analysis categorized the participants into three groups: the low-level normal group, the high-level normal group, and the slow-then-rapid decline group, comprising 796 (49.35%), 585 (36.27%), and 232 (14.38%) individuals, respectively. Among these groups, the numbers of individuals with low dietary diversity were 497 (62.44%), 311 (53.16%), and 166 (71.55%), respectively, with a statistically significant difference (P<0.05). Multinomial logistic regression analysis showed that after adjusting for demographic information, lifestyle behaviors, psychological well-being, and activities of daily living, compared with the high-level normal group, low dietary diversity was statistically associated with cognitive function in the slow-then-rapid decline group (OR=1.622, 95%CI: 1.103-2.384). Conclusion Low dietary diversity may increase the risk of cognitive impairment among the elderly.

Objective To investigate the clinical characteristics of patients with chronic abacterial pros-tafitis(CAP),the CAP related factors were analyzed,and a risk prediction model for CAP were constructed and validated.Methods The clinical dataes of 252 suspected CAP patients admitted to the hospital from June 2022 to December 2024 were collected,the patients were divided into modeling set(ni=177)and validation set(n=75)by 7∶3 ratio.Based on the modeling set dataes,the Lasso was used to screen CAP related predictive factors,a logistic multiple factor model was used to analyze the independent influence factors of CAP and a risk prediction model was constructed.The validation set patient dataes were used to plot ROC and DCA and validate the predic-tion model.Results There were 86 cases of CAP in the modeling set,accounting for 48.59％;32 cases of CAP in the validation set,accounting for 42.67％.The Logistic multiple regression analysis showed that BMI,waist to hip ratio,abnormal elevation of IL-8,COX-2,and PGE2 in prostate fluid were independent influence factors of CAP(P＜0.05),a Nomogram column chart based on this was established.The ROC analysis showed that the sensitivity of the model for detecting CAP in the modeling and validation sets were 0.814 and 0.802,respectively,and the specificity were 0.673 and 0.703,respectively.The DCA analysis showed that the net benefit thresholds for model-ing and validation sets by column charts are 0.1～0.9 and 0.2～1.0,respectively.Conclusions The occurrence of CAP is related to the patient's BMI,waist to hip ratio,the levels of IL-8,COX-2,and PGE2 in prostate fluid.The predictive model established based on this is highly accurate and it can help for CAP screening.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

The incidence of intracranial aneurysms is higher in population, and the death and disability rates after rupture are extremely high. Early detection of intracranial aneurysms, prediction of rupture risk, operation program, and evaluation of treatment outcomes are all the clinical concerns. With the continuously deepening integration of artificial intelligence technology and medicine, its application in the diagnosis and treatment of intracranial aneurysms is becoming increasingly widespread. This article reviews the current application status of artificial intelligence technology in the diagnosis and treatment of intracranial aneurysms.

Osteoporotic proximal humeral fracture (OPHF) is one of the common osteoporotic fractures in the aged, with an incidence only lower than vertebral compression fracture, hip fracture, and distal radius fracture. OPHF, secondary to osteoporosis and characterized by poor bone quality, comminuted fracture pattern, slow healing, and severely impaired shoulder joint function, poses a big challenge to the current clinical diagnosis and treatment. In the field of diagnosis, treatment, and rehabilitation of OPHF, traditional Chinese and Western medicine have accumulated rich experience and evidence from evidence-based medicine and achieved favorable outcomes. However, there is still a lack of guidance from a relevant consensus as to how to integrate the advantages of the two medical systems and achieve the integrated diagnosis and treatment. To promote the diagnosis and treatment of OPHF with integrated traditional Chinese and Western medicine, relevant experts from Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine have been organized to formulate Expert consensus on the diagnosis and treatment of osteoporotic proximal humeral fracture with integrated traditional Chinese and Western medicine ( version 2024) by searching related literatures and based on the evidences from evidence-based medicine. This consensus consists of 13 recommendations about the diagnosis, treatment and rehabilitation of OPHF with integrated traditional Chinese medicine and Western medicine, aimed at standardizing, systematizing, and personalizing the diagnosis and treatment of OPHF with integrated traditional Chinse and Western medicine to improve the patients ′ function.