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 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 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 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 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.

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.

Objective:To analyze the changes rule of serum procalcitonin (PCT) levels in patients with traumatic brain injury in plateau areas, and to evaluate its value in assessing the severity and prognosis of the patients.Methods:A prospective cohort study was conducted. The patients with traumatic brain injury admitted to the critical care medicine departments of Xining Third People's Hospital (at an altitude of 2 260 metres) and Golmud City People's Hospital (at an altitude of 2 780 metres) from May 2018 to September 2022 were enrolled. According to the Glasgow coma scale (GCS) score at admission, the patients were divided into mild injury group (GCS score 13-15), severe injury group (GCS score 9-12), and critical injury group (GCS score 3-8). All patients received active treatment. Chemiluminescence immunoassay was used to measure the serum PCT levels of patients on the 1st, 3rd, 5th, and 7th day of admission. The Kendall tau-b correlation method was used to analyze the correlation between serum PCT levels at different time points and the severity of the disease. The patients were followed up until October 30, 2022. The prognosis of the patients was collected. The baseline data of patients with different prognosis were compared. The Cox regression method was used to analyze the relationship between baseline data, serum PCT levels at different time points and prognosis. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of serum PCT levels at different time points for death during follow-up.Results:Finally, a total of 120 patients with traumatic brain injury were enrolled, including 52 cases in the mild injury group, 40 cases in the severe injury group, and 28 cases in the critical injury group. The serum PCT levels of patients in the mild injury group showed a continuous downward trend with the prolongation of admission time. The serum PCT levels in the severe injury and critical injury groups reached their peak at 3 days after admission, and were significantly higher than those in the mild injury group (μg/L: 3.53±0.68, 4.47±0.63 vs. 0.40±0.14, both P < 0.05), gradually decreasing thereafter, but still significantly higher than the mild injured group at 7 days. Kendall tau-b correlation analysis showed that there was a significant positive correlation between serum PCT levels on days 1, 3, 5, and 7 of admission and the severity of disease ( r value was 0.801, 0.808, 0.766, 0.528, respectively, all P < 0.01). As of October 30, 2022, 92 out of 120 patients with traumatic brain injury survived and 28 died, with a mortality of 23.33%. Compared with the survival group, the GCS score, serum interleukin-6 (IL-6) levels, white blood cell count (WBC) in peripheral blood, and PCT levels in cerebrospinal fluid at admission in the death group were significantly increased [GCS score: 5.20±0.82 vs. 4.35±0.93, IL-6 (ng/L): 1.63±0.45 vs. 0.95±0.27, blood WBC (×10 9/L): 14.31±2.03 vs. 11.95±1.98, PCT in cerebrospinal fluid (μg/L): 11.30±1.21 vs. 3.02±0.68, all P < 0.01]. The serum PCT levels of patients in the survival group showed a continuous downward trend with prolonged admission time. The serum PCT level in the death group peaked at 3 days after admission and was significantly higher than that in the survival group (μg/L: 4.11±0.62 vs. 0.52±0.13, P < 0.01), gradually decreasing thereafter, but still significantly higher than the survival group at 7 days. Cox regression analysis showed that serum IL-6 levels [hazard ratio ( HR) = 17.347, 95% confidence interval (95% CI) was 5.874-51.232], WBC in peripheral blood ( HR = 1.383, 95% CI was 1.125-1.700), PCT levels in cerebrospinal fluid ( HR = 1.952, 95% CI was 1.535-2.482) at admission and serum PCT levels on admission days 1, 3, 5, and 7 [ HR (95% CI) was 6.776 (1.844-24.906), 1.840 (1.069-3.165), 3.447 (1.284-9.254), and 6.666 (1.214-36.618), respectively] were independent risk factors for death during follow-up in patients with traumatic brain injury (all P < 0.05). ROC curve analysis showed that the AUC of serum PCT levels on days 1, 3, 5, and 7 for predicting death during follow-up in patients with traumatic brain injury was all > 0.8 [AUC (95% CI) was 0.898 (0.821-0.975), 0.800 (0.701-0.899), 0.899 (0.828-0.970), 0.865 (0.773-0.958), respectively], indicating ideal predictive value. The optimal cut-off value for serum PCT level at 3 days of admission was 1.88 μg/L, with the sensitivity of 78.6% and specificity of 88.0% for predicting death during follow-up. Conclusions:Abnormal expression of serum PCT levels in patients with traumatic brain injury on the 3rd day of admission was found. The serum PCT levels greater than 3 μg/L may be related to severe illness. The serum PCT levels greater than 1.88 μg/L can predict the poor prognosis of patients. Dynamic observation of changes in serum PCT levels has good evaluation value for the severity and prognosis of patients with traumatic brain injury in plateau areas.