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.

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 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 correlation between preoperative airway preparation and postoperative day 1 drainage volume in patients undergoing radical esophagectomy and the occurrence of postoperative pulmonary complications.Methods Analyzing the clinical data of esophageal cancer 147 patients who underwent thoracoscopic and laparoscopic radical surgery from January 2022 to June 2024,they were divided into PPCs group and non-PPCs group based on whether PPCs occurred postoperatively.Clinical data of the two groups were compared.Multivariate logistic regression analysis was applied to analyze the influencing factors for the occurrence of PPCs after radical resection of esophageal cancer,and a decision tree prediction model for postoperative PPCs was constructed.Receiver operating characteristic(ROC)curve was used to analyze the value of related factors in predicting the occurrence of PPCs after radical resection of esophageal cancer.Results Univariate analysis showed that age,albumin/fibrinogen ratio,neutrophil/lymphocyte ratio,preoperative respiratory preparation,and drainage volume on the first day after surgery were associated with the occurrence of PPCs after radical resection of esophageal cancer(P＜0.05).Multivariate logistic regression analysis indicated that age,albumin/fibrinogen ratio and drainage volume on the first day after surgery were independent influencing factors for the occurrence of PPCs after radical resection of esophageal cancer(P＜0.05).The decision tree model identified drainage volume on the first day after surgery,albumin/fibrinogen ratio,age and neutrophil/lymphocyte ratio as predictive factors.The incidence rate of PPCs in the group without preoperative respiratory preparation was significantly higher than that in the group with preoperative respiratory preparation(62.5％vs.37.5％,P＜0.05).A drainage volume of 246.59 ml on the first day after surgery was the optimal cutoff value for predicting the occurrence of PPCs after radical resection of esophageal cancer,and specificity was 93.04％,sensitivity was 87.5％,area under ROC curve(AUC)was 0.958,95％CI was 0.911-0.984.Moreover,the incidence rate of PPCs in patients with a drainage volume≤246.59 ml on the first day after surgery was significantly higher than that in patients with a drainage volume＞246.59 ml(77.78％vs.3.60％,P＜0.01).Conclusion Preoperative airway preparation and postoperative drainage volume are closely related to the occurrence of postoperative pulmonary complications(PPCs)after thoracoscopic radical surgery for esophageal cancer.Therefore,targeted measures should be taken for airway preparation before surgery,and changes in the patient's condition should be closely monitored after surgery to accurately determine the timing of drainage tube removal,which plays an important role in effectively preventing and treating PPCs.

Objective To explore the correlation between preoperative airway preparation and postoperative day 1 drainage volume in patients undergoing radical esophagectomy and the occurrence of postoperative pulmonary complications.Methods Analyzing the clinical data of esophageal cancer 147 patients who underwent thoracoscopic and laparoscopic radical surgery from January 2022 to June 2024,they were divided into PPCs group and non-PPCs group based on whether PPCs occurred postoperatively.Clinical data of the two groups were compared.Multivariate logistic regression analysis was applied to analyze the influencing factors for the occurrence of PPCs after radical resection of esophageal cancer,and a decision tree prediction model for postoperative PPCs was constructed.Receiver operating characteristic(ROC)curve was used to analyze the value of related factors in predicting the occurrence of PPCs after radical resection of esophageal cancer.Results Univariate analysis showed that age,albumin/fibrinogen ratio,neutrophil/lymphocyte ratio,preoperative respiratory preparation,and drainage volume on the first day after surgery were associated with the occurrence of PPCs after radical resection of esophageal cancer(P＜0.05).Multivariate logistic regression analysis indicated that age,albumin/fibrinogen ratio and drainage volume on the first day after surgery were independent influencing factors for the occurrence of PPCs after radical resection of esophageal cancer(P＜0.05).The decision tree model identified drainage volume on the first day after surgery,albumin/fibrinogen ratio,age and neutrophil/lymphocyte ratio as predictive factors.The incidence rate of PPCs in the group without preoperative respiratory preparation was significantly higher than that in the group with preoperative respiratory preparation(62.5％vs.37.5％,P＜0.05).A drainage volume of 246.59 ml on the first day after surgery was the optimal cutoff value for predicting the occurrence of PPCs after radical resection of esophageal cancer,and specificity was 93.04％,sensitivity was 87.5％,area under ROC curve(AUC)was 0.958,95％CI was 0.911-0.984.Moreover,the incidence rate of PPCs in patients with a drainage volume≤246.59 ml on the first day after surgery was significantly higher than that in patients with a drainage volume＞246.59 ml(77.78％vs.3.60％,P＜0.01).Conclusion Preoperative airway preparation and postoperative drainage volume are closely related to the occurrence of postoperative pulmonary complications(PPCs)after thoracoscopic radical surgery for esophageal cancer.Therefore,targeted measures should be taken for airway preparation before surgery,and changes in the patient's condition should be closely monitored after surgery to accurately determine the timing of drainage tube removal,which plays an important role in effectively preventing and treating PPCs.

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 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.

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.

Abstract Survival analysis has been widely used in the field of medical research. The Cox proportional hazard model is commonly used, but its practical application is limited. Machine learning method can compensate for the shortcomings of the Cox proportional hazard model in terms of nonlinear data processing and prediction accuracy. This article reviewed the advance of machine learning methods represented by neural networks, within the field of survival analysis, and highlighted the principles and benefits of three machine learning methods that DeepSurv, Deep-Hit and random survival forest, providing methodological insights for the analysis of complex survival data.