Objective To analyze the clinical significance of subjective visual vertical (SVV) tests at different head deflection angles in assessing utricle function in patients with benign paroxysmal positional vertigo (BPPV). Methods A total of 61 BPPV patients who were treated at the Hearing Impairment and Vertigo Diagnosis and Treatment Center of Otolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine from August 2022 to May 2023 were retrospectively included, and 29 healthy adults were selected as controls. SVV tests were performed on all research subjects at different head deflection angles: upright head (0°), left head 45° (L45°), right head 45° (R45°). The test results between the two groups were compared. Results SVV absolute value at R45° in BPPV group was lower than that in the control group (P＝0.003); there was no significant difference in SVV values at 0° and L45° between the two groups. There was no statistical difference in SVV values at different head deflection angles between the control group and the left BPPV group. SVV absolute value at R45° in right BPPV group was lower than that in the control group (P＜0.001); there was no statistical difference in SVV values at 0° and L45° between the two groups. Conclusions SVV test can provide subjective information about the utricle, and SVV tests at different head deflection angles can fine-tune evaluate the function of the utricle in BPPV patients.

Objective To analyze the usage of pediatric drugs in 17 pediatric specialty hospitals from 2016 to 2020, and provide reference and guidance for the development of the essential medicine list （EML） for children and the improvement of the National Reimbursement Drug List （NRDL） in China. Methods Based on the pediatric medication monitoring data from 17 children's specialized hospitals reported to the Chinese Medical Economic Information Network (CMEI) of the Chinese Pharmaceutical Association between 2016 and 2020, this study analyzes the overall situation of the sample hospitals and the clinical use of pediatric drugs according to the major categories of the Anatomical Therapeutic Chemical Classification System （ATC）. Results In the various ATC categories, the trend of systemic use of anti-infective drugs decreasing was significant in the average hospital expenditure, while the trend of respiratory and digestive system and metabolic drugs decreasing was significant in the average hospital DDDS. In 2020, the average number of hospital grade standards for essential drugs （2018 version） accounted for 15.82% of the total number of drug use standards, while the average number of hospital grade standards for medical insurance （2019 version） accounted for 8.23% of the total number of drug use standards. Conclusion The use of pediatric medication in sample hospitals from 2016 to 2020 was generally reasonable, and there would still a certain gap between the actual clinical usage habits with the existing EML and NRDL，which still need to be adjusted.

To analyze the factors affecting the cost of hospitalization for patients and provide insights using the intrauterine lesion surgery group (DRG code NE19) as an example.

Objective:To establish a risk prediction model of liver failure after liver resection for hepatocellular carcinoma.Method:A retrospective case-control study was designed. Clinical data and laboratory results, including gender, age, and preoperative 18 laboratory indicators, were collected from 320 patients with hepatocellular carcinoma undergoing liver resection in Eastern Hepatobiliary Surgery Hospital Affiliated to Naval Medical University from January 1, 2013 to December 31, 2023. According to the surgical time, 252 cases in the training cohort were divided into 62 and 190 cases with and without postoperative liver failure, respectively. Of the 68 cases in validation cohort, 34 developed postoperative liver failure and 34 did not. Binary Logistic regression analysis was used to conduct univariate analysis of gender, age, and 18 preoperative laboratory indicators, and multivariate analysis was carried out for significant results to determine the influencing factors of liver failure after liver resection for hepatocellular carcinoma, and Logistic regression model was established.Result:In the training cohort, indicators significantly associated with liver failure after liver resection for hepatocellular carcinoma included age ( P=0.016), platelets ( P=0.005), prealbumin ( P<0.001), and alkaline phosphatase ( P<0.001). Logistic regression was used to construct a nomogram model and draw a calibration curve by combining these four indicators. In the training cohort, the nomogram model showed good discriminability in predicting the risk of liver failure after hepatectomy for hepatocellular carcinoma. The area under the curve of was 0.82 (95% CI 0.76-0.88), and the sensitivity was 73% and specificity was 80% when the optimal cut-off value was 0.2646. In the validation cohort, the predictive performance of the nomogram model was comparable to that of the training cohort, with an area under the curve of 0.81 (95% CI 0.71-0.92), sensitivity of 82%, and specificity of 77%. Conclusion:Preoperative platelet and prealbumin decreases, alkaline phosphatase increases, and elderly patients are prone to liver failure after liver resection. The nomogram model constructed with preoperative test data has shows good discriminatory ability and accuracy in predicting liver failure after liver resection for hepatocellular carcinoma.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective:To systematically evaluate the prevalence of malnutrition in elderly patients with diabetes.Methods:A total of eight databases, namely PubMed, Embase, Web of Science, The Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, Chinese Biomedical Literature Database (CBM), and VIP Database, were systematically searched for cross-sectional studies on malnutrition in elderly diabetic patients published from the inception of the databases to September 13, 2023. Two researchers independently conducted literature screening, data extraction, and quality assessment. Data analysis was performed using Stata 16.0 software.Results:A total of 22 studies were included, involving 6 349 elderly diabetic patients. Results of the meta-analysis showed that the overall prevalence of malnutrition in elderly patients with diabetes was 32.3% (95% CI: 0.21 to 0.43), and the prevalence of at-risk of malnutrition was 49.0% (95% CI: 0.31 to 0.67). Subgroup analysis showed that the prevalence of malnutrition in elderly diabetic patients with chronic complications (56.8%) was significantly higher than those without chronic complications (21.9%). Inpatients also showed a higher prevalence compared with outpatients and community (44.4%, 29.0%, and 18.5%, respectively). The prevalence of malnutrition as per mini-nutritional assessment scale was higher than that as per mini-nutritional assessment short-form scale (35.8% vs. 23.3%, P<0.05). There was no significant difference in the prevalence of malnutrition in elderly diabetic patients of different genders ( P>0.05). Conclusions:The prevalence of malnutrition and at-risk of malnutrition in elderly diabetic patients is high. In clinical practice, we should not only strengthen the early diagnosis of malnutrition in patients, but also emphasize the screening of malnutrition risk, implement timely corresponding interventions, and promote patient education on nutrition and health, to improve the prognosis and quality of life in elderly diabetes patients.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.