Radiomic nomogram based on bi-parametric magnetic resonance imaging to predict the International Society of Urological Pathology grading ≥ 3 prostate cancer: a multicenter study.

PURPOSE: To create a reliable radiomic nomogram for the prediction of the International Society of Urological Pathology (ISUP) grading ≥ 3 prostate cancer (PCa) patients. METHODS: patients with verified PCa were obtained from three different hospitals. The patients were divided into training, internal validation, and two external validation groups. A radiomic signature (rad-score) extracted from T2WI, diffusion-weighted imaging, and apparent diffusion coefficient (ADC) maps were constructed in the training cohort. Eight clinical features were performed to develop a clinical model using univariate and multivariate logistic regression. The combined model incorporated the radiomic signature and clinical model. The model's performance was assessed by the receiver operating characteristic (ROC) curve. RESULTS: Rad-score, magnetic resonance imaging T-stage, and ADC value were significant predictors of ISUP ≥ 3 PCa. A nomogram of these three factors was shown to have greater diagnostic accuracy than using only the radiomic signature or clinical model alone. The area under the ROC curve was 0.85, 0.88, 0.81, 0.81 for the training, internal, and two external validation cohorts, respectively. In the stratified analysis based on the MR scanner model, the area under the ROC curve of predicting ISUP ≥ 3 PCa for GE, Siemens, and combined groups were 0.84, 0.83, and 0.84, respectively, in the combined training group and an internal validation group. CONCLUSIONS: The proposed nomogram has the potential to predict the differentiation degree of ISUP PCa patients.

[Strategic considerations in health economics for the complete treatment of patients with chronic HBV infection].

The World Health Organization (WHO) released the Global Health Sector Strategy 2016, which explicitly proposes a 90% reduction in the new hepatitis B virus (HBV) infection rate and a 65% reduction in HBV-related mortality by 2030. However, at present, there are still 296 million chronic hepatitis B virus-infected patients worldwide, and nearly 900,000 patients die every year from cirrhosis and liver cancer caused by HBV infection. Antiviral treatment for chronic hepatitis B virus infection can effectively inhibit HBV replication, reduce liver inflammation and necrosis, effectively block and reverse liver fibrosis, and even early cirrhosis, thereby lowering cirrhosis-related complications, liver cancer, and liver disease-related mortality. Although the domestic and foreign guidelines have gradually eased antiviral treatment indications for chronic hepatitis B, there are still a considerable number of chronic hepatitis B patients with nonconformity who cannot receive antiviral treatment because they do not meet the existing standards, resulting in the progression of more severe diseases. This study analyzed the prevalence of hepatitis B, the therapeutic effect of antiviral drugs, domestic and international guideline treatment standards, the assessment of key indicators changes in the guidelines, comprehensively considered the coverage rate and treatment standards for antiviral treatment, and explored the changes in disease burden and cost-effectiveness following increasing the coverage rate and reducing treatment thresholds in order to achieve the global strategic goal of eliminating hepatitis B as soon as possible as a public health threat.

[Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers].

Objective: To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia. Methods: In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction. Results: The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51. Conclusion: Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.

[Evolution and regional differences in the supportive environment for influenza vaccination among the elderly population in China].

Seasonal influenza leads to a significant disease burden, and older people infected with influenza are susceptible to various complications. Influenza immunization can prevent infection effectively and significantly reduce the risk of complications and severe cases. Creating a supportive environment for vaccination is crucial in advancing the influenza vaccination rate among the elderly population. In China, the present environment for supporting influenza vaccinations among the elderly is primarily comprised of policies for free vaccination and expense reimbursement, which exhibit noteworthy regional variations across cities and regions. This study systematically analyses the supportive environment and regional disparities associated with influenza vaccination among the elderly in China. It aims to comprehend the opportunities for influenza prevention and control resulting from the current background of influenza vaccination and to identify potential health inequality challenges caused by regional differences. The findings should inform the introduction of relevant national policies and programs to protect the health and well-being of the elderly population.

COVID-19 vaccines and adverse events of special interest: A multinational Global Vaccine Data Network (GVDN) cohort study of 99 million vaccinated individuals.

BACKGROUND: The Global COVID Vaccine Safety (GCoVS) Project, established in 2021 under the multinational Global Vaccine Data Network™ (GVDN®), facilitates comprehensive assessment of vaccine safety. This study aimed to evaluate the risk of adverse events of special interest (AESI) following COVID-19 vaccination from 10 sites across eight countries. METHODS: Using a common protocol, this observational cohort study compared observed with expected rates of 13 selected AESI across neurological, haematological, and cardiac outcomes. Expected rates were obtained by participating sites using pre-COVID-19 vaccination healthcare data stratified by age and sex. Observed rates were reported from the same healthcare datasets since COVID-19 vaccination program rollout. AESI occurring up to 42 days following vaccination with mRNA (BNT162b2 and mRNA-1273) and adenovirus-vector (ChAdOx1) vaccines were included in the primary analysis. Risks were assessed using observed versus expected (OE) ratios with 95 % confidence intervals. Prioritised potential safety signals were those with lower bound of the 95 % confidence interval (LBCI) greater than 1.5. RESULTS: Participants included 99,068,901 vaccinated individuals. In total, 183,559,462 doses of BNT162b2, 36,178,442 doses of mRNA-1273, and 23,093,399 doses of ChAdOx1 were administered across participating sites in the study period. Risk periods following homologous vaccination schedules contributed 23,168,335 person-years of follow-up. OE ratios with LBCI > 1.5 were observed for Guillain-Barré syndrome (2.49, 95 % CI: 2.15, 2.87) and cerebral venous sinus thrombosis (3.23, 95 % CI: 2.51, 4.09) following the first dose of ChAdOx1 vaccine. Acute disseminated encephalomyelitis showed an OE ratio of 3.78 (95 % CI: 1.52, 7.78) following the first dose of mRNA-1273 vaccine. The OE ratios for myocarditis and pericarditis following BNT162b2, mRNA-1273, and ChAdOx1 were significantly increased with LBCIs > 1.5. CONCLUSION: This multi-country analysis confirmed pre-established safety signals for myocarditis, pericarditis, Guillain-Barré syndrome, and cerebral venous sinus thrombosis. Other potential safety signals that require further investigation were identified.