METHODS: Employing a mixed-methods approach, this research included a literature review and a cross-sectional survey of medicine prices using the World Health Organization/Health Action International (WHO/HAI) methodology. Data were collected from both public and private sectors across six provinces in Thailand during April-May 2023. Additionally, international price comparisons were conducted with countries including Australia, Canada, Denmark, Malaysia, and New Zealand.
RESULTS: The research identified a significant reduction in the median price ratios (MPRs) of medicines, closer alignment of prices with international benchmarks, and decreased variability in pricing between regions and sectors. These changes illustrated the positive effects of Thailand's pricing policies implemented over the past 16 years.
CONCLUSIONS: The strategic interventions implemented by the Thai government have markedly enhanced the regulation and affordability of medicine prices. However, to sustain these achievements and ensure the viability of the local pharmaceutical industry, ongoing efforts and policy adaptations are essential. This study emphasises the critical need for continuous evaluation of these policies to respond effectively to evolving healthcare and economic conditions.
METHODS: Study metrics were recorded. Learning points were captured during network development, categorized and included in a thematic analysis from which lessons learnt were identified.
RESULTS: 12 trials were supported by sites coordinated at national level and integrated at European level. A total of 9 CDA cycles were completed, resulting in 436 site CDAs signed in a median of 8.11 days. Lessons learnt included the importance of: relationship building by early engagement with partners; reducing misunderstanding by clear communication; flexibility, adaptability and experiential learning which are required for service improvement. Practical actions that infrastructure developers and users can take include operational planning with a view to fostering collaborations across stakeholders, sharing information about different approaches to clinical operations, and raising awareness of the need for explicit work on collaboration, communication, and planning. Traditionally, these activities are repeated for each trial. The use of a persistent network allows the benefits of collaboration to be recycled.
DISCUSSION: Building a successful framework for collaboration allows dedication and determination to carry over from one study to another. The initial investment of time to share assumptions and "state the obvious" by each user will support future trials.
METHODS: This is a retrospective observational study of OAG patients who underwent standalone or combined iStent procedures were reviewed. Inclusion criteria included age over 18 years and open angle on gonioscopy. Exclusion criteria were prior incisional glaucoma surgeries, missing data, or follow-up shorter than 6 months. The primary outcome was surgical success between the two groups after one year. Secondary outcomes included differences in IOP reduction and medication use.
RESULTS: We included 48 eyes with primary (n = 44) and secondary OAG (n = 4). Nineteen eyes had standalone while 29 eyes had combined procedures. Kaplan-Meier analysis revealed overall surgical success in 31.3% of eyes after one year. Qualified success was higher in the combined group than the standalone group [62.5% (10 eyes) vs 27.3% (3 eyes), p = 0.239]. At 24 months, mean IOP reduced by 2.2 ± 2.5 mmHg vs 3.3 ± 2.9 mmHg, p = 0.333), and the number of medications reduced by 1.1 ± 1.2 vs 1.3 ± 0.1, p
METHODS: Following PRISMA guidelines, a systematic search was conducted in PubMed and Embase databases. Keywords and standardized index terms related to MEP were used. The search was performed without restriction on the publication date. Screening, data extraction, and quality assessment were carried out. Data on demographics, clinical presentations, management modalities, and treatment outcomes were analyzed.
RESULTS: The search yielded 487 titles, with 36 studies eligible for inclusion. A total of 530 patients with MEP were reported, with a mean age of 50.1 ± 11.62 years. Proptosis was the most common symptom (95%), followed by visual impairment (57.3%), orbital pain (38.3%), ophthalmoplegia (28.6%), and headache (23%). Our patient represented the only case of a patient with a spontaneous CSF leak. Surgical resection was performed in 85%, adjuvant radiotherapy in 15.7%, and 1 patient received primary radiotherapy, and 8 patients were closely followed up with no intervention.
CONCLUSIONS: MEP associated with spontaneous CSF rhinorrhea is extremely rare and poses diagnostic and therapeutic challenges. Conservative management for select cases of MEP can be a good choice, sparing the patient from surgical complications, especially for skull base areas that are difficult to access.
METHODS: The snowball sampling technique was used to collect data through the combination of online electronic questionnaires and offline paper questionnaires, so as to explore the choking phenomenon of elite athletes by attributing the influence of training variables on self-efficacy. The research team conducted a survey of elite athletes in Central China between October and December 2023. In this study, 350 questionnaires were distributed, 350 questionnaires were collected after the questionnaires were distributed, and 328 valid questionnaires were finally eliminated through screening. And the relevant statistical analysis is carried out on the data.
RESULTS: The results confirmed the significant correlations between attribution training and fear of failure (β = -0.548, p
OBJECTIVE: This review aims to explore the role of AI in forecasting outcomes related to chemotherapy development, cancer diagnosis, and treatment response, synthesizing current advancements and identifying critical gaps in the field.
METHODS: A comprehensive literature search was conducted across PubMed, Embase, Web of Science, and Cochrane databases up to 2023. Keywords included "Artificial Intelligence (AI)," "Machine Learning (ML)," and "Deep Learning (DL)" combined with "chemotherapy development," "cancer diagnosis," and "cancer treatment." Articles published within the last four years and written in English were included. The Prediction Model Risk of Bias Assessment tool was utilized to assess the risk of bias in the selected studies.
CONCLUSION: This review underscores the substantial impact of AI, including ML and DL, on cancer diagnosis, chemotherapy innovation, and treatment response for both solid and hematological tumors. Evidence from recent studies highlights AI's potential to reduce cancer-related mortality by optimizing diagnostic accuracy, personalizing treatment plans, and improving therapeutic outcomes. Future research should focus on addressing challenges in clinical implementation, ethical considerations, and scalability to enhance AI's integration into oncology care.