Plos One
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Confounding by disease severity is an issue in pharmacoepidemiology studies of rheumatoid arthritis (RA), due to channeling of sicker patients to certain therapies. To address the issue of limited clinical data for confounder adjustment, a patient-level prediction model to differentiate between patients prescribed and not prescribed advanced therapies was developed as a surrogate for disease severity, using all available data from a US claims database. ⋯ A prediction model demonstrated good discrimination across multiple claims databases to identify RA patients with a prescription claim for advanced therapies during different time-at-risk periods as proxy for current and future moderate-to-severe disease. This work provides a robust model-derived risk score that can be used as a potential covariate and proxy measure to adjust for confounding by severity in multivariable models in the RA population. An R package to develop the prediction model and risk score are available in an open source platform for researchers.
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Prioritizing zoonotic diseases is one of the emerging tasks for developing multi-sectoral collaboration within One Health. Globally, many efforts have been made to prioritize zoonotic diseases at national levels, especially in low resource settings. Prioritization of zoonoses has been conducted in different countries at different levels (i.e. national, regional and local) for different purposes. India has also initiated prioritization of zoonotic diseases at the national level. However, in a country like India with wide climatic variations, different animal-human and vector densities, it is important to look at these zoonotic conditions in local settings too. The present study aims to determine which zoonoses should be prioritized for collaboration between stakeholders in the Indian city of Ahmedabad. ⋯ Prioritization of zoonotic diseases at the local level is essential for development of effective One Health strategies. This type of participatory disease prioritization workshop is highly recommended and can be replicated in other Indian cities, as well as in other low and middle-income countries.
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If interprofessional collaborative practice is to be an important component of healthcare reform, then an evidentiary base connecting interprofessional education to interprofessional practice with significantly improved health and healthcare outcomes is an unconditional necessity. This study is a scoping review of the current peer reviewed literature linking interprofessional collaborative care and interprofessional collaborative practice to clearly identified healthcare and/or patient health-related outcomes. The research question for this review was: What does the evidence from the past decade reveal about the impact of Interprofessional collaborative practice on patient-related outcomes in the US healthcare system? ⋯ The results suggest a need for more research on the measurable impact of interprofessional collaborative practice and/or care on patient health-related outcomes to further document its benefits and to explore the models, systems and nature of collaborations that best improve population health, increase patient satisfaction, and reduce cost of care.
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This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the effectiveness of machine learning methods for delta-radiomics feature selection and building classification models. ⋯ The results indicated that delta-features could potentially provide better treatment assessment than single-time-point features. The treatment assessment is substantially affected by the time point for computing the delta-features and the combination of machine learning methods for feature selection and classification.
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Cervical cancer imposes a substantial health burden worldwide including in Australia and is caused by persistent infection with one of 13 sexually transmitted high-risk human papillomavirus (HPV) types. The objective of this study was to assess the cost-effectiveness of adding a nonavalent new Gardasil-9® (9vHPV) vaccine to the national immunisation schedule in Australia across three different delivery strategies. ⋯ This cost-effectiveness evaluation suggests that the routine two-dose 9vHPV vaccination strategy of preadolescent girls against HPV is very cost-effective in Australia from both the health system and societal perspectives. If equally priced, the 9vHPV option is the most economically viable vaccine. Overall, this analysis seeks to contribute to an evidence-based recommendation about the new 9vHPV vaccination in the national immunisation program in Australia.