Effects of bioglass nanoparticles on bioactivity and mechanical property of poly(3-hydroxybutirate) scaffolds

The development of composite scaffold materials in bone tissue engineering is gaining appeal, as the beneficial properties of two or more types of material can be compounded together to better respond to the mechanical and physiological demands of the host tissue. In this study, poly (3-hydroxybutyrate) was reinforced with a different weight ratio of nanobioglass (0, 2.5, 5, 7.5 and 10 wt%). The nanocomposite scaffolds were successfully prepared by the salt leaching process with various volume fractions of porosities (70, 80 and 90 wt% of NaCl). The results of our studies showed a favorable interaction between polymer and bioglass nanoparticles, which improved interfaces and mechanical properties, especially in samples which were prepared with 70 wt% NaCl. The Young's modulus of samples ranged from 7.23 MPa to 48.27 MPa, which were in the range of the Young's modulus of cancellous bone. The analysis results of samples which were immersed in SBF showed that hydroxyapatite formed on the nanocomposite scaffold surfaces, and they exhibited high bioactivity compared to the pure PHB scaffolds. In this study, nanobioglass, as a reinforcement phase with low mass fraction, is shown to be more effective than micro-materials with high mass fraction.</p

A critical review of model-based economic studies of depression: modelling techniques, model structure and data sources

Depression is the most common mental health disorder and is recognized as a chronic disease characterized by multiple acute episodes/relapses. Although modelling techniques play an increasingly important role in the economic evaluation of depression interventions, comparatively little attention has been paid to issues around modelling studies with a focus on potential biases. This, however, is important as different modelling approaches, variations in model structure and input parameters may produce different results, and hence different policy decisions. This paper presents a critical review of literature on recently published model-based cost-utility studies of depression. Taking depression as an illustrative example, through this review, we discuss a number of specific issues in relation to the use of decision-analytic models including the type of modelling techniques, structure of models and data sources. The potential benefits and limitations of each modelling technique are discussed and factors influencing the choice of modelling techniques are addressed. This review found that model-based studies of depression used various simulation techniques. We note that a discrete-event simulation may be the preferred technique for the economic evaluation of depression due to the greater flexibility with respect to handling time compared with other individual-based modelling techniques. Considering prognosis and management of depression, the structure of the reviewed models are discussed. We argue that a few reviewed models did not include some important structural aspects such as the possibility of relapse or the increased risk of suicide in patients with depression. Finally, the appropriateness of data sources used to estimate input parameters with a focus on transition probabilities is addressed. We argue that the above issues can potentially bias results and reduce the comparability of economic evaluations.Hossein Haji Ali Afzali, Jonathan Karnon and Jodi Gra

Community, parental and adolescent awareness and knowledge of meningococcal disease

Abstract not availableBing Wanga, Michelle Clarke, Hossein Haji Ali Afzali, Helen Marshal

Electrospun PGA/gelatin nanofibrous scaffolds and their potential application in vascular tissue engineering

Hadi Hajiali1, Shapour Shahgasempour1, M Reza Naimi-Jamal2, Habibullah Peirovi11Nanomedicine and Tissue Engineering Research Center, Shahid Beheshti University of Medical Sciences; 2Department of Chemistry, Iran University of Science and Technology, Tehran, IranBackground and methods: In this study, gelatin was blended with polyglycolic acid (PGA) at different ratios (0, 10, 30, and 50 wt%) and electrospun. The morphology and structure of the scaffolds were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and differential scanning calorimetry. The mechanical properties were also measured by the tensile test. Furthermore, for biocompatibility assessment, human umbilical vein endothelial cells and human umbilical artery smooth muscle cells were cultured on these scaffolds, and cell attachment and viability were evaluated.Results: PGA with 10 wt% gelatin enhanced the endothelial cells whilst PGA with 30 wt% gelatin increased smooth muscle cell adhesion, penetration, and viability compared with the other scaffold blends. Additionally, with the increase in gelatin content, the mechanical properties of the scaffolds were improved due to interaction between PGA and gelatin, as revealed by Fourier transform infrared spectroscopy and differential scanning calorimetry.Conclusion: Incorporation of gelatin improves the biological and mechanical properties of PGA, making promising scaffolds for vascular tissue engineering.Keywords: polyglycolic acid, gelatin, nanofiber, vascular tissue engineering, biocompatible scaffold&amp;nbsp

Model performance evaluation (validation and calibration) in model-based studies of therapeutic interventions for cardiovascular diseases: A review and suggested reporting framework

Decision analytic models play an increasingly important role in the economic evaluation of health technologies. Given uncertainties around the assumptions used to develop such models, several guidelines have been published to identify and assess ‘best practice’ in the model development process, including general modelling approach (e.g., time horizon), model structure, input data and model performance evaluation. This paper focuses on model performance evaluation. In the absence of a sufficient level of detail around model performance evaluation, concerns regarding the accuracy of model outputs, and hence the credibility of such models, are frequently raised. Following presentation of its components, a review of the application and reporting of model performance evaluation is presented. Taking cardiovascular disease as an illustrative example, the review investigates the use of face validity, internal validity, external validity, and cross model validity. As a part of the performance evaluation process, model calibration is also discussed and its use in applied studies investigated. The review found that the application and reporting of model performance evaluation across 81 studies of treatment for cardiovascular disease was variable. Cross-model validation was reported in 55 % of the reviewed studies, though the level of detail provided varied considerably. We found that very few studies documented other types of validity, and only 6 % of the reviewed articles reported a calibration process. Considering the above findings, we propose a comprehensive model performance evaluation framework (checklist), informed by a review of best-practice guidelines. This framework provides a basis for more accurate and consistent documentation of model performance evaluation. This will improve the peer review process and the comparability of modelling studies. Recognising the fundamental role of decision analytic models in informing public funding decisions, the proposed framework should usefully inform guidelines for preparing submissions to reimbursement bodies.Hossein Haji Ali Afzali, Jodi Gray, Jonathan Karno

Lifetime costs of invasive meningococcal disease: a Markov model approach

Introduction: Invasive meningococcal disease (IMD) is an uncommon but life-threatening infectious disease associated with high sequelae rates in young children and an increased risk of mortality in adolescents and young adults. Funding decisions to reject inclusion of new meningococcal serogroup B vaccines on national immunisation schedules have been criticised by IMD patients, their families, paediatricians and charity organisations. We aim to estimate the lifetime costs of IMD with the best available evidence to inform cost-effectiveness analyses. Methods: A Markov model was developed taking healthcare system and societal perspectives. A range of data including age-specific mortality rates, and probabilities of IMD-related sequelae were derived from a systematic review and meta-analysis. All currencies were inflated to year 2017 prices by using consumer price indexes in local countries and converted to US dollars by applying purchasing power parities conversion rates. Expert panels were used to inform the model development process including key structural choices and model validations. Results: The estimated lifetime societal cost is US$319,896.74 per IMD case including the direct healthcare cost of US$65,035.49. Using a discount rate of 5%, the costs are US$54,278.51 and US$13,968.40 respectively. Chronic renal failure and limb amputation result in the highest direct healthcare costs per patient. Patients aged < 5 years incur the higher healthcare expenditure compared with other age groups. The costing results are sensitive to the discount rate, disease incidence, acute admission costs, and sequelae rates and costs of brain injuries and epilepsy. Conclusions: IMD can result in substantial costs to the healthcare system and society. Understanding the costs of care can assist decision-making bodies in evaluating cost-effectiveness of new vaccine programs.Bing Wang, Hossein Haji Ali Afzali, Lynne Giles, Helen Marshal

Improving the accuracy and comparability of model-based economic evaluations of health technologies for reimbursement decisions: a methodological framework for the development of reference models

Increasingly, decision analytic models are used within economic evaluations of health technologies (e.g., pharmaceuticals) submitted to national reimbursement bodies in countries like Australia and UK, where such models play a fundamental role in informing public funding decisions. Concerns regarding the accuracy of model outputs and hence the credibility of national reimbursement decisions are frequently raised. We propose a framework for developing reference models for specific diseases to inform economic evaluations of health technologies and their appraisal. The structure of a reference model reflects the natural history of the condition under study and defines the clinical events to be represented, the relationships between the events, and the effect of patient characteristics on the probability and timing of events. We contend that the use of reference models will improve the accuracy and comparability of public funding decisions. This can lead to the more efficient allocation of public funds.Hossein Haji Ali Afzali, Jonathan Karnon and Tracy Merli