Aims Use of an absorbable antibacterial envelope during implantation prevents cardiac implantable electronic device infections in patients with a moderate-to-high infection risk. Previous studies demonstrated that an envelope is cost-effective in high-risk patients within German, Italian, and English healthcare systems, but these analyses were based on limited data and may not be generalizable to other healthcare settings. Methods and results A previously published decision-tree-based cost-effectiveness model was used to compare the costs per quality-adjusted life year (QALY) associated with adjunctive use of an antibacterial envelope for infection prevention compared to standard-of-care intravenous antibiotics. The model was adapted using data from a Danish observational two-centre cohort study that investigated infection-risk patients undergoing cardiac resynchronization therapy (CRT) reoperations with and without an antibacterial envelope (n = 1943). We assumed a cost-effectiveness threshold of €34 125/QALY gained, based on the upper threshold used by the National Institute for Health and Care Excellence (£30 000). An antibacterial envelope was associated with an incremental cost-effectiveness ratio (ICER) of €12 022 per QALY in patients undergoing CRT reoperations, thus indicating that the envelope is cost-effective when compared with standard of care. A separate analysis stratified by device type showed ICERS of €6227 (CRT defibrillator) and €29 177 (CRT pacemaker) per QALY gained. Conclusions Cost-effectiveness ratios were favourable for patients undergoing CRT reoperations in the Danish healthcare system, and thus are in line with previous studies. Results from this study can contribute to making the technology available to Danish patients and align preventive efforts in the pacemaker and ICD area.
We evaluated the FDA approved SARS-CoV-2 immunoassay (developed at Mount Sinai, by Krammer and colleagues) for the identification of COVID-19 seroconversion and potential cross-reactivity of the assay in a United Kingdom (UK) National Health Service (NHS) hospital setting. In our "set up" cohort we found that the SARS-CoV-2 IgG was detectable in 100% of patients tested 14 days post positive COVID-19 nucleic acid test. Serum samples taken from pregnant women in 2018 were used as a negative control group with zero false positives. We also analysed samples from patients with non-COVID-19 viral infections, paraproteinaemia or autoantibodies and found false positive results in 6/179. Modification of the sensitivity threshold to five standard deviations from the mean of the control group eliminated all false positive result in the set up cohort. We confirmed the validity of the test with a revised threshold on an independent prospective "validation cohort" of patient samples. Taking data from both cohorts we report a sensitivity of the Mount Sinai assay of 96.6% (28/29) and specificity of 100% (299/299) using a revised threshold cut-off, at a time point at least 14 days since the diagnostic antigen test. Finally, we conducted a health economic probabilistic sensitivity analysis (PSA) on the costs of producing the tests, and the mean cost we estimate to be 13.63 pounds sterling (95%CI 9.63 - 18.40), allowing its cost effectiveness to be tested against other antibody tests. In summary, we report that the Mount Sinai IgG ELISA assay is highly sensitive test for SARS-Cov-2 infection, however modification of thresholding was required to minimise false positive results.
Background Schizophrenia is a serious mental health condition characterised by distortions in thought processes, perception, mood, sense of self, and behaviour. Lurasidone, a second-generation atypical antipsychotic, represents an additional treatment option alongside existing antipsychotics for adolescents and adults with schizophrenia. An economic model was developed to evaluate the incremental costs of lurasidone as a first-line treatment option compared to existing antipsychotics. Methods A Markov model was developed to estimate the cost impact of lurasidone as a first-line treatment option for both adolescents and adults. The sequence-based model incorporated the following health states: stable (no relapse or discontinuation), discontinuation (due to adverse events or other reasons), and relapse. Data used to determine the movement of patients between health states were obtained from network meta-analyses (NMAs). The time horizon ranged from three to five years (depending on the patient population) and a six-weekly cycle length was used. Unit costs and resource use were reflective of the UK NHS and Personal Social Services and consisted of the following categories: outpatient, adverse events, primary and residential care. Extensive deterministic sensitivity analysis was undertaken to assess the level of uncertainty associated with the base case results. Results Lurasidone is demonstrated to be cost-saving as a first-line treatment within the adolescent and adult populations when compared to second-line and third-line respectively. Lurasidone is more expensive in terms of treatment costs, resource use (in the stable health state) and the treatment of adverse events. However, these costs are outweighed by the savings associated with the relapse health state. Lurasidone remains cost-saving when inputs are varied in sensitivity analysis and scenario analysis. Conclusions Lurasidone is a cost-saving first-line treatment for schizophrenia for both adolescents and adults.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.