Objective: Antidepressant drugs and cognitive-behavioural therapy (CBT) are effective treatment options for depression and are recommended by clinical practice guidelines. As part of the Assessing Cost-effectiveness -- Mental Health project we evaluate the available evidence on costs and benefits of CBT and drugs in the episodic and maintenance treatment of major depression.
Method: The cost-effectiveness is modelled from a health-care perspective as the cost per disability-adjusted life year. Interventions are targeted at people with major depression who currently seek care but receive non-evidence based treatment. Uncertainty in model inputs is tested using Monte Carlo simulation methods.
Results: All interventions for major depression examined have a favourable incremental cost-effectiveness ratio under Australian health service conditions. Bibliotherapy, group CBT, individual CBT by a psychologist on a public salary and tricyclic antidepressants (TCAs) are very cost-effective treatment options falling below 10,000 Australian dollars per disability-adjusted life year (DALY) even when taking the upper limit of the uncertainty interval into account. Maintenance treatment with selective serotonin re-uptake inhibitors (SSRIs) is the most expensive option (ranging from 17,000 Australian dollars to 20,000 Australian dollars per DALY) but still well below 50,000 Australian dollars, which is considered the affordable threshold.
Conclusions: A range of cost-effective interventions for episodes of major depression exists and is currently underutilized. Maintenance treatment strategies are required to significantly reduce the burden of depression, but the cost of long-term drug treatment for the large number of depressed people is high if SSRIs are the drug of choice. Key policy issues with regard to expanded provision of CBT concern the availability of suitably trained providers and the funding mechanisms for therapy in primary care.
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http://dx.doi.org/10.1080/j.1440-1614.2005.01652.x | DOI Listing |
Rev Gaucha Enferm
January 2025
Universidade Federal de Pernambuco (UFPE), Recife, Pernambuco, Brasil.
Objective: To analyze the concept of sexual dysfunction in postpartum women and identify their essential attributes, antecedents, and effects.
Method: Concept analysis based on a framework by Walker and Avant, elaborated in eight stages, which were: concept selection; identification of the use of the concept; determination of essential attributes; construction of the model case; additional case; identification of antecedents and effects; and definition of empirical references. Furthermore, an integrative review was carried out simultaneously, with a view to supporting the analysis of the concept.
Rheumatol Int
January 2025
Department of Rheumatology, Immunology and Internal Medicine, University Hospital in Kraków, Kraków, Poland.
Systemic lupus erythematosus (SLE) is a multisystem autoimmune rheumatic disease (ARD) that results from the dysregulation of multiple innate and adaptive immune pathways. Late-onset SLE (Lo-SLE) is the term used when the disease is first diagnosed after 50-65 years, though the standard age cut-off remains undefined. Defining "late-onset" as lupus with onset after 50 years is more biologically plausible as this roughly corresponds to the age of menopause.
View Article and Find Full Text PDFRadiol Artif Intell
January 2025
From the Department of Radiation Oncology (A.S.G., V.H., H.S.) and Department of Radiology and Imaging Sciences (B.D.W.), Emory University School of Medicine, 1701 Uppergate Dr, C5008 Winship Cancer Institute, Atlanta, GA 30322; Department of Radiology, University of Miami {School of Medicine?}, Miami, Fla (S.S., A.A.M.); Department of {Radiology?} Northwestern University {Feinberg School of Medicine?}, Chicago, Ill (L.A.D.C.); Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, Ga (Y.L.); Department of Psychology, Emory University, Atlanta, Ga (M.T.); and Department of Radiology, Duke University Medical Center, Durham, NC (B.J.S.).
Purpose To develop and evaluate the performance of NNFit, a self-supervised deep-learning method for quantification of high-resolution short echo-time (TE) echo-planar spectroscopic imaging (EPSI) datasets, with the goal of addressing the computational bottleneck of conventional spectral quantification methods in the clinical workflow. Materials and Methods This retrospective study included 89 short-TE whole-brain EPSI/GRAPPA scans from clinical trials for glioblastoma (Trial 1, May 2014-October 2018) and major-depressive-disorder (Trial 2, 2022- 2023). The training dataset included 685k spectra from 20 participants (60 scans) in Trial 1.
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