Nicole R Provenza

Feb 6, 2025 | digitalcommons.library.tmc.edu | Sudhanvan Iyer |Kathryn Jones |Jill K. Robinson |Nicole R Provenza

KeywordsInformation Dissemination, Humans, Neurosciences, EcosystemAbstractIn this paper, we provide an overview and analysis of the BRAIN Initiative data-sharing ecosystem. First, we compare and contrast the characteristics of the seven BRAIN Initiative data archives germane to data sharing and reuse, namely data submission and access procedures and aspects of interoperability.

Jan 26, 2025 | nature.com | Joshua Chen |Robert Garcia |Ariadna Robledo |Joshua Woods |Fatima Alrashdan |Sean O’Leary | +7 more

Correction to: Nature Biomedical Engineering https://doi.org/10.1038/s41551-024-01281-9, published online 11 November 2024. In the version of this article initially published, the Data availability section did not include the statement “The data that support the findings of this study are openly available via figshare at https://doi.org/10.6084/m9.figshare.27616083” as is now amended in the HTML and PDF versions of the article. About this articleChen, J.C., Dhuliyawalla, A., Garcia, R. et al.

Nov 10, 2024 | nature.com | Joshua Chen |Robert Garcia |Ariadna Robledo |Joshua Woods |Fatima Alrashdan |Sean O’Leary | +7 more

AbstractMinimally invasive neural interfaces can be used to diagnose, manage and treat many disorders, with reduced risks of surgical complications. However, endovascular probes lack access to key cortical, subcortical and spinal targets, and are not typically explantable after endothelialization. Here we report the development and testing, in sheep, of endocisternal neural interfaces that approach brain and spinal cord targets through inner and outer spaces filled with cerebrospinal fluid.

Jun 7, 2024 | nature.com | Katherine E. Kabotyanski |Ricardo Najera |Garrett P. Banks |Himanshu Sharma |Nicole R Provenza |Benjamin Y. Hayden | +2 more

Treatment-resistant depression (TRD) affects approximately 2.8 million people in the U.S. with estimated annual healthcare costs of $43.8 billion. Deep brain stimulation (DBS) is currently an investigational intervention for TRD. We used a decision-analytic model to compare cost-effectiveness of DBS to treatment-as-usual (TAU) for TRD. Because this therapy is not FDA approved or in common use, our goal was to establish an effectiveness threshold that trials would need to demonstrate for this therapy to be cost-effective. Remission and complication rates were determined from review of relevant studies. We used published utility scores to reflect quality of life after treatment. Medicare reimbursement rates and health economics data were used to approximate costs. We performed Monte Carlo (MC) simulations and probabilistic sensitivity analyses to estimate incremental cost-effectiveness ratios (ICER; USD/quality-adjusted life year [QALY]) at a 5-year time horizon. Cost-effectiveness was defined using willingness-to-pay (WTP) thresholds of $100,000/QALY and $50,000/QALY for moderate and definitive cost-effectiveness, respectively. We included 274 patients across 16 studies from 2009–2021 who underwent DBS for TRD and had ≥12 months follow-up in our model inputs. From a healthcare sector perspective, DBS using non-rechargeable devices (DBS-pc) would require 55% and 85% remission, while DBS using rechargeable devices (DBS-rc) would require 11% and 19% remission for moderate and definitive cost-effectiveness, respectively. From a societal perspective, DBS-pc would require 35% and 46% remission, while DBS-rc would require 8% and 10% remission for moderate and definitive cost-effectiveness, respectively. DBS-pc will unlikely be cost-effective at any time horizon without transformative improvements in battery longevity. If remission rates ≥8–19% are achieved, DBS-rc will likely be more cost-effective than TAU for TRD, with further increasing cost-effectiveness beyond 5 years.