Journal of Clinical Investigation (J CLIN INVEST )
The Journal of Clinical Investigation has a respected history as a vital publication for the physician and scientist alike. Since 1924, the JCI has published research that examines the basic science behind clinical presentation. The JCI continues to offer expanded commentary on published articles and series focused on critical topics in emerging areas of biomedicine.
- Impact factor12.81Show impact factor historyHide impact factor history
- 5-year impact14.69
- Cited half-life9.70
- Immediacy index2.59
- Article influence6.43
- WebsiteJournal of Clinical Investigation website
- Material typeDocument, Periodical, Internet resource
- Document typeInternet Resource, Computer File, Journal / Magazine / Newspaper
- Author cannot archive a pre-print version
- Author can archive a post-print version
- Personal websites, institutional and funding-body repositories
- Published source must be acknowledged
- Please use publisher PDF
- Cannot appear before publication
- Classification blue
Publications in this journal
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ABSTRACT: Patient responses to placebo and sham effects are a major obstacle to the development of therapies for brain disorders, including Parkinson's disease (PD). Here, we used functional brain imaging and network analysis to study the circuitry underlying placebo effects in PD subjects randomized to sham surgery as part of a double-blind gene therapy trial. Metabolic imaging was performed prior to randomization, then again at 6 and 12 months after sham surgery. In this cohort, the sham response was associated with the expression of a distinct cerebello-limbic circuit. The expression of this network increased consistently in patients blinded to treatment and correlated with independent clinical ratings. Once patients were unblinded, network expression declined toward baseline levels. Analogous network alterations were not seen with open-label levodopa treatment or during disease progression. Furthermore, sham outcomes in blinded patients correlated with baseline network expression, suggesting the potential use of this quantitative measure to identify "sham-susceptible" subjects before randomization. Indeed, Monte Carlo simulations revealed that a priori exclusion of such individuals substantially lowers the number of randomized participants needed to demonstrate treatment efficacy. Individualized subject selection based on a predetermined network criterion may therefore limit the need for sham interventions in future clinical trials.Journal of Clinical Investigation 07/2014; 124(8):3656-3666.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.
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