ArticleFrontiers in psychiatry2020
State-Independent and -Dependent Structural Connectivity Alterations in Depression.
Article in Frontiers in psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 2 syntheses or guidelines pooled it, 7 citations in OpenAlex.
- Meta-Analysis of Brain Volumetric Abnormalities in Patients with Remitted Major Depressive Disorder.Depression and anxiety · 2024Pooled it
- Brain connectivity in major depressive disorder: a precision component of treatment modalities?Translational psychiatry · 2023Pooled it
- A lateralized model of the pain-depression dyad.Neuroscience and biobehavioral reviews · 2021Review
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Some brain abnormalities persist at the remission phase, that is, the state-independent abnormalities, which may be one of the reasons for the high recurrence of major depressive disorder (MDD). Hence, it is of great significance to identify state-independent abnormalities of MDD through longitudinal investigation. Ninety-nine MDD patients and 118 healthy controls (HCs) received diffusion tensor imaging scanning at baseline. After 6-month antidepressant treatment, 68 patients received a second scan, among which 59 patients achieved full clinical remission. Differences in whole-brain structural connectivity (SC) between patients with MDD at baseline and HCs were estimated by two-sample
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