Evidence map›Paper›PMID 30718459›Full record

Trial reportTranslational psychiatry2019

Prefrontal networks dynamically related to recovery from major depressive disorder: a longitudinal pharmacological fMRI study.

Bernhard M Meyer, Ulrich Rabl, Julia Huemer, Lucie Bartova, Klaudius Kalcher, Julian Provenzano, Christoph Brandner, Patrick Sezen, Siegfried Kasper, Alan F Schatzberg and 3 more

Abstract readClinical Trial, Phase IV
In one paragraph

Trial report in Translational psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  8. TRPC4/5 inhibitors: Phase I results and proof of concept studies.European archives of psychiatry and clinical neuroscience · 2025
    Review
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  19. Prefrontal cortex and depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Bernhard M MeyerDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Ulrich RablDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Julia HuemerDepartment of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria.
Lucie BartovaDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Klaudius KalcherMR Centre of Excellence, Medical University of Vienna, Vienna, Austria.
Julian ProvenzanoDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Christoph BrandnerDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Patrick SezenDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Siegfried KasperDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Alan F SchatzbergDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA.
Ewald MoserMR Centre of Excellence, Medical University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0001-8278-9583
Gang ChenScientific and Statistical Computational Core, National Institute of Mental Health, Bethesda, MA, USA.
Lukas PezawasDivision of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria. lukas.pezawas@meduniwien.ac.at.ORCID http://orcid.org/0000-0002-1329-6352

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to lacking predictors of depression recovery, successful treatment of major depressive disorder (MDD) is frequently only achieved after therapeutic optimization leading to a prolonged suffering of patients. This study aimed to determine neural prognostic predictors identifying non-remitters prior or early after treatment initiation. Moreover, it intended to detect time-sensitive neural mediators indicating depression recovery. This longitudinal, interventional, single-arm, open-label, phase IV, pharmacological functional magnetic resonance imaging (fMRI) study comprised four scans at important stages prior (day 0) and after escitalopram treatment initiation (day 1, 28, and 56). Totally, 22 treatment-free MDD patients (age mean ± SD: 31.5 ± 7.7; females: 50%) suffering from a concurrent major depressive episode without any comorbid DSM-IV axis I diagnosis completed the study protocol. Primary outcome were neural prognostic predictors of depression recovery. Enhanced de-activation of anterior medial prefrontal cortex (amPFC, single neural mediator) indicated depression recovery correlating with MADRS score and working memory improvements. Strong dorsolateral PFC (dlPFC) activation and weak dlPFC-amPFC, dlPFC-posterior cingulate cortex (PCC), dlPFC-parietal lobe (PL) coupling (three prognostic predictors) hinted at depression recovery at day 0 and 1. Preresponse prediction of continuous (dlPFC-PL: R

Indexed as

Major Depressive DisorderMemory, Short-TermNerve NetPrefrontal CortexAdultCitalopramConnectomeFemaleGyrus CinguliHumansLongitudinal StudiesMagnetic Resonance ImagingMaleOutcome Assessment, Health CareParietal LobePrognosisCitalopramSelective Serotonin Reuptake Inhibitors

Identifiers

PMID30718459
PMCPMC6362173

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.