Skip to main navigation
Skip to search
Skip to main content
WashU Medicine Research Profiles Home
Help & FAQ
Home
Profiles
Departments, Divisions and Centers
Research output
Search by expertise, name or affiliation
Predicting remission in late-life major depression: A clinical algorithm based upon past treatment history
Erica L.F. Buchalter
, Hanadi Ajam Oughli
,
Eric J. Lenze
, David Dixon
,
J. Philip Miller
, Daniel M. Blumberger
, Jordan F. Karp
, Charles F. Reynolds
, Benoit H. Mulsant
Bursky Center for Human Immunology & Immunotherapy Programs (CHiiPs)
Institute of Clinical and Translational Sciences (ICTS)
COVID-19 Researchers
Institute for Informatics, Data Science and Biostatistics (I2DB)
Siteman Cancer Center
Department of Psychiatry
Intellectual and Developmental Disabilities Research Center (IDDRC)
Hope Center for Neurological Disorders
School of Medicine
Research output
:
Contribution to journal
›
Article
›
peer-review
33
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Predicting remission in late-life major depression: A clinical algorithm based upon past treatment history'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Remission
100%
Major Depressive Disorder
100%
Treatment History
100%
Late-life Depression
100%
Antidepressant Efficacy
100%
Clinical Algorithm
100%
Past Treatments
100%
Older Adults
75%
Venlafaxine
75%
Remission Rate
50%
Antidepressants
50%
Class of Priors
50%
DSM-IV
25%
High Dose
25%
Number of Patients
25%
Detailed Data
25%
Treatment Trials
25%
Prior Treatment
25%
Antidepressant Treatment
25%
Venlafaxine Extended Release
25%
Serotonin-norepinephrine Reuptake Inhibitors
25%
Successful Treatment Outcome
25%
Neuroscience
Antidepressant
100%
Major Depressive Disorder
100%
Venlafaxine
57%
Serotonin-Norepinephrine Reuptake Inhibitor
14%