Evidence map›Paper›PMID 42094082›Full record

ArticleNeuropsychiatric disease and treatment2026

Optimizing Identification and Management of Depression in Neurological Diseases: A Narrative Review and Expert Perspective.

Lucie Bartova, Mara Lisa Beuster, Bruno Bonetti, Giuseppe Maina, Pedro Morgado, Johan Nyberg

Abstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Lucie BartovaDepartment of Psychiatry and Psychotherapy, Clinical Division of General Psychiatry, and Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria.
Mara Lisa BeusterInselspital, University Hospital Bern, Bern, Switzerland.
Bruno BonettiDepartment of Neurosciences, Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy.
Giuseppe MainaDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.
Pedro MorgadoLife and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal; Clinical Academic Center - Braga, Braga, Portugal.
Johan NybergStortorgets Neurologmottagning, Helsingborg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive brain health is increasingly being recognized as critically important worldwide and incorporates elements of neurological and psychiatric health. This evolution in the view of cerebral wellbeing considers the many factors that can affect brain health and the interconnectedness of conditions affecting this organ. Such interplay between neurological and depressive diseases is highlighted by observations that these conditions share underlying pathophysiology and frequently co-occur in the same patient. A review of the literature on depression in post-stroke, Parkinson's disease, multiple sclerosis, and migraine, confirmed the high prevalence of depression in patients with neurological diseases, with approximately one third of patients with neurological diseases having depression. The search results also highlighted the importance of early detection of depression, and that appropriate treatment may substantially improve outcomes of both the depression and the neurological disease. However, there was a disparity in the amount of literature on depression in the different neurological diseases, with only three of the 80 retrieved articles discussing migraine and depression. Information on multidisciplinary care was also limited. Unmet needs with respect to management of depression in patients with neurological diseases include effective screening processes that can differentiate between overlapping symptoms. There is also a lack of clear, evidence-based treatment guidelines. Based on our clinical experience, we provide recommendations for best practice management of depression in patients with neurological diseases, including structured patient interviews to aid with diagnosis of depression, involvement of patient families and friends where relevant, multidisciplinary care that incorporates personalized treatment based on the specific symptoms, co-medications and needs of the patient, and continued follow up and monitoring. Antidepressant options are available with different mechanisms of action and adverse event profiles. Overall, evidence indicates that depression in neurological disorders is underdiagnosed and undertreated. We suggest that structured screening and tailored, multidisciplinary care can improve outcomes.

Indexed as

antidepressantbrain diseasemajor depressive disordermoodnervous system diseasepersonalized

Identifiers

PMID42094082
PMCPMC13142263

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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.