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Record W4319262254 · doi:10.1002/gps.5882

Distinguishing apathy from depression: A review differentiating the behavioral, neuroanatomic, and treatment‐related aspects of apathy from depression in neurocognitive disorders

2023· review· en· W4319262254 on OpenAlexaff
Krista L. Lanctôt, Zahinoor Ismail, Kritleen K. Bawa, Jeffrey L. Cummings, Masud Husain, Moyra E. Mortby, Philippe Robert

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2023
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of CalgaryHealth Sciences CentreUniversity of TorontoOntario Brain InstituteSunnybrook Health Science Centre
FundersNational Institute of General Medical SciencesNational Institute on AgingCerevel Therapeutics
KeywordsApathyNeurocognitiveDepression (economics)PsychologyPsychiatryClinical psychologyCognition

Abstract

fetched live from OpenAlex

OBJECTIVES: This narrative review describes the clinical features of apathy and depression in individuals with neurocognitive disorders (NCDs), with the goal of differentiating the two syndromes on the basis of clinical presentation, diagnostic criteria, neuropathological features, and contrasting responses to treatments. METHODS: Literature was identified using PubMed, with search terms to capture medical conditions of interest; additional references were also included based on our collective experience and knowledge of the literature. RESULTS: Evidence from current literature supports the distinction between the two disorders; apathy and depression occur with varying prevalence in individuals with NCDs, pose different risks of progression to dementia, and have distinct, if overlapping, neurobiological underpinnings. Although apathy is a distinct neuropsychiatric syndrome, distinguishing apathy from depression can be challenging, as both conditions may occur concurrently and share several overlapping features. Apathy is associated with unfavorable outcomes, especially those with neurodegenerative etiologies (e.g., Alzheimer's disease) and is associated with an increased burden for both patients and caregivers. Diagnosing apathy is important not only to serve as the basis for appropriate treatment, but also for the development of novel targeted interventions for this condition. Although there are currently no approved pharmacologic treatments for apathy, the research described in this review supports apathy as a distinct neuropsychiatric condition that warrants specific treatments aimed at alleviating patient disability. CONCLUSIONS: Despite differences between these disorders, both apathy and depression pose significant challenges to patients, their families, and caregivers; better diagnostics are needed to develop more tailored treatment and support.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.006
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.379
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations84
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Geriatric PsychiatrySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207