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Record W7117252910 · doi:10.1002/alz70857_100942

Behavioral Variant Frontotemporal Degeneration: Exploring the Diagnostic Journey

2025· article· en· W7117252910 on OpenAlexaboutno aff
Carrie Milliard, Shana G Dodge, Sweatha Reddy, Robert Reinecker, Mary Krause, Penny A. Dacks

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusPersonalitySample (material)Medical diagnosisFocus (optics)Diagnostic test

Abstract

fetched live from OpenAlex

BACKGROUND: Behavioral variant frontotemporal degeneration (bvFTD) is a form of FTD characterized by progressive changes in behavior, personality, and executive function. Key symptoms include apathy, disinhibition, loss of empathy, lack of insight, and speech and language difficulties. The overlap of these symptoms with psychiatric and neurological disorders frequently leads to misdiagnosis and substantial delays in obtaining an accurate diagnosis, causing frustration and distress for patients and their families. METHOD: The FTD Disorders Registry is a non-profit, direct-to-participant registry relaunched in 2024 with a new platform, research, and electronic remote consent protocol. Between May 2024 and the data freeze on January 3, 2025, 205 participants in the United States and Canada completed a survey on the diagnostic journey, of whom 50 specified bvFTD as the current known diagnosis. RESULT: 50 respondents described the journey to getting a bvFTD diagnosis, including persons diagnosed (n = 16), legally authorized representatives (n = 11), and care partners/reporters (n = 23). Respondents across roles noted the most distressing symptoms were mood changes (46%), problems with thinking and judgement (40%), memory issues (36%), and personality (36%) changes. The majority of respondents (76%) reported waiting more than a year from the onset of symptoms to receive a diagnosis, with 30% experiencing delays of 3 to 6 years and over half (66%) consulting 3 or more doctors before getting the correct diagnosis. Additionally, 52% of respondents were initially misdiagnosed, often receiving multiple other diagnoses including depression (73%), other psychiatric diagnoses (58%), anxiety (50%), and mild cognitive impairment (38%). CONCLUSION: Given the respondents' demographics, these findings are likely conservative. While based on a limited sample size, these data align with findings from the FTD Insights survey of 1800 participants. They underscore the challenges and complexities involved in diagnosing bvFTD, the prevalence of misdiagnosis, and the significant impact it can have on patients' and caregivers' lives. These findings highlight the need for targeted clinician education to recognize early signs of bvFTD and incorporate it into the differential diagnosis for patients with unexplained mood, cognitive, or personality changes. Future analyses will focus on larger sample sizes and utilizing validated tools to understand respondents' socioeconomic and geographic factors correlate with diagnostic journey.

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)0.006
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.002
Scholarly communication0.0050.006
Open science0.0010.005
Research integrity0.0010.003
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 head0.107
GPT teacher head0.314
Teacher spread0.207 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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