The impact of sex on clinical profiles of patients with behavioral variant frontotemporal dementia
Bibliographic record
Abstract
INTRODUCTION: Sex differences in behavioral variant frontotemporal dementia (bvFTD) remain understudied, especially when controlling for sex differences already existing in the general population. METHODS: Clinical features were analyzed in 620 bvFTD participants. Sex-diagnosis interactions were examined in 1029 bvFTD and 1029 healthy control (HC) participants for neuropsychiatric symptoms, and in 1109 bvFTD and 1109 HC participants for cognitive, behavioral, and language measures. RESULTS: Males with bvFTD showed greater-than-expected loss of empathy and nighttime behavioral symptoms relative to females, based on sex-by-diagnosis interactions. They also exhibited higher-than-expected punishment sensitivity. In contrast, females with bvFTD showed greater-than-expected impairments in semantic fluency and picture naming relative to HC females. DISCUSSION: Findings reveal that males with bvFTD present with more prominent behavioral disturbances, while females with bvFTD experience greater language impairments. This work is an important step toward integrating social determinants of health, such as sex, into the diagnostic and care paradigms for bvFTD. HIGHLIGHTS: Males with behavioral variant frontotemporal dementia (bvFTD) show more empathy loss and nighttime behavioral symptoms Females with bvFTD have greater deficits in naming and semantic fluency Findings support including sex in diagnostic and care models for bvFTD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".