The Frontal Behavioral Inventory in the differential diagnosis of frontotemporal dementia
Bibliographic record
Abstract
A personality and behavioral disorder is an important and defining feature of frontal lobe dementia (FLD) or frontotemporal degeneration (FTD). The diagnosis usually depends on the progressive development of various behavioral symptoms rather than a set of neuropsychological measures. Quantification of the personality-behavior disorder is important for standardizing the diagnosis. An inventory was constructed to capture the major positive and negative behaviors and personality change, and it was administered prospectively to caregivers of 108 patients in a cognitive neurology clinic, at the time of first diagnostic assessment. The prevalence and extent of behavioral abnormality was quantitated in the clinic population of FLD, vascular dementia (VaD), Alzheimer's disease (AD), primary progressive aphasia (PPA), and depressive disorder (DD) patients. The mean scores of FLD patients were significantly above all other groups. Scores in VaD were also higher than in AD, PPA, and DD. Interrater reliability (Cohen's kappa of .90) and item consistency (a Cronbach alpha of .89) were both high. Perseveration, indifference, inattention, inappropriateness, and loss of insight rated highest in FLD, significantly different from all other groups. Apathy, aspontaneity, inflexibility, disorganization, impulsivity, personal neglect, and poor judgment were also significantly higher in FLD. Discriminant function correctly classified 92.7% versus all other patients (NON-FLD) in the study. A total of 18.8% of VaD patients were misclassified as FLD. Indifference, alien hand, and inappropriateness were the highest discriminant functions. Perseveration and verbal apraxia were important discriminatory items for FLD and PPA, respectively. The FBI is a standardized behavioral inventory useful to diagnose FLD, to differentiate it from other dementias, and to quantify the behavior disorder.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".