Quality of life and caregiver burden in familial frontotemporal lobar degeneration: Analyses of symptomatic and asymptomatic individuals within the LEFFTDS cohort
Bibliographic record
Abstract
OBJECTIVE: The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects evaluates familial frontotemporal lobar degeneration (FTLD) kindreds with MAPT, GRN, or C9orf72 mutations. Objectives were to examine whether health-related quality of life (HRQoL) correlates with clinical symptoms and caregiver burden, and whether self-rated and informant-rated HRQoL would correlate with each other. METHODS: ) Scale plus National Alzheimer's Coordinating Center (NACC) FTLD. HRQoL was measured with DEMQOL and DEMQOL-proxy; caregiver burden with the Zarit Burden Interview (ZBI). For analysis, Pearson correlations and weighted kappa statistics were calculated. RESULTS: plus NACC FTLD was negatively correlated with DEMQOL (r = -0.20, P = .001), as were ZBI and DEMQOL (r = -0.22, P = .0009). There was fair agreement between subject and informant DEMQOL (κ = 0.36, P <.0001). CONCLUSION: Lower HRQoL was associated with higher cognitive/behavior impairment and higher caregiver burden. These findings demonstrate the negative impact of FTLD on individuals and caregivers.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".