Effect on Neuropsychiatric Inventory–Questionnaire scores in the National Alzheimer's Coordinating Center Uniform Data Set
Bibliographic record
Abstract
BACKGROUND: Neuropsychiatric symptoms (NPS) are frequently encountered in neurodegenerative diseases including Alzheimer's disease (AD). The Neuropsychiatric Inventory-Questionnaire (NPI-Q) is the most frequently used assessment for NPS in patients with AD. It is an informant- based assessments wherein informants are asked to rate NPS in the patient. We have found that informant characteristics influence the Clinical Dementia Rating (CDR) in the National Alzheimer's Coordinating Center Uniform Data Set (NACC-UDS). We aimed to evaluate informant characteristics on the NPI-Q in patients with mild cognitive impairment or dementia due to AD participating in the NACC-UDS. METHOD: We included all participants from the NACC-UDS that had AD as the principal diagnosis, and information about the number of Clinician Judgments of Behavioural Symptoms (CJbS), informant characteristics, CDR global score (CDR-GS) and the outcome NPI-Q severity score. We performed a conditional growth model using multilevel linear regression analysis. RESULT: We included 21276 participants, totalling 56301 visits with a median of 3 (1-5) visits. Patients' age at the initial visit was 74.0±9.4 years and 54.1% were females. Informants were 66.2±13.1 years, 68.7% were females, and the relationship was 60.4% spouse or partner, 27.7% children and 11.9% other. The NPI-Q scores were affected by informant characteristics. The associations were 0.39 (CI 95%:0.31 to 0.46) higher with female informants. The NPI-Q was 0.34 (CI 95%: 0.23 to 0.45) higher when informants were children of the patients compared with spouses or partners. The frequency of visits was associated with an NPI-Q score 0.25 lower (CI 95%:-0.39 to -0.11) when visiting daily, 0.53 lower (CI 95%:-0.64 to -0.42) when visiting at least once per week, and 0.60 lower (CI 95%:-0.74 to -0.46) when visiting less than once a week compared with living with the patient. As expected, NPI-Q scores increased with higher CDR-GS and CJbS. CONCLUSION: We found that the NPI-Q severity scores are modified by informant characteristics in the NACC-UDS patients with AD diagnosis. These results are clinically relevant because NPI-Q is often used to inform treatment of NPS in patients with AD and informant characteristics are not considered when undertaking treatments.
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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 | 0.063 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".