Early Improvements of Individual Symptoms With Antipsychotics Predict Subsequent Treatment Response of Neuropsychiatric Symptoms in Alzheimer’s Disease
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to identify individual symptoms whose early improvements contributed to subsequent treatment response to antipsychotics for neuropsychiatric symptoms (NPSs) in patients with Alzheimer's disease (AD) using the dataset of the Clinical Antipsychotic Trials of Intervention Effectiveness-Alzheimer's Disease (CATIE-AD). METHODS: The CATIE-AD study was conducted between April 2001 and November 2004 at 45 sites in the United States. Data for 421 patients with DSM-IV AD with NPSs treated with antipsychotics were analyzed in the present study. Treatment response was defined as a reduction of ≥ 9 points in the Neuropsychiatric Inventory (NPI) score or a reduction of ≥ 25% from baseline in Brief Psychiatric Rating Scale (BPRS) total score at week 8. Logistic regression analyses were performed to examine associations between response and clinical and demographic characteristics, including each total or individual symptom score reduction at week 2. RESULTS: Reduction in NPI or BPRS total score at week 2 and several individual symptom score reductions (euphoria/elation, irritability, hallucinations, anxiety, agitation, apathy, disinhibition, and depression among NPI subitems; excitement, suspiciousness, disorientation, hostility, depressive mood, and emotional withdrawal among BPRS subitems) at week 2 were significantly associated with subsequent treatment response at week 8 (all P values < .05); Early non-improvements of irritability and suspiciousness were shown to be especially influential clinical markers in predicting subsequent treatment nonresponse. Furthermore, healthier condition at baseline was significantly associated with treatment response at week 8 (P < .05). CONCLUSIONS: Although further research to validate these preliminary findings is needed, focusing on early improvements of individual symptoms could help identify subsequent treatment responders to antipsychotics in AD patients with NPSs. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00015548.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".