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Effectiveness of Gabapentin for the Treatment of Behavioral Disorders in Dementia

2000· article· en· W2079500634 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Psychopharmacology · 2000
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGabapentinMedicineDementiaAdverse effectSedationAnesthesiaClinical Global ImpressionPopulationClinical trialInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Twelve patients with moderate to severe dementia and severe behavioral disorders were treated with open-label gabapentin (200-1,200 mg/day) for 8 weeks in a prospective case-series design. Patients were nonresponders to previous trials of neuroleptics. Behaviors were measured at 2-week intervals with the Neuropsychiatric Inventory (NPI), the Cohen-Mansfield Agitation Inventory (CMAI), and the Clinical Global Impression Scale (CGI). Gabapentin was generally well tolerated in this population. Although 42% of patients experienced adverse events such as gait instability and sedation, only two patients discontinued treatment prematurely because of adverse events. Average patient scores for the CMAI and the NPI remained unchanged after gabapentin. On the CGI, two patients were much improved, three were minimally improved, six were unchanged, and one was minimally worse. Gabapentin may have a role in treating a subgroup of dementia patients with severe behavioral disorders who have not responded to neuroleptics.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.071
GPT teacher head0.520
Teacher spread0.450 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it