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Record W2980339424 · doi:10.1016/j.jalz.2019.06.3048

P3‐022: INDIVIDUALIZED SYMPTOM TRACKING WITH SYMPTOMGUIDE<sup>TM</sup> ALLOWS FOR CLINICALLY MEANINGFUL INTERPRETATION OF MMSE SCORE CHANGES IN A DEMENTIA DRUG TRIAL

2019· article· en· W2980339424 on OpenAlexaff
Justin Stanley, Taylor Dunn, Susan E. Howlett, Kenneth Rockwood

Bibliographic record

VenueAlzheimer s & Dementia · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsDalhousie UniversityGreenfield Research (Canada)
Fundersnot available
KeywordsDementiaMedicineDonepezilCognitionPlaceboVascular dementiaPhysical therapyInternal medicinePsychiatryDiseasePathology

Abstract

fetched live from OpenAlex

A positive treatment response reflects a significant improvement in outcome measures in treated patients compared to placebo. Although such differences may be statistically significant they may not represent clinically meaningful change to patients or their caregivers. We compared change in SymptomGuide™-dementia (SG-D; clinically meaningful symptoms set as treatment goals by caregivers) to change in Mini-Mental State Examination (MMSE) scores. This secondary analysis used data from VASPECT, a six-month open-label trial of donepezil. Subjects with SG-D data available (N=128/148) were 75.4±9.2 years old (52.3% women) with mild-moderate vascular dementia (VaD) or mixed Alzheimer/vascular dementia (AD/VaD). The SG-D is a symptom-tracking system with a menu of 32 symptoms (8-12 descriptors/symptom) with options to add unique symptoms. Caregivers identified symptoms important to them and rated change on a 7-point scale from very much improved (+3) to very much worse (-3) at three and six months. Efficacy was measured as change in MMSE at six months. The 100 subjects who completed the study with SG-D data available were analyzed. SG-D symptoms were categorized into five domains: behaviour, cognition, daily function, executive function, and physical manifestations. On average, caregivers set 8.1 symptoms. The most common were executive function (268/811, 33%) and cognition symptoms (252/811, 31%). Overall symptom change correlated with MMSE change (r=0.35, p<0.001) at six months. When subjects were stratified by a 2-point MMSE change, net improvement was seen across all domains (mean Behaviour goal rating=0.77, p=0.005; Cognition: 0.68, p<0.001; Daily Function: 0.32, p=0.008, Executive Function: 0.91, p<0.001; Physical Manifestations: 0.75, p<0.001). Subjects with MMSE decline also declined only in daily function symptoms (−0.94, p=0.002). “Social Interaction/Withdrawal” symptoms most often responded to a 2-point improvement on MMSE (OR=13.0, 95% CI 1.70−99.38, p=0.013), followed by “Disorientation to Time” (11.3, 1.61−78.57, p=0.015), and “Interest/Initiative” (9.0, 1.42−57.12, p=0.020). A 2-point change in MMSE correlated with changes in individualized SG-D symptoms in people with VaD or AD/VaD. Outcome measures, such as the SG-D, that are inherently clinically meaningful to patients and their caregivers, can help translate from clinical trials into everyday dementia practice.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.003

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 head0.035
GPT teacher head0.336
Teacher spread0.301 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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