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Record W2363062074

Analysis of the Comprehensive Treatment for Patients with Severe Dementia in Alzheimer's Disease in Community

2014· article· en· W2363062074 on OpenAlexaboutno aff
Hong Huji

Bibliographic record

VenueChina Foreign Medical Treatment · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDementiaMontreal Cognitive AssessmentDiseaseActivities of daily livingInternal medicineCognitionSevere dementiaIntervention (counseling)Physical therapyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective To analyze the treatment effect of patients with severe dementia in Alzheimer's disease in community.Methods 13 cases of patients with severe dementia in Alzheime's disease in community were selected and given the comprehensive treatment. The revised Hasegawa Dementia Scale(HDS-R), Activity of Daily Living Scale(ADL) and Concise Montreal cognitive assessment scale(MoCA) were used to evaluate and the efficacy of the patients before treatment and at 3, 6 months after treatment was compared, respectively. Results After 6 months of treatment, the Activity of Daily Living Scale was 25.37±4.67, the difference was statistically significant compared with that before treatment, P0.05; in MoCA scale, only the score of the three aspects of name, language, directional force was higher than that of before treatment, respectively, and which was 2.20 ±0.71, 1.27±0.41,3.89 ±0.91, respectively, the differences were statistically significant, P 0.05; the difference in scores of other four aspects and HDS-R after treatment were not significant as compared with those before treatment, P0.05. Conclusion The clinical treatment of dementia in Alzheimer's disease is very difficult to obtain a satisfactory effect, and more attention should be paid to early prevention and the intervention should be carried on at the stage of mild cognitive impairment.

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 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)0.000
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 score0.014
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.276
Teacher spread0.241 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2014
Admission routes1
Has abstractyes

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