EVALUATION OF THE EFFECTIVENESS OF NEUROPSYCHOLOGICAL SCALES IN DIAGNOSING PRE-DEMENTIA AND DEMENTIA DISORDERS IN PATIENTS WITH ALZHEIMER'S DISEASE
Bibliographic record
Abstract
Background. Dementia is currently the seventh leading cause of death in the world. Alzheimer's disease (AD) is the leading form of dementia worldwide, accounting for about 60-70% of cases. Almost 10 million new cases of dementia occur each year. Aim. To evaluate the effectiveness of using neuropsychological scales MMSE, FAB and MoCA in the diagnosis of pre-dementia and dementia disorders taking into account the leading impairments of cognitive functions in individuals with AD. Material and methods. The study included 85 patients (M/W=26/59 (30.6%/69.4%) with cognitive disorders due to AD, aged 74±12.5 years. Clinical and neuropsychological study of the presence and severity of cognitive impairment in patients with AD was performed. Result. According to the results of a comparative analysis of the use of neuropsychological scales MoCA, MMSE, and FAB in the diagnosis of pre-dementia and dementia disorders in patients with AD, it was found that the MoCA scale (AUC=0.96) had the highest predictive value in our study. The combined use of MMSE and FAB scales (AUC=0.95) also showed high prognostic significance in the diagnosis of pre-dementia and dementia disorders. The lowest prognostic significance was shown by the use of the FAB scale (AUC=0.73). At the stage of pre-demanding disorders in persons with AD, opto-spatial disorders are either absent or have an insignificant degree of severity. According to the results of the study, opto-spatial disorders at the pre-demand stage in patients with AD were detected significantly less frequently (χ2=11.14; pPearson<0.001). Conclusion. The MoCA scale (AUC=0.96) has the highest predictive value in the diagnosis of pre-demanding and dementia disorders in patients with AD in our study. Additional diagnostics of opto-spatial disorders in patients with AD allows increasing the sensitivity (from 80% to 90%) and specificity (from 92.3% to 94.1%) of the MoCA scale in the diagnosis of pre-demanding and dementia disorders in patients with AD.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".