Relationship between Alzheimer's disease and non-verbal listening comprehension obstacle
Bibliographic record
Abstract
Objective To study the relationship between Alzheimer's disease(AD)and non-verbal listening comprehension obstacle, and to observe the different specific performance of AD patients in the non-verbal listening comprehension tests involving music and non-verbal semantics, in order to identify the value of these tests in the differential diagnosis of AD. Methods The internalized 104 subjects meeting inclusion and exclusion criteria were divided into 4 groups of normal group(n=24), a-MCI group(amnesia-mild cognitive impairment, n=30), mild-AD group(n=27)and moderate AD group(n=23). All subjects received a series of central non-verbal listening comprehension tests which were scored and evaluated, including categorizing and naming according to the sound which involved the non-verbal semantic aspect, judging the emotion and rhythm according to the melody which involved the music aspect.Then the scores were analyzed.Mini-mental state examination(MMSE)and Montreal cognitive assessment(MoCA)were used for assessing the degrees of cognitive impairment. Results All test scores had a positive moderate to high correlations with MMSE and MoCA(all r>0.4, P<0.01), in which sound classification and nomination had better positive correlations than other tests.The statistically significant differences were found in all tests among the four groups(all P<0.05). There was a significant difference in sound nomination between a-MCI group and normal group(P< 0.05). There were significant differences in sound classification, nomination and judging melody rhythm between mild AD group and normal group or a-MCI group(both P<0.05). There were significant differences in all tests between moderate AD group and normal group or a-MCI group(both P<0.05). The sound classification tests, especially sound nomination tests, had better diagnostic value than the rhythm and emotion judgment tests for identifying AD. Conclusions Patients with AD, even with a-MCI, can develop the non-verbal listening comprehension obstacle, which is aggravated along with the exacerbation of cognitive impairment.AD patient's semantic aspect-involving non-verbal listening ability degeneration is faster than involving the music aspect.Non-verbal listening comprehension tests involving non-verbal semantic aspect, especially sound nomination tests, have better diagnostic values. Key words: Alzheimer's disease; Comprehension; Listening comprehension obstacle
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
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".