Application effect analysis of five cognitive function screening scales in the elderly
Bibliographic record
Abstract
ObjectiveTo explore the application effect of cognitive screening scales commonly used in memory clinics of tertiary Grade A general hospitals，so as to provide a reference for the diagnosis of neurocognitive disorders.MethodsA total of 155 patients who were admitted to the memory clinic from October 2020 to May 2022 and complained of memory loss were selected.After initial diagnosis by a neurologist，they were prescribed cognitive impairment screening with the consent of the patients.After the appointment，the Chinese version of ACE⁃Ⅲ，MMSE，CDT4，MoCA，AD8 and ADL scales were screened by nurses with cognitive screening training qualification.The patients brought the cognitive screening results，relevant laboratory and imaging examination to the neurology department for diagnosis and treatment.ResultsAmong the 155 patients，72 were in the normal group，38 were in the MCI group，and 45 were in the dementia group.The correlation between five cognitive screening scales and related factors showed that age，years of education，degree of cognitive impairment were more significantly correlated with the Chinese version of ACE⁃Ⅲ and MoCA.The area under the ROC curve of Chinese ACE⁃Ⅲ，MMSE，MoCA and AD8 in MCI group was 0.698⁃0.788，and the specificity of MoCA，Chinese ACE⁃Ⅲ and AD8 in MCI diagnosis was 78.9%，76.3% and 73.7%，respectively.The sensitivity was 70.8%，58.3% and 56.9%，respectively.The area under ROC curve of the Chinese version of ACE⁃Ⅲ，MMSE and MoCA was between 0.915⁃0.931.The sensitivity of MMSE，Chinese version of ACE⁃Ⅲ and MoCA for dementia diagnosis was 91.7%，84.7% and 83.3%，and the highest specificity was 86.7%，84.4% and 84.4%，respectively.ConclusionMoCA and the Chinese version of ACE⁃Ⅲ should be used in the memory clinic of ClassⅢGrade A general hospitals for elderly patients with memory loss and certain educational background.The accuracy of cognitive screening scale in MCI screening was MoCA>Chinese ACE⁃Ⅲ>AD8，and the accuracy of dementia screening was MMSE>Chinese ACE⁃Ⅲ>MoCA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".