Exploring presence of cognitive deficits and psychiatric symptoms in patients with mild cognitive impairment
Bibliographic record
Abstract
Abstract: BACKGROUND: Mild cognitive impairment (MCI) represents an early clinical stage during which there may be an opportunity to prevent further cognitive decline. In this context, there has been increased interest in psychiatric symptoms and how they may facilitate early diagnosis and prevention of cognitive decline. The present study aims to explore the presence of cognitive deficits and psychiatric symptoms in patients with MCI. MATERIALS AND METHODS: In the present study, 30 individuals, within the age range of 60–80 years, with a diagnosis of MCI from a neurologist were selected. The Montreal Cognitive Assessment (MoCA) was used to screen cognitive impairment in these patients. Further, the Clinical Dementia Rating (CDR) Scale and the Neuropsychiatric Inventory (NPI) were used to assess the severity of cognitive impairment and the frequency and severity of psychiatric symptoms in them, respectively. Appropriate statistical analysis was done. RESULTS: The two most commonly prevalent psychiatric symptoms were anxiety and apathy. Out of 30 patients with MCI, 7 had no significant psychiatric symptoms, and out of the remaining patients, 15 had >1 neuropsychiatric symptom. The mean age was found to be 72 (72 ± 5.07), and the mean MoCA score was 19 (19 ± 4.43). The mean CDR Global Score was 0.5 (0.5 ± 0.09), and the Sum of Boxes was 2.52 (2.52 ± 1.11). The mean NPI score was 12.7 (12.7 ± 9.39). It was found that there was no significant relationship between the presence of cognitive impairment and psychiatric symptoms ( P > 0.05) in patients with MCI. CONCLUSION: Thus, the presence of late-onset psychiatric symptoms, with or without any decline in cognition, should raise suspicions of neurodegeneration and thus require greater clinical attention and early identification.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".