Subjective Cognitive Complaints in Distant Phase After Stroke – Preliminary Study
Bibliographic record
Abstract
Introduction. Subjective cognitive decline (SCD) is often reported by healthy individuals and by different clinical groups. Current data do not clearly show the relationship between SCD and cognitive functioning, but the predictors of SCD are: age, depression and sociodemographic factors. Inconclusive data also applies topeople suffering from stroke in the distal post-stroke phase. Correct identification of the causes of SCD will help to take adequate forms of psychological therapy (neuropsychological rehabilitation and/or psychotherapy). Methodology. The aims of research was to compare the intensity and structure of SCD as well as theirdeterminants in healthy persons and those after stroke. In our study 193 adults participated: 118 osób without brain pathology and 75 patients who suffered stroke 2–3 years earlier. DEX-S and ProCog as methods of evaluation of SCD and cognitive assessment techniques: the Montreal Cognitive Assessment Scale (MoCA), WAIS-R subtests and intensity of depressive mood (Geriatric Depression Scale – 15) were used in the study. Results. Patients after stroke were characterized by more severe SCD than healthy people. People in both groups likewise (low) rated one’s own long-term memory, general cognitive and executive function. It has also been shown that people after stroke have significantly lower cognitive competencies compared to healthyindividuals, but similar (low) level of depressive mood. The later part of the analysis showed that some complaints may be determined by depressive mood, others are due to the interaction of cognitive deficits and depressive mood. Conclusion. Our results confirm the need for proper qualifications complaints in patients after stroke (in distant post-stroke phase). Keywords: subjective cognitive decline, stroke, cognitive functioning, depression
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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 | 0.001 | 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 | 0.001 | 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) | 0.002 | 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 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".