COGNITIVE IMPAIRMENT AND ITS IMPACT ON QUALITY OF LIFE IN RURAL INDIAN FEMALE AFTER STROKE: A CROSS SECTIONAL STUDY
Bibliographic record
Abstract
Stroke is main cause of death and disability which mainly affect higher function like cognitive impairment which affects the quality of life. The MoCA used to assessment of cognitive impairment and stroke specific quality of life for assessment of quality of life. The aim was to assess the effect of Cognitive Impairment on quality of life in Rural Indian women after stroke. The cognitive impairment was measured with the use of the MoCA and Quality of Life was measured by SS-Quality of Life questionnaire. Female stroke patient with age in between 41-70 year who was diagnosed by the physician is included in the study. Result of this study indicated that the cognitive functions ans quality of life significantly affected in rural females following stroke. (0.571; p=0.0001).the finding is the cognitive deficits occurred after stroke and it hamper the quality of life in majority of patient.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".