Prevalence and Associated Factors of Cognitive Impairment Among Stroke Survivors at Comprehensive Specialized Hospitals in Northwest Ethiopia: Multi-Centered Cross-Sectional Study
Bibliographic record
Abstract
Background: Deficit in cognitive impairment is the most serious of the stroke sequelae. Post-stroke cognitive impairment is associated with impaired daily living activities and decreased capacity for independent living and functional performance. As a result, the purpose of this study was to determine the prevalence and associated factors of cognitive impairment among stroke survivors at comprehensive specialized hospitals in Ethiopia's Amhara region by 2022. Methods: A multi-centered cross-sectional study was designed at an institution. During the study period. Data was gathered by conducting structured questionnaire interviews with participants and reviewing medical charts with trained data collectors. The participants were chosen using a systematic random sampling technique. The Montreal cognitive assessment basic was used to assess cognitive impairment. Descriptive statistics, binary and multivariate logistic regression methods were used to analyze the data. The Hosmer-Lemeshow goodness-of-fit test was used to assess the fitness of the model. The AOR with a P value of 0.05 at 95% CI was reported, and variables were considered statistically significant. Results: This study enrolled 422 stroke survivors. Overall, 58.3% of stroke survivors had cognitive impairment (95% CI 53.4-63.0%). The study participants' age with AOR; 7.12 (4.40-11.45), being hypertensive with AOR; 7.52 (3.46-16.35), arriving at the hospital after 24 hours with AOR; 4.33 (1.49-12.05), less than three months after stroke with AOR; 4.83 (3.95-12.19), dominant hemisphere lesion with AOR; 4.83 (3.95-12.19) and being illiterate with AOR; 5.26 (4.43-18.64) were found significant factors. Conclusion: Cognitive impairment was discovered to be relatively common among stroke survivors in this study. More than half of stroke survivors who attended comprehensive specialized hospitals during the study period were found to have cognitive impairment. Age, hypertension, arriving at the hospital after 24 hours, less than three months after stroke, dominant hemisphere lesion, and illiterate educational status were all significant factors in cognitive impairment.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".