Poststroke depressive symptoms and their relationship with quality of life, functional status, and severity of stroke
Bibliographic record
Abstract
OBJECTIVE: The present study aimed to investigate the relationship between depressive symptoms in 6 months after stroke and the quality of life (QOL), clinical and socio-demographical characteristics, functional status, and severity of stroke. METHODS: Ninety consecutive stroke patients who attended the neurology outpatient clinic at Erciyes University, Kayseri, Turkey from March 2004 to March 2005 were evaluated for the study. Seventy outpatients who had a stroke 6 months previously were included in the study. As a data-collecting device, Short Form 36, Functional Independence Measure (FIM), Canadian Neurological Scale, and Beck Depression Inventory (BDI) were used. In addition, a questionnaire was administered to obtain clinical and socio-demographic data. RESULTS: Seventy patients were included in the study. Depression measured using BDI was identified in 47.1% of the patients. Total FIM scores, especially motor subscale scores, were decreased in the depressive patients. No difference was found in the stroke severity scores of the depressed and non-depressed patients. The QOL subscale scores, such as physical functioning, bodily pain, general health perception, vitality, social functioning, and mental health, were lower in the patient group with high BDI scores. There was a positive correlation between age and BDI scores of the patients. Negative correlations were found between the scores of QOL and FIM in both total and motor subscale scores. CONCLUSION: Poststroke depression seems to be associated with age, education level, QOL, and functional status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".