Impact of post stroke depression and anxiety on health-related quality of life in young Filipino adults
Bibliographic record
Abstract
Background: Health-related quality of life (HRQoL) is important to assess in young adults who suffer from various physical and mental consequences after stroke. We aimed to evaluate the HRQoL of young adults after ischemic or hemorrhagic stroke and to determine the association of anxiety and depression with poor HRQoL in this special population. Methods: We administered the European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L) to assess the HRQoL in our study population. This tool describes health outcomes in five dimensions. Socio-demographic and clinical data including modified Rankin scale (mRS), Barthel Index and Hospital Anxiety and Depression Scale scores were available from our previous cross-sectional study on young adults with stroke. We performed bivariate analyses to assess the association of psychiatric comorbidities with categorical characteristics and determined risk factors for poor HRQoL using multivariable logistic regression analysis. Results: < 0.01) when compared to those without both conditions. Anxiety and depression were significantly correlated with poor quality of life on all dimensions of the EQ-5D-5L. Similarly, Barthel Index was a significant predictor for problems in HRQoL (OR 0.17, 95% CI 0.03-1.02 on the mobility dimension and OR 0.08, 95% CI 0.01-0.55 on the self-care dimension). Cerebral hemorrhage was an independent predictor for poorer self-care dimension scores (OR 4.99, 95% CI 1.42-17.56). Conclusions: Our study showed that anxiety, depression and poor functional status are associated with poorer HRQoL in young adult Filipinos after stroke. Screening for psychiatric conditions and evaluating mobility are crucial in the management of this special population after stroke.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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".