Screening for Post-Stroke Depression and Cognitive Impairment at Baseline Predicts Long-Term Patient-Centered Outcomes After Stroke
Bibliographic record
Abstract
BACKGROUND: Independence and reintegration into community roles are important patient-centered outcomes after stroke. Depression and cognitive impairment are common post-stroke conditions that may impair long-term function even years after a stroke. However, screening for these post-stroke comorbidities remains infrequent in stroke prevention clinics and the utility of this screening for predicting long-term higher-level function has not been evaluated. AIMS: To evaluate the ability of a validated brief Depression, Obstructive sleep apnea, and Cognitive impairment screen (DOC screen) to predict long-term (2-3 years after stroke) community participation and independence in instrumental activities of daily living post stroke. METHODS: One hundred twenty-four patients (mean age, 66.3 [standard deviation = 15.7], 52.4% male) completed baseline depression and cognitive impairment screening at first stroke clinic visit, and telephone interviews 2 to 3 years post stroke to assess community independence (Frenchay Activities Index [FAI]) and participation (Reintegration to Normal Living Index [RNLI]). A subset of these patients also consented to complete detailed neuropsychological testing at baseline. Univariate and multivariate linear (FAI) and logistic (RNLI) regression analyses were used to determine the individual relationship between baseline data (predictors) and follow-up scores. RESULTS: = .27; P < .001). Measures of executive dysfunction were the strongest correlates of poor instrumental activity. Higher depression risk was the only significant predictor of participation on the RNLI in regression modeling (odds ratio = 0.46, P = .028). CONCLUSIONS: Baseline DOC screening in stroke prevention clinics shows that symptoms of depression and cognitive impairment are independent predictors of impaired higher-level functioning and community reintegration 2 to 3 years after stroke. Novel rehabilitation and psychological interventions targeting people with these conditions are needed to improve long-term patient-centered outcomes.
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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 | 0.004 |
| 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 | 0.001 | 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".