Detection and treatment of post stroke depression: results from the registry of the Canadian stroke network
Bibliographic record
Abstract
BACKGROUND: Depression occurs in approximately one-third of patients following stroke based on studies that screen entire stroke populations. Less is known about the detection and treatment of post stroke depression (PSD) in routine clinical practice. METHODS: This was a prospective cohort study of 7643 consecutive stroke patients >66 years of age, from 13 designated stroke centres in Ontario, Canada. PSD was defined as (a) presence of strong evidence of depression documented in the patient chart plus a prescribed antidepressant and a psychiatric consult, or (b) prescription of a new antidepressant following admission. The prevalence of PSD was determined and patients with and without PSD were compared on a variety of measures. Patients admitted to specialized stroke units were compared to patients admitted to standard units in order to determine if PSD detection and treatment rates differed. RESULTS: PSD was diagnosed in 4.8%, and 6.7% were treated with a new antidepressant. Patients with PSD had more severe strokes, more functional handicap, longer hospital stays and were less likely to be discharged home (all p < 0.001). Patients admitted to specialized stroke units were more likely to be diagnosed with depression (5.2% vs 4.0%, p < 0.014) and were more likely to receive a new prescription for an antidepressant (7.8% vs 4.5%; p < 0.001). CONCLUSIONS: Rates of diagnosed and treated PSD in routine clinical practice are low and appear significantly lower than those from studies that utilize active screening of entire stroke populations. These results support the routine screening of all patients for PSD using validated instruments. Specialized stroke unit care may improve PSD detection and treatment rates.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".