Supplementary Material for: Feasibility and Diagnostic Accuracy of Early Mood Screening to Diagnose Persisting Clinical Depression/Anxiety Disorder after Stroke
Bibliographic record
Abstract
Background: Depression/anxiety disorders are common after stroke and have a negative impact on outcomes. Guidelines recommend that all stroke survivors are screened for these problems. However, there is no consensus on timing or method of assessment. We investigated the feasibility and accuracy of a very early screening strategy and the diagnostic accuracy this has for depression/anxiety disorders at 1 month. Methods: Screening tools were Hospital Anxiety and Depression Scale (HADS) and Depression Intensity Scale Circles (DISCs); we also assessed cognition using the Montreal Cognitive Assessment (MoCA). Screening was offered to sequential stroke admissions. At 1 month we assessed for clinical depression/anxiety disorder using Mini-International Neuropsychiatric Interview (MINI) and retested screening tools. We described test accuracy of acute depression/anxiety screening for clinical diagnosis of depression/anxiety disorder at 1 month and described temporal change in screening test scores. We assessed feasibility by describing proportions that were able, agreed to and completed the screening tests. Results: Over 4 months, 102/146 admissions were suitable for screening following initial medical assessment, 69 (68%) agreed to screening, of whom 33 (48%) required researcher assistance to complete the screening test battery. Median time to assessment was 2 days (IQR: 1-4). Early HADS suggested n = 9 (13%) with depression; DISCs n = 25 (37%). Median acute MoCA was 21/30. At 1 month, n = 61 (88%) provided data. Repeat scores showed improvement over time; HADS (anxiety) mean difference: 2.5 (95% CI: 1.2-3.7), HADS (depression) mean difference: 1.6 (95% CI: 0.3-2.9). MINI defined n = 12 (20%) with depression and n = 6 (10%) with anxiety disorder. Comparing baseline screening to 1-month clinical diagnosis, HADS sensitivity was 0.25 (95% CI: 0.09-0.53) and specificity 0.94 (95% CI: 0.84-0.98); DISCs sensitivity was 0.92 (95% CI: 0.65-0.99) and specificity 0.78 (95% CI: 0.64-0.87). Conclusions: Even amongst ‘medically stable' stroke patients, depression/anxiety screening at the acute stage may not be feasible or accurate. Half of participants required assistance from the researcher to complete assessments. The poor predictive accuracy of HADS for depression/anxiety disorder at 1 month may be due in part to the high prevalence of cognitive impairment in our sample. Screening in the first few days after stroke does not appear useful for detecting clinically important and sustained depression/anxiety problems.
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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 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.855 | 0.252 |
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".