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Record W2062122733 · doi:10.1159/000360755

Feasibility and Diagnostic Accuracy of Early Mood Screening to Diagnose Persisting Clinical Depression/Anxiety Disorder after Stroke

2014· article· en· W2062122733 on OpenAlexaboutno aff
Rosalind Lees, David J. Stott, Terence J. Quinn, Niall M. Broomfield

Bibliographic record

VenueCerebrovascular Diseases · 2014
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnxietyDepression (economics)Montreal Cognitive AssessmentHospital Anxiety and Depression ScaleMoodStroke (engine)Mood disordersPsychiatryInternal medicineCognitionCognitive impairment

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.308
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2014
Admission routes1
Has abstractyes

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