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Prevalence of Anxiety After Stroke : An Updated Systematic Review and Meta-Analysis of Observational Studies

2017· other· en· W6964505711 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyRating scaleObservational studyCINAHLStroke (engine)Inter-rater reliabilityMEDLINEMeta-analysisSystematic reviewSample size determination

Abstract

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Background and aimsAnxiety after stroke is common and can be debilitating. A 2013 systematic review found the prevalence of post-stroke anxiety to be 18% when measured by interview and 25% when measured by rating scale (2). We aimed generate an updated measure of prevalence. Secondary aims were to measure the prevalence of anxiety subtypes; and explore the influence on prevalence of: the method of measuring anxiety, time post-stoke, and study setting.Methods A sensitive search of databases (Embase, MEDLINE, PsycINFO, AMED, CINAHL and ProQuest Dissertations & Theses) was performed. Studies were screened against pre-specified criteria (3). Study data were extracted using a pre-piloted form and risk of bias within studies was assessed (4). A second reviewer screened a sample of papers and checked data extraction and quality appraisal. Interrater agreement was moderate to high for the abstract and full text screens (Cohenu2019s u03ba = 0.63 and 0.91, respectively). Meta-analysis, subgroup, and sensitivity analyses were performed using RevMan 5.3, with results presented as forest plots.Results22564 unique records were obtained. 80 publications reporting 51 studies were included in the review; all 51 were included in meta-analyses. 11 studies measure anxiety using clinical interviews; 40 used rating scalesPrevalence by clinical interview = 18.0% (95% CI: 13.3 u2013 22.6, I2 = 85%, Figure 1)Prevalence by rating scales = 25.1% (95% CI: 21.4 u2013 28.9, I2 = 96%, Figure 2)Heterogeneity in both meta-analyses was highCommunity-based studies reported a statistically significant lower prevalence than population-based studies: 16.0% (95% CI: 14.9 u2013 17.2) vs 25.6 (95% CI: 17.3 u2013 33.8). There was no statistically significant change in prevalence over time when measured by interview or rating scale. Higher quality studies tended towards lower prevalence. There was insufficient data to perform meta-analysis of anxiety subtypes. From four studies reporting anxiety subtype prevalence, there was no clear predominant subtype.SummaryAnxiety after stroke is common u2013 affecting around 1 in 5 stroke survivors u2013 although there was significant heterogeneity between studiesPractitioners should be aware of anxiety after stroke at all time points and settingsFuture research should focus on the prevalence of anxiety subtypes and interventions for post-stroke anxiety (1)References(1) Knapp, P. et al., 2017. Interventions for treating anxiety after stroke. Cochrane Database of Systematic Reviews, Volume 5, p. CD008860.(2) Campbell Burton CA, Murray J, Holmes J, Astin F, Greenwood D, Knapp P. Frequency of anxiety after stroke: a systematic review and meta-analysis of observational studies. International Journal of Stroke. 2013; 8: p. 545-599.(3) Dunn-Roberts AS, Sahib N, Cook L, Knapp P. Frequency of anxiety after stroke, an updated systematic review and meta-analysis. PROSPERO 2018 CRD42018093718 Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018093718 (4) Wells GA, Shea B, O'Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. [Online].; 2018 [cited 2018 August 12. Available from: www.ohri.ca/programs/clinical_epidemiology/oxford.asp

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.685
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0030.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.000

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 head0.231
GPT teacher head0.362
Teacher spread0.132 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2017
Admission routes1
Has abstractyes

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