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Record W3158402337 · doi:10.1016/j.ynstr.2021.100332

Post-traumatic stress disorder and its association with stroke and stroke risk factors: A literature review

2021· review· en· W3158402337 on OpenAlexaff
Jon Perkins, Stacy Schantz Wilkins, Saadat Kamran, Ashfaq Shuaib

Bibliographic record

VenueNeurobiology of Stress · 2021
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStroke (engine)EtiologyRisk factorTraumatic stressAssociation (psychology)Psychological interventionMedicineTraumatic brain injuryClinical psychologyPsychiatryPsychologyInternal medicinePsychotherapist

Abstract

fetched live from OpenAlex

Stroke is a major cause of mortality and disability globally that has multiple risk factors. A risk factor that has recently gained more attention is post-traumatic stress disorder (PTSD). Literature searches were carried out for updated PTSD information and for the relationship between PTSD and stroke. The review was divided into two sections, one exploring PTSD as an independent risk factor for stroke, with a second concentrating on PTSD's influence on stroke risk factors. The study presents accumulating evidence that shows traumatic stress predicts stroke and is also linked to many major stroke risk factors. The review contributes knowledge to stroke aetiology and acts as a reference for understanding the relationship between PTSD and stroke. The information presented indicates that screening and identification of traumatic experience would be beneficial for directing stroke patients to appropriate psychological and lifestyle interventions. In doing so, the burden of stroke may be reduced worldwide.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.008
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.043
GPT teacher head0.363
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations38
Published2021
Admission routes1
Has abstractyes

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