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Record W2046985997 · doi:10.5402/2012/147285

Acute Relationship between Cognitive and Psychological Symptoms of Patients with Mild Traumatic Brain Injury

2012· article· en· W2046985997 on OpenAlexaff
Élaine de Guise, Joanne LeBlanc, Simon Tinawi, Julie Lamoureux, Mitra Feyz

Bibliographic record

VenueISRN Rehabilitation · 2012
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill UniversityUniversité de MontréalMcGill University Health CentreMontreal General Hospital
Fundersnot available
KeywordsRivermead post-concussion symptoms questionnaireAnxietyDepression (economics)NeuropsychologyTraumatic brain injuryCognitionPsychologyConcussionClinical psychologyPsychiatryRehabilitationPoison controlMedicineInjury preventionPhysical therapyMedical emergency

Abstract

fetched live from OpenAlex

Objective. The goal of this study was to explore the relationship between acute psychological reactions and cognition as well as postconcussive symptoms in patients with MTBI. Research Methods. Sociodemographic and medical history data were gathered for 59 patients diagnosed with MTBI. Validated and standardized tools were used to assess anxiety, depression, and cognitive function two weeks after trauma. Postconcussive symptoms were assessed with the Rivermead postconcussive questionnaire. Results. Despite the absence of significant neuropsychological deficits, a very high level of anxiety and depression was observed in our cohort. Level of anxiety and depression were positively related to cognitive performances and to postconcussive symptoms. Moreover, patients with preexisting alcohol and psychological problems were more likely to present with acute depression after MTBI. Conclusions. Early psychological rehabilitation should be provided to decrease the intensity and frequency of postconcussive symptoms and diminish the risk of these problems becoming chronic.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.107
GPT teacher head0.409
Teacher spread0.302 · 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 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

Citations7
Published2012
Admission routes1
Has abstractyes

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