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Record W2033647496 · doi:10.1016/j.acn.2005.12.008

Misdiagnosis of the persistent postconcussion syndrome in patients with depression

2006· article· en· W2033647496 on OpenAlexaff
Grant L. Iverson

Bibliographic record

VenueArchives of Clinical Neuropsychology · 2006
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersNational Academy of Neuropsychology
KeywordsDepression (economics)NeuropsychologyPsychiatryTraumatic brain injuryPost-concussion syndromeMedicinePsychologyConcussionInjury preventionPoison controlPhysical therapyCognitionMedical emergency

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the prevalence of postconcussion-like symptoms in patients with depression. Participants were 64 physician-diagnosed inpatients or outpatients with depression who had independently-confirmed diagnoses on the Structured Clinical Interview for DSM-IV. All completed the British Columbia Postconcussion Symptom Inventory, a 16-item measure designed to assess the frequency and severity of symptoms based on ICD-10 criteria for postconcussion syndrome. Specific endorsement rates of postconcussion-like symptoms ranged from 31.2% to 85.6% for symptoms rated mild or greater, and from 10.9% to 57.8% for symptoms rated moderate-to-severe. Approximately 9 out of 10 patients with depression met liberal self-report criteria for a postconcussion syndrome and more than 5 out of 10 met conservative criteria for the diagnosis. Implications for forensic neuropsychology will be discussed.

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)0.011
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.363
Teacher spread0.321 · 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

Citations273
Published2006
Admission routes1
Has abstractyes

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