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Record W4377085110 · doi:10.1177/20597002231173772

Do concussed and non-concussed head trauma individuals have similar symptoms? A retrospective chart review of chronic post-concussive symptomatology

2023· article· en· W4377085110 on OpenAlexaff
Shazia Malik, Rahim Ahmed, Teresa Gambale, Michel P. Rathbone

Bibliographic record

VenueJournal of Concussion · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConcussionPost-concussion syndromeMedicineHead traumaHead injuryTraumatic brain injuryChronic traumatic encephalopathyPopulationPhysical therapyPoison controlInjury preventionPsychiatrySurgeryEmergency medicine

Abstract

fetched live from OpenAlex

Many head trauma patients who present with prolonged post-concussion symptoms do not meet the American Congress of Rehabilitation Medicine (ACRM) diagnostic criteria for mild traumatic brain injuries (mTBI). This population has not been extensively studied and its clinical characteristics are currently uncertain. A retrospective chart review was conducted to explore the symptomatic differences between mTBI and non-mTBI head trauma patients presenting at a concussion clinic with chronic post-concussion symptoms (PCSx). Patient information was extracted from 161 charts, of which 128 subjects met the ACRM criteria for mTBI (ACRM + PCSx), while 33 did not (non-ACRM + PCSx). These two groups were compared for demographic variables and symptomology. This study found that 20.5% of subjects presenting with chronic post-concussion symptoms do not meet ACRM criteria. No symptom-specific differences were found between the two populations in any of the categories tested. These results show that chronic post-concussion symptoms are similar in both mTBI and non-mTBI head trauma patients in the general population, suggesting a need for further research focusing on this group.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.355
Teacher spread0.326 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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