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Record W2314775066 · doi:10.1097/htr.0000000000000226

Prognostic Markers for Poor Recovery After Mild Traumatic Brain Injury in Older Adults: A Pilot Cohort Study

2016· article· en· W2314775066 on OpenAlexafffundabout
Vicki L. Kristman, Robert J. Brison, Michel Bédard, Paula Reguly, Shelley Chisholm

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsLakehead University
FundersCanadian Institutes of Health Research
KeywordsTraumatic brain injuryCohortMedicineCohort studyInternal medicineGerontologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify prognostic markers associated with poor recovery from mild traumatic brain injury (MTBI) in older adults. SETTING: Three Ontario emergency departments. PARTICIPANTS: Forty-nine participants aged 65 years and older that visited an emergency department for MTBI. DESIGN: Pilot prospective cohort study. MAIN MEASURES: Recovery from MTBI determined using the Rivermead Postconcussion symptom Questionnaire, the Glasgow Outcomes Scale-Extended, physical and mental health functioning (SF-12), and a single question on self-rated recovery assessed by telephone shortly after emergency department visit (baseline) and again 6 months later. Predictors were measured at baseline. RESULTS: Markers potentially associated with poor recovery included reporting worse health 1 year before the injury, poor expectations for recovery, depression, and fatigue. CONCLUSION: Recovery after MTBI in older adults may be associated more with psychosocial than with biomedical or injury-related factors.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation 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 score0.130
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.357
Teacher spread0.319 · 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.

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

Citations33
Published2016
Admission routes3
Has abstractyes

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