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Record W1990055699 · doi:10.3171/ped/2008/1/6/461

Prediction of cognitive sequelae based on abnormal computed tomography findings in children following mild traumatic brain injury

2008· article· en· W1990055699 on OpenAlexaff
Harvey S. Levin, Gerri Hanten, Garland Roberson, Xiaoqi Li, Linda Ewing‐Cobbs, Maureen Dennis, Sandra B. Chapman, Jeffrey E. Max, Jill V. Hunter, Russell Schachar, Thomas G. Luerssen, Paul R. Swank

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2008
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHospital for Sick Children
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Mental Health
KeywordsMedicineTraumatic brain injuryGlasgow Coma ScaleNeuropsychologyNeuropsychological assessmentPoison controlCognitionPediatricsAnesthesiaPsychiatryEmergency medicine

Abstract

fetched live from OpenAlex

OBJECT: The aim of this study was to determine whether the presence of intracranial pathophysiology on computed tomography (CT) scans obtained within 24 hours of mild traumatic brain injury (MTBI) in children adversely affects neuropsychological outcome during the 1st year postinjury. METHODS: A prospective longitudinal design was used to examine the neuropsychological outcomes in children (ages 5-15 years) who had been treated for MTBI, which was defined as a loss of consciousness for up to 30 minutes and a lowest Glasgow Coma Scale (GCS) score of 13-15. Exclusion criteria included any preinjury neurological disorder. Outcome assessments were performed within 2 weeks and at 3, 6, and 12 months postinjury. Outcomes were compared between patients with MTBI whose postinjury CT scans revealed complications of brain pathophysiology (32 patients, CMTBI group) and those with MTBI but without complications (48 patients, MTBI group). RESULTS: Significant interactions confirmed that the pattern of recovery over 12 months after injury differed depending on the intracranial pathology, presence and severity of injuries to body regions other than the head, preinjury attention-deficit hyperactivity disorder (ADHD), and socioeconomic status. Children in the CMTBI group had significantly poorer episodic memory, slower cognitive processing, diminished recovery in managing cognitive interference, and poorer performance in calculating and reading than patients in the MTBI group. Among the patients with mild or no extracranial injury, visuomotor speed was slower in those in the CMTBI group; and among patients without preinjury ADHD, working memory was worse in those in the CMTBI group. CONCLUSIONS: Neuropsychological recovery during the 1st year following MTBI is related to the presence of radiographically detectable intracranial pathology. Children with intracranial pathology on acute CT performed more poorly in several cognitive domains when compared with patients whose CT findings were normal or limited to a linear skull fracture. Depending on the presence of preinjury ADHD and concomitant extracranial injury, working memory and visuomotor speed were also diminished in patients whose CT findings revealed complications following MTBI. Computed tomography within 24 hours postinjury appears to be useful for identifying children with an elevated risk for residual neuropsychological changes.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.075
GPT teacher head0.308
Teacher spread0.233 · 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

Citations199
Published2008
Admission routes1
Has abstractyes

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