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Clinical assessment of head injuries in motorcyclists involved in traffic accidents: A prospective, observational study

2022· article· en· W4288061548 on OpenAlexaboutno aff
Cristiano Below, ISABELA CAMPOS BRIANTI, José Gustavo Parreira, PEDRO DE SOUZA LUCARELLI-ANTUNES, Nelson Saade, MURILO GOLIN, LUCA GIOVANNI ANTONIO PIVETTA, José Carlos Esteves Veiga, José Cesar Assef

Bibliographic record

VenueRevista do Colégio Brasileiro de Cirurgiões · 2022
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleObservational studyHead injuryPhysical examinationProspective cohort studyPoison controlInjury preventionTraumatic brain injuryEmergency medicinePediatricsSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: to review the clinical assessment of head injuries in motorcyclists involved in traffic accidents. METHOD: prospective observational study, including adult motorcyclists involved in traffic accidents in a period of 12 months. Patients sustaining signs of intoxication were excluded. A modification of the Canadian Head CT Rules was used to indicate computed tomography (CT). Patients not undergoing CT were followed by phone calls for three months. Collected variables were compared between the group sustaining head injuries and the others. We used chi-square, Fisher, and Student's t for statistical analysis, considering p<0.05 as significant. RESULTS: we included 208 patients, 99.0% were wearing helmets. Seventeen sustained signs of intoxication and were excluded. Ninety (47.1%) underwent CT and 12 (6.3%) sustained head injuries. Head injuries were significantly associated with Glasgow Coma Scale<15 (52.3% vs. 2.8% - p<0,001) and a positive physical exam (17.1% vs. zero - p<0,05). Four (2.1%) patients with intracranial mass lesions needed surgical interventions. None helmet-wearing patients admitted with GCS=15 and normal physical examination sustained head injuries. CONCLUSION: Head CT is not necessary for helmet-wearing motorcyclists admitted with GCS=15 and normal physical examination.

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)0.002
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.420
Teacher spread0.323 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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