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Record W4283696579 · doi:10.1080/02699052.2022.2093398

What are the demographic and clinical differences between those older adults with traumatic brain injury who receive a neurosurgical intervention to those that do not? A systematic literature review with narrative synthesis

2022· review· en· W4283696579 on OpenAlexaboutno aff
Jack Barrett, Julia Williams, Joanna Griggs, Simon S. Skene, Richard Lyon

Bibliographic record

VenueBrain Injury · 2022
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersNational Institute for Health and Care Research
KeywordsMedicineTriageIntervention (counseling)Traumatic brain injuryHead injuryMEDLINEChecklistPhysical therapyEmergency medicinePsychiatryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVES: This review aimed to identify the demographic and clinical differences between those older adults admitted directly under neurosurgical care and those that were not, and whether EMS clinicians could use these differences to improve patient triage. METHODS: The authors searched for papers that included older adults who had suffered a TBI and were either admitted directly under neurosurgical care or were not. Titles and abstracts were screened, shortlisting potentially eligible papers before performing a full-text review. The Newcastle-Ottawa Scale was used to assess the risk of bias. RESULTS: A total of nine studies were eligible for inclusion. A high abbreviated injury score head, Marshall score or subdural hematoma greater than 10 mm were associated with neurosurgical care. There were few differences between those patients who did and did not receive neurosurgical intervention. CONCLUSIONS: Absence of guidelines and clinician bias means that differences between those treated aggressively and conservatively observed in the literature are fraught with bias. Further work is required to understand which patients would benefit from an escalation of care and whether EMS can identify these patients so they are transported directly to a hospital with the appropriate services on-site.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.069
GPT teacher head0.361
Teacher spread0.292 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations7
Published2022
Admission routes1
Has abstractyes

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