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Record W4387966593 · doi:10.1097/tme.0000000000000489

Improving the Management of Adults With Mild Traumatic Brain Injury

2023· article· en· W4387966593 on OpenAlexaboutno aff
Rachel Helms

Bibliographic record

VenueAdvanced Emergency Nursing Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency departmentTraumatic brain injuryEmergency medicineComputed tomographyComputed tomographicMedical recordIntervention (counseling)Medical emergencyRadiologyPsychiatry

Abstract

fetched live from OpenAlex

The overuse of computed tomographic (CT) scans for patients who present to the emergency department (ED) after mild traumatic brain injury (mTBI) has been well-documented. The Canadian Computed Tomography Head Rule (CCHR) is a validated tool to guide ED providers in determining the need for emergent CT of mTBI patients. The purpose of this project was to reduce radiation exposure and ED length of stay by using the CCHR to decrease unnecessary CT scans in adults with TBI. Cost of care was also estimated. The CCHR implementation strategy included an education program for ED staff. The use of the CCHR was promoted throughout the intervention period. The outcomes measured were the number of CT scans ordered, ED length of stay, and the cost of avoidable CT scans. Data were collected through medical record reviews completed by the project leader and were evaluated using the independent samples t test. A total of 600 medical records were reviewed. There was a significant difference between adherence to the CCHR before (M = 64.6%) and after provider education (M = 74.3%). The percentage of CT scans that could have been avoided significantly decreased from baseline (M = 0.63) after provider education (M = 0.46). Length of stay for mTBI patients who were managed based on the CCHR (M = 184.9) was significantly less than the length of stay for those who were not (M = 260.1). The cost of avoidable scans was decreased by 37% over the course of the project. There were no incidents of missed diagnosis found. By increasing awareness of the CCHR and promoting its use, the number of head CT scans ordered, cost of care, and ED length of stay for patients who present after mTBI were significantly improved.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.327
Teacher spread0.307 · 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 designOther design
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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