Glasgow Coma Scale Scoring is Often Inaccurate
Bibliographic record
Abstract
INTRODUCTION: The Glasgow Coma Scale (GCS) is widely applied in the emergency setting; it is used to guide trauma triage and for the application of essential interventions such as endotracheal intubation. However, inter-rater reliability of GCS scoring has been shown to be low for inexperienced users, especially for the motor component. Concerns regarding the accuracy and validity of GCS scoring between various types of emergency care providers have been expressed. Hypothesis/Problem The objective of this study was to determine the degree of accuracy of GCS scoring between various emergency care providers within a modern Emergency Medical Services (EMS) system. METHODS: This was a prospective observational study of the accuracy of GCS scoring using a convenience sample of various types of emergency medical providers using standardized video vignettes. Ten video vignettes using adults were prepared and scored by two board-certified neurologists. Inter-rater reliability was excellent (Cohen's κ = 1). Subjects viewed the video and then scored each scenario. The scoring of subjects was compared to expert scoring of the two board-certified neurologists. RESULTS: A total of 217 emergency providers watched 10 video vignettes and provided 2,084 observations of GCS scoring. Overall total GCS scoring accuracy was 33.1% (95% CI, 30.2-36.0). The highest accuracy was observed on the verbal component of the GCS (69.2%; 95% CI, 67.8-70.4). The eye-opening component was the second most accurate (61.2%; 95% CI, 59.5-62.9). The least accurate component was the motor component (59.8%; 95% CI, 58.1-61.5). A small number of subjects (9.2%) assigned GCS scores that do not exist in the GCS scoring system. CONCLUSIONS: Glasgow Coma Scale scoring should not be considered accurate. A more simplified scoring system should be developed and validated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".