Assessment of the ABC/2 Method of Epidural Hematoma Volume Measurement as Compared to Computer-Assisted Planimetric Analysis
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Epidural hematoma volume (EDHV) is an independent predictor of prognosis in patients with epidural hematoma (EDH) and plays a central role in treatment decision making. This study's objective was to determine the accuracy and reliability of the widely used volume measurement method ABC/2 in estimating EDHV by comparing it to the computer-assisted planimetric method. METHODS: A data set of computerized tomography (CT) scans of 35 patients with EDH was evaluated to determine the accuracy of ABC/2 method, using computer-assisted planimetric technique to establish the reference criterion of EDHV for each patient. Another data set was constructed by randomly selecting 5 patients then replicating each case twice to yield 15 patients. Intra- and interobserver reliability were evaluated by asking four observers to independently estimate EDHV for the latter data set using the ABC/2 method. RESULTS: Estimation of EDHV using the ABC/2 method showed high intra- and interobserver reliability (intra-class correlation coefficient = .99). These estimates were closely correlated with planimetric measures (r = .99). But the ABC/2 method generally overestimated EDHV, especially in the nonellipsoid-like group. The difference between the ABC/2 measures and planimetric measures was statistically significant (p < .05). CONCLUSIONS: The ABC/2 method could be used for EDHV measurement, which would contribute to treatment decision making as well as clinical outcome prediction. However, clinicians should be aware that the ABC/2 method results in a general volume overestimation. Future studies focusing on justification of the technique to improve its accuracy would be of practical value.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it