Original and Modified Graeb Score Correlation With Intraventricular Hemorrhage and Clinical Outcome Prediction in Hyperacute Intracranial Hemorrhage
Bibliographic record
Abstract
Background and Purpose— The Graeb score is a visual rating scale of intraventricular hemorrhage (IVH) on noncontrast head CT. Little data exist in the hyperacute (<6 hour) period for reliability and predictive value of the modified Graeb Score (mGS) or the original Graeb Score (oGS) for clinical outcomes or their correlation with quantitative IVH volumes. Methods— A retrospective analysis of multicenter prospective intracranial hemorrhage study was performed. oGS and mGS inter-observer agreement and IVH volume correlation on the baseline noncontrast head CT were calculated by intraclass correlation coefficient and Pearson coefficient respectively. Predictors of poor outcome (modified Rankin Scale scores ≥4) at 3 months were identified using a backward stepwise selection multivariable analysis. oGS and mGS performance for modified Rankin Scale scores ≥4 was determined by receiver operating characteristic analysis. Results— One hundred forty-one patients (65±12 years) with median (interquartile range) time to CT of 82.5 (70.3–157.5) minutes were included. IVH was observed in 43 (30%) patients. Inter-observer agreement was excellent for both oGS (intraclass correlation coefficient, 0.90 [95% CI, 0.80–0.95]) and mGS (intraclass correlation coefficient, 0.97 [95% CI, 0.84–0.99]). mGS (R=0.79; P <0.01) correlated better than oGS (R=0.71; P <0.01) with IVH volumes ( P =0.02). Models of thresholded oGS and mGS were not different from a model of planimetric baseline intracranial hemorrhage and IVH volume for poor outcome prediction. Area under the curves were 0.70, 0.73, and 0.72, respectively. Conclusions— Excellent correlation for oGS and mGS with IVH volume was seen. Thresholded oGS and mGS are reasonable surrogates for planimetric IVH volume for hyperacute intracranial hemorrhage studies.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".