Interobserver Agreement in the Interpretation of Outpatient Head CT Scans in an Academic Neuroradiology Practice
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The repeatability of head CT interpretations may be studied in different contexts: in peer-review quality assurance interventions or in interobserver agreement studies. We assessed the agreement between double-blind reports of outpatient CT scans in a routine academic practice. MATERIALS AND METHODS: Outpatient head CT scans (119 patients) were randomly selected to be read twice in a blinded fashion by 8 neuroradiologists practicing in an academic institution during 1 year. Nonstandardized reports were analyzed to extract 4 items (answer to the clinical question, major findings, incidental findings, recommendations for further investigations) from each report, to identify agreement or discrepancies (classified as class 2 [mentioned or not mentioned or contradictions between reports], class 1 [mentioned in both reports but diverging in location or severity], 0 [concordant], or not applicable), according to a standardized data-extraction form. Agreement regarding the presence or absence of clinically significant or incidental findings was studied with κ statistics. RESULTS: The interobserver agreement regarding head CT studies with positive and negative results for clinically pertinent findings was 0.86 (0.77-0.95), but concordance was only 75.6% (67.2%-82.5%). Class 2 discrepancy was found in 15.1%; class 1 discrepancy, in 9.2% of cases. The κ value for reporting incidental findings was 0.59 (0.45-0.74), with class 2 discrepancy in 29.4% of cases. Most discrepancies did not impact the clinical management of patients. CONCLUSIONS: Discrepancies in double-blind interpretations of head CT examinations were more common than reported in peer-review quality assurance programs.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".