The Role of Neuroimaging in the Determination of Brain Death
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Brain death determination (BDD) is primarily a clinical diagnosis, where death is defined as the permanent loss of brainstem function. In scenarios where clinical examinations are inaccurate, ancillary imaging tests are required. The choice of ancillary imaging test is variable, but the common denominator for all of them is to establish a lack of cerebral blood flow. The purpose of this study was to compare the diagnostic accuracy and interrater reliability of different ancillary imaging tests used for BDD. METHODS: Archival data were retrospectively analyzed for all patients who underwent any ancillary imaging test for BDD at our institution. The results of ancillary imaging tests were compared with, the reference standard, the clinical checklist for declaration of brain death. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of different ancillary imaging tests for BDD were performed. Interobserver agreement between two observers was measured using kappa statistics for each of the imaging modalities. RESULTS: A total of 74 patients underwent 41 computer tomography perfusion (CTP), 54 CT angiogram, 15 radionuclide scans, 1 cerebral angiogram, 3 magnetic resonance imaging, and 71 nonenhanced CT (NECT) head for BDD. All ancillary tests (except NECT head) showed 100% specificity and PPV. CTP had the highest sensitivity and NPV. All ancillary imaging tests demonstrated very high interrater reliability. CONCLUSIONS: The uses of ancillary imaging tests for BDD are increasing. Within this study's limitations, CTP followed by radionuclide scan were found to be the most accurate and reliable ancillary imaging test for BDD.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| 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) | 0.001 | 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".