Abstract WMP16: Elevated Cerebral Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Values Are Associated With Poor Neurologic Outcome in Comatose Cardiac Arrest Patients
Bibliographic record
Abstract
Background: For cardiac arrest survivors initially comatose after restoration of spontaneous circulation (ROSC), the extent of brain injury and expected neurologic outcome are crucial for patient management decisions. Advanced diffusion imaging approaches such as neurite orientation dispersion and density imaging (NODDI) or diffusion kurtosis imaging may provide additional insight into tissue integrity and potential for recovery of consciousness complementary to standard diffusion tensor imaging (DTI). Methods: Multi-shell diffusion imaging was acquired in a prospective study of comatose cardiac arrest patients and in 5 controls. Neurite orientation dispersion (OD), intracellular volume fraction (ICVF), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) and fractional anisotropy (FA) were calculated. Median whole-brain values in patients with poor outcomes (no arousal recovery [AR] by discharge) were compared with those with AR and to controls (1-way ANOVA, post-hoc 1-sided Wilcoxon exact test). Results: 18 patients (mean ±SD 48±23 y, 39% men) and 5 controls (37±19 y, 40% men) were analyzed. Median (range) Glasgow Coma Scale was 3 [3-5]. 10 patients exhibited AR, 8 did not. Median [IQR] time-to-MRI was 5 [4-8] days. FA (P=0.009), MK (P=0.017), AK (P=0.026), RK (P=0.014), OD (P=0.018) and ICVF (P=0.0038) were significantly different (see Figure). FA control values were greater than AR and no AR (P<0.05). MK, AK, RK, OD and ICVF values in the no AR group were greater than in the AR and control groups (P<0.05). Discussion: This is the first report investigating early NODDI and diffusional heterogeneity changes in post-cardiac arrest comatose patients. Patients who failed to recover arousal demonstrated greater values for all kurtosis and NODDI metrics compared to controls. Potential bias from early withdrawal of life sustaining treatment and small cohorts are limitations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".