Correlation Between Computed Tomography-Based Tissue Net Water Uptake and Volumetric Measures of Cerebral Edema After Reperfusion Therapy
Bibliographic record
Abstract
Background: Cerebral edema after large hemispheric infarction is associated with poor functional outcome and mortality. Net water uptake (NWU) quantifies the degree of hypoattenuation on unenhanced-computed tomography (CT) and is increasingly used to measure cerebral edema in stroke research. Hemorrhagic transformation and parenchymal contrast staining after thrombectomy may confound NWU measurements. We investigated the correlation of NWU measured postthrombectomy with volumetric markers of cerebral edema and association with functional outcomes. Methods: In a pooled individual patient level analysis of patients presenting with anterior circulation large hemispheric infarction (core 80–300 mL or Alberta Stroke Program Early CT Score ≤5) in the HERMES (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke trials) data set, cerebral edema was defined as the volumetric expansion of the ischemic hemisphere expressed as a ratio to the contralateral hemisphere(rHV). NWU and midline-shift were compared with rHV as the reference standard on 24-hour follow-up CT, adjusted for hemorrhagic transformation and the use of thrombectomy. Association between edema markers and day 90 functional outcomes (modified Rankin Scale) was assessed using ordinal logistic regression. Results: Overall (n=144), there was no correlation between NWU and rHV (r s =0.055, P =0.51). In sub-group analyses, a weak correlation between NWU with rHV was observed after excluding patients with any degree of hemorrhagic transformation (r s =0.211, P =0.015), which further improved after excluding thrombectomy patients (r s =0.453, P =0.001). Midline-shift correlated strongly with rHV in all sub-group analyses (r s >0.753, P =0.001). Functional outcome at 90 days was negatively associated with rHV (adjusted common odds ratio, 0.46 [95% CI, 0.32–0.65]; P <0.001) and midline-shift (adjusted common odds ratio, 0.85 [95% CI, 0.78–0.92]; P <0.001) but not NWU (adjusted common odds ratio, 1.00 [95% CI, 0.97–1.03]; P =0.84), adjusted for age, baseline National Institutes of Health Stroke Scale, and thrombectomy. Prognostic performance of NWU improved after excluding patients with hemorrhagic transformation and thrombectomy (adjusted odds ratio, 0.90 [95% CI, 0.80–1.02]; P =0.10). Conclusions: NWU correlated poorly with conventional markers of cerebral edema and was not associated with clinical outcome in the presence of hemorrhagic transformation and thrombectomy. Measuring NWU postthrombectomy requires validation before implementation into clinical research. At present, the use of NWU should be limited to baseline CT, or follow-up CT only in patients without hemorrhagic transformation or treatment with thrombectomy.
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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 | 0.008 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".