Cerebral Hemodynamic Reserve and Early Neurologic Deterioration in Acute Ischemic Stroke
Bibliographic record
Abstract
Early neurological deterioration (END) is associated with increased mortality and morbidity. Although several predictive factors have been reported, there are little data about the hemodynamic factors. Our aim was to determine the capacity of cerebral hemodynamic reserve (CHR) to predict END. We studied 100 hospitalized patients with a first ever ischemic stroke of the middle cerebral artery (MCA) within the first 24 hours of symptoms onset. END was defined as a drop of at least one point in the Canadian Stroke Scale between admission and 72 hours. The mean flow velocity (mV) in the MCA and the CHR were measured by means of transcranial Doppler within the first 24 hours of admission. The CHR was expressed as the percentage increase in the MCA mV divided by the absolute increase in the end-tidal CO2 pressure in mm Hg after carbogen inhalation. END was observed in 23 patients. Reduced values of the mV in the symptomatic MCA (P = 0.043) and of the CHR in the symptomatic hemisphere (P < 0.001) were significantly associated with END. A CHR of less than 2%/1 mm Hg was independently associated with END (OR 8.45, 95% CI 1.82-39.2) after adjusting for potential confounders. CHR impairment within the first 24 hours of acute ischemic stroke is associated with a higher risk of END. This technique may be useful in selecting patients requiring a more intensive management.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 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".