The cerebrovascular response to norepinephrine: A scoping systematic review of the animal and human literature
Bibliographic record
Abstract
Intravenous norepinephrine (NE) is utilized commonly in critical care for cardiovascular support. NE's impact on cerebrovasculature is unclear and may carry important implications during states of critical neurological illness. The aim of the study was to perform a scoping review of the literature on the cerebrovascular/cerebral blood flow (CBF) effects of NE. A search of MEDLINE, BIOSIS, EMBASE, Global Health, SCOPUS, and Cochrane Library from inception to December 2019 was performed. All manuscripts pertaining to the administration of NE, in which the impact on CBF/cerebral vasculature was recorded, were included. We identified 62 animal studies and 26 human studies. Overall, there was a trend to a direct vasoconstriction effect of NE on the cerebral vasculature, with conflicting studies having demonstrated both increases and decreases in regional CBF (rCBF) or global CBF. Healthy animals and those undergoing cardiopulmonary resuscitation demonstrated a dose-dependent increase in CBF with NE administration. However, animal models and human patients with acquired brain injury had varied responses in CBF to NE administration. The animal models indicate an increase in cerebral vasoconstriction with NE administration through the alpha receptors in vessels. Global and rCBF during the injection of NE displays a wide variation depending on treatment and model/patient.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".