Hypocapnia and the injured brain: More harm than benefit
Bibliographic record
Abstract
OBJECTIVES: Hypocapnia is used in the management of acute brain injury and may be life-saving in specific circumstances, but it can produce neuronal ischemia and injury, potentially worsening outcome. This review re-examines the rationale for the use of hypocapnia in acute brain injury and evaluates the evidence for therapeutic and deleterious effects in this context. DATA SOURCES AND STUDY SELECTION: A MEDLINE/PubMed search from 1966 to August 1, 2009, was conducted using the search terms "hyperventilation," "hypocapnia," "alkalosis," "carbon dioxide," "brain," "lung," and "myocardium," alone and in combination. Bibliographies of retrieved articles were also reviewed. DATA EXTRACTION AND SYNTHESIS: Hypocapnia--often for prolonged periods of time--remains prevalent in the management of severely brain-injured children and adults. Despite this, there is no proof beyond clinical experience with incipient herniation that hypocapnia improves neurologic outcome in any context. On the contrary, hypocapnia can cause or worsen cerebral ischemia. The effect of sustained hypocapnia on cerebral blood flow decreases progressively because of buffering; subsequent normocapnia can cause rebound cerebral hyperemia and increase intracranial pressure. Hypocapnia may also injure other organs. Accidental hypocapnia should always be avoided and prophylactic hypocapnia has no current role. CONCLUSIONS: Hypocapnia can cause harm and should be strictly limited to the emergent management of life-threatening intracranial hypertension pending definitive measures or to facilitate intraoperative neurosurgery. When it is used, Paco2 should be normalized as soon as is feasible. Outside these settings hypocapnia is likely to produce more harm than benefit.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".