Incidence and characteristics of cerebral hypoxia after craniectomy in brain-injured patients: a cohort study
Bibliographic record
Abstract
OBJECTIVE: After craniectomy, although intracranial pressure (ICP) is controlled, episodes of brain hypoxia might still occur. Cerebral hypoxia is an indicator of poor outcome independently of ICP and cerebral perfusion pressure. No study has systematically evaluated the incidence and characteristics of brain hypoxia after craniectomy. The authors' objective was to describe the incidence and characteristics of brain hypoxia after craniectomy. METHODS: The authors included 25 consecutive patients who underwent a craniectomy after traumatic brain injury or intracerebral hemorrhage and who were monitored afterward with a brain tissue oxygen pressure monitor. RESULTS: The frequency of hypoxic values after surgery was 14.6% despite ICP being controlled. Patients had a mean of 18 ± 23 hypoxic episodes. Endotracheal (ET) secretions (17.4%), low cerebral perfusion pressure (10.3%), and mobilizing the patient (8.6%) were the most common causes identified. Elevated ICP was rarely identified as the cause of hypoxia (4%). No cause of cerebral hypoxia could be determined 31.2% of the time. Effective treatments that were mainly used included sedation/analgesia (20.8%), ET secretion suctioning (15.4%), and increase in fraction of inspired oxygen or positive end-expiratory pressure (14.1%). CONCLUSIONS: Cerebral hypoxia is common after craniectomy, despite ICP being controlled. ET secretion and patient mobilization are common causes that are easily treatable and often not identified by standard monitoring. These results suggest that monitoring should be pursued even if ICP is controlled. The authors' findings might provide a hypothesis to explain the poor functional outcome in the recent randomized controlled trials on craniectomy after traumatic brain injury where in which brain tissue oxygen pressure was not measured.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".