Assessing the relationship between brain tissue oxygenation and neurological dysfunction in critically ill patients: study protocol
Bibliographic record
Abstract
Background: Acute and chronic neurological complications amongst survivors of critical illness is common, however, the underlying etiology of this neurological dysfunction is unknown. This is the first study to use near-infrared spectroscopy to non-invasively measure brain tissue oxygenation, as a surrogate marker of cerebral perfusion, and correlate these values with subsequent neurological dysfunction. We will test the hypothesis that poor cerebral oxygenation during the first 24 hours of critical illness is correlated with acute and chronic neurological complications. Methods: This single-centre prospective observational study will be performed in a 33-bed medical/surgical intensive care unit (ICU). Adult patients are eligible for enrolment if they are admitted to the ICU within 24 hours, require mechanical ventilation, and/or vasopressor support. For 24 hours, cerebral oxygenation levels will be measured with the FORESIGHT oximeter; vital signs and tissue oxygenation will be captured with data monitoring software. Participants will be screened daily for delirium with the confusion assessment method-ICU. Long-term neurological function will be assessed with the Repeatable Battery for the Assessment of Neuropsychological Status and the kinesiological instrument for normal and altered reaching movements (KINARM) robot. Conclusions: This study will provide novel information regarding the determinants of cerebral oxygenation during the acute phase (i.e. 24 hours) of critical illness, and its potential relationship with subsequent neurological complications. Should a relationship exist between cerebral oxygenation and neurological complications, future studies will be aimed at using brain tissue oxygenation as a therapeutic target to prevent acute and chronic neurological dysfunction. Clinical Trial Registration: This trial is registered on clinicaltrials.gov (Identifier: NCT02344043), retrospectively registered January 8, 2015.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.018 |
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".