Detecting Awareness in the Intensive Care Unit Using Functional Near‐Infrared Spectroscopy
Bibliographic record
Abstract
OBJECTIVE: Signs of awareness after acute severe brain injury are critical for informing goals-of-care decisions, ranging from the continuation of aggressive life-sustaining therapy to comfort-focused end-of-life measures. However, awareness may go undetected in some critically ill patients when assessed using bedside behavioral neurological examination. Here, we use functional near-infrared spectroscopy to identify covert awareness in acute brain injured patients who are unable to follow behavioral commands. METHODS: We conducted a prospective, consecutive cross-sectional study of 32 critically ill patients in a single intensive care unit (ICU). All had acute brain injuries from various causes and lacked behavioral command-following on bedside examination, as determined by using the Coma Recovery Scale-Revised. Using functional near-infrared spectroscopy, an optical bedside neuroimaging technique, we assessed brain activity while patients were instructed to perform a mental imagery task in which a positive response was dependent upon preserved awareness. We referred to this phenomenon as covert awareness. RESULTS: Of 32 acutely brain injured patients (mean age = 63, ± 12 years, 15 females), 8 (25%) were able to willfully modulate their brain activity when instructed to imagine playing a game of tennis-providing evidence of covert awareness despite no observable behavioral signs that this was the case. We found no association between covert awareness and 3-month functional outcomes using the Glasgow Outcome Scale-Extended. INTERPRETATION: Functional near-infrared spectroscopy detected preserved consciousness in 25% of patients who lacked behavioral command following in an intensive care setting. This finding highlights the need for further research to assess the use of advanced neuroimaging techniques in the clinical assessment of critically ill patients. Such methods could ensure that goals of care decisions are based on a more accurate understanding of a patient's level of awareness. ANN NEUROL 2025;98:1201-1209.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".