A Clinical Trial of a Novel Electroencephalography Device as a Predictor of Postoperative Delirium.
Bibliographic record
Abstract
Postoperative delirium is a public health and research priority. The International Perioperative Neurotoxicity Working Group recommends baseline cognitive function be assessed for older patients prior to surgery and anesthesia. Perioperative cognitive screening tools trialed in anesthesia are not routinely incorporated into clinical practice related to validity, reliability, or practicality concerns. The ideal perioperative cognitive screening tool would be rapid; easily administrable; valid; reliable; automatically scored; void of language, cultural, and education bias; and cost-efficient. No such tool currently exists. We explored baseline and postoperative neurocognitive characteristics that may help to establish predictive and trend metrics for perioperative neurocognitive assessment in older surgical patients using a novel, Food and Drug Administration-cleared point-of-care electroencephalography device (WAViMed™, Boulder, CO). To our knowledge, our study is the first to assess the device as a perioperative neurocognitive assessment tool. Although an association between P300 auditory-evoked potentials and Montreal Cognitive Assessment scores was not identified, further investigation is warranted given the magnitude of impact that such a device might have on patient outcomes and healthcare costs.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".