Assessing Intracranial Pressure Visualizations Displayed on ICU Bedside Physiologic Monitors
Bibliographic record
Abstract
Neurocritical care is considered a complex socio-technical environment where clinicians deal with large amounts of data and need to make timely decisions to provide optimal care for patients, improve outcomes, and reduce mortality. Intracranial pressure (ICP) is one of the key physiologic indicators clinicians track to minimize the risk of secondary brain injury. The understanding and teaching of pathophysiologic ICP trends is perceived as challenging to both novice and advanced clinicians. We propose new ICP visualizations with the goal of facilitating a better understanding of ICP concepts on bedside physiologic monitors to support complex decision-making. We have conducted interviews with clinicians to receive feedback on preliminary designs. Interviews revealed that the staff physician appreciated visualizations with more depth and with calculated parameters to describe the raw data. Contrarily, the trainees and nurses saw the most value in visualizations that were less abstract and easier to interpret.
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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 | 0.025 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".