A Description of a New Continuous Physiological Index in Traumatic Brain Injury Using the Correlation between Pulse Amplitude of Intracranial Pressure and Cerebral Perfusion Pressure
Bibliographic record
Abstract
To describe a new continuous index of physiologic measurement in a traumatic brain injury (TBI) population, the moving correlation coefficient between intracranial pressure (ICP) pulse amplitude (AMP) and cerebral perfusion pressure (CPP), which we refer to as RAC. We use patient examples of sustained intracranial hypertension, systemic arterial hypotension, and plateau waves, as well as the retrospective analysis of 358 non-decompressive craniectomy (DC) TBI patients with high-frequency ICP and arterial blood pressure data, to explore the relationships of this new index, RAC, with AMP, ICP, CPP, RAP (correlation coefficient between AMP and ICP), pressure reactivity index (PRx), and pulse amplitude index (PAx). We compared the RAC-CPP relationship to that observed between CPP and both PRx and PAx. RAC displays temporal responsiveness to sustained increased ICP, arterial hypotension, and plateau waves, with positive values found during episodes of high ICP and low CPP. Analysis of AMP versus CPP and AMP versus ICP relationships in data from the entire non-DC cohort show lower breakpoints for AMP/CPP at CPP = 40 mm Hg and upper breakpoints for AMP/ICP at ICP = 50-60 mm Hg. RAC trends to positive values with increasing ICP, particularly with ICP values above the peak in AMP (ICP >50 mm Hg), though its interpretation requires concomitant interpretation of AMP, RAP, and PRx/PAx to determine contributions of compensatory reserve and cerebrovascular responsiveness to the changes observed in RAC. There is a parabolic relationship between RAC versus CPP, with trends toward positive RAC values near (and beyond) limits for low and high CPPs, suggesting that RAC may be used in the determination of optimum CPP. RAC appears to carry information regarding both cerebrovascular responsiveness and cerebral compensatory reserve. This contributes to RAC's uniqueness and complex interpretation. Further prospective, clinical studies of RAC in CPP optimum estimation and outcome prediction in TBI are required.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".