Association of Age and Sex With Multi-Modal Cerebral Physiology in Adult Moderate/Severe Traumatic Brain Injury: A Narrative Overview and Future Avenues for Personalized Approaches
Bibliographic record
Abstract
The impact of age and biological sex on outcome in moderate/severe traumatic brain injury (TBI) has been documented in large cohort studies, with advanced age and male sex linked to worse long-term outcomes. However, the association between age/biological sex and high-frequency continuous multi-modal monitoring (MMM) cerebral physiology is unclear, with only sparing reference made in guidelines and major literature in moderate/severe TBI. In this narrative review, we summarize some of the largest studies associating various high-frequency MMM parameters with age and biological sex in moderate/severe TBI. To start, we present this by highlighting the representative available literature on high-frequency data from Intracranial Pressure (ICP), Cerebral Perfusion Pressure (CPP), Extracellular Brain Tissue Oxygenation (PbtO2), Regional Cerebral Oxygen Saturations (rSO2), Cerebral Blood Flow (CBF), Cerebral Blood Flow Velocity (CBFV), Cerebrovascular Reactivity (CVR), Cerebral Compensatory Reserve, common Cerebral Microdialysis (CMD) Analytes and their correlation to age and sex in moderate/severe TBI cohorts. Then we present current knowledge gaps in the literature, discuss biological implications of age and sex on cerebrovascular monitoring in TBI and some future avenues for bedside research into the cerebrovascular physiome after TBI.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".