Cerebrovascular Autoregulation Monitoring in the Management of Adult Severe Traumatic Brain Injury: A Delphi Consensus of Clinicians
Bibliographic record
Abstract
BACKGROUND: Several methods have been proposed to measure cerebrovascular autoregulation (CA) in traumatic brain injury (TBI), but the lack of a gold standard and the absence of prospective clinical data on risks, impact on care and outcomes of implementation of CA-guided management lead to uncertainty. AIM: To formulate statements using a Delphi consensus approach employing a group of expert clinicians, that reflect current knowledge of CA, aspects that can be implemented in TBI management and CA research priorities. METHODS: A group of 25 international academic experts with clinical expertise in the management of adult severe TBI patients participated in this consensus process. Seventy-seven statements and multiple-choice questions were submitted to the group in two online surveys, followed by a face-to-face meeting and a third online survey. Participants received feedback on average scores and the rationale for resubmission or rephrasing of statements. Consensus on a statement was defined as agreement of more than 75% of participants. RESULTS: Consensus amongst participants was achieved on the importance of CA status in adult severe TBI pathophysiology, the dynamic non-binary nature of CA impairment, its association with outcome and the inadvisability of employing universal and absolute cerebral perfusion pressure targets. Consensus could not be reached on the accuracy, reliability and validation of any current CA assessment method. There was also no consensus on how to implement CA information in clinical management protocols, reflecting insufficient clinical evidence. CONCLUSION: The Delphi process resulted in 25 consensus statements addressing the pathophysiology of impaired CA, and its impact on cerebral perfusion pressure targets and outcome. A research agenda was proposed emphasizing the need for better validated CA assessment methods as well as the focused investigation of the application of CA-guided management in clinical care using prospective safety, feasibility and efficacy studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.199 | 0.183 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".