Continuous Thermal Diffusion-Based Cerebral Blood Flow Monitoring in Adult Traumatic Brain Injury: A Scoping Systematic Review
Bibliographic record
Abstract
Thermal diffusion flowmetry (TDF) is an appealing candidate for monitoring of cerebral blood flow (CBF) in neurocritical-care patients as it provides absolute measurements with a high temporal resolution, potentially allowing for bedside intervention that could mitigate secondary injury. We performed a systematic review of TDF-regional(r)CBF measurements and their association with (1) patient functional outcome, (2) other neurophysiological parameters, and (3) imaging-based tissue outcomes. We searched MEDLINE, EMBASE, SCOPUS, BIOSIS, GlobalHealth, and the Cochrane Databases from inception to October 2018 and relevant conference proceedings published over the last 5 years. Nine articles that explored the relationship between TDF-rCBF, mortality, and Glasgow Outcome Scale (GOS) or GOS-Extended (GOS-E) at various intervals were included. Despite being based on an overall weak body of evidence, our analysis suggests a link between sustained low or high CBF and poor functional outcome. Twenty-five studies reporting associations with neurophysiological parameters were included. The available data also point to an association between low or high TDF-rCBF and intracranial hypertension. TDF-rCBF appears to correlate well with regional brain tissue oxygenation measurements. We found no studies reporting on imaging-based tissue outcome in relation to TDF. In conclusion, despite being based on a relatively weak body of evidence, the available literature suggests a link between consistently abnormal TDF-rCBF values, intracranial hypertension, and poor functional outcome. TDF-rCBF also appears to correlate well with regional measurements of brain tissue oxygenation. Currently, such monitoring should be considered experimental, requiring much further evaluation prior to widespread adoption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".