Transcranial Doppler Ultrasound and Concussion–Supplemental Symptoms with Physiology: A Systematic Review
Bibliographic record
Abstract
Sport-related concussion (SRC) can impair the cerebrovasculature both acutely and chronically. Transcranial Doppler (TCD) ultrasound assessment has the potential to illuminate the mechanisms of impairment and provide an objective evaluation of SRC. The current systematic review investigated studies employing TCD ultrasound assessment of intracranial arteries across three broad categories of cerebrovascular regulation: neurovascular coupling (NVC), cerebrovascular reactivity (CVR), and dynamic cerebral autoregulation (dCA). The current review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42021275627). The search strategy was applied to PubMed, as this database indexes all biomedical journals. Original articles on TCD for athletes with medically diagnosed SRC were included. Title/abstract and full-text screening were completed by three authors. Two authors completed data extraction and risk of bias using the Methodological Index for Non-Randomized Studies and Scottish Intercollegiate Guideline Network checklists. Of the 141 articles identified, 14 met the eligibility criteria. One article used an NVC challenge, eight assessed CVR, and six investigated dCA. Methodologies varied widely among studies, and results were heterogeneous. There was evidence of cerebrovascular impairment in all three domains roughly 2 days post-SRC, but the magnitude and recovery of these impairments were not clear. There was evidence that clinical symptom resolution occurred before cerebrovascular function, indicating that physiological deficits may persist despite clinical recovery and return to play. Collectively, this emphasizes an opportunity for the use of TCD to illuminate the cerebrovascular deficits caused by SRC. It also highlights that there is need for consistent methodological rigor when employing TCD in a SRC population.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".