The feasibility of monitoring trauma patients with a wireless, wearable Doppler ultrasound
Bibliographic record
Abstract
BACKGROUND: Early detection of reduced stroke volume (SV) or cardiac output (CO) may expedite resuscitative interventions during traumatic hemorrhage; corrected carotid artery flow time (ccFT) has been proposed as a surrogate for SV during blood volume loss. STUDY DESIGN AND METHODS: We conducted a prospective cohort study to assess the feasibility of using a wireless, wearable Doppler ultrasound capable of measuring ccFT in traumatically injured patients at a level 1 trauma center. A convenience sample of 33 patients was enrolled. We assessed device placement, data transfer and capture, and signal quality by assessing the ability to capture at least 15 consecutive cardiac cycles in the minute prior to blood pressure monitor cycling. A post hoc analysis examined ccFT variations between transfused and non-transfused patients. RESULTS: Device placement succeeded in 94% of patients (n = 31) and the data were captured and transferred from all 31. The consecutive cardiac cycles before blood pressure measurement exceeded 15 (p = .015) in 93% of patients (n = 28). We observed ccFT below 270 ms and longer time spent under this threshold during resuscitation in transfused patients. Patients with low ccFT experienced more severe injuries and longer hospital and ICU stays. DISCUSSION: This is the first study that demonstrates the feasibility of using a wearable Doppler ultrasound in trauma patients on admission to the trauma bay. Although findings suggest that ccFT could serve as an early marker of hemodynamic compromise, further large-scale, multicenter studies are needed to validate its predictive value and clinical utility in guiding trauma resuscitation.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".