The Use of the Radiographic Appearance of the Azygos Vein to Assess Volume Status in Trauma Patients
Bibliographic record
Abstract
BACKGROUND: The assessment of hypovolemia in victims of trauma is a critical aspect of resuscitation and care in the initial presentation of a patient. This study attempted to validate the use of the appearance of the azygos vein (AV) on initial chest radiographs as a parameter that may add to this initial assessment. METHODS: The design involved a blinded independent assessment of serial chest radiographs from consecutive trauma cases from January 21, 2008, until September 13, 2008, by a trained Radiologist and a Trauma Team Leader (TTL) and then comparing this assessment to mean arterial pressure (MAP) and heart rate estimates of volume status in serial severe trauma patients. This is an insensitive but specific measure of volume status. RESULTS: In this population with high prevalence of hypovolemia, the presence of an AV ≤ 0.5 cm yielded a sensitivity of 4.9% and 9.8% for the TTL and Radiologist, respectively, in patients with a mean arterial pressure <70 and heart rate >100. The specificity was 98.8% and 91.6%, which translates into a positive likelihood ratio of 4.08 and 1.17 for the TTL and Radiologist, respectively. The Kappa score for agreement between the two readers was 0.4. CONCLUSION: When a small AV can be seen by the TTL, it may be a useful adjunct to the assessment of volume status.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".