Radial-to-femoral pressure gradient quantification in cardiac surgery
Bibliographic record
Abstract
Background A radial-to-femoral pressure gradient (RFPG) can occur in roughly one-third of cardiac surgical patients. Such a gradient has been associated with smaller stature and potentially smaller radial artery diameter. We hypothesized that preoperative radial artery diameter could be a predictor of RFPG. We also investigated the clinical impact of using a femoral versus a radial arterial catheter in terms of vasoactive support. Methods Using ultrasound, we measured the bilateral radial artery diameters of 160 cardiac surgical patients. All arterial pressure values were continuously recorded. Significant RFPG was defined as ≥25 mm Hg in systolic and/or ≥10 mm Hg in mean arterial pressure. One hundred and forty-nine additional patients were used to validate the impact of our observations. Results Using 78,013 pressure datapoints in 129 patients, 34.8% of patients had an RFPG with a mean duration of 54 ± 48 minutes. Patients with a radial artery diameter <1.8 mm were more likely to have an RFPG (n = 14 [48.3%] vs 12 [22.2%]; P = .042). Patients with only a radial catheter received more phenylephrine ( P = .016) despite undergoing shorter and less complex procedures. In the validation cohort, similar observations were made, and patients with a radial artery catheter received a longer duration of vasoactive support in the intensive care unit. Conclusions A significant RFPG occurs in one-third of cardiac surgical patients and in 48% of those with a radial artery diameter <1.8 mm. The use of a single radial arterial catheter instead of dual radial and femoral catheters was associated with greater vasopressor requirements in the operating room and in the intensive care unit. We do not recommend the use of a single radial artery catheter in cardiac surgery.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".