Estimation of Right Atrial Pressure by Ultrasound-Assessed Jugular Vein Distensibility in Patients With Heart Failure
Bibliographic record
Abstract
BACKGROUND: Clinical evaluation of central venous pressure is difficult, depends on experience, and is often inaccurate in patients with chronic advanced heart failure. We assessed the ultrasound-assessed internal jugular vein (JV) distensibility by ultrasound as a noninvasive tool to identify patients with normal right atrial pressure (RAP ≤7 mm Hg) in this population. METHODS: We measured JV distensibility as the Valsalva-to-rest ratio of the vein diameter in a calibration cohort (N=100) and a validation cohort (N=101) of consecutive patients with chronic heart failure with reduced ejection fraction who underwent pulmonary artery catheterization for advanced heart failure therapies workup. RESULTS: A JV distensibility threshold of 1.6 was identified as the most accurate to discriminate between patients with RAP ≤7 versus >7 mm Hg (area under the receiver operating characteristic curve, 0.74 [95% CI, 0.64–0.84]) and confirmed in the validation cohort (receiver operating characteristic, 0.82 [95% CI, 0.73–0.92]). A JV distensibility ratio >1.6 had predictive positive values of 0.86 and 0.94, respectively, to identify patients with RAP ≤7 mm Hg in the calibration and validation cohorts. Compared with patients from the calibration cohort with a high JV distensibility ratio (>1.6; n=42; median RAP, 4 mm Hg; pulmonary capillary wedge pressure, 11 mm Hg), those with a low JV distensibility ratio (≤1.6; n=58; median RAP, 8 mm Hg; pulmonary capillary wedge pressure, 22 mm Hg; P <0.0001 for both) were more likely to die or undergo a left ventricular assist device implant or heart transplantation (event rate at 2 years: 42.7% versus 18.2%; log-rank P =0.034). CONCLUSIONS: Ultrasound-assessed JV distensibility identifies patients with chronic advanced heart failure with normal RAP and better outcomes. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03874312.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".