A Simple Echocardiographic Prediction Rule for Hemodynamics in Pulmonary Hypertension
Bibliographic record
Abstract
BACKGROUND: Pulmonary hypertension (PH) has diverse causes with heterogeneous physiology compelling distinct management. Differentiating patients with primarily elevated pulmonary vascular resistance (PVR) from those with PH predominantly because of elevated left-sided filling pressure is critical. METHODS AND RESULTS: We reviewed hemodynamics, echocardiography, and clinical data for 108 patients seen at a referral PH clinic with transthoracic echocardiogram and right heart catheterization within 1 year. We derived a simple echocardiographic prediction rule to allow hemodynamic differentiation of PH attributed to pulmonary vascular disease (PH(PVD), defined as pulmonary artery wedge pressure [PAWP]≤15 mm Hg and PVR>3 WU). Age averaged 61.3±14.8 years, μPAWP and PVR were 16.4±7.1 mm Hg and 6.3±4.0 WU, respectively, and 52 (48.1%) patients fulfilled PH(PVD) hemodynamic criteria. The derived prediction rule ranged from -2 to +2 with higher scores suggesting higher probability of PH(PVD): +1 point for left atrial anterior-posterior dimension <3.2 cm; +1 for presence of a mid systolic notch or acceleration time <80 ms; -1 for lateral mitral E:e'>10; -1 for left atrial anterior-posterior dimension >4.2 cm. PVR increased stepwise with score (for -2, 0, and +2, μPVR were 2.5, 4.5, and 8.1 WU, respectively), whereas the inverse was true for pulmonary artery wedge pressure (corresponding μPAWP were 21.5, 16.5, and 10.4 mm Hg). Among subjects with complete data, the score had an area under the curve (AUC) of 0.921 for PH(PVD). A score ≥0 had 100% sensitivity and 69.3% positive predictive value for PH(PVD), with 62.3% specificity. No patients with a negative score had PH(PVD). Patients with a negative score and acceleration time >100 ms had normal PVR (μPVR=1.8 WU, range=0.7-3.2 WU). CONCLUSIONS: We present a simple echocardiographic prediction rule that accurately defines PH hemodynamics, facilitates improved screening and focused clinical investigation for PH diagnosis and management.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".