Accuracy and reliability of qualitative echocardiography assessment of right ventricular size and function in neonates
Bibliographic record
Abstract
BACKGROUND: Subjective assessment of right ventricular (RV) function by neonatal echocardiography lacks validation. Incorrect diagnostic assignment in patients with suspected pulmonary hypertension (PH) may lead to unnecessary treatment or missed treatment opportunities. METHODS: Six evaluators (experts [n = 3], novice [n = 3]) were asked to independently rate RV characteristics (global function, dilation, and septal flattening) based on standardized echocardiography images. We randomly selected 60 infants, ≥35 weeks gestation at birth, of whom 30 were clinically unwell with acute pulmonary hypertension (aPH) and 30 were healthy controls. aPH was defined by echocardiography presence of right-left shunting across transitional shunts or elevated right ventricular systolic pressure as estimated by the magnitude of the regurgitant jet across the tricuspid valve with impaired oxygenation. Inter-rater comparative evaluation within groups and between groups was performed using Kappa statistics. RESULTS: Global agreement between evaluators for subjective assessment of RV function (0.3 [0.03], P < 0.001), size (0.14 [0.02], P < 0.001), and septal flattening (0.2 [0.02], P < 0.001) was uniformly poor. Agreement in RV function assessment was marginally better for both expert (0.32 [0.08], P < 0.001 vs 0.13 [0.081], and P < 0.001) and novice (0.4 [0.08], P < 0.001 vs 0.06 [0.07], and P < 0.001) evaluators. Overall, the diagnosis of aPH vs control was misclassified in 18% of cases. CONCLUSION: This study demonstrated significant variability in qualitative assessment of RV size and function by trained evaluators, regardless of level of expertise attained. The reliability of objective measures of RV hemodynamics requires prospective evaluation.
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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 | 0.010 | 0.041 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".