The interpretation of hepatic venous pressure gradient tracings – excellent interobserver agreement unrelated to experience
Bibliographic record
Abstract
BACKGROUND AND AIMS: The hepatic venous pressure gradient (HVPG) plays an important role in the diagnosis, prognosis and therapy of patients with cirrhosis and portal hypertension. One barrier to its widespread use is the potential for a low reproducibility. We aimed to evaluate the interobserver agreement in the interpretation of optimally acquired HVPG tracings from patients with cirrhosis and different degrees of portal hypertension. METHODS: Two hundred and fifteen tracings obtained from 51 patients with cirrhosis in a single centre were interpreted independently by two hepatologists: one experienced observer and one inexperienced observer. Correlation was performed by Pearson linear regression and the intraclass correlation coefficient (ICC). A Bland-Altman plot was constructed to visualize how the differences between observers compared across the range of measurements. Logistic regression was used to identify predictors of ≥10% variation between observers' readings. RESULTS: There was a significant linear relationship between observers' readings r = 0.98 (P = 0.001). The ICC between observers (interobserver agreement) was also excellent at 0.991 (P = 0.001). Using the Bland-Altman technique, the mean difference between the observers' readings was 0.2 mmHg (95% CI: -1.2 mmHg to 1.6 mmHg). Thirteen per cent of all readings and 9% of readings with an HVPG of ≥10 mmHg differed by ≥10%. As expected, a lower baseline HVPG was a predictor of this variability. CONCLUSIONS: Interobserver reproducibility in the assessment of optimally acquired HVPG tracings is excellent without differences related to experience. The data provide further support that the HVPG can be used accurately in clinical and research settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".