Test–Retest Reliability and Consistency of HVPG and Impact on Trial Design: A Study in 289 Patients from 20 Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND AND AIMS: Portal hypertension (PH) is a major driver for cirrhosis complications. Portal pressure is estimated in practice by the HVPG. The assessment of HVPG changes has been used for drug development in PH. This study aimed at quantifying the test-retest reliability and consistency of HVPG in the specific context of randomized controlled trials (RCTs) for the treatment of PH in cirrhosis and its impact on power calculations for trial design. APPROACH AND RESULTS: We conducted a search of published RCTs in patients with cirrhosis reporting individual patient-level data of HVPG at baseline and after an intervention, which included a placebo or an untreated control arm. Baseline and follow-up HVPGs in the control groups were extracted after digitizing the plots. We assessed reliability and consistency and the potential impact of study characteristics. We retrieved a total of 289 before and after HVPG measurements in the placebo/untreated groups from 20 RCTs. The time span between the two HVPG measurements ranged between 20 minutes and 730 days. Pre-/post-HVPG variability was lower in studies including only compensated patients; therefore, modeled sample size calculations for trials in compensated cirrhosis were lower than for decompensated cirrhosis. A higher proportion of alcohol-associated cirrhosis and unicentric trials was associated with lower differences between baseline and follow-up measurements. The smallest detectable difference in an individual was 26% and 30% in compensated and decompensated patients, respectively. CONCLUSIONS: The test-retest reliability of HVPG is overall excellent. Within-individual variance was higher in studies including higher proportions of decompensated patients. These findings should be taken into account when performing power analysis for trials based on the effects on HVPG or when considering HVPG as a tool to guide therapy of PH.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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".