Comparison of Two Pericardial Bioprostheses in AVR: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of Two Pericardial Bioprostheses in AVR (NCT03796442), a randomized na study. The primary outcome is Transvalvular Mean Pressure Gradient (mPG).

2. Clinical Question

The primary endpoint is a continuous measurement of pressure gradient across the implanted valve. The posted group means are 14.1 mmHg for AVALUS and 13.9 mmHg for CEPME. The registry also reports a sponsor analysis labelled non-inferiority, with a one-sided t-test p-value of < 0.001. That reported test addresses a different inferential question from a simple test of whether the two group means differ; its interpretation depends on the non-inferiority margin and analysis details, which are not reported in the registry record.

The question is therefore not whether either valve is universally preferable. It is how the reported hemodynamic measurements compare at the specified follow-up and what can be concluded from the available statistical summaries. The registry also lists clinical outcomes, including mortality and valve-related events, but the posted numeric results do not cover every listed secondary outcome. The evidence should be read as a record of this randomized comparison, rather than as a complete account of all possible outcomes or longer-term performance.

3. Trial Design

The registry describes a multicenter, randomized controlled trial with parallel groups and no masking. Participants underwent aortic valve replacement using either the Avalus bioprosthesis or the Carpentier-Edwards Perimount Magna Ease bioprosthesis. The registry lists the study as completed and records enrollment of 140. The recorded study start was 2019-01-23, and primary completion was 2021-05-13. The sponsor was Seoul National University Hospital.

The primary outcome was the transvalvular mean pressure gradient measured by transthoracic echocardiography at postoperative 1 year. It is reported as a mean with standard deviation. The outcome summaries list 66 participants in the AVALUS group and 63 in the CEPME group. These outcome denominators differ from the safety denominators, which are reported separately in the adverse-event data. The registry record does not explain the relationship between those denominators, so they should not be treated as interchangeable.

The registry lists six secondary outcomes, including effective orifice area, operative mortality and morbidities, all-cause mortality, cardiac death, and aortic valve-related events. Numeric summaries are posted for effective orifice area, all-cause mortality, and cardiac death. The registry record does not report numeric results for the other listed secondary outcomes in the information available for this analysis.

The registry record does not report the planned sample-size assumptions, the non-inferiority margin, the detailed randomization procedure, or the original statistical analysis plan. It also does not report the analysis populations, handling of missing observations, or whether interim analyses were planned or conducted. Those omissions limit assessment of how closely the reported analyses followed the original design.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Transvalvular Mean Pressure Gradient (mPG), measured over at postoperative 1 year.

The primary endpoint is transvalvular mean pressure gradient (mPG), in mmHg, at postoperative 1 year. It is measured by transthoracic echocardiography and summarized as a group mean with a standard deviation. The gradient describes the pressure difference across the replacement valve during blood flow. As a continuous hemodynamic measure, it provides a way to compare valve performance between randomized groups at a specified follow-up time.

Using a continuous endpoint retains information about the measured values rather than reducing them to a yes-or-no category. The group means describe the central values, while the standard deviations indicate the amount of variation among observations within each group. Neither the means nor the standard deviations alone establish whether the between-group contrast is clinically important or statistically conclusive.

The endpoint is measured after surgery, at the registry’s stated postoperative 1-year time point. It therefore represents performance at that follow-up, not a description of all early postoperative measurements or longer-term outcomes. The registry record does not report a threshold for clinical importance or the non-inferiority margin used in the sponsor’s analysis. Without those details, a reader can describe the observed contrast and its uncertainty but cannot reconstruct the full clinical interpretation of the sponsor’s non-inferiority conclusion.

7. Results Posted in the Registry

• CEPME Group: mean 13.90 versus 14.10 on control; difference -0.20 (95% CI -1.83 to 1.43), standardized effect d = -0.04; z-test p = 0.810.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Effective Orifice Area (EOA)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • CEPME Group: mean 1.53 versus 1.48 on control; difference 0.05 (95% CI -0.08 to 0.18), standardized effect d = 0.13; z-test p = 0.461.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between CEPME Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With All-cause Mortality

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • CEPME Group: 8.6% (6/70) versus 1.4% (1/70) on control; risk difference 7.1 percentage points (95% CI 0.0 to 14.3), risk ratio 6.00 (0.74–48.55); unadjusted two-proportion z-test p = 0.053.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between CEPME Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Cardiac Death

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • CEPME Group: 2.9% (2/70) versus 1.4% (1/70) on control; risk difference 1.4 percentage points (95% CI -3.4 to 6.2), risk ratio 2.00 (0.19–21.56); unadjusted two-proportion z-test p = 0.559.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between CEPME Group and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results cover a mix of hemodynamic and clinical outcomes. Effective orifice area is a continuous hemodynamic measure, while all-cause mortality and cardiac death are event counts. These outcomes complement the primary pressure-gradient endpoint by describing other aspects of valve performance and clinical follow-up, but they are not interchangeable with the primary outcome.

The available secondary estimates do not form a consistent, conclusive pattern that can be used to settle the primary comparison. The continuous endpoint provides information about valve hemodynamics, and the mortality outcomes concern relatively infrequent events. Their uncertainty, together with the absence of numeric results for several listed secondary outcomes, limits any overall judgment across the full range of outcomes. Numeric findings and their intervals should be considered individually rather than collapsed into a single claim about the trial.

Secondary results generally carry less confirmatory weight when several outcomes are examined without a reported plan to control multiplicity. In general, testing multiple outcomes increases the chance of finding an apparently unusual result even when there is no underlying difference. The registry record does not report whether the trial used a hierarchy, adjustment, or other multiplicity strategy. Consequently, the unadjusted secondary p-values are exploratory signals, not stand-alone proof of an effect.

The secondary outcomes also do not replace the sponsor’s primary non-inferiority analysis. They may help describe the broader outcome profile, but the record does not provide sufficient analysis details to establish how they were incorporated into the trial’s confirmatory conclusions. Results for operative mortality, operative morbidities, and aortic valve-related events are not reported in the registry record for this analysis. Their absence from the posted numeric results should not be interpreted as zero events or as evidence of no difference.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Effective Orifice Area (EOA)
• Number of Participants With Op Mortality
• Number of Participants With Op Morbidities
• Number of Participants With All-cause Mortality
• Number of Participants With Cardiac Death
• Number of Participants With Aortic Valve-related Events

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a continuous variable: a measured pressure gradient summarized by a mean and standard deviation in each group. The recalculated comparison uses the group summaries to express the mean difference as CEPME minus AVALUS. A negative estimate means the CEPME sample mean is lower; it does not, on its own, establish a meaningful or reliable advantage. The recalculated estimate is -0.2 mmHg.

What does a mean difference test address?

In general, a two-group mean comparison asks whether the observed group means are compatible with a specified difference, commonly zero. The unadjusted p-value of 0.81 is not the probability that the groups are equal, nor is it the probability that the result occurred by chance. It describes how compatible the data are with the null model used for that recalculation. A large p-value does not demonstrate that the treatments are equivalent; showing equivalence or non-inferiority requires a defined margin and a test designed for that question.

The registry’s reported primary analysis is a one-sided t-test labelled non-inferiority, with p< 0.001. A one-sided test evaluates evidence in a designated direction, unlike a two-sided test that considers departures on either side. In general, a non-inferiority analysis asks whether the data rule out an unacceptable loss relative to a prespecified margin. The margin, its clinical rationale, the test statistic, and the confidence interval for the reported analysis are not reported in the registry record. The reported p-value therefore cannot be fully interpreted or reproduced from the posted summaries.

What do standard deviations and standard errors describe?

In general, a standard deviation describes variation among individual measurements in a group. A standard error describes uncertainty in an estimated quantity, such as a group mean. They answer different questions: the standard deviation characterizes the spread of observations, while the standard error reflects the precision of an estimate. The primary outcome standard deviations are 4.3 mmHg for AVALUS and 5.1 mmHg for CEPME. The recalculation uses the posted group summaries; it does not adjust for covariates or account for any unreported features of the trial analysis.

General statistical methods rely on assumptions. For a t-test, these include assumptions about the distribution of the outcome and, depending on the test variant, the relationship between group variances. The registry record labels the sponsor test as a one-sided t-test but does not provide enough detail to assess those assumptions or determine whether the sponsor used a pooled-variance or another form of t-test. Randomization supports a causal comparison in principle, but does not resolve questions about missing observations, protocol deviations, or the analysis population.

How should binary outcomes be interpreted?

All-cause mortality and cardiac death are binary outcomes at the participant level: each participant either had the recorded event or did not, within the stated follow-up. The recalculated risk difference compares the observed event proportions between groups, with CEPME minus AVALUS as the direction. The all-cause mortality risk difference is 0.071, and the cardiac-death risk difference is 0.014. These estimates are accompanied by intervals that express uncertainty. The registry does not report adjusted analyses for these outcomes, and the recalculated comparisons should be understood as unadjusted.

For binary outcomes with relatively few events, estimates may be sensitive to the occurrence or absence of a small number of events. In general, confidence intervals for event comparisons can be wide when event counts are limited, and point estimates such as risk ratios or odds ratios can be unstable. The registry also posts relative measures for mortality, but the uncertainty is substantial. Those measures should not be interpreted as reliable evidence of a large underlying effect without considering their intervals and the sparse counts.

General statistical principle: multiple outcomes and repeated comparisons increase the chance that at least one unadjusted result appears notable by chance. The registry lists several secondary outcomes, but a multiplicity adjustment strategy is not reported in the registry record. The secondary p-values therefore have less confirmatory weight than a result from a prespecified, appropriately controlled testing plan. This is particularly important when interpreting findings near conventional significance thresholds.

The recalculated analyses are simple, unadjusted calculations from the posted summary statistics. They are useful for understanding the size and uncertainty of the reported contrasts, but they cannot reproduce analyses that rely on participant-level data, covariate adjustment, stratification, missing-data handling, or a prespecified non-inferiority procedure. Those details are not reported in the registry record. The sponsor’s own reported primary analysis remains the relevant trial analysis, subject to the limitations in its available documentation.

11. Confidence Intervals and Precision

The primary recalculated mean difference is -0.2 mmHg, with a 95% confidence interval from -1.832 to 1.432 mmHg. In general, a confidence interval is a range of values compatible with the data and the assumptions of the method used. It communicates uncertainty about the estimated difference; it is not a range containing a fixed proportion of individual participants’ measurements, and it is not a probability statement about the particular interval after it has been calculated.

For the primary contrast, the interval includes zero and extends to values on both sides of zero. Thus, the posted summaries are compatible with a modestly lower or a modestly higher mean in CEPME relative to AVALUS under the recalculation. The interval is more informative than the point estimate alone because it makes the uncertainty visible. The unadjusted p-value of 0.81 is consistent with the interval’s inclusion of zero, but neither result proves equivalence.

The interval does not address whether every value within it is clinically important, because the registry record does not report a threshold for clinical importance or the sponsor’s non-inferiority margin. It also does not establish how the trial’s own reported non-inferiority analysis behaved: the registry reports its p-value but not its estimate or confidence interval.

For secondary outcomes, the mortality intervals likewise communicate uncertainty and should be read with the observed counts in mind. The all-cause mortality risk-difference interval runs from < 0.001 to 0.143, while the cardiac-death interval runs from -0.034 to 0.062. These are recalculated, unadjusted intervals, not substitutes for a prespecified sponsor analysis. Precision is limited by the available event data, and the registry does not report adjusted estimates or a multiplicity procedure for these comparisons.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size figures are planning illustrations based on the observed effect, not the trial’s original design calculations. For the continuous outcomes and participant-level binary outcomes shown, the figures are participants per arm. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; each scenario targets the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.

The column for 80% power describes the number of participants per arm that a hypothetical future study would plan for to have an 80% chance of detecting the specified effect under those assumptions, if that effect and the model assumptions were correct. The 90% power column makes the analogous planning calculation for a higher chance of detecting that effect, and therefore generally requires more participants. These values are not observed power for the completed trial.

Each row represents a different planning target: the full observed effect, 75% of the observed effect, or 50% of the observed effect. Smaller target effects require more participants because they are harder to distinguish from sampling variation. The illustrations should not be treated as a recommendation for a future trial: a design would need a clinically justified target, a specified analysis, and assumptions relevant to the planned population and outcome. For time-to-event outcomes, the stated convention is total events; the listed outcomes discussed in these calculations are not time-to-event outcomes.

The calculations inherit uncertainty from the observed effect. If the observed estimate is unusually large or small, planning directly from it can produce misleading figures. The displayed values are consequently best read as conditional illustrations of how sample size changes with the target effect, power level, and stated assumptions, rather than as a definitive design justification.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.200; pooled standard deviation σ = 4.708.
2. n = 2 × (1.96 + 0.842)² × 4.708² / -0.200² = 8,697.0, rounded up to 8,698 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.199999999999999                      # observed difference in means
sigma <- 4.70756636728174                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(3796442)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 8,698 (80% power), 11,643 (90% power)
 75% of observed effect: n per arm = 15,462 (80% power), 20,699 (90% power)
 50% of observed effect: n per arm = 34,789 (80% power), 46,572 (90% power)
power.t.test: 8698 
Simulated power at n = 8,698 per arm: 0.794 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary analysis as a one-sided t-test for non-inferiority, with p< 0.001. The independent recalculation instead uses the posted group means and standard deviations to produce a simple unadjusted mean difference, confidence interval, and p-value. These analyses answer different questions and are not interchangeable.

The sponsor’s own analysis takes precedence when describing the trial’s primary inference. The recalculation is supplementary: it gives a transparent summary of the contrast implied by the posted descriptive statistics but does not recreate the sponsor’s full non-inferiority test. The registry record does not report the non-inferiority margin, the sponsor’s effect estimate and interval, or enough methodological detail to verify that test independently.

The recalculated primary contrast is -0.2 mmHg, with a 95% confidence interval from -1.832 to 1.432 mmHg and unadjusted p-value 0.81. It should not be used to overturn or relabel the sponsor’s reported analysis. At the same time, the sponsor p-value alone does not reveal the margin’s clinical meaning or the degree of precision around the estimated contrast. A complete assessment of the non-inferiority conclusion would require those missing details.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple secondary outcomes in addition to the primary endpoint. When several hypotheses are tested, the chance of at least one apparently notable result can increase. In general, a prespecified hierarchy or a statistical adjustment can help control that risk, but these approaches can also affect the interpretation and power of individual comparisons. A multiplicity strategy is not reported in the registry record. The secondary recalculations are therefore unadjusted and should be treated as exploratory rather than as a collection of independent confirmatory findings.

The record identifies one sponsor-reported primary analysis: a one-sided t-test labelled non-inferiority. It does not report whether any interim analyses were planned or conducted, the original statistical analysis plan, or the non-inferiority margin. It also does not provide the sponsor’s estimate and confidence interval for that analysis. These missing details prevent a full assessment of the prespecified testing framework and the extent to which the reported analysis can be independently checked.

Information on missing data and analysis populations is also not reported in the registry record. The primary outcome summaries list 66 participants in AVALUS and 63 in CEPME, whereas the safety summaries list 70 at risk in each group. The record does not explain why these denominators differ, whether observations were unavailable, or how participants were handled in the sponsor analysis. The difference should not be attributed to a particular reason without further information.

In general, missing outcome data can affect estimates if availability is related to group assignment or outcome status. Likewise, an analysis of participants as randomized and an analysis restricted to those with observed outcomes can answer different questions. Because the registry does not describe the analysis populations or missing-data methods, it is not possible to judge these issues from the posted summaries. These limitations matter for interpreting both the primary comparison and the secondary results.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: nonstructural valve dysfunction (4.3%), cardiac deaths (2.9%), thromboembolism (2.9%), prosthetic valve endocarditis (2.9%), permanent pacemaker implantation (2.9%).

The safety summary reports serious adverse events affecting 5 participants in AVALUS and 6 in CEPME, with 70 at risk in each group. Other adverse events are reported as affecting 0 participants in each group. The record also lists deaths as 1 in AVALUS and 6 in CEPME. These are descriptive safety figures; the registry record does not provide an adjusted comparison or enough detail to interpret them as causal effects.

Listed serious-event terms include nonstructural valve dysfunction at 4.3%, cardiac deaths at 2.9%, thromboembolism at 2.9%, prosthetic valve endocarditis at 2.9%, permanent pacemaker implantation at 2.9%, and bleeding event at 1.4%. These percentages describe the registry’s listed terms and should not be added together: event categories may overlap, and the record does not explain the relationship between the term-specific percentages and the participant-level serious-event counts.

The safety denominators differ from those in the primary outcome summaries. The registry record does not explain that difference, nor does it provide detailed event timing or adjudication information. The counts therefore describe the posted safety record but do not, alone, establish comparative risk or explain why events occurred.

17. What the Result Does, and Does Not, Mean

The posted primary summaries show similar sample means at postoperative 1 year, with a recalculated CEPME-minus-AVALUS mean difference of -0.2 mmHg. The confidence interval includes zero and allows for differences in either direction. This describes the estimate and its uncertainty; it does not establish that the devices have identical performance, nor does it demonstrate that a clinically meaningful difference is absent.

The registry’s reported non-inferiority p-value is evidence from the sponsor’s own analysis, but it cannot be fully appraised without the margin, estimate, interval, and fuller method description. The recalculation should not be substituted for that analysis. A non-inferiority conclusion is tied to a prespecified acceptable margin, and a p-value without that context cannot show how the observed result relates to the clinical boundary.

The secondary findings add context but are limited by their unadjusted nature, uncertainty, and incomplete numeric reporting. Mortality counts should not be interpreted as proof of a treatment-caused difference. Similarly, the absence of posted numeric results for some listed secondary outcomes does not mean that no events occurred or that the groups were alike on those outcomes.

The record supports a description of the randomized comparison, the reported endpoint summaries, and the sponsor’s stated test result. It does not establish longer-term outcomes beyond the reported follow-up, explain results for every listed outcome, or provide all information needed to reproduce the primary analysis. The results should be understood within those bounds rather than generalized to every setting, patient, or valve-related outcome.

18. Why This Trial Matters Statistically

This trial illustrates why a result should be read through both its design and its statistical estimand. The primary outcome is a continuous hemodynamic measure, while the sponsor’s stated question is non-inferiority. A simple difference test and a non-inferiority test are not equivalent: the latter depends on a margin that defines how much difference is acceptable for the stated purpose. The registry provides the sponsor’s p-value but not that margin, leaving an important interpretive link undocumented.

It also shows why a point estimate needs its interval. The recalculated primary difference is close to zero, but the confidence interval extends to either side. The data therefore do not support an unqualified claim of equality. Precision and the clinical threshold matter alongside a p-value, particularly when the inferential goal is non-inferiority rather than detection of any difference.

The contrast between outcome denominators also emphasizes the value of transparent analysis populations and missing-data reporting. The primary summaries and safety summaries use different denominators, and the registry record does not explain why. Without that context, readers cannot determine whether the summaries reflect different analysis sets, outcome availability, or other reasons.

Finally, the trial demonstrates the limits of interpreting multiple secondary outcomes without a reported multiplicity plan. Secondary measures can broaden the clinical picture, but unadjusted findings are more appropriately treated as exploratory. Clear reporting of the non-inferiority margin, analysis populations, missing-data methods, and secondary testing strategy would make the reported evidence easier to assess independently.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several trial-specific details needed to interpret the primary non-inferiority result are not reported in the registry record. These include the non-inferiority margin, the clinical rationale for that margin, the sponsor’s effect estimate and confidence interval, and the detailed statistical analysis plan. Although the sponsor reports a one-sided t-test p-value of < 0.001, the available information is insufficient to reconstruct the test or assess how the result compares with the margin.

The posted primary outcome denominators are 66 for AVALUS and 63 for CEPME, whereas safety data report 70 at risk in each group. The registry does not explain the denominator difference or describe the analysis populations and missing-data handling. The randomized design is important, but the available summaries do not establish how all randomized participants were represented in each outcome analysis.

Numeric results are not reported for every listed secondary outcome. The available recalculated comparisons are unadjusted, and the record does not describe control of multiplicity. Estimates for binary outcomes are based on the posted event counts, and the record does not provide detailed adjudication or timing information for those events. The adverse-event terms and serious-event summaries also lack enough detail to assess possible overlap among categories.

The primary endpoint is reported at postoperative 1 year; the available information does not establish performance beyond that follow-up. The registry record also does not report the trial’s original sample-size assumptions, any interim analyses, or full details of outcome assessment and analysis. These limitations restrict independent verification and generalization of the findings.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Comparison of Two Pericardial Bioprostheses in AVR — NCT03796442.
• Registry record last updated 2023-02-08; status last verified 2023-01.
• Results first posted 2023-02-08.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT03796442 is a completed, multicenter, randomized, parallel-group trial comparing Avalus with Carpentier-Edwards Perimount Magna Ease during aortic valve replacement for aortic valve disease. The registry lists enrollment of 140, no masking, and Seoul National University Hospital as sponsor.

The primary outcome is transthoracic echocardiographic transvalvular mean pressure gradient at postoperative 1 year. The registry reports a sponsor non-inferiority analysis with a one-sided t-test p-value of < 0.001. The unadjusted recalculation gives a mean difference of -0.2 mmHg, with a 95% confidence interval from -1.832 to 1.432 mmHg.

Secondary and safety results are available for selected outcomes, but numeric results are not reported for every listed secondary outcome. Important details—including the non-inferiority margin, original design assumptions, analysis populations, and missing-data methods—are not reported in the registry record.