MultiPoint Pacing IDE Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for MultiPoint Pacing IDE Study (NCT01786993), a randomized phase 3 study. The primary outcome is Percentage of Non-responders With MPP Compared to Biventricular Pacing.

2. Clinical Question

The CCS classified a participant as worsened, improved, or unchanged according to clinical events and changes in New York Heart Association (NYHA) class or patient global assessment (PGA). For participants who were responders at the 3-month visit, those classified as improved or unchanged between 3 and 9 months remained responders; those classified as worsened were counted as non-responders. The endpoint therefore focuses on change over this follow-up interval among those who had already responded at the earlier visit, rather than simply describing response at a single visit for everyone enrolled.

3. Trial Design

The MultiPoint Pacing IDE Study was a phase 3, randomized, double-blind, parallel-group clinical study. The registry describes it as prospective and multicenter, with a maximum of 50 investigational centers located in the United States. Its listed enrollment is 506; the study summary describes a maximum of 506 participants implanted with a quadripolar cardiac resynchronization therapy device system. The registry lists Abbott Medical Devices as sponsor and the study status as completed.

Participants were assigned to the MultiPoint Pacing arm or the Biventricular arm. The intervention names are MultiPoint Pacing and Traditional Biventricular Pacing, respectively. The record lists 201 participants in the MPP outcome group and 180 in the biventricular outcome group for the reported primary measure. These are the outcome denominators recorded for that comparison; they should not be interpreted as a statement about why they differ from the overall enrollment.

The primary outcome timeframe is 3 months to 9 months. The outcome was the percentage of patients classified as non-responders using the Clinical Composite Score. The registry describes the study objective as evaluating safety and efficacy at 9 months, but the primary outcome analyzed specifically concerns non-response over the interval after the 3-month assessment.

The record does not report the randomization procedure, allocation concealment details, the exact implementation of blinding, or the number of centers that enrolled participants. The original sample-size justification, the trial’s planned analysis details beyond the posted sponsor analysis, and any interim-analysis plan are not reported in the registry record. Those omissions limit what can be concluded about the trial’s design rationale and operational conduct from the registry information alone.

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.

Before assignment: 455 out of 469 subjects with an attempted implant (97% success rate) received Quadripolar BiV pacing between implant and 3 months. At 3 months, responder status was assessed per Clincial Composite Score and 1:1 randomziation was stratified by responder status. 381 patients were randomized to either BiV (n = 180) or MPP (n = 201) at 3 months.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Of 469 subjects who underwent an attempted implant, 31 subjects experienced a system-related complication between implant and 9 months (13 were LV lead-related, 16 were RA/RV lead-related and 3 were Quadripolar CRT-D pulse generator related. One subject experienced more than one category of complication).

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.

Population: A total of 381 subjects were randomized at 3 months, of whom 180 were in the BiV arm and 201 were in the MPP arm.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Non-responders With MPP Compared to Biventricular Pacing, measured over 3 months to 9 months.

The primary endpoint is the percentage of patients classified as non-responders with MPP compared with biventricular pacing between 3 months and 9 months. It uses the Clinical Composite Score, which classifies clinical status as worsened, improved, or unchanged. The registry’s description of worsening includes cardiovascular death, a heart-failure event, worsening in NYHA class, or worsening in PGA score compared with the last observation. Improvement requires survival without a heart-failure event and improvement in NYHA class, PGA score, or both. A patient who is neither improved nor worsened is classified as unchanged.

The endpoint applies a specific rule to participants who were responders at the 3-month visit: improved and unchanged status over the next interval counts as continued response, while worsened status counts as non-response. This makes the endpoint a measure of deterioration among earlier responders, rather than a general measure of all clinical outcomes or of the full course of heart failure.

Such a composite can capture several kinds of clinical change in one outcome. As a general statistical consideration, a composite endpoint can be easier to summarize than multiple separate outcomes, but its components may differ in clinical importance and frequency. The registry does not report component-specific primary endpoint results, so the overall non-response percentage cannot show which elements of the CCS contributed to the classifications.

7. Results Posted in the Registry

• Biventricular Arm: 25.0% (45/180) versus 29.9% (60/201) on control; risk difference -4.9 percentage points (95% CI -13.8 to 4.1), risk ratio 0.84 (0.60–1.17); unadjusted two-proportion z-test p = 0.290.

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the primary comparison as a difference of proportions and describes the sponsor’s method as a normal approximation for a binomial distribution. This is a comparison of the proportions classified as non-responders in two randomized groups. The reported effect estimate is -0.049. In plain terms, the estimate expresses the MPP proportion minus the biventricular proportion; a negative value indicates a lower observed proportion in the first group. The registry’s displayed percentages are 29.9% and 25.0%.

What does a difference of proportions measure?

For a binary outcome such as non-response, each participant is classified in one of two categories for the analysis: the event occurred or it did not. A proportion describes the share of a group with the event. A difference of proportions compares those shares by subtraction. General explanation: the estimate gives the observed contrast, while a confidence interval describes a range of values compatible with the data and the specified method. The interval does not remove uncertainty, and its interpretation depends on the analysis assumptions.

The registry’s sponsor result gives a 97.5% confidence interval with a lower bound of -0.138; the upper bound is not reported in the registry record. The separate unadjusted recalculation reports an interval from -0.138 to 0.041. It also reports an unadjusted p-value of 0.29. The sponsor analysis reports p = 0.013. Since the results differ, they must be kept distinct rather than blended into one inference. The sponsor’s own analysis takes precedence for the trial’s reported non-inferiority result.

How does non-inferiority differ from testing for a difference?

General explanation: a conventional difference test asks whether the data are inconsistent with no difference in either direction. A non-inferiority test instead asks whether the data rule out an unacceptable loss relative to a prespecified margin. The margin defines how much worse the intervention could be and still meet the criterion. A non-inferiority test therefore needs a stated margin and a confidence-interval rule. The registry identifies the sponsor analysis as non-inferiority or equivalence and describes the hypothesis as MPP not being inferior in non-response rate, but the margin and full interval are not reported in the registry record. Without those details, the p-value alone does not establish how the test was conducted or whether the criterion was satisfied.

The endpoint’s direction also matters. Here the event is non-response, so a larger proportion is less favorable on this particular measure. The sponsor estimate is negative, indicating a lower observed non-response proportion for MPP than for biventricular pacing. Still, estimating direction is not the same as establishing a clinically meaningful benefit or meeting a non-inferiority rule. The registry does not provide a clinical threshold for interpreting the size of this contrast.

Why can a recalculation differ from the sponsor result?

The recalculation is a simple unadjusted analysis of posted summary statistics. It does not reproduce a sponsor analysis if that analysis used a different inferential framework, analysis population, or other choices. The record does not report enough detail to identify the reason for the difference. It would therefore be inappropriate to attribute the discrepancy to a particular method or data-handling decision. The recalculated p-value and interval are useful as a distinct check on the posted group summaries, not as a replacement for the sponsor’s trial analysis.

General explanation: a normal approximation can be used to estimate uncertainty for a difference between binomial proportions. It treats the sampling distribution of the estimate as approximately normal. The adequacy of that approximation depends on the data and implementation; the registry names the method but does not report further diagnostic details. The methods used to define the sponsor confidence interval beyond the stated method are not reported in the registry record.

What do p-values and intervals contribute?

General explanation: a p-value assesses how compatible the observed data are with a specified null hypothesis under the analysis model. It is not the probability that the null hypothesis is true, and it does not quantify the probability that the observed difference will recur. A confidence interval communicates uncertainty about the effect estimate on its original scale. A wide interval signals less precision than a narrow interval, and an interval’s relationship to the relevant null or non-inferiority margin affects the interpretation. Because the sponsor’s upper confidence bound and the margin are absent, the posted sponsor statistics are incomplete for independently evaluating the non-inferiority criterion.

The registry does not report adjustments for baseline variables, missing-outcome methods, a per-protocol population, an intention-to-treat population, or multiplicity handling. These details can be important in a non-inferiority study because analysis populations and missing outcomes may affect the estimated contrast. Their absence should be treated as uncertainty about the reporting record, not as evidence that a particular approach was or was not used.

10. Confidence Intervals and Precision

The sponsor-reported estimate is -0.049, with a 97.5% confidence interval whose lower bound is -0.138; an upper bound is not reported in the registry record. The record also reports p = 0.013 for the sponsor’s non-inferiority or equivalence analysis. Without the upper bound and the non-inferiority margin, the interval information is incomplete for judging the sponsor’s stated criterion.

The unadjusted recalculation gives an estimate of -0.049 and a confidence interval from -0.138 to 0.041. This interval spans values on both sides of the null value. It is therefore compatible with a lower non-response proportion in the MPP group, little or no difference, or a higher proportion, under that recalculation. The unadjusted p-value is 0.29. This is not the sponsor’s test result, and the discrepancy means the two results should not be treated as if they were the same analysis.

General explanation: a confidence interval is a measure of statistical precision, not a guarantee that the true effect lies within the particular interval. Its width reflects sampling variability and the method used. Precision is distinct from clinical importance: even a precisely estimated difference would need interpretation in light of clinical context, while an imprecise estimate can leave materially different possibilities open.

The observed group percentages are based on the outcome denominators recorded as 201 and 180. The record does not report additional information needed to assess precision across subgroups or across individual CCS components. The incomplete sponsor interval and absent non-inferiority margin are especially important limits on interpreting the stated sponsor analysis.

11. 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 planning figures are participants per arm, not total event counts. They are illustrations based on the observed effect, not the trial’s original design assumptions. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The original sample-size assumptions and justification for the trial are not reported in the registry record.

Planning for 100% of the observed effect gives 1,327 participants per arm for 80% power and 1,776 participants per arm for 90% power. Planning for 75% of the observed effect gives 2,392 participants per arm for 80% power and 3,202 participants per arm for 90% power. Planning for 50% of the observed effect gives 5,453 participants per arm for 80% power and 7,299 participants per arm for 90% power.

In plain language, the 80% power column gives the planned participants per arm under the stated assumptions for a design with an 80% chance of detecting the specified effect if that effect is real and the assumptions hold. The 90% column applies the corresponding 90% target. These are design-planning quantities, not descriptions of what happened in the trial. Smaller effects require more participants under these assumptions, which is why the participant requirements rise as the planning effect is reduced from the observed effect.

This is not observed power. The figures do not establish that the completed trial had a particular probability of detecting an effect, and they do not replace the sponsor’s non-inferiority analysis. They are illustrations using the observed effect and the stated planning framework.

12. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.299; treatment proportion p₁ = 0.250; average p̄ = 0.274.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6309 = 1.2366.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6300 = 0.5302.
4. n = (1.2366 + 0.5302)² / (-0.0485)² = 1,326.7, rounded up to 1,327 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
p0 <- 0.298507462686567                          # control proportion
p1 <- 0.25                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1786993)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,327 (80% power), 1,776 (90% power)
 75% of observed effect: n per arm = 2,392 (80% power), 3,202 (90% power)
 50% of observed effect: n per arm = 5,453 (80% power), 7,299 (90% power)
power.prop.test: 1326.7 
Simulated power at n = 1,327 per arm: 0.800 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

13. Analyses Reported by the Sponsor

The registry’s sponsor analysis is identified as a non-inferiority or equivalence analysis using a normal approximation for a binomial distribution. It reports a difference of proportions of -0.049, a 97.5% confidence interval with lower bound -0.138, and p = 0.013. The upper confidence bound and the non-inferiority margin are not reported in the registry record.

The separate recalculation uses the posted group summary statistics to produce a simple unadjusted comparison. It reports the same displayed effect estimate of -0.049, but its confidence interval extends from -0.138 to 0.041 and its unadjusted p-value is 0.29. Those results are not consistent with the sponsor-reported inferential result. The recalculation is not a reconstruction of the sponsor’s full analysis, and the registry record does not report enough detail to explain the difference.

Because the discrepancy is present, the sponsor’s own analysis takes precedence when describing the trial’s reported analysis. That does not remove the need for caution: the record omits the margin and the sponsor interval’s upper limit, both needed to assess the non-inferiority result fully. The recalculation is best treated as a separate, unadjusted check of the posted proportions, not as a substitute for the sponsor analysis or as evidence that the sponsor result is wrong.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists two outcome measures and two analyses, but no secondary results are posted. It does not report whether the study used a multiplicity adjustment, how any primary and secondary outcomes were prioritized, or whether any additional comparisons were prespecified. The multiplicity plan is not reported in the registry record. Without that information, the impact of testing multiple outcomes or analyses cannot be evaluated from the posted record.

The primary analysis concerns a non-inferiority question, for which the prespecified margin and analysis population are important. The margin is not reported in the registry record. The record also does not identify whether the sponsor’s primary analysis used an intention-to-treat population, a per-protocol population, or another analysis set. These population definitions can matter in non-inferiority settings, but no particular choice can be inferred from the posted results.

Missing-outcome handling is also not described. The registry does not report the amount or pattern of missing primary outcome data, how missing CCS classifications were handled, or whether sensitivity analyses were conducted. It does not report an interim-analysis plan or any stopping rule. These omissions do not show that missing data or interim monitoring occurred; they mean the relevant details are not reported in the registry record.

General explanation: multiplicity arises when several statistical tests are conducted, because repeated testing can increase the chance of at least one apparently positive result. Missing outcomes can affect an estimate if the participants whose outcomes are unavailable differ systematically from those observed. Analysis-population choices can also influence a non-inferiority comparison. These are reasons the details matter, not claims about what happened in this study.

The record’s stated randomized, double-blind design does not fill these reporting gaps. The exact randomization and blinding procedures, allocation concealment, and methods for preserving blinding are not reported in the registry record. Consequently, the available entry supports a description of the broad design and the posted primary result, but not a full audit of the statistical analysis plan or its implementation.

15. Safety Results

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

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

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: lv lead dislodgement or migration (1.7%), ra/rv lead dislodgement or migration (0.5%), pulse generator erosion/extrusion (0.5%), generator malfunction (0.5%).

The registry reports serious adverse events in 4 participants in the MPP arm, with 201 at risk, and in 3 participants in the biventricular arm, with 180 at risk. Other adverse events are recorded for 40 participants in the MPP arm and 5 participants in the biventricular arm, using the same respective at-risk groups. These are separate event categories as labeled in the record; they should not be combined or interpreted as a comparative risk estimate without further details about definitions and collection.

The serious adverse-event terms listed most often are LV Lead Dislodgement or Migration at 1.7%, RA/RV Lead Dislodgement or Migration at 0.5%, Pulse Generator Erosion/Extrusion at 0.5%, and Generator Malfunction at 0.5%. The registry does not provide the event counts or denominators underlying each listed term in this summary, so these percentages should be read as reported rather than recalculated.

Deaths are not reported in the registry record. The serious adverse-event figures describe the posted safety counts, not a complete characterization of risk. The record does not provide event timing, severity beyond the serious-event classification, causal attribution, or details about how multiple events in the same participant were handled. These limitations prevent a more detailed safety comparison from the registry entry alone.

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

The posted primary outcome describes non-response according to the Clinical Composite Score between 3 months and 9 months. Non-response was recorded in 29.9% of the MPP arm and 25.0% of the biventricular arm. The sponsor’s analysis is identified as a non-inferiority or equivalence analysis and reports p = 0.013, but the registry does not report the non-inferiority margin or the complete confidence interval. Those missing details prevent a reader from independently verifying the non-inferiority criterion from the registry record.

The simple unadjusted recalculation gives a confidence interval from -0.138 to 0.041 and p = 0.29. Because the sponsor result and recalculation differ, they should not be combined into a single conclusion. The sponsor’s own analysis takes precedence for describing the study’s reported result, while the recalculation illustrates that a different, unadjusted comparison produces a different inferential result.

Neither result establishes that the treatments are identical. A non-significant result in a conventional difference test would not prove equivalence, and a non-inferiority finding requires a defined margin and a suitable analysis. The posted record lacks the margin and upper confidence bound needed to assess that claim fully. Statistical uncertainty should therefore be distinguished from a definitive statement about similarity or clinical value.

The endpoint is a composite classification, not a direct measure of every relevant aspect of heart failure or device performance. The record does not report the separate contributions of cardiovascular death, heart-failure events, NYHA changes, or PGA changes to the primary outcome. No secondary outcome results are posted. The outcome also focuses on participants who were responders at the 3-month visit when assigning continued response or non-response, so it should not be generalized to all possible follow-up definitions.

The registry results do not establish effects beyond the stated interval or for populations not represented by the enrolled study group. They also do not replace a broader assessment of safety: the listed adverse-event counts are limited registry summaries, and deaths are not reported in the registry record. Interpretation should remain tied to the outcomes, time window, and analysis details actually documented.

17. Why This Trial Matters Statistically

This study is statistically interesting because the primary question is framed as non-inferiority rather than a conventional search for any difference. Those questions require different interpretation. A non-inferiority conclusion depends on a prespecified margin and a confidence interval judged against that margin, yet the margin and the full sponsor interval are not reported in the registry record. The missing information limits independent assessment of the central claim.

The record also makes visible an important distinction between the sponsor’s reported analysis and a simple unadjusted recalculation. The sponsor reports a non-inferiority or equivalence analysis with p = 0.013, while the unadjusted recalculation reports p = 0.29 and an interval that includes the null value. The sponsor’s own analysis takes precedence, but the discrepancy shows why analysis details matter: estimates can be interpreted differently when the inferential question or method differs. The registry does not explain the discrepancy, so its cause should not be assumed.

The primary outcome itself illustrates the interpretive trade-offs of a composite. The CCS combines events and changes in functional class or patient assessment into improved, unchanged, and worsened categories. This creates a single outcome for the reported comparison, but the registry does not show how much each component contributed. A summary percentage can therefore conceal different clinical pathways to the same classification.

Finally, the record separates the primary outcome from limited safety summaries and does not post secondary results. This makes the scope of inference important: the main comparison addresses a particular non-response definition and interval, rather than every possible measure of treatment performance. Statistical interpretation is strongest when the endpoint definition, analysis framework, and reporting gaps are kept in view together.

18. 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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record does not report the non-inferiority margin or the sponsor analysis’s upper confidence bound. These are central details for evaluating the stated non-inferiority question. Although the sponsor analysis reports a p-value and lower confidence bound, the available information is insufficient to reconstruct the full decision rule or independently assess its conclusion.

The reported sponsor result differs from the simple unadjusted recalculation. The reason is not reported in the registry record. Details about analysis populations, missing outcome handling, baseline adjustment, and sensitivity analyses are also absent, so the difference cannot be attributed to a particular choice. The recalculation should not be treated as a replacement for the sponsor analysis.

The primary endpoint is a composite CCS classification. Component-specific results are not reported, limiting interpretation of which kinds of clinical change account for the overall non-response percentages. The endpoint’s rule is also specific to participants who were responders at the 3-month visit, which narrows what the outcome represents. No secondary results are posted despite the record listing two outcome measures and two analyses.

The registry does not report the original sample-size justification, randomization procedure, allocation concealment, detailed blinding procedures, interim-analysis plan, or multiplicity plan. Missing-outcome counts and methods are not reported. These omissions limit assessment of design rationale and analysis conduct, but they do not establish that any particular method or problem was present.

The safety entry is also limited: event timing, causal attribution, and details on how repeated events were counted are not reported, and deaths are not reported in the registry record. The listed groups and adverse-event terms provide a narrow summary rather than a full assessment of safety. The study’s stated follow-up for the primary outcome is 3 months to 9 months; longer-term results are not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: MultiPoint Pacing IDE Study — NCT01786993.
• Registry record last updated 2019-02-04; status last verified 2019-01.
• Results first posted 2016-09-30.
• 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.

22. Record Summary

The MultiPoint Pacing IDE Study is listed as a completed, phase 3, randomized, double-blind, parallel-group study sponsored by Abbott Medical Devices. It compared MultiPoint Pacing with traditional biventricular pacing in people with heart failure. The registry lists enrollment as 506 and describes a maximum of 506 implanted participants. The study start is listed as 2013-04 and primary completion as 2015-04.

The primary outcome was the percentage of non-responders based on the Clinical Composite Score between 3 months and 9 months. The posted group percentages are 29.9% for MPP and 25.0% for biventricular pacing. The sponsor reports a non-inferiority or equivalence analysis; the margin and complete confidence interval are not reported in the registry record. A simple unadjusted recalculation differs from the sponsor result, so the sponsor’s own analysis takes precedence when describing the reported trial analysis.

Serious and other adverse-event counts are reported by group, but the safety details are limited. Secondary results are not posted. The record supports a focused account of the primary endpoint and the reported analysis, while important design, analysis, and safety details remain unreported in the registry record.