Human Use Condition Study- Evaluation of Implanted Leads in Humans: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Human Use Condition Study- Evaluation of Implanted Leads in Humans (NCT04320849), a registered phase not stated study. The primary outcome is Number of Participants With in Vivo Cyclic Mean Curvature of Pacing and Defibrillation Leads in the Extravenous Region Determined During Specified Arm Movements.

2. Clinical Question

The question concerns device movement and shape inside the body, rather than whether a therapy changes a clinical disease outcome. The primary measure is framed as a count of participants, and its timeframe is approximately 1 month. The registry record does not report the observed count, the curvature measurements, or a numerical evaluation of the stiffness-curvature relationship. It also does not report a separate primary comparison between the listed lead models. Accordingly, the record defines a measurement objective but does not provide enough outcome information to estimate the magnitude or precision of any observed pattern.

3. Trial Design

This is a completed human-use condition study sponsored by Duke University. The registry record identifies Pacemaker Malfunction as the condition and gives the study title as an evaluation of implanted leads in humans. The stated purpose is to understand how the shape and motion of previously implanted pacemaker leads change in the body. The study began on 2021-06-01, and primary completion is recorded as 2022-04-30. Enrollment is listed as 117.

The described approach uses fluoroscopic evaluation of the three-dimensional curvature of implanted right ventricular leads. The primary measure concerns cyclic mean curvature in the extravenous region during specified arm movements. The description also refers to dynamic curvature in extravenous and intracardiac anatomy and to evaluating the relationship between lead stiffness and curvature. The primary outcome timeframe is approximately 1 month.

The record identifies an arm of patients with protocol identified right ventricular leads and lists several pacing and defibrillation lead types. It does not describe a treatment assignment or an allocation method. A randomized comparison is not identified, and the listed lead groups should not be interpreted as equivalent randomized arms or as a controlled comparison. The registry record does not report a protocol-defined comparator, a control group, or a statistical plan for comparisons among models.

The primary outcome population is described as consented patients with imaging data. That description does not establish that all enrolled participants had usable imaging or contributed to the endpoint. The number included in the primary analysis, reasons for any exclusions, and handling of incomplete imaging are not reported in the registry record. The completed status indicates the registry’s study status, but by itself does not indicate that primary results were posted or that every planned analysis was completed.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Consented patients with imaging data.

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 Number of Participants With in Vivo Cyclic Mean Curvature of Pacing and Defibrillation Leads in the Extravenous Region Determined During Specified Arm Movements, measured over Approximately 1 month.

The primary endpoint is the number of participants with in vivo cyclic mean curvature of pacing and defibrillation leads in the extravenous region determined during specified arm movements. The unit is participants, and the measure is designated as a count of participants with an event. The endpoint description places the observation in the context of lead movement in the body rather than a static measurement alone. It also states that lead stiffness and curvature will be evaluated in relation to one another.

As a general measurement principle, a participant-count endpoint can describe how many people meet a defined criterion, while a continuous curvature measurement can describe the size or distribution of curvature values. Those are different summaries: the count depends on the criterion used to classify a participant, whereas continuous measurements retain information about magnitude. The registry record does not report a threshold or detailed event definition for determining which participants count as having the endpoint. It also does not provide the resulting count or the underlying curvature values.

The endpoint is used to address the study’s stated measurement objective: characterizing dynamic lead curvature during specified movements. Its relevance is therefore descriptive and device-focused in the registry record. No claim about clinical benefit, device failure, or patient outcome follows from the endpoint definition alone. Without the observed result and a clear account of the analysis population, the size and precision of the measured pattern cannot be assessed.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

How should a participant-count endpoint be understood?

General: A binary endpoint classifies each participant according to whether a defined event or criterion is present. A count then totals the participants who meet that definition. To interpret the count, readers need the definition of the event and the number of participants whose data were evaluated. The count alone does not show the proportion of the analysis population meeting the criterion, and this summary must not derive one when the underlying analysis denominator and result are absent.

In this study, the primary measure is described as the number of participants with in vivo cyclic mean curvature in the extravenous region determined during specified arm movements. The endpoint is designated as a participant count. However, the registry record does not report the operational rule for classifying a participant as having the endpoint, the observed count, or the number analyzed. It also does not provide the individual curvature values. The endpoint definition and its result are therefore distinct pieces of information, and the record contains the former without reporting the latter.

What would an estimate of precision tell readers?

General: Statistical precision concerns how much uncertainty surrounds an estimate. A confidence interval is one way to express that uncertainty: it presents a range of estimates compatible with the data and the method’s assumptions. A narrow interval indicates greater precision than a wide interval, but neither width nor interval location establishes that a design is unbiased or that a measurement is clinically important. For a participant-count outcome, interpretation also depends on the event definition and analysis denominator.

No confidence interval or other uncertainty estimate for the primary outcome is reported in the registry record. No primary outcome test statistic or significance result is reported either. It is consequently not possible to assess whether the posted data would support a precise estimate, whether a model comparison was conducted, or how sensitive any statistical inference would be to assumptions. The number of analyses listed in the registry is not a description of their methods or results.

How should lead groups be compared?

General: Random assignment can help balance measured and unmeasured participant characteristics between groups, supporting a causal interpretation of group contrasts when other design and analysis conditions are also met. Without randomization, a difference between groups can be associated with group membership while also reflecting other factors. Statistical adjustment can address measured covariates under suitable assumptions, but it cannot automatically eliminate unmeasured confounding.

The registry record does not state an allocation method and does not identify a randomized comparison. It lists protocol identified lead types but does not provide a like-for-like control comparison or a statistical model for comparing them. Therefore, no causal contrast between lead models can be inferred from the description alone. The record also does not report covariates, adjustment procedures, or model estimates. The stated objective of evaluating stiffness in relation to curvature is an analysis aim, not evidence that a statistical association was found.

What do the planning assumptions represent?

General: A sample-size calculation is a design tool. It estimates the number of participants that would be needed under specified assumptions about the target effect, variability, significance level, allocation, and analysis method. A planning calculation is not a measure of the observed study’s power after results are known. A calculation built around an observed effect is especially dependent on how that effect was estimated; it does not establish that the original trial was designed around that effect.

The planning assumptions stated for this record describe a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect defined as a stated fraction of the observed effect. The stated approach distinguishes participants per arm for non-time-to-event outcomes from total events for time-to-event calculations. The primary outcome is a participant count, not a time-to-event measure. The registry record does not report its own sample-size justification, and the observed primary effect needed to understand an effect-based planning illustration is not reported in the registry record. Any such planning output should therefore be treated as a hypothetical design illustration, not as an observed trial result or observed power.

Why can over-dispersion matter?

General: For count data, a statistical model may assume a particular relationship between the average count and its variability. Over-dispersion means the observed variation is greater than the model’s assumption allows. If it is ignored, standard errors can be too small and confidence intervals can be too narrow, making the evidence appear more precise than it is. Whether over-dispersion is relevant depends on the endpoint structure and analysis model; it is not a feature that can be diagnosed from a count description alone.

The primary endpoint is specified as a count of participants meeting an endpoint, rather than a reported total of repeated events. The registry record does not provide the data distribution, model, or diagnostics needed to determine whether over-dispersion was assessed or relevant. No statistical model for the primary measure is reported.

What can be concluded from the registry entries?

The record identifies the measurement objective, population description, timeframe, enrollment, and study status. It does not report the primary result, the analysis denominator, missing-data handling, or detailed statistical methods. The methods that would determine how to estimate and interpret the endpoint therefore cannot be reconstructed from the registry record. Statistical concepts can clarify what information would be needed, but they cannot fill in unreported results or methods.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Consented Patients With RV Pacing Leads and Defibr")
n      <- c(109)
events <- c(109)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Consented Patients With RV Pacing Leads and Defibr  109  109  100.0  96.7  100.0  96.6  100.0  96.7  100.0

11. Multiplicity, Missing Data and Analysis Populations

The registry record lists three outcome measures and three analyses, but does not report how the analyses were defined, which were confirmatory, or whether any adjustment for multiple testing was planned or performed. Multiplicity arises when several outcomes, comparisons, time points, or statistical tests are considered: without an appropriate plan, the chance of at least one apparently notable result can increase. That is a general statistical concern, not evidence that a particular result in this study is misleading. The record does not provide enough information to assess whether multiplicity is relevant to any reported inference.

The primary outcome population is described as consented patients with imaging data. This does not specify the analysis population in operational detail. The registry record does not report the number with available imaging, the number analyzed, the reasons for missing or unusable observations, or how incomplete data were handled. It also does not state whether the analysis included all enrolled participants, only those with complete imaging, or another defined group. Enrollment of 117 should not be treated as the primary endpoint denominator without that information.

Missing-data methods can affect interpretation when participants without evaluable outcomes differ from those with evaluable outcomes. As a general principle, complete-case analysis, imputation, and other methods rely on different assumptions; the method and its assumptions should be stated to judge their implications. No such approach is reported in the registry record. The record also does not describe a prespecified statistical analysis plan, protocol deviations, or sensitivity analyses. These omissions limit assessment of how analysis choices may have affected the endpoint estimate, but they do not establish that data were missing or that a particular method was used.

12. 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.

The registry record lists one group, described as consented patients with right ventricular pacing leads and defibrillation leads. For that group, 117 participants are listed as at risk for serious adverse events and 0 as affected. The record also lists 117 at risk for other adverse events and 0 affected, with 0 deaths. These are the recorded figures for the listed safety categories.

A zero count means no events are recorded in that category in this registry entry. It does not establish that the risk is zero, that every participant was observed for the same duration, or that no event occurred outside the recorded reporting framework. The registry record does not report event definitions, the safety observation window, or the method used to collect adverse events. The primary endpoint timeframe is approximately 1 month, but that does not establish the safety follow-up duration.

The group-level safety figures do not provide a comparison between lead models or a control group. They should therefore be read descriptively, not as a comparative estimate of safety. The zero counts also do not replace the missing primary curvature outcome result.

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

The registry record describes a study designed to observe the curvature and motion of previously implanted right ventricular leads during specified arm movements. It identifies a primary participant-count endpoint and states that lead stiffness and curvature were to be evaluated in relation to one another. Those details explain the study’s measurement focus, but the record does not report the primary endpoint result or the numerical relationship between stiffness and curvature.

Without the observed count, analysis denominator, or precision estimate, the posted information does not show how many participants met the endpoint or how consistently the measurement was estimated. It also does not permit assessment of variation across participants or of differences among listed lead types. The endpoint description does not report a result for each model, and the registry record does not identify a randomized or like-for-like comparison.

The study should not be interpreted as demonstrating that a lead type improves or worsens a clinical outcome. Its stated focus is lead curvature and motion, not a reported comparison of patient outcomes. The registry record does not report an association with pacemaker malfunction, a rate of device failure, or a clinical effect. The listed condition is not itself evidence that the study measured or established a change in that condition.

The safety entries record zero serious adverse events, zero other adverse events, and zero deaths in the reported group. Those entries are informative as registry-reported counts, but without definitions and follow-up details they do not establish absence of all possible harms. Overall, the record offers a study description and selected safety counts, while leaving the central measurement result and important analysis details unreported. Interpretation should remain limited to that distinction.

14. Why This Trial Matters Statistically

This study is statistically interesting because it focuses on a dynamic physical measurement rather than a treatment-versus-control clinical endpoint. Lead curvature during movement can be described as a measurement objective, but drawing conclusions depends on how the measurement is defined, collected, and summarized. The registry record identifies fluoroscopic evaluation and specified arm movements, yet does not provide the observed curvature data or the rule used to classify participants for the primary count. That gap illustrates why an outcome definition is not a substitute for an outcome result.

The distinction between enrollment and the analysis population is also important. The registry lists enrollment of 117 while defining the primary population as consented patients with imaging data. Without an analyzed denominator, readers cannot determine how much of the enrolled group contributes to the primary measure. Clear reporting of evaluability and missing data is essential for interpreting a participant count.

Design also shapes the claims that statistical analysis can support. The record does not report random allocation or a like-for-like control comparison. Lead types may differ in characteristics beyond the features of interest, so a group contrast would need careful design and analysis before being interpreted causally. A stated aim to evaluate stiffness and curvature does not itself establish a relationship between them.

Finally, the record separates a completed study status from available evidence about its primary endpoint. It lists safety counts but not the principal measurement result, precision estimates, or detailed methods. This is a useful reminder that registration information can describe what investigators intended to measure while still leaving readers unable to assess the size, uncertainty, or robustness of the findings.

15. 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.

The central limitation for statistical interpretation is that the registry record does not report the primary outcome result. No participant count meeting the endpoint, analysis denominator, curvature estimate, or precision measure is given. Consequently, the intended measurement cannot be evaluated quantitatively from the record. The endpoint description also does not state the threshold or complete operational definition used to determine whether a participant has the endpoint.

The record identifies consented patients with imaging data as the endpoint population, but does not say how many had usable imaging or how missing or unusable data were handled. Enrollment of 117 therefore cannot be assumed to equal the analysis population. Without details on exclusions and completeness, the possibility of selection effects cannot be assessed.

The study description does not state an allocation method and does not provide a randomized or like-for-like control comparison. Any comparison across lead types would need to account for differences between the groups, but the registry record does not report comparative estimates, covariate adjustment, or a model. It also does not report the numerical result of the intended stiffness-curvature evaluation.

Further limitations include the absence of a reported statistical analysis plan, multiplicity approach, and detailed outcome-analysis methods. The safety entries lack reported event definitions and observation duration. The registry record lists three outcome measures and three analyses, but does not provide their detailed findings. These limitations concern what can be assessed from the record; they do not establish that particular procedures were omitted or that any specific bias occurred.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Human Use Condition Study- Evaluation of Implanted Leads in Humans — NCT04320849.
• Registry record last updated 2024-01-19; status last verified 2024-01.
• Results first posted 2024-01-19.
• 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.

19. Record Summary

NCT04320849 is a completed study sponsored by Duke University, with enrollment listed as 117. The study evaluates the in vivo curvature and movement of previously implanted right ventricular pacing and defibrillation leads using fluoroscopic assessment during specified arm movements. The primary endpoint is a participant count for cyclic mean curvature in the extravenous region, with a timeframe of approximately 1 month. The primary population is described as consented patients with imaging data.

The registry record does not report the primary endpoint result, its analysis denominator, precision estimates, or detailed statistical methods. It does not identify randomized allocation or a like-for-like control comparison. The safety record lists 0 serious adverse events, 0 other adverse events, and 0 deaths among 117 participants at risk in the reported group. These safety counts do not substitute for the unreported primary measurement result.