The Effects of Dis/Reconnection of Implant Abutments on Peri-implant Bone Levels: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effects of Dis/Reconnection of Implant Abutments on Peri-implant Bone Levels (NCT04043286), a randomized na study. The primary outcome is Changes in Peri-implant Marginal Bone Level Between Baseline (Implant Placement) and 1 Year Follow up.

2. Clinical Question

The clinical question concerns the relationship between the abutment connection strategy and measured change in bone level around implants. The primary measure was taken on the mesial and distal aspects of implants using standardized digital periapical radiographs. The stated aim also included soft-tissue changes in the posterior maxilla and mandible. The registry lists changes in keratinized mucosa width and lingual mucosa thickness among the secondary outcomes, along with implant success rate according to the 2017 Classification Criteria Set by the American Academy of Periodontology.

The study is described as split-mouth: both approaches are represented within the study, rather than assigning each participant to only one approach. The posted primary outcome gives arm-level results, but the registry record does not report how within-participant pairing was handled in the sponsor's analysis. The clinical question is therefore clear, while some details needed to assess how the reported comparison used the split-mouth structure are not reported in the registry record.

3. Trial Design

The registry describes a randomized, unmasked, split-mouth clinical study of definitive abutment connection and peri-implant outcomes. The official title describes a 1-year study, and the primary endpoint timeframe is baseline at implant placement and 1 year follow-up. The record lists the study model as parallel as well as describing the groups as split-mouth. Those descriptions are both retained in the record; the registry does not explain the relationship between them.

In the test group, definitive abutments were connected to the implants on the day of surgery, with no disconnection or reconnection during the prosthetic phase. In the control group, healing abutments were connected on the day of surgery and were subjected to multiple disconnections and reconnections during the study. The intervention is listed as a device, named “Definitive abutment.” The primary outcome was change in peri-implant marginal bone level, and the registry also lists secondary measures of soft-tissue change and implant success.

The record reports enrollment of 19. The primary outcome results list 17 participants in each group. It does not explain why those counts differ, whether every enrolled participant contributed to each analysis, or how missing measurements were handled. Recruitment began on 2019-09-30, primary completion was 2023-09-18, and the study status is completed. The sponsor is Loma Linda University.

The registry record does not report the trial's original sample-size justification, detailed randomization procedure, allocation concealment, or statistical analysis plan. It also does not report whether there were interim analyses or how the analysis accounted for the split-mouth structure. Those omissions limit assessment of design and analysis choices beyond the registry entries and results posted in the record.

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: 19 participants were initially enrolled. 2 participants withdrew: one moved away during the COVID-19 pandemic, and another agreed to participate and signed the consent form but later withdrew due to being unable to attend the scheduled surgery.

Overall Study

Reasons for not completing this period:

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 Changes in Peri-implant Marginal Bone Level Between Baseline (Implant Placement) and 1 Year Follow up, measured over At baseline (implant placement) and 1 year follow up.

The primary endpoint is change in peri-implant marginal bone level between baseline, defined as implant placement, and the 1-year follow-up. The measure is expressed in millimeters. Standardized digital periapical radiographs were taken at both time points using the long-cone paralleling technique with a custom jig. Measurements were made on the mesial and distal aspects to assess bone loss, and change was calculated by comparing the 1-year measurements with baseline values.

This continuous endpoint describes the magnitude of change rather than simply classifying an implant as having or not having a particular event. A mean can summarize the average change within each group, while the standard deviation describes how dispersed individual measurements are around that mean. The registry reports group means and standard deviations for the outcome.

Measuring at baseline and follow-up makes the endpoint relevant to change over the stated observation period. Standardized imaging and a custom jig are intended to make measurements comparable across the two assessments, as described in the registry. The record does not provide details about assessor masking, measurement reliability, or the handling of multiple mesial and distal measurements when forming participant-level results. Those details are not reported in the registry record.

7. Results Posted in the Registry

• Test Group: mean 0.32 versus 0.80 on control; difference -0.48 (95% CI -0.97 to 0.01), standardized effect d = -0.66; z-test p = 0.055.

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.

Changes in Keratinized Mucosa Width

• 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:
  • Test Group: mean 0.42 versus 0.90 on control; difference -0.48 (95% CI -0.90 to -0.06), standardized effect d = -0.77; z-test p = 0.024.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Test Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Changes in Lingual Mucosa Thickness

• 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:
  • Test Group: mean 0.38 versus 0.71 on control; difference -0.33 (95% CI -0.64 to -0.02), standardized effect d = -0.72; z-test p = 0.035.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Test Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes cover keratinized mucosa width, lingual mucosa thickness, and implant success rate. For the two continuous soft-tissue measures, the group summaries show lower mean changes in the test group than in the control group. The registry also posts sponsor-reported comparisons for those measures. The results do not form a uniform pattern of precision: their reported p-values and confidence intervals differ in how strongly they distinguish the estimates from zero.

These outcomes provide context alongside the primary bone-level measure, but they do not replace it. Similar direction in group means across continuous outcomes may be consistent with a broader pattern in the observed measurements, but it does not establish a common mechanism or confirm the primary result. The record lists implant success rate as a secondary outcome, but the results presented do not provide a posted success-rate estimate in the registry record used for this explanation; detailed results for that measure are not reported in the registry record.

Secondary findings generally carry less evidential weight when many outcomes are examined without a reported multiplicity strategy. Testing multiple outcomes increases the possibility that at least one result will appear notable by chance. The record does not report whether the investigators adjusted for multiplicity or designated particular secondary outcomes as confirmatory. Their findings are therefore best treated as supportive or exploratory rather than as independent confirmation. This caution applies even where a reported unadjusted p-value is near a conventional threshold; it does not erase the estimates, but places them in the context of uncertainty and the number of outcomes considered.

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

• Changes in Keratinized Mucosa Width
• Changes in Lingual Mucosa Thickness
• Implant Success Rate According to the 2017 Classification Criteria Set by the American Academy of Periodontology (AAP)

9. Statistical Interpretation

10. Statistical Methods Explained

The primary measure is continuous, so the record reports means and standard deviations for the two groups. A mean is the arithmetic average of measured values. A standard deviation describes how much individual observations vary around that average; it is not the uncertainty in the estimated mean itself. The posted outcome is a change from baseline to follow-up, and the group summaries describe those changes.

What does a mean difference represent?

A mean difference subtracts one group's mean from the other's. Its sign depends on which group is subtracted from which. The unadjusted recalculation expresses the primary comparison as test group minus control group, producing -0.48 millimeters. The sponsor reports a value of 0.48 for the mean difference in final values. Since the record does not state the sponsor's subtraction order in a way that resolves the contrast, and the two analyses also differ in their intervals and p-values, the discrepancy cannot be dismissed as a sign convention alone. The sponsor's own analysis takes precedence, but the disagreement should remain visible to readers.

What does a confidence interval convey?

A confidence interval describes uncertainty around an estimated contrast under the assumptions of the method used. A narrower interval indicates greater precision than a wider interval, all else equal. When an interval includes zero for a difference, the data and method do not rule out no difference at the stated confidence level. This does not prove that the groups are the same. When an interval excludes zero, it indicates that zero is not among the values supported by that interval under its assumptions; it does not establish clinical importance.

Why can analyses disagree?

The sponsor's primary analysis is identified as Wilcoxon (Mann-Whitney), with the parameter described as mean difference in final values. The recalculation is an unadjusted comparison based on posted summary statistics. These are not identical analysis approaches. The registry does not report the sponsor's full statistical plan, details of the test implementation, or how the analysis incorporated the split-mouth design. The trial's own analysis should not be replaced by a reanalysis based on arm-level summaries, but the recalculation can highlight that the posted means and the reported inferential result do not align straightforwardly.

A Wilcoxon (Mann-Whitney) procedure is a rank-based comparison. In general, rank-based methods compare the relative ordering of observations between groups rather than relying solely on the observed means. Their results can differ from a method that compares means directly, particularly when distributions or data structure differ. The registry nevertheless labels the reported parameter as a mean difference; it does not provide further explanation of how that parameter and test were combined.

Why does the split-mouth structure matter?

In general, measurements from two approaches applied within the same participant may be correlated. An analysis that uses the within-participant structure can account for that relationship, whereas a calculation that treats the group summaries as unrelated may not. The record describes the study as split-mouth, but does not state whether the sponsor's test used paired observations or explain the unit of analysis. A detailed account of that choice is not reported in the registry record. It is therefore not possible to determine from the record whether the reported method fully reflects the design.

What does over-dispersion mean in general?

For continuous outcomes, variability is reflected in the spread of observations around their mean. For count outcomes, over-dispersion generally means that variability is greater than a model's assumed distribution allows, which can make standard errors too small if ignored. The primary endpoint is continuous rather than a count, and the registry reports standard deviations. The record does not report a model-based assessment of over-dispersion, and no such assessment should be inferred from these summaries.

The posted p-values quantify how incompatible the data are with a specified no-difference hypothesis under the relevant analysis assumptions; they are not the probability that the hypothesis is true. An unadjusted p-value also does not account for testing multiple outcomes unless an adjustment is made. The registry record does not report a multiplicity strategy. Statistical evidence should therefore be read together with the estimate, its uncertainty, design structure, and the limits of the analysis details available.

11. Confidence Intervals and Precision

Precision concerns how narrowly an effect is estimated. The recalculated primary mean difference is -0.48 millimeters, with a 95% confidence interval from -0.971 to 0.011. The interval is broad enough to include zero and a range of values on either side of it. This indicates uncertainty in the recalculated contrast; it is not proof that the groups have identical outcomes.

The sponsor's reported primary confidence interval is 0.10 to 0.85, with the reported estimate of 0.48. That interval excludes zero, unlike the recalculated interval. The difference between the two intervals is part of the discrepancy, not merely a question of whether the point estimates are close. The registry does not explain the divergence in the intervals or provide the details needed to identify its cause. The sponsor's own analysis takes precedence, while the recalculation serves as a check based on the posted summary statistics.

Confidence intervals are general measures of estimation uncertainty, conditional on an analysis method and its assumptions. They do not measure every source of uncertainty: design choices, outcome measurement, missing data, and analysis population can also affect interpretation. The registry record does not provide all of those details. In particular, the split-mouth design is described, but how its within-participant structure was represented in the sponsor's analysis is not reported.

The group standard deviations also show that observed values vary within both groups; they should not be mistaken for confidence intervals. The sample counts are limited, and the uncertainty intervals should be read as an important part of the findings rather than treating the point estimates as exact. A confidence interval is compatible with a range of effects under its method, not a guarantee that the true effect lies within it.

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 justification. For these continuous outcomes, the figures are participants per arm, not total events. The illustrations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses the stated fraction of the observed effect as the effect to detect.

The 80% power column gives the number of participants per arm estimated to provide an 80% chance of detecting the assumed effect under those planning assumptions, if that effect and the assumptions hold. The 90% power column uses a higher target chance of detection and therefore calls for a larger planned sample in the listed scenarios. These are design calculations, not descriptions of what occurred in the trial.

Read the rows as alternative planning targets: planning for 100% of the observed effect uses the full observed effect as the assumed target; planning for 75% or 50% uses a smaller assumed effect. Smaller effects are harder to distinguish from random variation, so they require more participants per arm in these illustrations. This relationship is general to sample-size planning and is visible in the listed values.

This is not observed power. The registry record does not report the original sample-size assumptions or justification, so the planning figures should not be attributed to the investigators' original design. They also do not resolve the discrepancy between the sponsor's analysis and the summary-statistic recalculation.

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 = -0.480; pooled standard deviation σ = 0.731.
2. n = 2 × (1.96 + 0.842)² × 0.731² / -0.480² = 36.4, rounded up to 37 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 <- -0.48                      # observed difference in means
sigma <- 0.730513518013185                     # 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(4043286)
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 = 37 (80% power), 49 (90% power)
 75% of observed effect: n per arm = 65 (80% power), 87 (90% power)
 50% of observed effect: n per arm = 146 (80% power), 195 (90% power)
power.t.test: 37.3 
Simulated power at n = 37 per arm: 0.795 (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 sponsor reports a Wilcoxon (Mann-Whitney) analysis for the primary outcome, with a mean difference in final values of 0.48, a 95% confidence interval from 0.10 to 0.85, and p = 0.009. The unadjusted recalculation from the posted group summaries gives a test-minus-control mean difference of -0.48, a 95% confidence interval from -0.971 to 0.011, and p = 0.055. The estimates have opposite signs and their confidence intervals and p-values differ.

The sponsor's own analysis takes precedence over the recalculation. The recalculation is a simple comparison of posted summary statistics, not a substitute for the trial's reported analysis. The record does not provide enough information to establish why the two results differ, including how the sponsor handled the split-mouth structure or the details of the test implementation. It would be inappropriate to select whichever result is more favorable or to treat the recalculation as a correction of the sponsor's analysis. Instead, readers should distinguish the reported sponsor result from the separate unadjusted check and recognize the unresolved discrepancy.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and multiple secondary outcomes, but does not report a multiplicity adjustment or testing hierarchy. When several hypotheses are tested, the chance of obtaining at least one apparently notable result by chance can increase. In general, adjustment procedures or a prespecified hierarchy can address that concern, but the registry record does not state whether any such approach was used. Secondary p-values should therefore be interpreted as unadjusted evidence unless the record says otherwise.

The record gives enrollment of 19 and primary outcome group counts of 17 in each group. It does not explain the difference between enrollment and the posted outcome counts, identify reasons for missing measurements, or report an analysis population such as intention-to-treat or per-protocol. The handling of missing data, including whether values were imputed or whether analyses used only available measurements, is not reported in the registry record.

The description of the study as split-mouth raises a design consideration: paired measurements within one participant may not be statistically independent. The sponsor analysis is listed as Wilcoxon (Mann-Whitney), but the record does not specify whether the procedure used paired data, how observations were grouped for analysis, or how the randomization was implemented. The summary-statistic recalculation is unadjusted and cannot recover participant-level pairing from arm means and standard deviations.

The registry record also does not report interim analyses, a detailed statistical analysis plan, or the trial's original sample-size justification. These omissions do not establish that the procedures were absent; they mean the procedures are not documented in the registry record. As a result, readers cannot fully assess prespecification, missing-data decisions, or protection against multiplicity from the posted record alone.

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 5% reporting threshold.

The posted serious adverse event counts are zero in the control group and zero in the test group, with 17 participants at risk in each group. The record also lists zero other adverse events and zero deaths in each group. These are recorded counts for the groups and observation period represented in the registry; they should not be read as proof that no events could occur or that the approaches have no safety risks.

Zero observed events provide limited information about uncommon outcomes, particularly in a study with the posted group sizes. The registry does not give further detail about adverse-event collection, definitions, timing, or whether all participants completed safety follow-up. Those details are not reported in the registry record. The figures should therefore be interpreted as the recorded event counts, not as a comprehensive characterization of safety.

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

The results describe measurements recorded for a randomized split-mouth study of abutment connection strategies, with peri-implant marginal bone-level change as the primary outcome. The group means differ in the posted summaries, and the sponsor reports a statistically distinguishable mean difference. A separate unadjusted recalculation yields a different estimate direction and an interval that includes zero. The disagreement limits how confidently the comparative result can be interpreted from the registry record alone.

A statistical result does not by itself establish clinical importance. The record does not report a threshold for a clinically meaningful change in millimeters, so the size of the difference cannot be classified as clinically important from these registry entries alone. Nor does a p-value measure the probability that a treatment works, or that a finding is due to chance. It is conditional on a particular analysis and its assumptions.

The findings also do not establish that one abutment strategy causes every observed difference. Randomization is a feature of the design, but important analysis details are not reported, including how the split-mouth pairing was handled. The record does not explain the disparity between enrollment and outcome counts or describe missing-data methods. These limitations affect interpretation of both the primary and secondary comparisons.

The secondary outcomes offer additional measurements of soft tissue and implant success, but unadjusted secondary findings carry less weight when the multiplicity approach is unknown. The event counts record no adverse events or deaths in either group, but the study record does not provide enough information to treat zero observed counts as evidence of no risk.

Overall, the registry supports a description of the observed summaries and the sponsor's reported analysis, alongside a notable discrepancy with a simple recalculation. It does not, by itself, settle the clinical importance, reproducibility, or broader applicability of the findings.

18. Why This Trial Matters Statistically

This study is statistically interesting because its design is described as split-mouth while the registry also identifies the model as parallel. A split-mouth design can create within-participant comparisons, which may be useful statistically when properly represented in the analysis. The record does not explain how the sponsor's analysis incorporated that structure, leaving readers unable to assess an important connection between design and inference.

The primary outcome also illustrates why estimates, uncertainty intervals, and analysis methods need to be read together. The posted group means produce an unadjusted recalculation that differs from the sponsor-reported result in sign, interval, and p-value. The sponsor's own analysis takes precedence, but the discrepancy shows why a summary statistic alone cannot reproduce every trial analysis and why transparent reporting of methods matters.

The record further demonstrates the difference between observed results and planning calculations. Sample-size illustrations based on the observed effect can help readers understand how assumptions about the target effect and power influence planned enrollment. They are not the trial's original sample-size justification and do not reveal the chance that the actual study detected an effect.

Finally, several secondary outcomes and limited safety counts require careful framing. Without a reported multiplicity plan or full accounting of analysis populations and missing data, secondary results are less definitive. The registry is useful for understanding what was measured and what results were posted, while its omissions show why detailed statistical reporting is essential for independent assessment.

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 limitations are specific to the registry record for this trial. It describes the study as split-mouth but also lists a parallel model, without explaining how those design labels fit together. The analysis method is identified as Wilcoxon (Mann-Whitney), but the record does not say whether the sponsor accounted for within-participant pairing. This is important because the statistical interpretation can depend on whether measurements are treated as paired or unrelated.

The primary outcome has a clear discrepancy between the sponsor's reported analysis and the unadjusted recalculation from group summaries. The sponsor's analysis takes precedence, but the record does not explain the difference. Outcome counts also do not match the enrollment count as stated: enrollment is 19, while the primary outcome results list 17 in each group. Reasons for this and the handling of missing observations are not reported.

The registry does not report the original sample-size justification, full statistical analysis plan, multiplicity strategy, interim analyses, or analysis populations. It also does not give details about assessor masking, measurement reliability, or how mesial and distal readings were combined for participant-level analysis. These details are not reported in the registry record and should not be assumed either way.

The study concerns implants in posterior maxilla and mandible regions and reports a 1-year follow-up. The registry does not provide enough information to judge how broadly the results apply beyond the studied setting or follow-up. The limited posted adverse-event counts likewise do not characterize uncommon risks or longer-term safety.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: The Effects of Dis/Reconnection of Implant Abutments on Peri-implant Bone Levels — NCT04043286.
• Registry record last updated 2024-12-04; status last verified 2024-11.
• Results first posted 2024-12-04.
• 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

The registry describes a completed randomized, unmasked study of definitive abutment connection and peri-implant outcomes, with a split-mouth description and a parallel model designation. Enrollment was 19. The primary endpoint measured change in marginal bone level from implant placement to 1 year, using standardized periapical radiographs.

Primary outcome summaries list 17 participants in each group. The sponsor reports a mean difference of 0.48, a 95% confidence interval from 0.10 to 0.85, and p = 0.009. An unadjusted recalculation gives -0.48, a 95% confidence interval from -0.971 to 0.011, and p = 0.055; the sponsor's own analysis takes precedence, and the discrepancy is not explained in the registry record.

Secondary outcomes include soft-tissue measures and implant success. The record does not report multiplicity handling, missing-data methods, the original sample-size justification, or how the sponsor's analysis accounted for the split-mouth design. Recorded adverse events and deaths were zero in both groups.