A RCT of Ultrasound Guided IUD Insertion: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A RCT of Ultrasound Guided IUD Insertion (NCT03493815), a randomized na study. The primary outcome is Number of Participants Who Had IUD Removed Within 6 Months.

2. Clinical Question

3. Trial Design

The registry describes a randomized, parallel-group trial comparing transabdominal ultrasound-guided IUD insertion with traditional blind insertion. Masking was listed as none. The record gives an enrollment of 85 and lists the study status as completed. The study began on 2018-03-08, with primary completion on 2019-04-30. The phase is listed as NA. The sponsor was Milton S. Hershey Medical Center.

The brief summary describes the rationale as evaluating ultrasound-guided insertion against traditional blind insertion at an academic health institute, where provider skill level can vary. It states the hypothesis that ultrasound guidance would lead to lower IUD discontinuation rates and greater patient satisfaction. A hypothesis is a planned expectation, not evidence that the expected pattern occurred.

The posted primary outcome is the number of participants whose IUD was removed within 6 months. Its analysis population excluded participants lost to follow-up when their outcome was unknown. The secondary outcomes were malposition at the 4-6 Week Visit, change in pain score, and satisfaction with the IUD at 6 months. The record lists four outcome measures and four analyses overall.

The registry record does not report how the random sequence was generated, whether allocation was concealed, or whether the randomization used stratification or blocks. The original sample-size justification and design assumptions are not reported in the registry record. The posted planning illustrations are separate from the trial's original design and should not be interpreted as evidence about how the trial was planned.

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

Analysis population for the primary outcome, as defined in the registry: Participants who had an IUD inserted and either discontinued the IUD or continued the IUD until the 6m visit were included. Participants who were lost to followup (outcome unknown) were excluded.

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: Four subjects (2 per group) were randomized but unable to insert IUD and therefore were excluded from analysis.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Who Had IUD Removed Within 6 Months, measured over 6 Months.

The primary endpoint counts participants whose IUD was removed within 6 months. The registry describes the outcome as IUD discontinuation during the 6-month post-insertion period. It therefore addresses whether the device remained in use over that stated follow-up period, rather than measuring the reason for removal, time to removal, or a continuous measure of use.

The registry's primary-outcome population included participants who had an IUD inserted and either discontinued it or continued the IUD until the 6m visit. Participants lost to follow-up with an unknown outcome were excluded. The record does not explain how the analysis handled other possible missing information or whether any imputation was used.

This endpoint is relevant to the study's stated hypothesis about discontinuation. It is a participant count, so the posted group values express how many participants had the event among those included in the outcome analysis. Such a count is useful for comparing event occurrence, but by itself does not explain why removal occurred or establish that insertion technique caused an individual's outcome. The outcome also does not capture satisfaction, pain, or malposition as substitutes for discontinuation; those were reported separately as secondary outcomes.

7. Results Posted in the Registry

• Traditional Blind IUD Insertion: 25.0% (8/32) versus 18.2% (6/33) on control; risk difference 6.8 percentage points (95% CI -13.1 to 26.8), risk ratio 1.38 (0.54–3.52); unadjusted two-proportion z-test p = 0.504.

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.

Number of Participants With Malpositioned IUD at 4-6 Week Visit

• 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:
  • Traditional Blind IUD Insertion: 16.2% (6/37) versus 9.4% (3/32) on control; risk difference 6.8 percentage points (95% CI -8.7 to 22.4), risk ratio 1.73 (0.47–6.36); unadjusted two-proportion z-test p = 0.400.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Traditional Blind IUD Insertion and the control. The interval gives the range of effects that remain compatible with the data.

Change in Pain Score

• 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:
  • Traditional Blind IUD Insertion: mean 2.10 versus 2.30 on control; difference -0.20 (95% CI -1.19 to 0.79), standardized effect d = -0.09; z-test p = 0.691.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Traditional Blind IUD Insertion and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants Satisfied With IUD at 6 Months

• 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:
  • Traditional Blind IUD Insertion: 84.0% (21/25) versus 88.9% (24/27) on control; risk difference -4.9 percentage points (95% CI -23.5 to 13.7), risk ratio 0.95 (0.76–1.17); unadjusted two-proportion z-test p = 0.606.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Traditional Blind IUD Insertion and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend the comparison beyond IUD removal to include malposition, pain, and satisfaction. Taken together, they address different aspects of the insertion and follow-up experience: a device-position outcome, a pain-score measure, and a participant-reported satisfaction outcome. The registry's reported analyses use methods matched to the outcome forms, including a binary regression for malposition, a two-sided t-test for pain, and Fisher Exact for satisfaction.

Across these outcomes, the posted estimates do not provide a precise, consistent basis for a firm conclusion about a difference between insertion approaches. Their uncertainty should be read with the primary result, not as a substitute for it. The secondary outcomes do not resolve the uncertainty in the primary endpoint because they measure different outcomes and have their own analysis populations and limitations.

General: When several outcomes are tested, the chance of at least one apparently unusual result can increase if each test is considered independently. Adjustment methods or a prespecified hierarchy can address some multiplicity concerns, but the registry record does not report whether such a plan was used. As a result, unadjusted secondary p-values carry less weight than a clearly designated primary analysis and should be treated as exploratory unless the record establishes otherwise.

The secondary data also have outcome-specific denominators, which differ from the primary endpoint population. The record does not give a single common analysis population for all outcomes, so comparisons across endpoints should not be treated as if they were measured in exactly the same set of participants. The secondary findings add context, but do not establish that one approach is preferable or that there is no meaningful difference.

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

• Number of Participants With Malpositioned IUD at 4-6 Week Visit
• Change in Pain Score
• Number of Participants Satisfied With IUD at 6 Months

9. Statistical Interpretation

10. Statistical Methods Explained

What does the primary risk difference describe?

General: A risk difference compares the proportion of participants with an event in one group with the proportion in another group. A value of zero represents equal observed event proportions; positive or negative values indicate the direction depends on which group is subtracted from which. In this analysis, the recalculated comparison is traditional blind insertion relative to ultrasound-guided insertion. The estimate is 0.068, with a 95% confidence interval from -0.131 to 0.268. Because the interval spans zero, the data are compatible with a range of differences in either direction. The estimate is a simple unadjusted comparison, not an adjusted model result.

How is a risk ratio different?

General: A risk ratio divides one group's event risk by the other's. A ratio of 1 represents equal risks, while values on either side represent relative differences, with interpretation depending on the numerator and denominator. The registry's reported analysis used binary regression with a complementary log-log link and gave a risk ratio of 0.73, a 95% confidence interval from 0.28 to 1.90, and p = 0.51. The interval includes 1. The registry record does not provide further detail on covariate adjustment or the exact model specification beyond the named method and reported measure.

The recalculated risk difference and the reported risk ratio are not interchangeable: one expresses an absolute difference, and the other a relative comparison. They also come from different analyses. A model-based estimate can differ from a direct calculation based on posted group counts because the estimand and modeling approach differ. The discrepancy flag is false, so the record does not identify a disagreement requiring special handling.

What does the confidence interval add?

General: A confidence interval conveys the range of effect estimates reasonably compatible with the observed data under the method's assumptions. It captures uncertainty in the estimate; it is not a range containing a known true value with certainty, and it does not account automatically for every possible source of bias. For the primary risk difference, the interval crosses zero. For the reported risk ratio, it crosses 1. In each case, the interval allows both a difference and no difference under the corresponding scale. The width also signals that the estimate is imprecise.

Why does the choice of scale matter?

General: Absolute and relative measures answer related but distinct questions. An absolute difference describes a change in event frequency between groups, while a ratio describes how the frequencies compare proportionally. Neither measure alone describes clinical importance, and both depend on a clear definition of the event, population, follow-up, and comparison direction. Here, the primary endpoint is removal within 6 months, and the primary population excludes participants whose outcome was unknown. The reported measures must be interpreted with those definitions in mind.

What role does the p-value play?

General: A p-value describes how compatible observed data are with a specified null hypothesis under the analysis assumptions. It is not the probability that the null hypothesis is true, nor a measure of effect size or clinical importance. The registry reports p = 0.51 for the primary model-based analysis, while the unadjusted recalculation reports p = 0.504. These values are close but belong to their respective methods. Neither establishes that the groups are equivalent, and neither removes the uncertainty reflected in the confidence intervals.

How should secondary analyses be viewed?

The posted secondary outcomes include a binary count for malposition, a continuous pain-score outcome, and a binary satisfaction count. The malposition and satisfaction outcomes are expressed as participant counts, while pain is expressed as a mean and standard deviation. The registry reports a binary regression analysis for malposition, a two-sided t-test for pain, and a Fisher Exact analysis for satisfaction.

General: Different outcome types often require different summaries and tests. A binary outcome concerns whether an event occurred; a continuous outcome summarizes measured values on a scale. A t-test compares group means under its assumptions, while Fisher Exact is a method for comparing categorical counts. The registry record does not report further diagnostics, assumptions checks, or model details for these analyses. Secondary findings are also subject to the interpretive caution that multiple tests can produce apparently noteworthy results by chance when considered together.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data locate an effect estimate. The primary unadjusted risk-difference estimate is 0.068, with a 95% confidence interval from -0.131 to 0.268. This interval is broad and spans zero, so the estimated difference is compatible with outcomes favoring either group as well as little or no difference on this scale. The estimate should not be read as a precise measure of the effect.

The sponsor's reported risk ratio is 0.73, with a 95% confidence interval from 0.28 to 1.90. For a ratio, 1 is the null value; the interval includes it and also permits a range of relative effects in either direction. These limits reinforce that the primary comparison is uncertain. The recalculated risk-difference interval and reported risk-ratio interval use different scales and methods, so their numerical limits should not be compared directly.

General: Confidence intervals describe uncertainty under a particular statistical method and its assumptions. Wider intervals generally indicate less precision, while narrower intervals indicate more precision. They do not guarantee that bias, missing data, measurement error, or limitations in study conduct are absent. In this trial, the primary outcome population excluded unknown follow-up outcomes, and the record does not report a missing-data sensitivity analysis. The intervals therefore should be interpreted together with the outcome definition and analysis population.

Failure to exclude a null value is not proof of no effect, and a confidence interval should not be treated as a formal equivalence test. The registry record does not report an equivalence or noninferiority objective or margin. The uncertainty is a central part of the result, not a reason to choose one endpoint estimate over another.

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 illustrations are planning calculations based on the observed effect, not the original trial design. For this non-time-to-event outcome, the displayed figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The calculation considers effects set at 100%, 75%, or 50% of the observed effect.

The 80% power column describes the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect were the true one. The 90% power column gives the corresponding planning figure for a 90% chance. Higher target power generally requires more participants, and a smaller effect is harder to detect, so the figures increase when the calculation uses a smaller fraction of the observed effect.

For the primary outcome, the figures range from 571 participants per arm when planning for 100% of the observed effect at 80% power to 2,879 participants per arm when planning for 50% of the observed effect at 90% power. These values are illustrations, not evidence that the trial had a particular probability of detecting an effect. This is not observed power.

The original sample-size justification, target effect, and design assumptions are not reported in the registry record. The planning figures should therefore not be used to infer whether the completed trial met its original target or whether the design was adequate. They illustrate how required sample size depends on the assumed effect and target power under the stated calculation assumptions.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.182; treatment proportion p₁ = 0.250; average p̄ = 0.216.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5819 = 1.1405.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5799 = 0.4880.
4. n = (1.1405 + 0.4880)² / (0.0682)² = 570.5, rounded up to 571 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 <- 0.181818181818182                          # 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(3493815)
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 = 571 (80% power), 764 (90% power)
 75% of observed effect: n per arm = 986 (80% power), 1,319 (90% power)
 50% of observed effect: n per arm = 2,151 (80% power), 2,879 (90% power)
power.prop.test: 570.5 
Simulated power at n = 571 per arm: 0.798 (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.

14. Analyses Reported by the Sponsor

The registry's own primary analysis is the binary regression with a complementary log-log link. It reports a risk ratio of 0.73, a 95% confidence interval from 0.28 to 1.90, and p = 0.51. This is the sponsor's reported model-based result and should be kept distinct from the unadjusted recalculation based directly on the posted group counts.

The recalculation expresses the comparison as a risk difference of 0.068 for traditional blind insertion relative to ultrasound-guided insertion, with a 95% confidence interval from -0.131 to 0.268 and p = 0.504. The two analyses summarize the same primary outcome using different effect scales and methods. The group counts provide a descriptive view; the sponsor's regression gives the analysis reported in the registry.

The registry record does not describe additional model covariates or enough specification detail to reconstruct every feature of the sponsor's analysis. The discrepancy flag is false. Both reported and recalculated results indicate substantial uncertainty, and the risk-ratio interval includes 1 while the risk-difference interval includes zero. The recalculation is supplementary, not a replacement for the sponsor's analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies the removal outcome as primary and lists malposition, pain, and satisfaction as secondary outcomes. It does not report a multiplicity strategy, such as a correction for testing multiple outcomes, a hierarchical testing sequence, or a distinction between confirmatory and exploratory secondary analyses. The statistical plan for multiplicity is not reported in the registry record.

General: If several hypotheses are tested, interpreting each p-value as though it were the only test can overstate the strength of evidence across the overall set of outcomes. This does not make the secondary results unusable, but it makes them less decisive, especially when no adjustment or prespecified interpretation plan is documented. The primary endpoint should remain the main statistical focus, with secondary endpoints interpreted as additional context.

Missing-data information is limited. For the primary outcome, participants lost to follow-up with unknown outcome were excluded. The record does not report the number of such participants, the reasons for loss to follow-up, whether missingness differed by arm, or whether sensitivity analyses addressed the unknown outcomes. It also does not report imputation methods. Because the primary comparison is based on participants with an observed outcome, it may not fully represent all randomized participants if missingness is related to outcome or treatment assignment.

The reported denominators vary across outcomes. The registry does not provide a single analysis-population description that explains all these differences, nor does it report an intention-to-treat analysis for every outcome. The endpoint-specific population descriptions and denominators should therefore be considered when comparing results. The randomization supports a between-group comparison, but exclusions or outcome-specific missingness can affect how well the analysis preserves the original randomized comparison.

Further details on the statistical analysis plan, allocation process, and handling of missing data are not reported in the registry record. Their absence limits assessment of prespecification and robustness, but does not by itself show that the analyses were conducted improperly.

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

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: malpositioned iud (2.5%).

The adverse-event record lists serious adverse events among 40 participants at risk in the ultrasound-guided arm, with 1 affected, and among 41 participants at risk in the traditional blind insertion arm, with 0 affected. Deaths are recorded as 0 in each arm. The registry lists malpositioned IUD at 2.5% among the top serious terms.

Other adverse events are separately recorded: 19 affected among 40 at risk in the ultrasound-guided arm and 20 affected among 41 at risk in the traditional blind arm. These are not the serious-event counts and should not be conflated with them. The registry record does not provide further detail in the registry record about the event definitions, severity grading, relatedness assessment, or timing.

General: Safety counts describe events recorded under the study's reporting procedures; they do not by themselves establish whether an event was caused by an intervention. The groups at risk and the number affected are useful context, but the small number of serious events limits what can be concluded about comparative safety. The registry record does not report a formal comparative safety analysis, and these figures should be read as descriptive rather than as proof of a safety difference or the absence of one.

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

The registry record documents a randomized comparison of transabdominal ultrasound-guided and traditional blind IUD insertion, with removal within 6 months as the primary outcome. The observed primary counts were 6 and 8, with outcome denominators of 33 and 32. The sponsor's reported model-based estimate and the unadjusted recalculation both have substantial uncertainty. The primary confidence intervals include their respective null values.

These findings do not establish that the approaches have identical effects. A result that does not distinguish the groups statistically can reflect uncertainty as well as a genuinely small difference. The wide intervals allow a range of plausible effects, so the result is not precise enough to settle the direction or magnitude of the primary comparison.

Nor does the comparison demonstrate that ultrasound guidance reduces discontinuation, improves satisfaction, or changes pain or malposition. The registry summary describes these as study interests or outcomes, but observed counts and estimates must be interpreted with their uncertainty. The secondary analyses do not remove the limitations of the primary result, and no multiplicity plan is reported.

The result also does not explain why an IUD was removed, establish the experience of participants lost to follow-up, or answer questions beyond the outcomes and follow-up periods recorded. The primary outcome excludes participants whose follow-up status was unknown. No medical advice follows from these statistical results; they describe the posted trial data and their precision.

General: A randomized design is intended to support fair comparison by assigning participants to groups, but randomization does not guarantee that a small study will estimate effects precisely or that missing data and measurement limitations are absent. Interpretation requires attention to the outcome definition, analysis population, reported methods, and uncertainty—not only the point estimate or p-value.

18. Why This Trial Matters Statistically

This trial is statistically instructive because its primary result can be described on both an absolute and a relative scale. The recalculated risk difference expresses the difference in event frequency, while the sponsor's reported risk ratio expresses a relative comparison. Keeping those measures distinct helps prevent a model-based estimate from being mistaken for a direct calculation from group counts.

It also illustrates why event counts and p-values are not enough on their own. The primary outcome counts are straightforward to interpret descriptively, but the confidence intervals show that the comparison remains imprecise. A nonsignificant p-value should not be translated into proof of equivalence or no effect. Reporting the interval alongside the estimate makes the range of uncertainty more visible.

Another important issue is the analysis population. The primary outcome excludes participants whose follow-up outcome was unknown, while the secondary outcome denominators vary. This underscores the need to understand who contributed to each analysis before comparing outcomes or generalizing the findings to all randomized participants.

Finally, the registry contains multiple outcomes and several corresponding analyses. Without a reported multiplicity plan, secondary p-values need cautious interpretation. The trial therefore offers a useful example of how design, outcome definition, missingness, statistical scale, and multiplicity affect interpretation together. The lesson is not that one insertion approach should be selected, but that the posted evidence has to be read with its uncertainties and limits in view.

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 limitations affect interpretation. The study was unmasked, so participants and providers were not reported as blinded. The registry does not describe how randomization was generated or whether allocation was concealed. These design details are not reported in the registry record, which limits assessment of how assignment was implemented.

The primary endpoint analysis excluded participants lost to follow-up when the outcome was unknown. The number and reasons for those losses, their distribution by arm, and sensitivity analyses are not reported in the registry record. The outcome-specific denominators also vary, and the registry does not provide a comprehensive explanation of the analysis population for every endpoint.

The primary comparison is imprecise, as reflected by confidence intervals that include the null values on both reported scales. The registry record does not report the original sample-size justification or the study's design assumptions, so the planning illustrations based on observed effects cannot establish whether the trial was originally designed to detect a particular difference.

The registry identifies multiple secondary outcomes but does not report a multiplicity plan. Further details about model covariates, diagnostic checks, outcome ascertainment procedures, and the rationale for the analysis methods are not reported in the registry record. The reported follow-up periods are outcome-specific, so the findings do not describe outcomes beyond those stated timeframes.

These limitations qualify the strength and scope of the statistical conclusions; they do not, on their own, demonstrate that the trial was conducted improperly. They mean that the posted results should be treated as an uncertain comparison in the populations and timeframes described, rather than as a definitive account of all possible outcomes.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A RCT of Ultrasound Guided IUD Insertion — NCT03493815.
• Registry record last updated 2020-05-21; status last verified 2020-05.
• Results first posted 2020-05-11.
• 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

NCT03493815 is a completed randomized, parallel-group trial sponsored by Milton S. Hershey Medical Center. It compared transabdominal ultrasound-guided IUD insertion with traditional blind insertion and reported no masking. Enrollment was 85.

The primary outcome was the number of participants whose IUD was removed within 6 months. The sponsor reported a binary regression risk ratio of 0.73, with a 95% confidence interval from 0.28 to 1.90 and p = 0.51. The unadjusted recalculation gives a risk difference of 0.068, with a 95% confidence interval from -0.131 to 0.268 and p = 0.504.

Secondary outcomes concerned malposition, pain, and satisfaction. The record also reports adverse-event counts. The primary comparison is uncertain, and missing outcome handling, original design assumptions, and multiplicity procedures are not fully reported in the registry record.