Comparing Pediatric Dental Oral Sedation Outcomes With and Without Meperidine in Children Aged 3-7 Years: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparing Pediatric Dental Oral Sedation Outcomes With and Without Meperidine in Children Aged 3-7 Years (NCT04068948), a randomized phase 4 study. The primary outcome is Number of Participants With Successful Sedation.

2. Clinical Question

The trial also set out to examine the relationship between child temperament and sedation outcome in each group. The registry lists child temperament according to the CBQ-SF as a secondary outcome, but detailed results for that outcome are not reported in the registry record.

The comparison concerns a behavioral rating at completion of the dental procedure, not a broader measure of dental health or a general assessment of sedation. The registry describes the objective as assessing whether removing meperidine is associated with the same behavioral success outcomes as the regimen that includes it. The posted results therefore address the recorded outcome in these trial groups; they do not, on their own, establish how the regimens compare in other populations or settings.

3. Trial Design

This was a randomized, parallel-group Phase 4 trial listed as completed. The registry reports enrollment of 37 and records the study start as 2019-06-25 and primary completion as 2022-12-31. It identifies University of Washington as the sponsor. The masking field is listed as single; who was masked and how masking was maintained are not reported in the registry record.

The two groups received oral regimens before pediatric dental procedures. One group received midazolam 0.5mg/kg, hydroxyzine 1.0mg/kg, and meperidine 1.5mg/kg. The other received midazolam 0.5mg/kg and hydroxyzine 1.0mg/kg without meperidine. The posted primary outcome counts are 11 successful ratings among 20 participants in the meperidine group and 9 among 17 in the group without meperidine.

Random assignment is intended to make treatment groups comparable, on average, with respect to factors that could affect the outcome. In a trial with limited enrollment, however, randomization does not ensure that every relevant characteristic is balanced in the realized groups. The registry record does not report the sequence-generation method, allocation concealment, the timing or detailed process of assignment, or baseline characteristics that would help assess the groups' comparability.

The registry describes a primary outcome and a secondary temperament outcome. Details about the original sample-size justification, planned statistical methods, analysis populations, interim analyses, or protocol changes are not reported in the registry record. The results include group counts and an unadjusted comparison, but that does not supply the missing detail about the full prespecified analysis plan.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Successful Sedation, measured over At completion of procedure.

The primary endpoint is the number of participants rated as having successful sedation at completion of the dental procedure. Behavior during sedation was assessed with the Houpt Behavior Rating Scale. Excellent, Very Good, and Good ratings were classified as successful; Fair, Poor, and Aborted ratings were classified as failed sedation. The endpoint is therefore a binary classification of the behavioral rating, reported as a count in each group.

A behavioral outcome is relevant to the trial's stated question because its objective concerns success in completing dental treatment under oral sedation. Turning the scale into success or failure gives a direct group-level count for that objective. It also simplifies the comparison: the analysis can estimate how much the proportion classified as successful differs between regimens.

This binary endpoint necessarily compresses the rating scale. It does not show how ratings were distributed within the success category or within the failure category. Nor does the posted primary outcome describe other dimensions of the procedure, such as duration, specific behaviors, or later outcomes. Those measures are not reported in the registry record as part of this primary endpoint. The endpoint should therefore be interpreted as the registry-defined behavioral success measure at procedure completion, rather than as a complete account of every possible sedation outcome.

7. Results Posted in the Registry

• Midazolam, Hydroxyzine: 52.9% (9/17) versus 55.0% (11/20) on control; risk difference -2.1 percentage points (95% CI -34.3 to 30.2), risk ratio 0.96 (0.53–1.75); unadjusted two-proportion z-test p = 0.900.

8. Statistical Interpretation

9. Statistical Methods Explained

The principal comparison is a risk difference for a binary outcome. A risk, in this context, is the proportion of participants in a group who had successful sedation. The risk difference subtracts the success proportion in one group from the success proportion in the other. The comparison is defined as the group receiving midazolam and hydroxyzine without meperidine relative to the group receiving all three drugs. A negative estimate therefore corresponds to a lower observed success proportion in the group without meperidine.

What does the risk difference tell us?

The risk difference expresses an absolute contrast between group proportions. Its zero value corresponds to equal proportions. Estimates on either side of zero indicate the direction of the observed contrast, while the size of the estimate describes the absolute separation between the proportions. The reported estimate is close to zero. That point estimate is only one summary of the data; its uncertainty is important, especially when the group counts are limited.

How should the p-value be read?

The registry reports an unadjusted p-value of 0.9 for the comparison. A p-value is calculated under a statistical model in which the null hypothesis of no group difference is used as a reference. It measures how unusual data at least as incompatible with that null model would be under the model's assumptions. It is not the probability that the null hypothesis is true, and it does not measure the probability that the observed result will repeat. A large p-value does not establish equality, equivalence, or absence of a meaningful effect.

The record labels the value unadjusted. Whether it came from a particular test, whether the test was prespecified, and which assumptions were used are not reported in the registry record. The posted confidence interval and p-value are useful summaries, but the record does not document enough detail to reconstruct the full analysis procedure.

What role does the confidence interval play?

A confidence interval gives a range of estimates compatible with the observed data under the method used to construct it. For this risk difference, zero represents no difference. The reported interval crosses zero, so it includes values corresponding to lower success in either group as well as no difference. Its breadth indicates that the estimate is imprecise. The method used to calculate the interval is not reported in the registry record, so assumptions specific to that method cannot be assessed from the record.

The registry also reports relative measures, including a risk ratio and an odds ratio, each with confidence limits. These express a contrast on a relative rather than absolute scale. They answer a related question but should not be confused with the risk difference: a relative measure compares group risks or odds as a ratio, while the risk difference compares them by subtraction. The confidence limits for the relative measures also span the null value for a ratio. These different scales do not remove the uncertainty in the comparison.

Why does the outcome definition matter?

The endpoint combines ratings of Excellent, Very Good, or Good as successful and ratings of Fair, Poor, or Aborted as unsuccessful. This makes a readily interpretable binary outcome, but it also discards distinctions among ratings within either category. The reported count comparison addresses this prespecified-looking registry definition; whether the classification or cut point was established before enrollment is not reported in the registry record.

The endpoint is measured at completion of the procedure. It is not a time-to-event outcome and is not reported as a repeated measure. The registry reports the number meeting the success definition in each group and the corresponding comparison. Further details about assessor training, inter-rater agreement, or the handling of uncertain ratings are not reported in the registry record.

What does randomization contribute?

Randomization assigns participants to groups by chance and is intended to reduce systematic differences in factors that may affect outcomes. It supports a causal comparison when the allocation process is sound and participants are analyzed appropriately. The trial is identified as randomized, but details of sequence generation, concealment, adherence, crossovers, and the analysis population are not reported in the registry record. Those omissions limit assessment of how closely the posted comparison reflects the intended randomized comparison.

General statistical context: randomization does not prevent chance imbalances, and a small trial can leave substantial uncertainty even when its allocation process is valid. Likewise, an unadjusted group comparison can be informative, but the registry record does not report whether adjusted analyses were planned or conducted. No adjusted treatment estimate is posted. The interpretation should therefore stay with the reported unadjusted comparison and its uncertainty.

10. Confidence Intervals and Precision

The posted risk-difference estimate is close to zero, but the confidence interval is wide and includes zero. Its limits also extend to differences favoring either regimen. This means the observed data do not locate the underlying difference precisely: they remain compatible with no difference as well as with potentially appreciable differences in both directions. The confidence interval should be read as a range reflecting uncertainty, not as a range in which the true value is guaranteed to lie.

The unadjusted p-value is 0.9, but it does not make the estimate precise. A p-value and a confidence interval summarize related evidence in different ways. The p-value gives a test-based measure relative to a null hypothesis; the interval shows the range of effect estimates compatible with the data under its construction method. Here, the interval's inclusion of zero aligns with the lack of a small p-value, but neither result proves equivalence.

Precision is limited by the amount of information in the outcome counts. The registry reports 11 successes among 20 participants in the group receiving meperidine and 9 among 17 in the group without it. With counts of this size, the estimate can remain uncertain even when the observed proportions are close. The registry record does not report the confidence-interval method, so details such as its specific coverage properties cannot be evaluated.

The interval is for the risk difference and should not be mistaken for an interval around an individual participant's outcome or for a prediction interval in a future setting. The posted comparison pertains to the trial groups and the endpoint definition at procedure completion. Broader generalization would require evidence beyond this estimate.

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 display expresses sample size as participants per arm; it does not report total events. Its figures are planning illustrations based on the observed effect, not the trial's own original design assumptions. The stated calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to a stated fraction of the observed effect.

The 80% power column indicates the participants per arm that the illustration estimates would be needed for 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 quantity for a 90% chance. These are design targets under a model, not guarantees about the result of a future study. The row labels describe planning for 100%, 75%, or 50% of the observed effect. Smaller target effects require more participants because they are harder to distinguish from random variation.

The figures are not observed power for this trial. They are hypothetical planning calculations based on the observed effect, which is itself uncertain and may not represent the true effect. The original sample-size justification, target effect, and assumptions used when designing the trial are not reported in the registry record. The planning display therefore should not be read as evidence about what the investigators originally intended to enroll or as proof that the completed trial did or did not meet its original design goals.

When reading the curve alongside the planning values, focus on how the required participants per arm change as the target effect changes. The curve is a planning aid under the listed assumptions; it does not add precision to the trial's observed treatment estimate.

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 = 0.550; treatment proportion p₁ = 0.529; average p̄ = 0.540.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7049 = 1.3815.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7047 = 0.5931.
4. n = (1.3815 + 0.5931)² / (-0.0206)² = 9,198.9, rounded up to 9,199 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 <- 0.55                          # control proportion
p1 <- 0.529411764705882                          # 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(4068948)
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 = 9,199 (80% power), 12,315 (90% power)
 75% of observed effect: n per arm = 16,341 (80% power), 21,875 (90% power)
 50% of observed effect: n per arm = 36,735 (80% power), 49,177 (90% power)
power.prop.test: 9198.9 
Simulated power at n = 9,199 per arm: 0.803 (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. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary behavioral success outcome and a secondary outcome concerning child temperament according to the CBQ-SF and its association with sedation outcomes. The brief description also identifies temperament as a secondary objective. Detailed results for the temperament outcome are not reported in the registry record.

Multiplicity arises when several outcomes, comparisons, subgroups, or statistical tests are considered. Each additional test can increase the chance of finding an apparently notable result by chance if no adjustment or other control is used. The registry record does not report a multiplicity strategy, a hierarchy among secondary analyses, or whether any adjustment for multiple testing was planned. Only the posted unadjusted primary comparison can therefore be interpreted as recorded; it should not be assumed that it accounts for other possible tests.

The registry identifies two outcome measures and zero analysis entries, while also posting aggregate primary outcome counts and an unadjusted comparison. The record does not provide a complete analysis plan or enough detail to determine whether other analyses were performed outside the registry entries. No protocol-based explanation for the analysis set, exclusions, or handling of departures from assigned treatment is reported in the registry record.

Missing-data methods are also not reported in the registry record. It is not stated whether outcome ratings were available for every randomized participant, how missing ratings were handled, or whether any imputation or sensitivity analysis was used. The posted arm counts should be read as the outcome counts recorded, without assuming how unreported missingness was addressed.

The registry record does not identify an intention-to-treat, per-protocol, or other analysis population. Nor does it report an interim-analysis plan, stopping rule, or detailed treatment of protocol deviations. These details matter because different analysis populations or missing-data assumptions can affect a treatment estimate. Their absence does not invalidate the posted result, but it limits independent assessment of how the analysis was conducted.

14. 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 posted serious adverse event figures are 0 in the group receiving midazolam, hydroxyzine, and meperidine and 0 in the group receiving midazolam and hydroxyzine. The other adverse event figures are also 0 in each group, and deaths are recorded as 0 in each group. The registry lists 20 participants at risk for serious and other adverse events in the meperidine group and 17 in the group without meperidine.

These are recorded counts for this trial, not proof that the regimens have no adverse effects or that the groups have identical safety. Zero events in a trial can coexist with uncertainty about uncommon events, and the registry record does not report detailed event definitions, collection procedures, or the adverse-event observation period. It also lists no serious adverse event terms.

Safety counts should be considered separately from the primary behavioral success endpoint. They do not establish a treatment benefit or an overall safety comparison, particularly without fuller information on event ascertainment and follow-up. The figures describe what the registry records for these groups and outcomes only.

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

The primary comparison describes behavioral success at the end of a dental procedure under the registry's rating definition. The observed success counts are similar in scale across the two groups, and the reported risk-difference estimate is close to zero. The confidence interval is broad and crosses zero, while the unadjusted p-value is 0.9. Together, these results show that the trial did not precisely determine the direction or size of the difference in the defined outcome.

The result does not prove that the regimens are the same. A failure to identify a clear difference is not equivalent to evidence of equivalence. Demonstrating equivalence or non-inferiority requires a prespecified margin and an analysis designed to test that question; neither is reported in the registry record. The interval's breadth means that effects favoring either group remain compatible with the posted data.

The result also does not establish that either regimen is effective or ineffective in a general clinical sense. It reports a comparison in this randomized trial for a particular behavioral classification, in children undergoing dental procedures, at the stated site. It does not directly answer questions about other patient groups, treatment settings, outcomes, or follow-up periods.

The posted safety figures record no serious adverse events, other adverse events, or deaths in either group. Those counts should not be interpreted as proof of no risk. Detailed safety methods and event follow-up are not reported in the registry record. Similarly, the secondary temperament objective cannot be resolved from the posted primary outcome comparison, and detailed results for it are not reported in the registry record.

The most defensible reading is therefore limited: the posted aggregate data show a small observed contrast in success proportions, with substantial uncertainty around the treatment difference. They do not establish equivalence, settle safety, or answer the unreported secondary analyses.

16. Why This Trial Matters Statistically

This trial illustrates the difference between an observed estimate and a precise conclusion. The point estimate for the behavioral outcome is close to zero, but the confidence interval is wide enough to include effects in either direction. Reading only the point estimate or the p-value would miss the uncertainty that is central to interpreting the comparison.

It also highlights why a nonsignificant result should not be treated as proof of equivalence. The trial's stated objective concerns whether a regimen without meperidine produces the same behavioral success outcomes as one with meperidine. The posted comparison does not establish sameness: no equivalence or non-inferiority margin is reported, and the interval remains broad. The distinction is important whenever a study's scientific question concerns whether treatments are sufficiently similar rather than whether a conventional difference test is statistically significant.

The endpoint itself adds an interpretive consideration. Several Houpt ratings are combined into each of two categories. That makes the outcome easy to summarize as counts, but it conceals variation among ratings within each category. Readers should understand the operational definition before generalizing the result to broader concepts such as overall procedural experience.

Finally, the registry illustrates the limits of a compact results record. The aggregate counts and comparison are informative, yet details about masking, missing data, analysis populations, multiplicity, and outcome assessment are not reported in the registry record. Such details help readers judge how robustly the posted estimate represents the randomized comparison. Statistical interpretation depends not only on a point estimate, but also on its precision, outcome definition, and analysis context.

17. 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 posted group counts are limited in scale, and the confidence interval for the primary risk difference is wide. This leaves substantial uncertainty about both the direction and size of the treatment difference. The observed estimate should not be treated as a precise measure of what would occur in a broader population.

The registry record does not report detailed eligibility criteria beyond the age range and pediatric dental setting described in the trial title and summary. It also does not report baseline characteristics, so readers cannot assess how the groups compared on measured factors that might relate to behavior or sedation outcomes. The masking field is single, but the identity of the masked parties and the masking procedures are not reported in the registry record.

Further limitations concern outcome assessment and analysis. The primary endpoint is a binary classification of a behavioral rating, but details on assessor training, rating reliability, and handling of missing or uncertain ratings are not reported. The record does not identify the analysis population, missing-data approach, or planned multiplicity strategy. It does not report a protocol-level sample-size justification or the original design assumptions.

The safety results are limited to posted counts. Event definitions, collection methods, and follow-up duration are not reported in the registry record, so zero recorded events cannot resolve the possibility of events that are uncommon or not captured. Detailed results for the secondary temperament outcome are also not reported. These limitations leave important aspects of the trial's execution and interpretation unclear, in addition to the statistical uncertainty in the primary estimate.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Comparing Pediatric Dental Oral Sedation Outcomes With and Without Meperidine in Children Aged 3-7 Years — NCT04068948.
• Registry record last updated 2024-01-24; status last verified 2023-12.
• Results first posted 2023-12-05.
• 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.

21. Record Summary

NCT04068948 is a completed randomized, parallel-group Phase 4 trial sponsored by University of Washington. It compares oral midazolam and hydroxyzine with the same regimen plus meperidine in children undergoing dental treatment. The registry lists enrollment of 37, a single-masking designation, and a primary outcome of successful sedation at procedure completion.

Success was defined as an Excellent, Very Good, or Good Houpt Behavior Rating Scale result. The posted counts are 11 of 20 participants in the meperidine group and 9 of 17 in the group without meperidine. The reported unadjusted p-value is 0.9, and the risk-difference confidence interval includes zero and is broad. The registry records no serious adverse events, other adverse events, or deaths in either group.

Detailed analysis methods, missing-data procedures, analysis populations, and secondary temperament results are not reported in the registry record. The primary comparison is therefore best read as an imprecise estimate of the defined behavioral outcome, not as proof of equivalence or a complete account of comparative safety.