Effectiveness of Customized Handle Toothbrush: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effectiveness of Customized Handle Toothbrush (NCT04845633), a randomized na study. The primary outcome is Clinical Plaque Evaluation of Healthy Children and Down Syndrome of Both Groups at the Baseline.

2. Clinical Question

The research question is motivated by the practical challenge that mental, physical, or motor difficulties may make oral care more difficult for some people. The study description proposes a customized grip as a possible way to support independent brushing. The posted outcome data, however, address plaque scores rather than independence, ease of use, or the process of customizing a handle.

The registry also lists plaque evaluation after 1 week as a secondary outcome. Those later measurements can describe the observed pattern after the study period, but they do not alter the timing of the registered primary outcome. Interpretation depends on keeping baseline and follow-up evidence distinct and on recognizing that the comparison groups include both different toothbrushes and different populations.

The record does not report a direct customized-versus-conventional treatment contrast within each population for every endpoint. In particular, the posted baseline comparisons use the healthy customized-handle group as the reference for other arms. Differences involving children with Down syndrome therefore combine differences in population and toothbrush assignment, rather than isolating a toothbrush effect.

3. Trial Design

The registry describes a randomized, double-masked, parallel trial with an enrollment of 48. It lists four arms: healthy children using a conventional toothbrush, healthy children using a toothbrush with a customized handle, children with Down syndrome using a conventional toothbrush, and children with Down syndrome using a toothbrush with a customized handle. Each arm has a posted sample size of 12.0. The record lists the phase as NA and the status as completed.

The sponsor is Damascus University. The recorded study start is 2021-04-09, and the primary completion date is 2021-05-14. The conditions listed are Dental Plaque, Dental Prophylaxis, and Dental Care. The brief description frames the customized handle as a modification intended to address difficulties with oral care and support independent brushing. The arm descriptions themselves contain no additional procedural detail.

Randomized allocation and a parallel model are stated in the record, but the method used to generate the allocation sequence, conceal assignments, or maintain balance is not reported in the registry record. Although double masking is registered, the identities of the masked parties and how masking was implemented are not reported. The record also does not describe the conventional toothbrushes, the construction or fitting of customized handles, brushing instructions, adherence monitoring, or co-interventions.

The record lists one primary outcome measure at baseline and one secondary outcome measure at 1 week. It does not report the original sample-size justification, the planned statistical analysis, or an analysis population definition. The registry contains no reported analyses. Accordingly, the posted arm summaries and recalculated pairwise comparisons should be read as the available numerical account, not as a complete report of the study protocol or its analysis procedures.

The main design distinction for interpretation is that the baseline endpoint occurs before brushing. These measurements can characterize starting plaque scores but cannot establish the effect of a toothbrush used during the study. The later endpoint provides a follow-up snapshot, though the registry record does not provide sufficient details to reconstruct the intended treatment-effect analysis.

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 Clinical Plaque Evaluation of Healthy Children and Down Syndrome of Both Groups at the Baseline, measured over Baseline: Pre-brushing.

The primary endpoint is the clinical plaque evaluation at baseline, described as pre-brushing. It is a continuous score reported as a mean with standard deviation. Plaque is disclosed and evaluated on buccal and lingual non-restored tooth surfaces using the Turesky Modification of the Quigley-Hein Plaque Index. The index ranges from 0 to 5: lower scores indicate less plaque, while higher scores indicate more plaque. The description gives examples ranging from no plaque to plaque covering two-thirds or more of the tooth crown side. Scores across examined surfaces are combined into a mouth-level index by dividing the total score by the number of examined surfaces.

This measure is used to quantify visible plaque burden in a standardized clinical form. A continuous score retains gradations in plaque coverage rather than reducing assessment to a yes-or-no classification. The registry describes examination of all teeth and specifies the surfaces assessed, which gives context for what the resulting score represents. The measure is a clinical plaque index; it is not itself a measure of brushing independence, comfort, usability, or long-term oral health.

Because the primary endpoint is explicitly measured before brushing, the posted primary means are baseline descriptions. They may help readers understand whether the groups began with similar or different plaque levels, but they do not measure change attributable to the customized handle or conventional toothbrush. The registry's after-1-week plaque evaluation is a separate secondary outcome and should not be substituted for the baseline primary endpoint.

The record does not report further endpoint details such as assessor training, assessor reliability, or how missing tooth surfaces would be handled. Those details would help assess measurement consistency and the exact construction of the mouth-level score.

7. Results Posted in the Registry

• Healthy Children Using Conventional Toothbrush: mean 3.19 versus 3.05 on control; difference 0.14 (95% CI -0.25 to 0.53), standardized effect d = 0.29; z-test p = 0.484.
• Children With Down Syndrome Using Conventional Toothbrush: mean 3.63 versus 3.05 on control; difference 0.58 (95% CI 0.26 to 0.90), standardized effect d = 1.46; z-test p = <0.001.
• Children With Down Syndrome Using Toothbrush With Customized Handle: mean 3.41 versus 3.05 on control; difference 0.36 (95% CI 0.05 to 0.67), standardized effect d = 0.94; z-test p = 0.021.

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.

Clinical Plaque Evaluation of Healthy Children and Down Syndrome of Both Groups After a Week

• 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:
  • Healthy Children Using Toothbrush With Customized Handle: mean 0.38 versus 1.41 on control; difference -1.03 (95% CI -1.36 to -0.70), standardized effect d = -2.51; z-test p = <0.001.
  • Children With Down Syndrome Using Conventional Toothbrush: mean 2.23 versus 1.41 on control; difference 0.82 (95% CI 0.44 to 1.20), standardized effect d = 1.74; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Healthy Children Using Toothbrush With Customized Handle than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Children With Down Syndrome Using Conventional Toothbrush than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists plaque evaluation after 1 week as a secondary endpoint. Across the four arm means, scores are lower in the customized-handle groups than in the conventional-toothbrush groups within each population. This overall descriptive pattern differs from the primary endpoint's role: the primary outcome is a pre-brushing baseline measure, whereas the secondary outcome is measured later. The two endpoints therefore describe different stages of the study and cannot be treated as interchangeable estimates.

The secondary comparisons posted do not provide a full set of direct treatment contrasts within both populations. One compares healthy children assigned to the customized handle with healthy children assigned to the conventional toothbrush. The other compares children with Down syndrome using a conventional toothbrush with healthy children using a conventional toothbrush, so it changes population rather than isolating toothbrush type. A direct customized-versus-conventional comparison among children with Down syndrome is not reported in the comparisons.

As a result, the pattern across the secondary arm summaries can be noted, but the registry record does not support a complete inferential comparison of customized and conventional handles for each population. Nor does it report an analysis comparing change from baseline, which could address starting differences in plaque scores. The secondary outcome adds follow-up information, but it does not resolve those limitations in the analysis available.

Unadjusted secondary findings carry less weight because they are not accompanied by a reported multiplicity plan or a prespecified hierarchy of outcomes and contrasts. When several outcomes or comparisons are considered, some may appear persuasive by chance. The registry reports no analyses, so the statistical summaries are recalculated from arm-level results rather than drawn from a documented sponsor analysis. The appropriate reading is descriptive and cautious, not a conclusive test of efficacy.

The secondary endpoint is also limited to plaque score at 1 week. The record does not report longer-term follow-up, adherence, independent brushing, ease of handling, or other outcomes that would address the broader aims described in the study summary. It is therefore a narrow clinical measure of plaque at a particular follow-up point, rather than a complete evaluation of the proposed practical benefit.

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

• Clinical Plaque Evaluation of Healthy Children and Down Syndrome of Both Groups After a Week

9. Statistical Interpretation

10. Statistical Methods Explained

Clinical trial results often combine descriptive summaries, comparisons between groups, uncertainty intervals, and tests of statistical compatibility. These quantities answer related but distinct questions. A group mean describes the average observed score; a standard deviation describes variation among observations; a confidence interval describes uncertainty around a contrast; and a p-value assesses how compatible the data are with a specified null model. None of these, by itself, establishes that a treatment caused an outcome difference.

What does a mean and standard deviation describe?

The primary outcome is a continuous plaque score, so the registry reports each group's mean and standard deviation. The mean gives the central average on the score scale. The standard deviation describes how dispersed individual scores are around that average. A mean difference expresses the contrast between two group means, with its sign depending on which group is used as the reference. For the baseline comparisons, the healthy customized-handle group is the reference. A positive contrast therefore means the other group's posted mean is higher than that reference mean; a negative contrast would mean it is lower.

As a general statistical point, standard deviation is not the same as standard error. The standard deviation describes participant-level variability, whereas the standard error describes the uncertainty in an estimated mean. Standard errors tend to become smaller when estimates are based on more information, though that general relationship does not determine whether a study was adequately designed. The record reports standard deviations for the arms and the recalculated comparisons include standard errors for the group means.

How should a confidence interval be read?

A confidence interval gives a range of values that are reasonably compatible with the data under the method's assumptions. In repeated use, a confidence-interval procedure has a stated coverage property; it is not the probability that the true effect lies in one particular interval. A narrow interval indicates more precise estimation than a wide interval, all else equal. A wide interval may include both little or no difference and differences that could matter, leaving greater uncertainty about the size and direction of the contrast.

For a difference in means, an interval that includes zero is compatible with no group difference under the interval's calculation. An interval entirely above or below zero indicates that the corresponding unadjusted calculation places the contrast on one side of zero. That does not show that the contrast is causal, clinically important, or free from bias. The outcome timing, group comparability, analysis choices, and missing information remain important to interpretation.

What does an unadjusted p-value mean?

A p-value is calculated under a statistical model that assumes a null hypothesis, commonly no difference for the contrast being tested. It describes how unusual data at least as incompatible with that null would be under the model. A small p-value is not the probability that the null hypothesis is true, and it does not quantify the chance that a finding occurred by luck in a simple everyday sense. It also does not measure the size or clinical importance of a difference.

The posted p-values are unadjusted, meaning they do not account for the presence of other tested comparisons. When many contrasts are examined, the chance of at least one small p-value can increase even if no true differences exist. The registry does not report a multiplicity procedure or the intended hierarchy of tests, so the p-values should be interpreted as individual, exploratory pieces of evidence rather than as an established family-wise conclusion.

Why is the baseline comparison not a treatment-effect estimate?

A treatment effect concerns outcomes under different treatment assignments, ideally compared within a population and at a time when the intervention has been applied. The registered primary measure is baseline, before brushing. It describes starting plaque scores rather than post-treatment outcomes. Moreover, the posted baseline contrasts compare the healthy customized-handle group with groups that can differ in both population and toothbrush assignment. Those contrasts cannot separate a population difference from a toothbrush difference.

The 1-week endpoint is temporally later and includes group means that can be described by assignment. However, the record does not report a complete direct treatment contrast within each population or an adjusted analysis. In general, a randomized design can support causal comparison when allocation, follow-up, and analysis are appropriately carried out, but the registry fields alone do not document all those details. The observed summaries should not be promoted beyond what their structure supports.

Why can over-dispersion matter?

As a general statistical concept, over-dispersion occurs when observed variability exceeds what a model assumes. If a model understates variability, standard errors may be too small, confidence intervals too narrow, and p-values too optimistic. That concern is especially relevant when a statistical model makes assumptions about the distribution of an outcome. The posted plaque summaries use means and standard deviations, but the registry does not report diagnostic checks or a model-based analysis that would establish whether over-dispersion was assessed. No conclusion about over-dispersion in this trial can therefore be drawn from the record.

The plaque index has a bounded score scale, and its distributions could matter for the suitability of a particular model. General statistical practice is to consider the measurement scale, distribution, sample size, and analysis plan together. The registry record does not report participant-level data, distribution plots, model diagnostics, or a prespecified method, so it is not possible to evaluate those features from the posted summaries alone.

What is the role of recalculation?

The displayed pairwise estimates, confidence intervals, and p-values are recalculated from posted summary statistics. Such calculations are simple, unadjusted comparisons and need not match a sponsor's planned analysis, which may have used a different model or additional information. The registry does not report sponsor analyses, and no discrepancy is flagged. The recalculated values are useful for reading the summary data consistently, but they cannot replace a prespecified analysis or resolve missing methodological details.

Finally, statistical significance and precision are not the same. A contrast can have an interval that excludes zero while still being estimated imprecisely in a practical sense, and a result that does not meet a significance threshold can still have an interval compatible with meaningful differences in either direction. Interpretation should consider the estimate, its interval, endpoint timing, design, multiplicity, and reporting completeness together.

11. Confidence Intervals and Precision

The baseline comparison of healthy children using a conventional toothbrush with the healthy customized-handle reference has a recalculated mean difference of 0.14 and a 95% confidence interval from -0.252 to 0.532. The interval crosses zero and spans values on either side of no difference, so the summary is compatible with a range of baseline contrasts. It is not precise enough to establish a clear direction for this comparison.

For children with Down syndrome using a conventional toothbrush, compared with the healthy customized-handle reference, the estimated difference is 0.58, with a 95% confidence interval from 0.263 to 0.897. For children with Down syndrome using a customized-handle toothbrush, the corresponding difference is 0.36, with a 95% confidence interval from 0.054 to 0.666. Both intervals are above zero, but both compare different populations with the reference group. They should not be interpreted as estimates of a toothbrush effect.

At 1 week, the posted recalculated comparison between healthy children using a customized handle and healthy children using a conventional toothbrush is -1.03, with a 95% confidence interval from -1.358 to -0.702. The interval is below zero, indicating lower mean plaque scores for the customized-handle group in this unadjusted contrast. It is still a secondary result, and the registry does not report a full analysis plan or adjusted treatment estimate.

For any interval, width reflects statistical precision under the calculation method, not freedom from bias or certainty about clinical importance. The record does not report assessor reliability, missing-data handling, or a sponsor analysis that could clarify uncertainty beyond the summary-based calculations. The confidence intervals consequently describe only the recalculated contrasts and their model-based sampling uncertainty.

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 planning figures are participants per arm, not total events. They are illustrations based on the observed effect and are not the trial's original enrollment justification. The planning 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 the stated fraction of the observed effect. The trial's own original design assumptions are not reported in the registry record.

The 80% power column gives the estimated participants per arm under those assumptions for a design with an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column gives the corresponding planning estimate for a 90% chance. These are design calculations, not probabilities that the observed finding is true, and they do not describe the achieved power of this completed trial.

The rows consider planning for 100%, 75%, and 50% of the observed effect. The smaller the effect a future study is intended to detect, the more participants per arm it generally needs, because a smaller signal is harder to distinguish from random variation. The figures can vary substantially across the posted contrasts because the observed effects and variability differ.

These sample-size estimates should be treated cautiously. They use effects observed in the current study, which may be unstable, particularly in small groups, and they assume a simplified comparison between two equally allocated arms. They do not account for unreported design features such as multiple comparisons, loss to follow-up, clustering, or a different primary analysis. They are planning illustrations, not observed power.

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 = 0.140; pooled standard deviation σ = 0.490.
2. n = 2 × (1.96 + 0.842)² × 0.490² / 0.140² = 192.4, rounded up to 193 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 <- 0.14                      # observed difference in means
sigma <- 0.490102030193714                     # 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(4845633)
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 = 193 (80% power), 258 (90% power)
 75% of observed effect: n per arm = 343 (80% power), 458 (90% power)
 50% of observed effect: n per arm = 770 (80% power), 1,031 (90% power)
power.t.test: 193.3 
Simulated power at n = 193 per arm: 0.800 (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. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and one secondary outcome, with four outcome measures and no reported analyses. It does not report how many comparisons were planned, which comparison was primary for inference, or whether any adjustment for multiple testing was specified. The recalculated p-values are unadjusted. Without a documented testing strategy, they should not be read as if they came from a single, prespecified confirmatory test.

Multiplicity matters because the chance of finding at least one apparently notable result can rise when many hypotheses are tested. Adjustments or hierarchical strategies can address that issue, but no such approach is reported in the registry record. It would be inappropriate to infer that the trial did or did not use a procedure that the record does not describe.

The record does not report missing-data counts, reasons for missingness, imputation methods, or whether all randomized participants were included in each outcome analysis. It also does not define an intention-to-treat, per-protocol, or other analysis population. The arm summaries list 12.0 participants in each arm, but that does not establish how all assigned participants were handled in the analyses or whether any observations were unavailable for specific endpoints.

Other statistical-plan details are also not reported in the registry record. These include the original sample-size justification, planned models, covariate adjustment, treatment of baseline values, handling of departures from assumptions, and any interim analyses. No assumptions about these procedures can be made from the posted values alone.

These omissions affect how confidently the p-values and intervals can be treated as confirmatory. They do not demonstrate that the analyses were improperly conducted; they mean that the registry record does not provide enough information to assess those aspects. A complete trial report would be needed to understand the prespecified analysis, exclusions, missingness, and multiplicity decisions.

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

The posted data establish that plaque scores were recorded for the trial arms at baseline and after 1 week, and they describe the observed group means and variability. At baseline, group averages differed to varying degrees, including higher means in the Down syndrome groups than in the healthy customized-handle group. The primary outcome is pre-brushing, so these differences are descriptions of starting scores rather than evidence that one toothbrush caused a difference.

At 1 week, the customized-handle arm means are lower than the conventional-toothbrush arm means within each population. That pattern is notable as a descriptive observation. However, the registry's posted comparisons do not provide direct within-population contrasts for both groups, a baseline-adjusted treatment analysis, or a reported sponsor analysis. The pattern therefore does not by itself prove that the customized handle caused lower plaque scores.

The results also do not establish whether customized handles improved independent brushing, made brushing easier, or changed longer-term oral health. Those aims appear in the study description, but they are not measured by the posted plaque endpoint. The registry does not report the construction process, usability assessment, adherence, or follow-up beyond 1 week.

The recalculated confidence intervals quantify sampling uncertainty for specified contrasts under their calculation assumptions. They do not account for unreported sources of bias, incomplete outcome reporting, or multiplicity. A p-value does not state the probability that a treatment works, and a statistically notable contrast is not automatically clinically important. Conversely, uncertainty around a contrast does not establish that groups are equivalent.

Safety interpretation is also limited. The registry lists zero adverse events and deaths, but the event summaries also list zero participants at risk in every group. Those fields cannot be used to conclude that no adverse events occurred among the enrolled participants. Taken together, the record supports a cautious description of plaque-score patterns, not a definitive claim about treatment effectiveness, benefit, harm, or broader oral-health outcomes.

16. Why This Trial Matters Statistically

This trial is statistically interesting because it combines two populations with two toothbrush assignments, while the registered primary endpoint is measured before brushing. That structure makes it especially important to distinguish baseline group differences from treatment effects. A mean contrast may look like a comparison between toothbrushes, yet if the groups also differ in population or endpoint timing, it cannot isolate the handle's contribution.

The study also illustrates why follow-up contrasts need to match the question. The after-1-week means show an overall descriptive pattern, but the posted comparisons do not contain direct treatment contrasts for both populations. A complete analysis would need to make clear how randomized assignment, baseline plaque, follow-up values, and the planned comparisons were handled. Those details are not reported in the registry record.

Precision and multiplicity are relevant as well. The group sizes are modest, and the recalculated intervals vary in width. The unadjusted p-values should be interpreted in the context of multiple possible comparisons, especially because the registry does not report the intended inferential hierarchy or adjustment strategy. The sample-size illustrations demonstrate how planning needs depend on the effect size targeted, but they are not the study's original design rationale or evidence of achieved power.

For biostatisticians and clinical researchers, the central lesson is to align the endpoint, comparison, and scientific question before interpreting a result. A clear description of the analysis population, missing data, direct treatment contrasts, and multiplicity plan would make the evidence easier to evaluate. The posted record makes the numerical patterns visible while leaving those analytic details unresolved.

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 registry record provides limited information about the procedures used to implement randomization and masking. It does not identify the masked parties or describe allocation concealment, the customization process, brushing instruction, adherence, or assessor training. These omissions make it difficult to judge implementation and measurement consistency.

The primary endpoint is a baseline, pre-brushing plaque score, so it is not a post-treatment outcome. The follow-up endpoint is listed after 1 week, but the registry does not report a change-from-baseline or baseline-adjusted analysis. The posted comparisons also do not give a direct customized-versus-conventional contrast within each population for the secondary endpoint. Differences involving healthy children and children with Down syndrome may reflect population differences as well as assignment.

The registry lists no reported analyses, and does not report a statistical plan, original sample-size justification, missing-data approach, or analysis population. The recalculated estimates are based on summary statistics and are unadjusted. The record also does not describe the distribution of individual plaque scores or provide information on the reliability of clinical assessments.

Follow-up is limited in the posted record to 1 week. The study description's broader aims concerning independent oral care are not measured in the reported endpoints. Adverse-event fields list zero participants at risk alongside zero events, making safety conclusions unavailable from those entries. These are limitations of the available registry record; they do not establish what procedures or analyses may have been documented elsewhere.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Effectiveness of Customized Handle Toothbrush — NCT04845633.
• Registry record last updated 2021-08-12; status last verified 2021-06.
• Results first posted 2021-08-12.
• 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

The registry describes a completed, randomized, double-masked, parallel trial sponsored by Damascus University, with an enrollment of 48. It compares conventional and customized-handle toothbrush groups among healthy children and children with Down syndrome. The primary measure is a baseline, pre-brushing plaque score using the Turesky Modification of the Quigley-Hein Plaque Index; plaque evaluation after 1 week is listed as a secondary measure.

The posted arm summaries show baseline plaque means and follow-up means, with recalculated unadjusted comparisons. Baseline contrasts are descriptive and do not estimate toothbrush effects. The secondary means show a pattern of lower scores in customized-handle arms, but the posted comparisons do not provide direct treatment contrasts for both populations. The registry record contains no reported analyses or original statistical plan, and the adverse-event entries have zero participants at risk. Interpretation should therefore remain cautious and focused on the observed plaque-score summaries.