Success Rate of 4 Injection Protocols for Mandibular First Molars With Symptomatic Irreversible Pulpitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Success Rate of 4 Injection Protocols for Mandibular First Molars With Symptomatic Irreversible Pulpitis (NCT04929522), a randomized na study. The primary outcome is Number of Participants With Successful Injection Technique Assessed by Verbal Rating Scale (VRS).

2. Clinical Question

3. Trial Design

The registry record describes a completed, randomized, triple-blind, parallel-group clinical trial with four injection-protocol arms. Enrollment was 160 participants, with 40 assigned to each arm in the posted outcome results. The record identifies Ain Shams University as the sponsor. The phase is listed as not applicable.

The comparator was a standard inferior alveolar nerve block (IANB). The other arms combined IANB with an intra-osseous injection (IANB+IO), a periodontal ligament injection (IANB+PDL), or buccal infiltration (IANB+BI). All four arm descriptions refer to Articaine HCL 4% with 1:100,000 adrenaline and 3.6 ml. The record describes the trial as triple-blind but does not report which roles were masked or how masking was maintained.

The primary outcome counted participants meeting the registry's success definition, assessed 15 minutes from delivery of anesthesia. The reported procedure-related context includes rubber dam placement, caries removal, access preparation and pulpectomy. A secondary outcome concerned changes in heart rate before, during and after injection. Although the record lists two outcome measures, posted secondary results are not included in the information available in the registry record.

The registry lists the study as completed and gives enrollment and study timing information. The original design rationale, including the trial's own sample-size assumptions, is not reported in the registry record. The record also does not report the randomization method, allocation concealment process, detailed analysis populations, or the identity of the blinded parties.

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 Injection Technique Assessed by Verbal Rating Scale (VRS), measured over 15 minutes from delivery of anesthesia.

The primary endpoint is a count of participants classified as having a successful injection technique. Assessment was described as occurring 15 minutes from delivery of anesthesia. Participants rated pain on a scale with scores from 0 to 3: no pain, mild pain, moderate pain, or severe pain. Success was defined as a VRS score of 0 or 1; other scores were classified as failure. The registry outcome description also refers to NRS when describing how success was determined during treatment. That VRS/NRS discrepancy is not resolved in the registry record.

A count endpoint is useful for expressing how many participants in each arm met a stated criterion, rather than describing an average pain score. It permits direct comparison of the proportion meeting the binary success definition across protocols. In general, dichotomizing a rating scale makes the result easier to interpret as success versus failure, but it also discards information about differences among scores within those categories. That is a general property of binary endpoints, not a separate finding from this trial.

The posted counts were 16 of 40 for standard IANB, 37 of 40 for IANB+IO, 29 of 40 for IANB+PDL, and 26 of 40 for IANB+BI. These are outcome counts, not pain-score distributions. The record does not provide the individual score data or further detail on the endpoint assessment process.

7. Results Posted in the Registry

• IANB+IO: 92.5% (37/40) versus 40.0% (16/40) on control; risk difference 52.5 percentage points (95% CI 35.3 to 69.7), risk ratio 2.31 (1.57–3.41); unadjusted two-proportion z-test p = <0.001.
• IANB+PDL: 72.5% (29/40) versus 40.0% (16/40) on control; risk difference 32.5 percentage points (95% CI 12.0 to 53.0), risk ratio 1.81 (1.19–2.77); unadjusted two-proportion z-test p = 0.003.
• IANB+BI: 65.0% (26/40) versus 40.0% (16/40) on control; risk difference 25.0 percentage points (95% CI 3.8 to 46.2), risk ratio 1.62 (1.04–2.53); unadjusted two-proportion z-test p = 0.025.

8. Statistical Interpretation

9. Statistical Methods Explained

For a binary endpoint, each participant is placed in one of two categories: successful or not successful. The analysis can then compare the fraction of participants in each arm who met the success definition. Here, success was defined as reporting VRS 0 or 1, and the endpoint is reported as the number of successful participants in each arm. The posted denominators are 40 in each arm.

What does a risk difference express?

A risk difference subtracts the observed success proportion in the reference arm from the observed success proportion in a comparison arm. A value above zero means the observed proportion was higher in the comparison arm; a value below zero would mean it was lower. The posted risk differences are 0.525 for IANB+IO, 0.325 for IANB+PDL, and 0.25 for IANB+BI, each compared with standard IANB. These estimates are absolute differences on the proportion scale, rather than relative measures.

The registry record also includes relative risk and odds ratio estimates. A relative risk compares the proportions directly, while an odds ratio compares the odds of success. These measures answer related but different questions and can have different numerical scales. The risk difference is often straightforward to interpret as an absolute contrast, while relative measures express a comparison relative to the reference arm. The posted relative risks are 2.312, 1.812 and 1.625 for IO, PDL and BI, respectively; the corresponding odds ratios are 18.5, 3.955 and 2.786. These estimates should not be treated as interchangeable with the risk differences.

What do the confidence intervals and p-values add?

A confidence interval describes a range of values reasonably compatible with the observed data under the statistical model and method used. It communicates precision as well as the direction of an estimate. The posted 95% intervals for the risk differences are 0.353 to 0.697 for IO, 0.120 to 0.530 for PDL, and 0.038 to 0.462 for BI. Each interval is above zero, while their different widths indicate differing degrees of precision.

A p-value measures how unusual results at least as extreme as those observed would be under a specified null model, assuming the model and analysis conditions hold. It does not measure the probability that the null hypothesis is true, nor does it describe the size or clinical importance of an effect. The posted p-values are unadjusted: <0.001, 0.003 and 0.025 for IO, PDL and BI. The registry record does not report whether the analyses were prespecified, which statistical test was used, or whether an adjustment for multiple comparisons was planned or performed.

Why does the binary definition matter?

Turning a pain rating into success or failure focuses the analysis on crossing the stated threshold: no pain or mild pain qualifies as success. As a general statistical matter, a binary threshold can simplify comparisons, but it loses information about how participants' scores are distributed within each category. A participant with no pain and a participant with mild pain count alike as successful under this definition. The record's outcome wording refers both to VRS and NRS, and does not clarify that inconsistency. Interpretation therefore depends on the registry's stated threshold and the reported counts.

What do the analysis details not tell us?

The posted comparisons use equal arm sizes of 40 and identify standard IANB as the reference. The registry record does not report covariate adjustment, a model specification, assumptions checks, handling of missing observations, an intention-to-treat definition, or a per-protocol analysis. These details matter because they explain how the estimates were obtained and which participants were included. They should not be inferred from the randomized, triple-blind description alone.

General statistical caution also applies to interpreting multiple outcomes and comparisons. Repeated testing can increase the chance of at least one small p-value under a broader null situation unless the analysis plan addresses multiplicity. The trial reports three primary-outcome contrasts in the available results, but how the original investigators handled that issue is not reported in the registry record. The posted p-values are therefore best interpreted as individual, unadjusted comparisons.

10. Confidence Intervals and Precision

The risk-difference confidence intervals indicate both direction and uncertainty around the estimates. For IANB+IO versus standard IANB, the estimate is 0.525, with a 95% confidence interval from 0.353 to 0.697. For IANB+PDL, the estimate is 0.325, with an interval from 0.120 to 0.530. For IANB+BI, the estimate is 0.25, with an interval from 0.038 to 0.462. Each interval lies above zero, but none identifies a single exact value for the underlying difference.

In general, a confidence interval is a range generated by a statistical method that, over repeated use under its assumptions, would cover the true value at the stated rate. It is not a guarantee that the particular interval contains the true value, and it does not mean that all values in the interval are equally likely. The registry record does not name the interval method or report model diagnostics.

The IO interval is narrower than the PDL interval, and the BI interval extends closer to zero. These features describe precision in the posted estimates; they do not establish that one protocol is superior to another. Each contrast is against standard IANB, and the registry record does not provide confidence intervals for direct comparisons between combination protocols. The BI estimate, in particular, spans a range from a comparatively small positive difference to a substantially larger one, so its precise magnitude remains uncertain.

Sample size, event frequency and the analysis method can all affect interval precision as a general matter. With 40 participants in each arm, the posted results offer finite-sample estimates, not exact population values. Confidence intervals also do not account for every potential source of uncertainty, such as outcome measurement ambiguity or unreported analysis choices. The VRS/NRS wording inconsistency and missing details about missing data and analysis populations therefore remain relevant when assessing how fully the interval captures uncertainty.

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 sample-size planning figures are illustrations based on the observed differences, not the trial's original design calculations. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses the stated fraction of the observed effect as the effect to detect. These are participants per arm, not total participants or total events.

The 80% power column gives the number of participants per arm estimated to provide an 80% chance of detecting the specified effect under the planning assumptions, if that effect and the assumptions were correct. The 90% power column gives the corresponding number per arm for a 90% chance. Power describes a design's long-run detection probability under a specified effect and statistical model; it does not describe the probability that a result is true.

For example, the planning rows consider detecting 100%, 75% or 50% of each observed effect. As the targeted effect becomes smaller, more participants per arm are needed in the displayed scenarios. The required counts also differ by comparison because the observed effects differ. The registry record does not report the original trial's sample-size justification or planning assumptions.

These figures are planning illustrations calculated from the observed effects, not observed power. The 80% and 90% values should not be read as a retrospective measure of the trial's success or as evidence that the trial was adequately designed. Actual future studies may use different assumptions, outcomes, analysis methods or target effects, which would lead to different planning estimates.

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 = 0.400; treatment proportion p₁ = 0.925; average p̄ = 0.663.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6687 = 1.3107.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5562 = 0.4681.
4. n = (1.3107 + 0.4681)² / (0.5250)² = 11.5, rounded up to 12 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 <- 0.4                          # control proportion
p1 <- 0.925                          # 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(4929522)
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 = 12 (80% power), 15 (90% power)
 75% of observed effect: n per arm = 24 (80% power), 31 (90% power)
 50% of observed effect: n per arm = 56 (80% power), 74 (90% power)
power.prop.test: 11.5 
Simulated power at n = 12 per arm: 0.846 (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

Three primary-outcome comparisons are posted, each contrasting one combination protocol with standard IANB. Their p-values are unadjusted. When several statistical tests are performed, the chance of obtaining at least one small p-value can increase under a general setting where all null hypotheses hold. Statistical plans can address this through prespecified testing hierarchies or multiplicity adjustments, but whether any such approach was specified or used is not reported in the registry record.

The record does not report a detailed missing-data plan, the number of participants with missing primary outcomes, or how any such observations were handled. Although 40 participants are listed for each arm, the posted results do not explain whether those counts represent everyone randomized, everyone assessed, or a particular analysis population. The record also does not describe an intention-to-treat population, a per-protocol population, or how protocol deviations were treated. Those distinctions can matter in a randomized trial because they define who contributes to the estimates.

Analysis methods beyond the posted effect estimates and p-values are not reported in the registry record. In particular, the statistical test or model, any covariate adjustment, assumptions checks, and any sensitivity analyses are not described. The primary-outcome wording is also not entirely consistent: it names the verbal rating scale but later refers to NRS when describing the success assessment. How that terminology was resolved during data collection or analysis is not reported in the registry record.

The registry lists one secondary outcome concerning heart rate before, during and after injection, but secondary results are not posted in the information available. Thus, conclusions about that outcome cannot be drawn from the posted primary comparisons. These absences do not show that the procedures were or were not carried out; they limit what can be assessed from the registry record.

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 1% reporting threshold.

The serious adverse event figures report zero serious events among 40 participants at risk in each of the four arms. The record also reports zero other adverse events among 40 participants at risk in each arm, and zero deaths in every arm. No serious adverse event terms are listed.

These are event counts in the registry record, not proof that no adverse events could occur. In general, observing zero events in a finite group does not establish that the underlying risk is zero. The posted figures also do not provide event descriptions, severity grading beyond the serious-versus-other categories, timing, or a causal assessment. The record does not report whether there were participants lost to safety follow-up or the duration of safety monitoring.

The safety counts should be read alongside the outcome results as registry-reported events for the enrolled groups. They do not support conclusions beyond the recorded counts and the limitations of the available safety information.

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

The posted primary results describe higher observed success counts in each of the three combination-protocol arms than in the standard IANB arm, using the registry's success definition of VRS 0 or 1. The largest posted risk difference is for IANB+IO, followed by IANB+PDL and IANB+BI. Each estimate is a comparison with standard IANB; the trial results do not directly rank the combination protocols against one another.

The confidence intervals quantify uncertainty around the estimated differences, and the posted intervals all lie above zero. They nevertheless span ranges of possible effect sizes, particularly for the PDL and BI comparisons. The unadjusted p-values indicate the results under individual statistical comparisons, but multiplicity handling is not reported. These statistics describe the posted data under the stated endpoint; they do not, on their own, establish clinical importance.

The result applies to the participants and procedures represented in this trial record. Enrollment was 160, with 40 participants per arm in the posted outcome results. The registry record does not provide enough detail about eligibility criteria, participant flow, missing observations, analysis populations, or external settings to determine how broadly the findings may apply. The use of a binary pain threshold also means the counts do not show the full distribution of pain ratings.

The registry's endpoint wording alternates between VRS and NRS, a measurement detail that remains unresolved. The record also does not include the original sample-size rationale or detailed statistical analysis plan. These limitations call for a bounded reading: the posted counts, effect estimates and intervals summarize the recorded comparisons, while questions about measurement, analysis choices, multiplicity and wider applicability remain open.

The safety record lists no serious adverse events, other adverse events or deaths in the posted groups. Those counts are descriptive and do not establish an absence of risk. No medical decision should be based on these statistical results alone.

16. Why This Trial Matters Statistically

This trial is statistically instructive because it reports a binary endpoint across four randomized arms and gives separate contrasts against one reference group. The endpoint converts a pain rating into a success/failure classification. That makes the primary count easy to interpret, while also making the exact threshold important: no pain or mild pain counted as success, and the other categories did not.

The three risk differences illustrate why absolute contrasts can aid interpretation. Each estimates the difference in observed success proportions relative to standard IANB, and each has a confidence interval that expresses uncertainty in that contrast. The estimates and intervals are more informative than a p-value alone because they describe both magnitude and precision. At the same time, they should not be read as direct evidence that one combination protocol outperforms another, since those head-to-head estimates are not posted.

The trial also highlights the issue of multiple comparisons. Three unadjusted p-values accompany the primary endpoint contrasts. Without a reported multiplicity plan, readers should distinguish the posted individual tests from a prespecified family-wide conclusion. The record's incomplete account of analysis populations and missing data further limits assessment of the statistical analysis.

Finally, the outcome description uses both VRS and NRS terminology, and the original sample-size rationale is not reported. These are practical reminders that statistical estimates depend on clear outcome definitions and transparent design and analysis documentation. The numerical comparisons can be described, but a full assessment requires details that the registry record does not report.

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.

Several trial-specific limitations affect interpretation of the posted results. The primary outcome description is internally inconsistent about the rating instrument: it defines success using VRS but also says success was determined by NRS during treatment. The registry record does not clarify which measure governed the reported classifications. The clinical activities named in the description include rubber dam placement, caries removal, access preparation and pulpectomy, but no further detail on endpoint assessment or timing within those activities is reported.

The registry lists 40 participants in each arm but does not report a participant-flow account, missing outcome counts, analysis population definitions, or handling of protocol deviations. It therefore is not possible to determine from the record whether every randomized participant contributed to the endpoint counts. The statistical test or model and any covariate adjustment are also not reported.

Each combination protocol is compared with standard IANB, but direct comparisons among the three combination arms are not posted. The three reported p-values are unadjusted, and the registry record does not say whether multiplicity was considered in the original plan. No original sample-size justification is reported, so the planning illustrations based on observed effects should not be mistaken for evidence about the trial's prospective design.

Although the study is described as triple-blind, the record does not identify who was masked or explain how masking was maintained. It also does not report detailed eligibility criteria or enough information to evaluate how representative the enrolled participants were of other clinical settings. The secondary heart-rate outcome is listed without posted results. Safety reporting contains counts but no further detail on monitoring period, event descriptions or follow-up completeness.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Success Rate of 4 Injection Protocols for Mandibular First Molars With Symptomatic Irreversible Pulpitis — NCT04929522.
• Registry record last updated 2021-10-07; status last verified 2021-10.
• Results first posted 2021-10-07.
• 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 record describes a completed randomized, triple-blind, parallel-group trial comparing four injection protocols for mandibular first molars with symptomatic irreversible pulpitis. Enrollment was 160, with 40 participants listed in each arm. The primary endpoint counted participants classified as successful based on a pain rating 15 minutes after anesthesia delivery.

Successful counts were 16 of 40 for standard IANB, 37 of 40 for IANB+IO, 29 of 40 for IANB+PDL, and 26 of 40 for IANB+BI. The posted risk differences versus standard IANB were 0.525, 0.325 and 0.25, respectively. Each reported 95% confidence interval was above zero; the p-values were unadjusted.

The registry lists a secondary heart-rate outcome but does not include its results in the record described. It reports zero serious adverse events, other adverse events and deaths in each arm. The original sample-size rationale, multiplicity approach, missing-data handling and detailed analysis plan are not reported in the registry record.