An Intervention to Reduce Risk Factors for Adolescent Pregnancy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for An Intervention to Reduce Risk Factors for Adolescent Pregnancy (NCT04222959), a randomized na study. The primary outcome is Sexual/Reproductive Health Behaviors.

2. Clinical Question

The registry describes preliminary effects as the study aim. The posted primary result is a count of participants meeting the outcome description, accompanied by an unadjusted risk-difference estimate and its confidence interval. The record does not report the criteria used to classify contraceptive use as consistent, or additional details about how the outcome was measured. Those details are not reported in the registry record.

3. Trial Design

The registry identifies NCT04222959 as a randomized, parallel-group trial with no masking. The study is titled “An Intervention to Reduce Risk Factors for Adolescent Pregnancy,” and its official title is “Girls Invest: A Mobile-Enabled Economic Empowerment Intervention for Girls.” The listed condition is behavioral changes, and the intervention is classified as behavioral. San Diego State University is the listed sponsor.

The intervention group received app trainings and a savings account with $100 deposited. The wait-list control group was to receive the intervention after the six-month follow-up. This timing defines the comparison at the primary endpoint: the intervention group had received Girls Invest, while the control group was still in the wait-list period. The registry reports a parallel model, but additional details about allocation procedures, concealment, or implementation are not reported in the registry record.

The registry lists enrollment as 240 and gives a start date of 2021-12-01, a primary completion date of 2023-12-28, and completed status. These registry entries describe the study record; the primary outcome counts are based on participants in the outcome-specific analysis population, rather than the enrollment figure. For the primary outcome, that population is described as participants who reported having had sex in the past six months.

The primary endpoint timeframe is six-month follow-up. The registry also lists feeling depressed and feeling worried, tense, or anxious as secondary outcomes. It records four outcome measures, while the posted results described in the record include the primary outcome and these two secondary outcomes. The record reports no analyses under its analyses listing. The original protocol’s statistical plan, including any planned adjustment, missing-data handling, or analysis-population rules, is not reported in the registry record.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Participants who reported having had sex in the past 6 months.

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 Sexual/Reproductive Health Behaviors, measured over 6 month follow-up.

The primary endpoint is titled “Sexual/Reproductive Health Behaviors.” It counts participants who reported condom use or other contraception use and consistency of use at six-month follow-up. The registry defines the population for this endpoint as participants who reported having had sex in the past six months. Thus, the endpoint is a participant count within that stated population, not a measure of contraceptive behavior for every person enrolled in the trial.

This outcome is relevant to the study’s stated aim because the intervention was designed to address health-behavior risks associated with adolescent pregnancy. A count provides the number of participants recorded as meeting the outcome description in each group. The accompanying comparison expresses the group contrast as a risk difference, with a confidence interval and an unadjusted p-value listed in the posted results.

The registry description combines several elements: condom use, other contraception use, and consistency of use. The record does not provide further operational definitions, such as the specific threshold for consistency, how different contraceptive methods were combined, or how participants’ reports were collected. Those measurement details are not reported in the registry record. Interpretation should therefore stay close to the stated endpoint description and not treat the count as a more detailed measure of behavior than the record documents.

7. Results Posted in the Registry

• Girls Invest Intervention: 43.6% (24/55) versus 43.6% (17/39) on control; risk difference 0.0 percentage points (95% CI -20.3 to 20.4), risk ratio 1.00 (0.63–1.60); unadjusted two-proportion z-test p = 0.996.

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.

Feeling Depressed

• 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:
  • Girls Invest Intervention: 11.6% (5/43) versus 23.0% (14/61) on control; risk difference -11.3 percentage points (95% CI -25.6 to 2.9), risk ratio 0.51 (0.20–1.30); unadjusted two-proportion z-test p = 0.141.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Girls Invest Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Felt Worried, Tense, or Anxious

• 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:
  • Girls Invest Intervention: 18.6% (8/43) versus 44.3% (27/61) on control; risk difference -25.7 percentage points (95% CI -42.7 to -8.6), risk ratio 0.42 (0.21–0.83); unadjusted two-proportion z-test p = 0.006.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Girls Invest Intervention than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes do not all show the same pattern. The estimate for feeling depressed is negative, but its confidence interval includes zero. The estimate for feeling worried, tense, or anxious is also negative, and its interval excludes zero. This mix is a reminder that separate outcomes can yield different estimates and different levels of statistical uncertainty even within the same trial.

These findings are related to, but do not replace, the primary result. The primary endpoint concerns sexual and reproductive health behavior among participants who reported having had sex in the past six months. The secondary outcomes concern reported emotional states. They address different questions and use different outcome populations, so their patterns cannot be treated as confirmation or contradiction of the primary estimate.

The unadjusted secondary comparison for feeling worried, tense, or anxious is more distinct from zero than the primary result, while the depression comparison remains compatible with zero. However, the registry does not report a multiplicity adjustment or indicate how these secondary outcomes were prioritized in the analysis plan. When multiple outcomes are examined, the chance of obtaining at least one result that appears notable can increase. In general, multiplicity procedures account for this feature, but no such procedure is reported in the registry record.

For that reason, the secondary findings carry less weight as confirmatory evidence than a result from a clearly prespecified analysis with an appropriate multiplicity plan. They are best read as descriptive and hypothesis-generating signals, with the uncertainty and reporting limitations kept in view. No additional inference should be drawn about the primary endpoint from the secondary outcomes alone.

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

• Feeling Depressed
• Felt Worried, Tense, or Anxious

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference express?

The primary comparison is expressed as a risk difference. In general, a risk difference subtracts the event proportion in one group from the event proportion in the other group. A value near zero represents little separation in the observed proportions. A positive or negative value indicates the direction of the contrast according to the order used for the comparison. For the primary result, the listed group proportions are 0.436 for Girls Invest and 0.436 for control, and the estimated risk difference is 0.001. The registry does not describe an adjusted model for this comparison.

What does the confidence interval contribute?

In general, a confidence interval describes the range of estimates compatible with the observed data under the method used to construct it. It conveys uncertainty around the point estimate; it is not a guarantee that the true effect lies within the interval. For the primary comparison, the 95% confidence interval runs from -0.203 to 0.204. Because this interval includes zero and extends to both negative and positive values, the observed data do not pin down the direction or size of a group difference with high precision. The registry does not state the interval-construction method.

How should the p-value be read?

In general, a p-value describes how unusual data at least as incompatible with a specified null model would be if that model were true, using the test’s assumptions. It is not the probability that the null hypothesis is true, nor does it measure the probability that the result arose by chance. The primary comparison lists an unadjusted p-value of 0.996. The record does not report the test procedure used for the posted comparison, so the p-value should be read as the listed unadjusted result rather than as evidence about a particular undocumented model.

Why distinguish counts from proportions?

The endpoint is recorded as a count of participants, but the groups have different outcome denominators. Counts alone can be misleading when the number of participants contributing to each outcome differs. The proportions listed with the comparison provide the corresponding group-level context. These proportions are outcome-specific and should not be confused with the enrollment figure or the adverse-event reporting denominators.

The primary endpoint population is defined as participants reporting sex in the past six months. The posted comparison uses 55 as the Girls Invest outcome denominator and 39 as the control outcome denominator. The registry does not explain why these denominators differ from other outcome denominators in the record, nor does it provide a participant flow account linking enrollment, follow-up, and endpoint availability. In general, outcome-specific denominators may reflect differing eligibility or response availability, but the reason in this trial is not reported in the registry record.

What does randomization contribute?

In general, random allocation is intended to make treatment groups comparable on average at the point of assignment, including on factors that may not be measured. This supports interpretation of between-group comparisons, but it does not remove uncertainty, guarantee balance in a particular trial, or address problems in measurement, missing data, or analysis. The record labels this study randomized, but details about the allocation sequence, concealment, and implementation are not reported in the registry record. Masking is listed as none, so the record does not describe masked treatment assignment or outcome assessment.

The trial has a parallel-group model: participants were assigned to the intervention or wait-list condition, with the latter scheduled to receive the intervention after six-month follow-up. The registry does not report whether the primary comparison followed an intention-to-treat approach, whether participants were analyzed according to assignment, or whether there were deviations from the assigned conditions. Those details are important for understanding how the randomized design was carried through the analysis.

What does over-dispersion mean for these results?

In general, over-dispersion means that observed variability is greater than a statistical model assumes. It is an important issue for some count outcomes and can make standard errors too small if ignored. The primary outcome is reported as participants with an event, a binary outcome, and the record lists no dispersion measure. No over-dispersion assessment or model-based count analysis is reported in the registry record. It would not be appropriate to infer that such an assessment was done.

The analysis listing contains no reported analyses. Consequently, the registry does not provide an analysis specification that would clarify covariate adjustment, handling of clustering, missing outcomes, or any alternative model. The posted risk-difference comparisons are interpretable as group contrasts with the stated counts and uncertainty intervals, but the exact testing and estimation procedures are not reported. General statistical explanations do not fill that reporting gap.

11. Confidence Intervals and Precision

The primary estimate is a risk difference of 0.001, and its 95% confidence interval ranges from -0.203 to 0.204. The point estimate is very close to zero, but the interval is much wider than the point estimate. It includes zero as well as values on either side, so the data are compatible with materially different directions and sizes of association. The posted result is therefore imprecise even though its central estimate is near zero.

A confidence interval is useful because it communicates uncertainty rather than relying only on a point estimate. In general, a narrower interval indicates greater precision, while a wider interval leaves more possible values consistent with the data and method. An interval that includes zero does not prove that there is no effect, and an interval excluding zero does not by itself establish clinical importance. The registry does not report a threshold for what difference would be meaningful for this endpoint.

The secondary outcome intervals also differ in their precision. The interval for feeling depressed extends from -0.256 to 0.029 and includes zero. The interval for feeling worried, tense, or anxious extends from -0.427 to -0.086 and does not include zero. These intervals describe unadjusted comparisons; uncertainty from testing multiple outcomes is not reflected in the individual intervals as posted.

Interpretation is also limited by outcome-specific denominators and missing-data details that are not reported. The registry does not state how many participants lacked outcome data, how missing responses were handled, or whether the intervals account for any features of the design beyond the listed group counts. Precision should therefore be understood from the posted estimates and intervals, without assuming unreported modeling choices.

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 expressed as participants per arm, not as total participants across arms and not as total events. They are based on the observed primary effect and list planning for 100%, 75%, and 50% of that observed effect. Under the listed assumptions, planning for 100% of the observed effect gives 17,761,814 participants per arm for 80% power and 23,778,029 participants per arm for 90% power. Planning for 75% gives 31,575,603 participants per arm for 80% power and 42,270,772 participants per arm for 90% power. Planning for 50% gives 71,042,953 participants per arm for 80% power and 95,106,357 participants per arm for 90% power.

The assumptions stated for this illustration are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The 80% power column describes the planned number per arm under which the calculation would have an 80% chance of detecting the specified effect under the assumptions, if that effect and the model assumptions held. The 90% column uses a higher probability of detection and consequently lists larger participant requirements. Smaller effects require more participants to distinguish them from random variation with the same planned power.

The curve should be read as a display of how the planning requirement changes with the effect size, not as a record of enrollment or outcomes. These are planning illustrations based on the observed estimate, not observed power. The original trial design’s sample-size assumptions and justification are not reported in the registry record.

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 = 0.436; treatment proportion p₁ = 0.436; average p̄ = 0.436.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7013 = 1.3746.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7013 = 0.5902.
4. n = (1.3746 + 0.5902)² / (0.0005)² = 17,761,813.5, rounded up to 17,761,814 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 <- 0.435897435897436                          # control proportion
p1 <- 0.436363636363636                          # 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(4222959)
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 = 17,761,814 (80% power), 23,778,029 (90% power)
 75% of observed effect: n per arm = 31,575,603 (80% power), 42,270,772 (90% power)
 50% of observed effect: n per arm = 71,042,953 (80% power), 95,106,357 (90% power)
power.prop.test: 17761814 
Simulated power at n = 17,761,814 per arm: 0.801 (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. Multiplicity, Missing Data and Analysis Populations

The registry record lists the primary outcome and secondary outcomes, but it does not report a multiplicity plan. In general, multiplicity arises when statistical tests are performed for several outcomes, comparisons, subgroups, or time points. If each is assessed without accounting for the broader set of tests, the chance of at least one apparently unusual result can rise. Adjustment procedures can address that issue, but the record does not state whether any procedure was planned or used.

The record also does not provide a complete statistical analysis plan. It does not report whether the primary analysis was prespecified in a protocol, which model or test was used, whether covariates were included, or how departures from the planned analysis would be handled. The analyses listing contains no reported analyses. Accordingly, the posted comparisons should be treated as the results available in the registry record, not as a complete account of every analysis that may have been contemplated.

Missing-data handling is not reported in the registry record. There is no description of the extent or reasons for missing primary or secondary outcome data, the assumptions used for any imputation, or whether analyses included only participants with observed outcomes. The primary endpoint population is stated as participants reporting sex in the past six months, but the record does not detail the classification process or how unavailable reports were addressed. The outcome-specific denominators also differ across endpoints, without an explanation in the record.

Analysis populations are similarly unclear. The registry does not say whether participants were analyzed according to randomized assignment, whether an intention-to-treat principle was used, or how nonadherence and intervention exposure were treated. It also does not report a participant flow account or the number of participants included in each analysis beyond the endpoint-specific denominators. These omissions limit assessment of the consequences of attrition, missingness, and any exclusions.

These are reporting limitations, not evidence that a particular analysis was mishandled. Without the plan and relevant details, readers cannot determine whether the posted comparisons reflect the intended confirmatory analysis or how robust they are to alternative reasonable choices.

15. 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 registry reports serious adverse events, other adverse events, and deaths separately for the intervention and wait-list groups. For serious adverse events, the listed at-risk figures are 138 for Girls Invest and 102 for control, with zero serious events in each group. For other adverse events, the at-risk figures are also 138 and 102, with zero other events in each group. The listed death counts are zero in both groups.

These are the adverse-event figures recorded for the registry’s safety reporting. The at-risk figures differ from the denominators used for the primary outcome, which is restricted to participants reporting sex in the past six months. The record does not explain the relationship between those safety denominators and the outcome-specific analysis populations.

Zero recorded events means that no events are listed in these categories for the stated reporting groups; it does not establish that no events occurred outside the recorded definitions or reporting period. The registry record does not provide further details about event collection, severity grading beyond the serious and other categories, attribution, or follow-up coverage. The figures should be read as registry safety counts, not as a complete assessment of all possible harms.

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

The primary result describes a near-zero estimated difference between the Girls Invest and wait-list groups in the proportion meeting the sexual and reproductive health behavior endpoint at six-month follow-up. The confidence interval is wide and includes zero, so the posted data do not identify a narrow range of plausible group differences. The unadjusted p-value is 0.996. Together, these statistics describe an uncertain primary comparison; they do not establish equivalence or prove that the groups had the same outcome.

The result also does not establish that the intervention does or does not change pregnancy risk. The endpoint is a reported behavioral measure, defined through contraceptive use and consistency, among participants reporting sex in the past six months. The registry does not post a pregnancy outcome in the material described, and the primary endpoint is not itself a direct measure of pregnancy incidence. It should not be interpreted as one.

The secondary outcomes concern feeling depressed and feeling worried, tense, or anxious. Their estimates and intervals provide separate, unadjusted comparisons, and the record does not report a multiplicity procedure. These outcomes do not establish the primary behavioral effect, and the primary comparison does not determine the secondary outcomes.

Randomization is a strength of the recorded design in general, but interpretation also depends on implementation, outcome measurement, missingness, and analysis choices. Details about allocation procedures, analysis populations, missing-data handling, and the original statistical plan are not reported in the registry record. These gaps prevent a full assessment of how the posted estimates were produced.

The appropriate reading is therefore limited to the reported group counts, estimated contrasts, intervals, and unadjusted p-values. They describe the posted data with substantial uncertainty for the primary endpoint. They do not provide medical advice, establish a definitive causal conclusion, or resolve whether a different study with a more precise design would yield a similar estimate.

17. Why This Trial Matters Statistically

This trial raises a useful statistical question about the relationship between a point estimate and its precision. The primary risk-difference estimate is close to zero, but its confidence interval is broad. Reading only the central estimate could make the result seem more settled than it is; reading the interval makes clear that a range of positive and negative differences remains compatible with the data and method.

The record also illustrates why outcome populations matter. The primary endpoint counts participants who reported sex in the past six months, whereas the registry’s enrollment figure and adverse-event reporting denominators describe different quantities. A denominator must be read in the context of the outcome it belongs to. Treating all denominators as interchangeable would obscure what each comparison actually represents.

Another statistical issue is the distinction between a primary endpoint and secondary outcomes. The secondary results include different patterns, but the record does not report a multiplicity plan. Without that context, an unadjusted secondary result should not be given the same confirmatory weight as a prespecified primary analysis. This is especially relevant when multiple outcomes are recorded and their analysis priorities are unclear.

Finally, the planning illustrations show how sensitive sample-size requirements can be to the effect size used for planning. The calculations are based on the observed primary effect, which is close to zero, and therefore lead to very large planning figures. They are not a reconstruction of the original trial design. The record does not report the original sample-size justification, and the planning illustration cannot substitute for it. Together, these features make the trial a practical example of interpreting estimates, intervals, outcome-specific denominators, and planning assumptions without overclaiming.

18. 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 primary endpoint description combines condom use, other contraception use, and consistency, but the registry does not report detailed definitions or the instrument used to measure them. The record also does not explain how the primary outcome population—participants reporting sex in the past six months—was determined, or how incomplete responses were handled. These gaps limit assessment of outcome classification and measurement.

The posted outcome denominators vary across the primary and secondary endpoints. The registry does not provide a participant flow account explaining those differences, nor does it report the amount or pattern of missing outcome data. As a result, the potential effect of missingness or endpoint-specific exclusions cannot be evaluated from the record.

The design is described as randomized, parallel, and unmasked, but allocation procedures, concealment, adherence, and any deviations from assigned conditions are not reported. The analysis population and whether participants were analyzed according to randomized assignment are also not reported. The analyses listing contains no reported analyses, and the original statistical plan is not available in the registry record.

The secondary results are unadjusted, and no multiplicity approach is reported. The record lists four outcome measures, while the results described include the primary outcome and two secondary outcomes; additional outcome details are not reported in the registry record. The trial’s original sample-size rationale and design assumptions are also not reported, so the planning illustration should not be treated as evidence about the study’s intended power.

Finally, the registry safety figures are counts within separate at-risk reporting groups, and details of adverse-event ascertainment and coverage are not reported. These limitations concern what can be concluded from the registry record; they do not establish that the underlying study lacked procedures that were not described there.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: An Intervention to Reduce Risk Factors for Adolescent Pregnancy — NCT04222959.
• Registry record last updated 2024-11-05; status last verified 2024-11.
• Results first posted 2024-11-05.
• 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.

22. Record Summary

NCT04222959 is a completed randomized, parallel-group trial of Girls Invest against a wait-list control, with no masking listed. The intervention combined app-based training with a savings account; control participants were to receive the intervention after six-month follow-up. The registry lists enrollment as 240 and identifies San Diego State University as sponsor.

The primary outcome counts participants reporting contraceptive use and consistency among those who reported having had sex in the past six months. The estimated risk difference is 0.001, with a 95% confidence interval from -0.203 to 0.204 and an unadjusted p-value of 0.996. The interval indicates substantial uncertainty around the near-zero estimate.

Two secondary outcomes are posted, with differing unadjusted results. No multiplicity plan, complete analysis strategy, or missing-data approach is reported in the registry record. Serious and other adverse-event counts and deaths are listed as zero in both groups, within their separate reporting denominators.