Uterotonic Prophylaxis Trial: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Uterotonic Prophylaxis Trial (NCT02408965), a randomized phase 4 study. The primary outcome is Number of Participants With Excessive Bleeding as Determined by the Composite Outcome Criteria.

2. Clinical Question

The trial was designed to examine prophylaxis rather than to compare treatment of bleeding after it had occurred. Its primary endpoint grouped several indicators of excessive bleeding into one binary outcome: a participant either met at least one listed criterion or did not. This allows the comparison to address a range of clinically consequential events and responses, rather than only one measure such as blood loss. It also means that the composite result does not, by itself, establish whether any particular component differed between groups. Component-specific primary results are not reported in the registry record.

3. Trial Design

This was a phase 4, randomized, parallel-group trial with quadruple masking. The registry lists an enrollment of 284 and a completed status. The record gives a start date of 2015-03 and a primary completion date of 2017-03. It lists the University of California, San Francisco as the sponsor.

Participants were assigned to Methergine or saline placebo. The intervention descriptions specify a single injection in each group when manual cervical dilation began the day before the procedure. The study summary places the clinical question among women undergoing D&E at 20 to 24 weeks. Details such as the randomization procedure, allocation concealment, the identities of the masked parties, and whether masking was maintained throughout are not reported in the registry record.

The posted primary outcome is the number of participants with excessive bleeding according to composite criteria, assessed approximately 1-2 hours after the procedure. The registry also lists nine outcome measures and nine analyses, while three secondary outcomes are described in detail: nausea, vomiting and cramping assessed approximately one hour after the procedure. The remaining outcome definitions and results are not reported in the registry record.

The enrolled group sizes in the primary results were 140 for Methergine and 144 for placebo. These are the denominators attached to the posted endpoint counts; they do not provide a complete account of enrollment, exclusions, follow-up or analysis-set membership. Those details, as well as the original protocol’s planned sample size and its assumptions, are 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.

Before assignment: Determined ineligible (n=28) Patient withdrew (n=6) Administrative error (n=2)

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 Excessive Bleeding as Determined by the Composite Outcome Criteria, measured over Approximately 1-2 hours after procedure.

The primary endpoint counts participants meeting the composite outcome criteria for excessive bleeding after D&E. The criteria include post-procedure total blood loss > 125cc, transfusion, admission for bleeding, re-aspiration for bleeding, balloon tamponade, uterine artery embolization, major surgery for bleeding, receipt of at least one uterotonic medication, a uterotonic prescription at discharge, or uterine compression by massage or manual pressure for 2 minutes. The assessment timeframe is approximately 1-2 hours after the procedure.

A composite endpoint is used when the clinical question concerns a set of related events or interventions rather than a single outcome. In general, combining criteria can capture multiple ways excessive bleeding may be recognized or managed and can yield one overall comparison. The trade-off is that the combined result does not indicate which component accounts for the observed counts. Components may differ in seriousness, frequency or clinical meaning, and a composite can be driven more by some components than by others. Component-level counts and comparisons are not reported in the registry record.

The posted outcome is binary at the participant level: a participant is counted if at least one criterion is met. The registry reports 78 participants in the Methergine group and 75 in the placebo group. These counts describe the composite endpoint, not the number of separate bleeding events or the count for each individual criterion.

7. Results Posted in the Registry

• Methergine: 55.7% (78/140) versus 52.1% (75/144) on control; risk difference 3.6 percentage points (95% CI -8.0 to 15.2), risk ratio 1.07 (0.86–1.33); unadjusted two-proportion z-test p = 0.539.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Number of Participants Who Reported Nausea up to One Hour After Procedure

• 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:
  • Methergine: 30.0% (42/140) versus 12.5% (18/144) on control; risk difference 17.5 percentage points (95% CI 8.2 to 26.8), risk ratio 2.40 (1.45–3.96); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Methergine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Patients Who Reported Vomiting up to One Hour After Procedure

• 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:
  • Methergine: 12.9% (18/140) versus 5.6% (8/144) on control; risk difference 7.3 percentage points (95% CI 0.6 to 14.0), risk ratio 2.31 (1.04–5.15); unadjusted two-proportion z-test p = 0.033.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Methergine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Participants Who Reported Cramping up to One Hour After Procedure

• 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:
  • Methergine: 71.4% (100/140) versus 58.3% (84/144) on control; risk difference 13.1 percentage points (95% CI 2.1 to 24.1), risk ratio 1.22 (1.03–1.46); unadjusted two-proportion z-test p = 0.021.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Methergine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes cover nausea, vomiting and cramping assessed approximately one hour after the procedure. Across these outcomes, the posted counts are higher in the Methergine group than in the placebo group. The reported and recalculated comparisons indicate that the group differences are not equally precise across outcomes. These secondary observations describe the reported outcomes but do not alter the primary endpoint result: the primary composite comparison remains statistically inconclusive on the posted analysis.

Secondary outcomes can add context by describing other events observed during the study. They are not substitutes for the prespecified primary question, and they should not be treated as independent confirmation of a primary effect. The registry record reports nine outcome measures and nine analyses, but only three secondary outcomes are described in detail. The record does not report whether these outcomes were designated in advance, how their analyses were prioritized, or whether the full set of analyses was adjusted for multiple comparisons.

When multiple outcomes are tested, the chance of obtaining at least one apparently notable result can increase even if no corresponding underlying difference exists. This is a general statistical concern, not evidence that a particular result is spurious. Without a reported multiplicity plan, secondary p-values should be regarded as exploratory or descriptive rather than as a set of definitive standalone conclusions. Their unadjusted status also means they do not account for other variables unless such adjustment is explicitly described, which it is not in the registry record.

The overall pattern can therefore be noted without elevating any one secondary result above the primary endpoint. The secondary results may inform what was observed in the groups, but their interpretation depends on outcome selection, multiplicity, completeness of reporting and the analysis plan. Those details are not reported in the registry record. They should be considered alongside, not in place of, the primary composite estimate and its uncertainty.

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

• Number of Participants Who Reported Nausea up to One Hour After Procedure
• Number of Patients Who Reported Vomiting up to One Hour After Procedure
• Number of Participants Who Reported Cramping up to One Hour After Procedure

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary because each participant is classified according to whether at least one composite criterion was met. For a binary endpoint, a group’s event count is interpreted alongside its denominator. The comparison can be expressed as a risk difference, a risk ratio or an odds ratio; these measures use different scales and should not be treated as interchangeable.

What does the risk difference describe?

The risk difference subtracts the event proportion in the comparator group from the event proportion in the intervention group. Here the reported direction is Methergine minus placebo, and the recalculated estimate is 0.036. A value of zero would represent equal observed proportions on this scale. The confidence interval, -0.080 to 0.152, includes zero. In general, a risk difference is often straightforward to interpret as an absolute difference in event probability, but its precision depends on the observed data and the analysis assumptions.

How should a confidence interval be read?

In general, a confidence interval describes uncertainty around an estimated effect under the method used to construct it. It is not a range that guarantees the true effect lies within its limits, nor is it a probability statement about the treatment effect. An interval spanning zero for a risk difference means the data do not clearly distinguish a positive difference from no difference or a negative difference at the interval’s stated level. The confidence level for the recalculated intervals is not reported in the registry record, so no level should be inferred from the posted limits alone.

What does the chi-squared test assess?

The registry reports a chi-squared test for the primary comparison. In general, this test assesses whether the observed distribution of a categorical outcome across groups is compatible with the null hypothesis of no association between group and outcome. Its p-value summarizes how unusual the data would be under that null hypothesis and the test assumptions. It does not give the probability that the null hypothesis is true, and it does not quantify clinical importance. The reported p-value is 0.5. The recalculated unadjusted p-value from the posted counts is 0.539.

Why do different effect measures matter?

The posted recalculation also gives a risk ratio of 1.07, with limits 0.863 and 1.327, and an odds ratio of 1.157, with limits 0.726 and 1.846. In general, a risk ratio compares event probabilities, while an odds ratio compares event odds. Both are relative measures; the risk difference is an absolute measure. When outcomes are not rare, odds ratios can differ appreciably in interpretation from risk ratios. Each measure depends on its scale, and a confidence interval’s relation to its null value must be interpreted on that same scale. These measures are recalculated from the posted summary data, not sponsor-reported adjusted estimates.

For all these effect measures, the recalculated intervals include their respective null values: zero for the risk difference and one for the risk ratio and odds ratio. This is consistent with the unadjusted p-value not indicating strong evidence against the null comparison. The measures do not establish that the groups are equivalent, and they do not resolve uncertainty about the individual components of the composite.

What is meant by unadjusted?

General statistical usage calls a comparison unadjusted when it compares the group summaries without accounting for additional covariates or other modeling features. The recalculated comparisons use the posted event counts and group sizes. Whether the trial’s own analysis adjusted for other variables, stratification factors or other design features is not reported in the registry record. The sponsor-reported chi-squared result is therefore distinct from the simple recalculation, and the registry result takes precedence as the sponsor’s own reported analysis.

The secondary endpoints are also binary counts. Their reported sponsor analyses use chi-squared tests, and the recalculated risk differences and relative measures are unadjusted. In general, unadjusted secondary comparisons can be useful descriptively, but they may not account for multiple testing or other analysis choices. The registry does not report a multiplicity strategy, a detailed statistical analysis plan, a missing-data method, or the analysis populations. These omissions limit how fully the test results can be reconstructed or interpreted.

11. Confidence Intervals and Precision

The primary recalculated risk difference is 0.036, with a confidence interval from -0.080 to 0.152. The interval includes zero and is broad enough to encompass effects in either direction. This means the point estimate alone gives an incomplete picture: the observed difference is not estimated with enough precision to rule out a range of potentially meaningful values. The registry’s chi-squared p-value is 0.5, while the unadjusted recalculated p-value is 0.539.

In general, confidence intervals communicate the uncertainty in an estimate more directly than a thresholded test result. They show a range of values compatible with the data and the method’s assumptions. A wide interval signals imprecision; an interval that includes the null value does not prove there is no effect. The confidence level for the recalculated intervals is not reported in the registry record, so the limits should be read as posted without assigning an unreported level.

The recalculated risk ratio is 1.07, with limits 0.863 to 1.327; the odds ratio is 1.157, with limits 0.726 to 1.846. These intervals also include their respective null values. Their scales differ from the risk-difference scale, so the numerical distances should not be compared directly across measures.

Precision is also limited by what the registry reports. The endpoint is a composite, and component-specific estimates and intervals are not reported in the registry record. Nor are detailed analysis-set membership, missing-data handling or the sponsor’s effect estimate and interval reported. The available summary therefore supports an overall, unadjusted comparison, but not fine-grained conclusions about separate bleeding criteria or the source of 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 sample-size figures are planning illustrations based on the observed effect, not the trial’s original design calculations. For these binary outcomes, the figures are participants per arm, not total events. In general, a planning row for 100% of the observed effect uses the observed effect as the target for a future design; rows for 75% and 50% plan around smaller effects. The primary endpoint illustrations therefore show how the required group size changes as the target effect is reduced.

The stated planning assumptions 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 original trial’s own sample-size assumptions and justification are not reported in the registry record. The planning calculation is not observed power.

In plain language, the 80% power column gives the estimated number of participants per arm for a design with an 80% chance of detecting the target effect under the stated assumptions, if that effect is present. The 90% power column gives the corresponding per-arm planning figure for a design targeting a 90% chance. These are design probabilities under assumptions, not probabilities that the trial result is correct.

The curve should be read as a planning relationship between the effect selected for detection and the required number of participants. Smaller target effects need more participants to distinguish them from random variation at the same stated significance level and power target. The displayed values are illustrations tied to observed estimates, which may themselves be imprecise. They do not establish what the trial would have found if it had enrolled a different number of participants, and they do not describe the probability that the completed trial detected its true effect.

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 = 0.521; treatment proportion p₁ = 0.557; average p̄ = 0.539.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7050 = 1.3817.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7045 = 0.5929.
4. n = (1.3817 + 0.5929)² / (0.0363)² = 2,957.4, rounded up to 2,958 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 <- 0.520833333333333                          # control proportion
p1 <- 0.557142857142857                          # 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(2408965)
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 = 2,958 (80% power), 3,959 (90% power)
 75% of observed effect: n per arm = 5,266 (80% power), 7,049 (90% power)
 50% of observed effect: n per arm = 11,864 (80% power), 15,881 (90% power)
power.prop.test: 2957.4 
Simulated power at n = 2,958 per arm: 0.808 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary analysis as a chi-squared test with p = 0.5. The recalculated unadjusted comparison, using the posted counts of 78 of 140 in the Methergine group and 75 of 144 in the placebo group, gives a risk difference of 0.036 and an unadjusted p-value of 0.539. The registry does not report a sponsor-estimated risk difference or a confidence interval for its chi-squared analysis.

The sponsor-reported result is the trial’s own posted inferential analysis and takes precedence over the simple recalculation. The recalculation is a check based on the summary counts, and it is not an adjusted analysis or a reconstruction of unreported methods. The registry does not explain whether differences in calculation, rounding or analytic implementation account for the two p-values. The reported and recalculated values point to the same broad interpretation: neither is strong evidence of a primary group difference, and the effect estimate remains uncertain.

The registry record marks no discrepancy between the posted result and the recalculated result. This does not mean that every analytic detail is available; the full statistical analysis plan, analysis populations and any adjustments are not reported in the registry record. The recalculation should therefore be read as a transparent summary-data comparison rather than a substitute for the sponsor’s analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity adjustment or a hierarchy for testing the primary and secondary outcomes. It lists nine outcome measures and nine analyses, while three secondary outcomes are described in detail. Without knowing whether the analyses were prespecified, which outcomes were confirmatory, or whether any correction or gatekeeping procedure was planned, the secondary p-values should not be read as if they were a single isolated test. In general, testing multiple outcomes can increase the chance of at least one result appearing notable by chance. This concern does not determine the validity of any individual result, but it changes how much weight unadjusted secondary findings can carry.

Missing-data procedures are not reported in the registry record. The posted endpoint counts and group denominators do not explain whether every randomized participant contributed an outcome, how missing observations were handled, or whether any imputation or sensitivity analysis was used. The analysis population is also not reported in detail: the registry does not state whether the primary analysis included all randomized participants, only participants with available outcome data, or another defined group. These omissions prevent a full assessment of the consequences of missing or excluded observations.

The record does not report a complete statistical analysis plan, including covariate adjustment, handling of protocol deviations, or planned sensitivity analyses. It also does not report the original sample-size justification or interim-analysis procedures. Those details should not be inferred from the posted p-values or from the planning illustrations, which are not the trial’s original design calculations.

These reporting gaps matter because they affect how reproducible and complete the analysis can be from registry summaries alone. The posted results support an interpretation of the listed group counts and reported tests. They do not establish that all outcomes, analyses, missing-data choices or planned comparisons are captured in the available record.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: admission to hospital for bleeding (2.9%).

The registry’s adverse-event summary lists 4 serious adverse events in the Methergine group and 0 in the placebo group. It lists 20 other adverse events for Methergine and 11 for placebo. Deaths are recorded as 0 in both groups. The top serious adverse-event term is admission to hospital for bleeding, reported as 2.9%.

These are descriptive registry figures. The record does not provide detail on event timing, severity grading, relatedness assessments, participant-level overlap, or the method used to select the top serious term. It is therefore not possible to determine from these summaries whether each event occurred in a different participant, whether events were judged related to the intervention, or how completely adverse events were collected.

The serious-event counts should be interpreted in the context of the group sizes and the limited detail available, not as a definitive comparison of safety. The absence of recorded deaths does not establish that no other harms occurred, and the counts alone do not establish causality. A fuller safety assessment would require details that are not reported in the registry record.

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

The primary result answers a narrow statistical question: whether the posted composite outcome counts differ between the randomized groups. The observed counts were 78 of 140 for Methergine and 75 of 144 for placebo. The sponsor-reported chi-squared p-value is 0.5; the recalculated risk difference is 0.036, with a confidence interval from -0.080 to 0.152. Taken together, these results do not provide strong statistical evidence of a difference in the primary composite outcome, while leaving uncertainty about the size and direction of any underlying difference.

This is not evidence that the two groups are equivalent. Equivalence requires a defined margin and a suitable analysis, neither of which is reported in the registry record. Nor does a result that does not provide strong evidence of a difference establish that no effect exists. The interval includes zero and extends to values on both sides, so the primary estimate is compatible with more than one interpretation.

The endpoint is composite. Its overall count does not show how often each listed criterion occurred, or whether particular types of bleeding, interventions or medication use contributed most. The registry record does not report component-level primary comparisons. Consequently, the overall estimate should not be read as a separate conclusion about each element of excessive bleeding or about outcomes beyond the stated timeframe.

The secondary outcomes provide descriptive information about nausea, vomiting and cramping, but they do not replace the primary result. Their interpretation is limited by the absence of a reported multiplicity plan and detailed analysis populations. Safety figures are also summary counts and lack the detail needed for causal conclusions. The trial record therefore describes a randomized comparison and its posted outcomes, but it does not resolve all questions about the composite components, missing data, analysis choices or the precision of smaller effects.

18. Why This Trial Matters Statistically

This trial illustrates why a clinical comparison cannot be reduced to a single p-value. The primary test result is accompanied by a recalculated risk difference and confidence interval, which show both the direction of the point estimate and the uncertainty around it. The interval spans zero, making clear that the available summary does not sharply distinguish a difference from no difference.

It also illustrates a central feature of composite endpoints. Combining multiple criteria can represent a broad clinical concept in one outcome, but the overall count does not show whether the components behave similarly. Without component-level results, readers cannot identify which criteria contribute most to the composite. This is especially important when a composite includes blood loss thresholds, interventions, medication use and procedural responses, which are not interchangeable measures.

The registry’s own chi-squared analysis and the unadjusted recalculation are close in their broad interpretation, while remaining distinct analyses. Comparing them helps readers see what can be reconstructed from summary counts and what remains dependent on the sponsor’s analytic choices. The record’s missing details about multiplicity, analysis populations and missing-data handling also show why transparent statistical reporting matters for interpreting a result beyond its headline test.

Finally, the planning illustrations distinguish precision and study design from retrospective claims about power. They show how assumptions about target effect and design parameters influence a future sample-size plan; they do not turn the completed trial’s result into a probability that the study detected an effect. Together, these features make the record useful for understanding uncertainty, composite outcome interpretation and the limits of summary-level clinical trial reporting.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record is not a full report of trial conduct or analysis. The specific eligibility criteria, participant flow, baseline characteristics, protocol deviations and analysis-population definitions are not reported in the registry record. The posted denominators therefore cannot, on their own, establish how all enrolled participants were handled in the analysis or whether outcome data were missing.

The primary outcome combines several different criteria, but criterion-specific counts and effect estimates are not reported. As a result, the overall estimate cannot show whether measured blood loss, a specific intervention, medication use or another component drove the observed composite counts. The timing is described as approximately 1-2 hours after the procedure; longer-term bleeding outcomes are not reported in the registry record.

The record does not report the randomization method, allocation concealment details, masking procedures beyond the quadruple-masking label, adherence to the assigned injection, or the statistical analysis plan. It also does not report the original sample-size rationale, interim analyses, multiplicity handling, missing-data procedures or whether the sponsor’s analysis adjusted for any design or participant characteristics. Those details cannot be inferred from the summary results.

Only three secondary outcomes are described in detail despite the registry listing nine outcome measures and nine analyses. The available safety summaries likewise do not provide event relatedness, timing, severity detail or participant-level overlap. These limitations constrain interpretation of secondary and safety findings, as well as the ability to assess the completeness and robustness of the primary analysis from the registry record alone.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Uterotonic Prophylaxis Trial — NCT02408965.
• Registry record last updated 2019-09-06; status last verified 2019-08.
• Results first posted 2019-09-06.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry describes NCT02408965, a completed phase 4 randomized, quadruple-masked, parallel-group trial sponsored by the University of California, San Francisco. Enrollment was 284. The trial compared a single methylergonovine maleate injection with saline placebo when manual cervical dilation began the day before D&E. The study summary identifies women undergoing D&E at 20 to 24 weeks as the population of interest.

The primary outcome was the number of participants meeting a composite definition of excessive bleeding approximately 1-2 hours after the procedure. The posted counts were 78 of 140 for Methergine and 75 of 144 for placebo. The sponsor reported a chi-squared p-value of 0.5; the recalculated unadjusted risk difference was 0.036, with a confidence interval from -0.080 to 0.152. The summary does not provide component-specific primary results.

Nausea, vomiting and cramping were reported as secondary outcomes. The record also includes summary adverse-event counts, but detailed analysis populations, missing-data procedures, multiplicity methods and the original sample-size justification are not reported in the registry record.