Fetal ST Segment and T Wave Analysis in Labor: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Fetal ST Segment and T Wave Analysis in Labor (NCT01131260), a randomized na study. The primary outcome is Number of Participants With Primary Composite Outcome.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group trial listed as completed in the registry. It compared an open group, in which fetal STAN data were available to caregivers, with a masked group, in which the electrode was inserted but the data were not shown to caregivers. The trial record lists single masking, but does not specify which individuals beyond caregivers were masked. The allocation ratio and details of sequence generation or concealment are not reported in the registry record.

The registry lists enrollment as 11108. The posted primary-outcome group counts were 5532 in the open group and 5576 in the masked group. The trial was sponsored by The George Washington University Biostatistics Center. Its listed start was 2010-11, primary completion was 2014-04, and status is completed. The phase is listed as NA.

The intervention was intended to add fetal heart electrical-activity information to existing electronic monitoring of fetal heart rate and maternal contractions. The registry describes the study purpose as testing whether use of the monitor would affect newborn health. It does not report the clinicians’ decision rules for acting on monitor information, adherence to monitoring, or the actual proportion of time the data were available or used.

The registry lists 21 outcome measures and 19 analyses. The primary outcome was a participant count for a composite, assessed from delivery through 1 month of age. Some secondary outcomes concern delivery events and maternal outcomes. Details of the trial’s original sample-size justification, planned analysis population, and handling of missing outcomes 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.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Umbilical cord artery blood was not able to be obtained from all participants.

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 Primary Composite Outcome, measured over From Delivery through 1 month of age.

The primary endpoint counts participants with a composite of intrapartum fetal death, neonatal death, an Apgar score at or below 3 at 5 minutes, neonatal seizure, umbilical artery blood pH at or below 7.05 together with a base deficit of at least 12 mmol/L in extracellular fluid, intubation for ventilation at delivery, or neonatal encephalopathy. The assessment timeframe is from delivery through 1 month of age.

A composite endpoint combines several events into one outcome. In general, this can capture a broader range of clinically serious outcomes than any single component, while allowing the trial to compare a single overall measure. Its interpretation depends on which events are included: components may differ in frequency and clinical character, and a combined count does not show which component accounts for the observed group totals. Component-level results are not reported in the primary outcome information described in the registry record.

The registry states that umbilical cord artery blood could not be obtained from all participants. Because the composite includes a cord-blood criterion, unavailable samples create a potential missing-data issue for that component. The record does not explain how missing cord-blood measurements were treated when determining composite status, or whether participants with unavailable measurements were handled differently in the analysis.

7. Results Posted in the Registry

• Masked Group: 0.7% (40/5576) versus 0.9% (52/5532) on control; risk difference -0.2 percentage points (95% CI -0.6 to 0.1), risk ratio 0.76 (0.51–1.15); unadjusted two-proportion z-test p = 0.196.

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 Neonates With Shoulder Dystocia During Delivery

• 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:
  • Masked Group: 2.8% (158/5576) versus 2.5% (141/5532) on control; risk difference 0.3 percentage points (95% CI -0.3 to 0.9), risk ratio 1.11 (0.89–1.39); unadjusted two-proportion z-test p = 0.354.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Masked Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Chorioamnionitis

• 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:
  • Masked Group: 4.8% (269/5576) versus 5.2% (286/5532) on control; risk difference -0.3 percentage points (95% CI -1.2 to 0.5), risk ratio 0.93 (0.79–1.10); unadjusted two-proportion z-test p = 0.403.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Masked Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants Who Had a Postpartum Blood Transfusion

• 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:
  • Masked Group: 1.3% (74/5576) versus 1.4% (80/5532) on control; risk difference -0.1 percentage points (95% CI -0.6 to 0.3), risk ratio 0.92 (0.67–1.26); unadjusted two-proportion z-test p = 0.592.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Masked Group and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes cover delivery method, indications for operative delivery, labor duration, shoulder dystocia, chorioamnionitis, postpartum transfusion, and postpartum endometritis, among other measures. The registry lists 13 posted secondary outcomes, while detailed comparison information in the record includes several event-count outcomes. Across those reported comparisons, the observed directions are not uniform, and the unadjusted p-values do not show a consistent pattern of clear group separation.

These outcomes provide context about other maternal and neonatal events but do not replace the primary composite. They address different events and timeframes, and an individual secondary result cannot determine the overall primary-outcome conclusion. The primary result itself remains uncertain, with its interval spanning the no-difference value. Secondary patterns do not resolve that uncertainty.

General explanation: when many outcomes are tested, the chance of finding at least one apparently unusual result by chance increases. Unadjusted secondary analyses do not account for that multiplicity, so an isolated result generally carries less evidential weight than a prespecified primary analysis. The registry record does not report whether a multiplicity adjustment was planned or used, nor does it specify which secondary comparisons were prespecified for formal inference. Secondary findings should therefore be read as exploratory unless further analysis-plan information is available.

The registry lists 21 outcome measures and 19 analyses, which indicates that the record contains multiple outcomes and comparisons. Those counts alone do not reveal how the testing family was defined or whether any formal hierarchy was used. The secondary results can help describe the posted outcome profile, but they do not support a broad claim that every outcome is unaffected or that a particular secondary event differs between strategies.

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

• Number of Participants by Delivery Method
• Number of Participants by Indication for Cesarean
• Number of Participants With an Indication for Forceps or Vacuum Delivery
• Median Duration of Labor Post-randomization
• Number of Neonates With Shoulder Dystocia During Delivery
• Number of Participants With Chorioamnionitis
• Number of Participants Who Had a Postpartum Blood Transfusion
• Number of Participants Experiencing Postpartum Endometritis

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the proportion with an event in one group with the proportion in another. A negative masked-minus-open difference means the observed event proportion is lower in the masked group than in the open group; a positive value means it is higher. The recalculated comparison is unadjusted, meaning it compares the posted group summaries without adjustment for other variables. It does not account for any covariates or stratification unless these are incorporated in the analysis, and such details are not reported for the recalculation.

For the primary endpoint, the posted values are participant counts: 52 in the open group and 40 in the masked group. The recalculated risk-difference interval spans zero, the value representing no difference on this scale. The unadjusted p-value is 0.196. This is a summary comparison of the posted counts, not a substitute for details of the trial’s full analysis plan.

How should the risk ratio be read?

A risk ratio compares event risks as a ratio rather than as an absolute difference. A ratio of 1 represents equal risks; values on either side represent relative differences. The sponsor’s reported primary analysis is a chi-squared analysis with a risk ratio of 1.31 and a 95% confidence interval from 0.87 to 1.98. The confidence interval includes 1, so the reported estimate is not statistically distinguishable from no relative difference at the confidence level stated. The registry gives p = 0.20 for that analysis.

The recalculated comparison and the sponsor’s reported analysis use different effect summaries and display different orientations of the group comparison. Those statistics should not be treated as interchangeable numbers. Both are based on the same posted primary group results and convey substantial uncertainty about the direction and size of any difference.

What does a p-value contribute?

General explanation: a p-value describes how unusual data at least as incompatible with a specified null model would be if that model were true, under the assumptions of the test. It is not the probability that the null hypothesis is true, and it does not measure the clinical importance of an effect. A larger p-value does not prove no effect; it indicates that the data do not provide strong evidence against the null model by that test.

The registry identifies chi-squared testing for the sponsor’s primary comparison. General explanation: a chi-squared test compares observed event counts with counts expected under a null hypothesis of no group association. Its use for a binary outcome is familiar, but the registry does not report additional implementation details such as continuity correction, covariate adjustment, or stratification. Those choices should not be inferred.

Why are confidence intervals useful?

General explanation: a confidence interval communicates the range of effect estimates reasonably compatible with the data and the statistical procedure. Its width reflects precision: a wider interval permits a broader range of effects, while a narrower interval constrains the plausible range more tightly. A confidence interval that includes the no-difference value signals that the data do not rule out no difference at the stated confidence level. It does not establish that all values in the interval are equally likely, or that values outside it are impossible.

The posted primary comparison is a count-based binary-outcome comparison. The registry does not report an adjusted model, covariate set, or the assumptions behind the sponsor’s complete analysis beyond identifying a chi-squared method. Thus, interpretation should remain tied to the stated aggregate comparison rather than assuming additional modeling.

Why can missing component data matter?

General explanation: when an outcome is a composite, missing information for one component can affect whether the overall endpoint can be classified. The consequences depend on the endpoint rules and the missing-data method. Here the registry explicitly notes that umbilical cord artery blood could not be obtained for all participants, and the cord-blood criterion is part of the primary composite. The approach used to classify participants without that measurement is not reported in the registry record. This uncertainty is distinct from the statistical interval around the group comparison: a confidence interval quantifies sampling uncertainty under an analysis, while it does not by itself resolve possible bias from missing outcome information.

11. Confidence Intervals and Precision

The sponsor reports a 95% confidence interval for the primary risk ratio from 0.87 to 1.98. The interval includes 1, the no-relative-difference value. It spans estimates that would represent different directions and sizes of association, so the primary result is not highly precise about the relative effect. The interval does not identify a single effect as established.

The unadjusted recalculation uses a risk-difference scale. Its interval extends across zero, the no-difference value on that scale. The posted p-value is 0.196. Together, these features indicate that the observed difference is uncertain: the data are compatible with no group difference and also with effects in either direction. The registry’s reported p-value, 0.20, is similarly not a statistically clear signal of a group difference.

General explanation: confidence intervals reflect both the amount of information in the data and the variability of the outcome. Binary outcomes with relatively few events can yield uncertain estimates even when the group counts are substantial. The primary endpoint is a composite, and the record notes that cord artery blood could not be obtained for all participants. The reported interval does not by itself reveal how that missing component was handled, nor does it incorporate uncertainty from unreported analytic choices.

Precision is not the same as importance. A statistically compatible range may include effects that would matter in practice, but the record does not specify a threshold for a clinically important difference. The results therefore do not support a firm conclusion of equivalence or a claim that a meaningful difference has been excluded.

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 for binary outcomes. They are illustrations based on the observed effect, not the trial’s original design calculation. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The trial’s own original sample-size assumptions are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm that would yield an 80% chance of detecting the specified effect under those assumptions, if that effect and the assumptions were correct. The 90% power column uses a higher target chance of detection and therefore calls for more participants per arm. These are planning calculations, not observed power: observed power is not a useful way to reinterpret the trial’s result after the data have been collected.

The rows illustrate planning for 100%, 75%, and 50% of the observed effect. Smaller effects require more participants because they are harder to distinguish from random variation. The figures become especially large when the assumed effect is reduced. This pattern is a general feature of power calculations, not evidence that the trial was intended to detect each of these effect sizes.

The calculation uses the observed effect as its starting point, so it is sensitive to the uncertainty in that estimate. A planning exercise based on an uncertain observed effect should not be mistaken for a new, independently justified target. The sample-size figures do not establish that the trial was underpowered or adequately powered for its original question; the original design assumptions are not reported.

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 = 0.009; treatment proportion p₁ = 0.007; average p̄ = 0.008.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.1282 = 0.2513.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.1282 = 0.1079.
4. n = (0.2513 + 0.1079)² / (-0.0022)² = 26,027.8, rounded up to 26,028 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 <- 0.0093998553868402                          # control proportion
p1 <- 0.00717360114777618                          # 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(1131260)
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 = 26,028 (80% power), 34,844 (90% power)
 75% of observed effect: n per arm = 47,814 (80% power), 64,008 (90% power)
 50% of observed effect: n per arm = 111,046 (80% power), 148,658 (90% power)
power.prop.test: 26027.8 
Simulated power at n = 26,028 per arm: 0.800 (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 sponsor’s primary analysis is reported as a chi-squared comparison of risk ratios: 1.31, with a 95% confidence interval from 0.87 to 1.98 and p = 0.20. The unadjusted recalculation from posted summary counts gives p = 0.196 for a risk-difference comparison. These are different effect scales, and the registry’s reported group ordering should be kept in mind when reading the direction of the risk ratio.

The recalculated p-value and sponsor-reported p-value are close and lead to the same broad reading: the comparison does not show a statistically clear difference. The recalculation is not flagged as discrepant with the sponsor’s analysis. The sponsor’s reported result is the registered analysis and should be understood on its own stated risk-ratio scale; the simple recalculation is an unadjusted check based on summary counts, not a replacement for the sponsor’s analysis.

The sponsor’s interval includes the no-relative-difference value, and the recalculated risk-difference interval spans zero. Neither summary establishes equivalence or proves that the true effect is absent. The registry does not give further detail about adjustments or other elements of the sponsor’s statistical procedure beyond the named test and reported result.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists multiple outcome measures and analyses, but it does not report a multiplicity plan, such as a prespecified hierarchy, family-wise error procedure, or false-discovery approach. It is therefore not possible to tell from the record whether and how the investigators accounted for the chance of false-positive findings across multiple tests. Unadjusted secondary p-values should be treated cautiously, particularly when interpreted individually.

Missing data are relevant to the primary composite. The registry states that umbilical cord artery blood could not be obtained from all participants, and one component of the composite depends on cord-blood pH and base deficit. The record does not report the number of participants lacking this measurement, the rules for classifying the composite when it was unavailable, or any imputation or sensitivity analysis. The possible effect of missing measurements on the result cannot be determined from the posted information.

The registry does not describe the analysis population in enough detail to establish whether the primary comparison followed an intention-to-treat principle, a per-protocol approach, or another population definition. It also does not report participant flow, exclusions after randomization, or missingness for other components. These omissions limit assessment of whether the posted group counts include all randomized participants and how incomplete outcome ascertainment was handled.

Randomization can support a fair comparison when allocation and follow-up are maintained and outcomes are analyzed appropriately. However, the record does not provide enough information to evaluate these details fully. Allocation concealment, sequence generation, protocol deviations, and the handling of withdrawals are not reported in the registry record. These are reporting limitations, not evidence that any particular procedure was or was not followed.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: congenital malformation (0.2%), postpartum hemorrhage (0.1%), neonatal death (0.1%), subgaleal hematoma (neonate) (0.1%), uterine rupture (0.0%).

The registry reports serious adverse event counts of 35 in the open group and 21 in the masked group. It reports zero other adverse events in each group. The at-risk counts listed are 5532 for the open group and 5576 for the masked group. These are descriptive safety figures and do not, by themselves, establish that the monitoring strategy caused or prevented an event.

The listed serious-event terms include congenital malformation at 0.2%, postpartum hemorrhage at 0.1%, neonatal death at 0.1%, subgaleal hematoma in a neonate at 0.1%, uterine rupture at 0.0%, and scalp abscess or pustules in a neonate at 0.0%. Percentages are reported as displayed in the registry and may be rounded. The record does not provide event-level comparisons or a causal assessment for each term.

Death counts in the adverse-event group information are not reported in the registry record. The safety information should be interpreted as a registry summary rather than a complete assessment of comparative safety; definitions, attribution, and the method used to collect or classify events are not described in the listed information.

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

The primary result describes a randomized comparison of making fetal STAN data available to caregivers versus keeping the data masked, with the electrode inserted in both groups. The posted counts and statistical comparisons do not show a statistically clear difference in the composite outcome. That is a statement about the evidence in the posted results, not a conclusion that the strategies are identical.

The confidence interval leaves room for differences in either direction. The result therefore cannot establish that access to the data improves newborn outcomes, that it worsens them, or that any possible difference is negligible. A finding that is not statistically clear is not a proof of no effect. The registry also does not report a clinical threshold for what size of difference would be considered important.

The endpoint combines several events, including death, severe indicators at birth, a cord-blood criterion, intubation at delivery, and neonatal encephalopathy. A combined result does not tell which components contributed to the counts. The record notes that cord artery blood was not obtained for all participants, and does not describe how this was handled in endpoint classification. These details constrain interpretation of the aggregate result.

The trial compares access to fetal STAN information as an adjunct to electronic fetal monitoring. It does not isolate the effect of the electrode, because the electrode was inserted in both groups. Nor do the registry entries establish how clinicians acted on available information or how the intervention was implemented in practice. The result should be understood within the specific comparison and outcome definitions recorded, rather than generalized to other monitoring protocols or settings without further evidence.

No medical decision should be based on this statistical summary alone. The registry result is one source of evidence, with uncertainty and reporting limitations that should remain visible when considering what the comparison can support.

18. Why This Trial Matters Statistically

This trial illustrates a common question in clinical monitoring research: whether adding information to an existing monitoring system changes patient outcomes, rather than simply whether the new signal can be measured. Because both groups had the fetal STAN electrode inserted, the randomized contrast concerns caregiver access to the data. That distinction helps define what the comparison can and cannot address.

The primary result also shows why an observed difference in counts should not be interpreted without its uncertainty. The group counts differ, but the confidence intervals span the no-difference values and the p-values are not statistically clear. Looking at the estimate and its interval together avoids treating either a numerical contrast or a non-significant test as a definitive conclusion.

Composite outcomes are statistically useful for capturing several serious events in one endpoint, but they require careful reading. A composite may combine outcomes with different frequencies and meanings, and an overall result does not reveal the contribution of each component. Missing cord-blood measurements are especially relevant because a cord-blood criterion is included in this trial’s primary composite.

The secondary outcomes further illustrate the challenge of multiple comparisons. A range of outcomes can help describe a trial, but unadjusted findings across many measures do not carry the same evidential weight as a clearly specified primary comparison. The record’s incomplete reporting of multiplicity and missing-data methods is therefore important to the statistical interpretation, not merely a technical detail.

Overall, the trial is a useful example of distinguishing a lack of clear evidence from evidence of no effect, and of matching conclusions to the endpoint, analysis, and precision actually reported.

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.

Several trial-specific details needed for a fuller assessment are not reported in the registry record. These include allocation concealment and sequence-generation methods, the allocation ratio, which parties were masked, and the analysis population. The registry lists single masking but does not give enough detail to determine precisely who was blinded beyond the description that caregivers could or could not see the monitor data.

The primary composite depends partly on cord artery blood measurements, which were unavailable for some participants. The number of unavailable samples and the rule used to classify the endpoint in those cases are not reported. Component-specific primary results and sensitivity analyses addressing this issue are also not reported, limiting assessment of how missing measurements may have affected the composite comparison.

The original sample-size justification and statistical analysis plan are not reported. Although planning illustrations based on the observed effect are available, they do not establish the trial’s original power target or design assumptions. The record also does not specify whether the reported primary analysis adjusted for any variables or how protocol deviations and withdrawals were handled.

The composite outcome spans delivery through 1 month of age and combines events with different clinical characteristics. The posted overall counts do not show which components occurred or how much each contributed to the comparison. The registry’s secondary outcome information is also incomplete relative to the listed outcome measures, and the approach to multiplicity is not reported. These limitations restrict interpretation of secondary comparisons and the broader outcome profile.

Finally, the registry summary does not describe how caregivers incorporated available STAN data into decisions. The comparison is therefore about the open-versus-masked monitoring strategy as implemented in the trial, but details needed to assess implementation and adherence are not reported.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Fetal ST Segment and T Wave Analysis in Labor — NCT01131260.
• Registry record last updated 2019-07-15; status last verified 2019-07.
• Results first posted 2019-04-05.
• 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.

23. Record Summary

NCT01131260, titled “Fetal ST Segment and T Wave Analysis in Labor,” is a completed randomized parallel-group trial sponsored by The George Washington University Biostatistics Center. It compared an open fetal STAN group, in which caregivers could see monitor data, with a masked group, in which the electrode was inserted but the data were withheld.

The primary outcome was a composite count of serious fetal and neonatal events from delivery through 1 month of age. The posted counts were 52 in the open group and 40 in the masked group. The sponsor reported a risk ratio of 1.31 with a 95% confidence interval from 0.87 to 1.98 and p = 0.20. The unadjusted recalculation also does not show a statistically clear difference.

The confidence intervals allow for effects in either direction, so the result does not establish equivalence or a treatment effect. Missing cord-blood measurements, multiplicity methods, and details of the analysis population are not reported in the registry record.