Corticosteroid Therapy in Neonates Undergoing Cardiopulmonary Bypass: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Corticosteroid Therapy in Neonates Undergoing Cardiopulmonary Bypass (NCT01579513), a randomized na study. The primary outcome is Number of Participants With a Clinically Derived Composite Morbidity-mortality Outcome.

2. Clinical Question

3. Trial Design

The registry describes a randomized, quadruple-masked, parallel-group trial comparing intraoperative methylprednisone with placebo. The listed sponsor is the Medical University of South Carolina. The study is marked completed; its start is recorded as 2012-06 and its primary completion date as 2018-05-25. The phase is listed as NA.

Eligible participants were neonates with congenital heart disease requiring surgery that used cardiopulmonary bypass during the first month of life. The intervention was a single intravenous dose of methylprednisolone at 30 mg/kg during anesthetic induction; the comparator was a single normal-saline placebo dose at the same time. Although the intervention list calls the drug methylprednisolone, the arm title and description use the spelling methylprednisone.

The registry lists enrollment as 190. For the primary outcome, the posted group denominators are 81 for intraoperative methylprednisone and 95 for placebo. These are the denominators associated with the outcome result; the registry record does not explain their relationship to the enrollment figure. The primary outcome was followed through hospital stay, with an expected average duration of 5 weeks.

Listed secondary outcomes are duration of mechanical ventilation after cardiac surgery, intensive care unit stay, hospital stay, and neurodevelopmental outcome. Numerical results for these outcomes are not reported in the registry record. Allocation concealment details, the original sample-size rationale, and the trial's own detailed analysis plan 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.

Primary Hospitalization

1 Year Neurodevelopmental Follow up

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 a Clinically Derived Composite Morbidity-mortality Outcome, measured over Participants will be followed for the duration of hospital stay, an expected average of 5 weeks.

The primary endpoint is the number of participants who experienced a clinically derived composite morbidity-mortality outcome after surgery and before hospital discharge. A participant met the endpoint if any one or more of the listed events occurred: death, cardiac arrest, extracorporeal membrane oxygenation, renal insufficiency defined as creatinine more than two times normal, hepatic insufficiency defined as aspartate aminotransferase or alanine aminotransferase more than two times normal, or rising lactic acidosis greater than 5mmol/L.

This is a binary participant-level endpoint: each participant is classified according to whether the composite occurred, rather than according to the number of separate component events. Because the endpoint combines several clinical events, the group comparison describes the frequency of experiencing at least one of those events; it does not by itself show which component accounts for the difference. Component-specific primary outcome counts are not reported in the registry record.

The registry says this composite was chosen because death rarely occurs in this population and because the investigators had found the endpoint to be highly associated with other important clinical outcomes in this population. The composite therefore captures a broader set of serious events than death alone. Its interpretation depends on the full definition: events within the composite may differ in severity and in how often they occur, and a participant can qualify through any one of them.

7. Results Posted in the Registry

• Intraoperative Methylprednisone: 33.3% (27/81) versus 42.1% (40/95) on control; risk difference -8.8 percentage points (95% CI -23.1 to 5.5), risk ratio 0.79 (0.54–1.17); unadjusted two-proportion z-test p = 0.232.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: the endpoint is counted as present if a participant experiences at least one qualifying event before discharge, and absent otherwise. For a binary endpoint, the event proportion is the number of participants with the event divided by the number with outcome data in that group. The posted proportions are 0.333 for intraoperative methylprednisone and 0.421 for placebo. These describe the observed groups; they are not estimates adjusted for other variables.

What does the risk difference express?

The risk difference is the event proportion in the intervention group minus the event proportion in the comparator group. The posted estimate is -0.088. Its negative sign reflects the lower observed proportion in the methylprednisone group according to this comparison's direction. A risk difference is expressed on the proportion scale, so zero represents equal proportions. The reported 95% confidence interval runs from -0.231 to 0.055 and includes zero. Thus, the estimated direction is not pinned down precisely by this interval: differences favoring either group, as well as no difference, remain compatible with the stated interval.

How should the p value be read?

The registry posts an unadjusted p value of 0.232. In general, a p value measures how unusual data at least as incompatible with a specified null hypothesis would be if that null hypothesis and the test assumptions were correct. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The registry does not report the detailed test specification or a model-based analysis for this comparison. The p value should therefore be read as the posted unadjusted result, not as evidence on its own that the groups are equivalent.

Why do the confidence interval and estimate matter?

A point estimate gives a single summary of the observed group contrast, while a confidence interval conveys uncertainty around that estimate under the analysis method. In general, a wide interval indicates that a broad range of underlying contrasts remains compatible with the data and method. Here, the risk-difference interval spans zero and includes both negative and positive values. The point estimate alone would conceal this uncertainty; the interval gives the more complete account of how precisely the comparison is estimated.

What do the relative measures add?

The registry also posts a risk ratio of 0.792, with interval limits 0.537 and 1.167, and an odds ratio of 0.688, with interval limits 0.371 and 1.273. These express the group contrast on different scales from the risk difference. A risk ratio compares event proportions as a ratio, while an odds ratio compares event odds. Their intervals include the null value for their respective measures. The measures are alternative descriptions of the same posted binary outcome comparison, not separate outcomes or independent confirmations.

For general context, the choice of effect scale affects how a result is communicated. Risk differences describe absolute separation in event proportions; ratios describe relative separation. Neither scale removes uncertainty, and neither should be interpreted without its interval and the event definition. The posted data give no component-specific breakdown of the composite, so estimates on any scale remain estimates for the combined endpoint.

What can be said about adjustment and analysis details?

The posted comparison is identified as unadjusted. The registry record lists no analysis entries and does not report covariate-adjusted estimates, subgroup analyses, or a detailed statistical analysis plan. It also does not report the trial's original sample-size assumptions, interim analyses, or procedures for handling missing outcomes. These omissions limit assessment of how the result was planned and how sensitive it may be to analytic choices. They do not change the numerical result that is posted, but they constrain what can be concluded about the methods behind it.

General statistical interpretation also depends on the study design and the quality of outcome ascertainment. Randomization supports a between-group comparison, but information about allocation procedures, adherence, outcome completeness, and masking implementation would help readers assess possible sources of bias. The record identifies the trial as randomized and quadruple-masked but does not detail these procedures. Therefore, the most secure description is the observed composite outcome comparison and its reported uncertainty, rather than a broader claim about causal mechanism or individual outcome components.

10. Confidence Intervals and Precision

The risk-difference estimate is -0.088, with a 95% confidence interval from -0.231 to 0.055. The interval is the key precision summary: it shows that the point estimate is uncertain and that the data are compatible with a range of contrasts. Because the limits fall on opposite sides of zero, the interval includes no difference as well as differences in either direction. The result does not tightly identify a single effect size or direction.

In general, a confidence interval is a range produced by a statistical procedure that, under its assumptions and repeated use, captures the parameter at its stated confidence level at the specified rate. It is not a range containing a fixed proportion of individual participant outcomes, and it is not the probability that the true effect lies within this particular interval. Its interpretation relies on the method used to calculate it; the detailed interval method is not reported in the registry record.

The registry also reports a risk ratio of 0.792, with interval limits 0.537 and 1.167, and an odds ratio of 0.688, with interval limits 0.371 and 1.273. Each measure uses a different effect scale, and each interval includes its scale's null value. This supports the same broad reading of uncertainty, rather than a precise conclusion about a group difference.

Precision is affected by the amount of outcome information and by the variability of the data, among other factors. The primary outcome denominators are 81 and 95, and the posted event counts are 27 and 40. Without additional information about outcome completeness, analysis assumptions, or component events, it is not possible to determine how the result would change under alternative analytic choices. The interval should therefore accompany the point estimate whenever the comparison is described.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrations based on fractions of the observed effect, not a report of the trial's original design target. Each listed figure is participants per arm, not a total across both arms. The assumptions stated for these calculations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect.

For the row planning for 100% of the observed effect, the illustration lists 479 participants per arm for 80% power and 640 participants per arm for 90% power. For 75% of the observed effect, it lists 861 participants per arm for 80% power and 1,152 participants per arm for 90% power. For 50% of the observed effect, it lists 1,956 participants per arm for 80% power and 2,618 participants per arm for 90% power.

In general, power is the chance that a specified statistical procedure will detect an effect of a chosen size under its planning assumptions. The 80% power column gives the illustrative per-arm size for an 80% chance of detecting the assumed effect at the stated significance level; the 90% column uses a higher target chance and therefore requires more participants per arm in these illustrations. Smaller assumed effects require more participants because they are harder to distinguish from random variation.

These are planning illustrations, not observed power. The trial's own original sample-size assumptions are not reported in the registry record. The figures should not be read as evidence that the trial was designed around these assumptions or as a measure of the probability that its result is correct.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.421; treatment proportion p₁ = 0.333; average p̄ = 0.377.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6854 = 1.3435.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6826 = 0.5745.
4. n = (1.3435 + 0.5745)² / (-0.0877)² = 478.1, rounded up to 479 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 <- 0.421052631578947                          # control proportion
p1 <- 0.333333333333333                          # 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(1579513)
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 = 479 (80% power), 640 (90% power)
 75% of observed effect: n per arm = 861 (80% power), 1,152 (90% power)
 50% of observed effect: n per arm = 1,956 (80% power), 2,618 (90% power)
power.prop.test: 478.1 
Simulated power at n = 479 per arm: 0.799 (20000 replicates)

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

13. Multiplicity, Missing Data and Analysis Populations

The registry lists the primary composite outcome and four secondary outcomes: duration of mechanical ventilation after cardiac surgery, intensive care unit stay, hospital stay, and neurodevelopmental outcome. Numerical results for those secondary outcomes are not reported in the registry record. The posted record therefore does not support a comparison of the primary finding with results across the secondary outcomes.

Multiplicity arises when multiple outcomes, comparisons, time points, or subgroup tests are examined. In general, conducting more tests can increase the chance of finding at least one apparently notable result by chance if no adjustment or prespecified strategy is used. The registry record does not report whether multiplicity was addressed, whether secondary outcomes were ordered or treated as exploratory, or whether any adjustment procedure was planned. This absence does not establish that no such procedures were used; it means they are not reported in the registry record.

The registry lists no analysis entries. It does not describe the analysis population, how participants were handled after randomization, or whether the primary comparison followed an intention-to-treat approach. Missing-data counts and methods for handling missing primary outcome information are also not reported in the registry record. The outcome denominators are posted as 81 and 95, but the record does not explain whether any randomized participants lacked outcome data or why these denominators differ from the listed enrollment figure.

These details matter because excluding participants or handling missing outcomes differently can affect an estimated group contrast. A reader would also need information about protocol deviations, treatment received, and the completeness of follow-up to assess the analysis population. Such information is not reported in the registry record, so the posted counts and unadjusted comparison should be interpreted as reported without assuming an unreported analysis strategy.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: extracorporeal membrane oxygenation (11.6%).

The registry's serious adverse event figures list 4 affected participants among 81 at risk in the intraoperative methylprednisone group and 11 among 95 at risk in the placebo group. These are counts of participants recorded as affected, not a comparison adjusted for other factors. The registry also lists 5 deaths in the methylprednisone group and 6 in the placebo group. It does not state in this adverse-event summary whether deaths overlap with the serious adverse event counts or with the primary composite outcome, so those categories should not be added together.

For other adverse events, the registry lists 2 affected participants among 81 at risk in the methylprednisone group and 2 among 95 at risk in the placebo group. Extracorporeal membrane oxygenation is the listed top serious adverse event term, reported as 11.6%. The registry does not provide enough detail in this summary to establish how event terms relate to participant counts or whether an individual could contribute to more than one term.

These safety figures are descriptive registry entries. No comparative uncertainty estimates or detailed adverse-event analysis are reported in the registry record. They should be read separately from the primary composite comparison, whose definition includes extracorporeal membrane oxygenation along with other clinical events.

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

The posted result describes a randomized comparison of intraoperative methylprednisone and placebo for a composite of serious events occurring after surgery and before hospital discharge in neonates undergoing cardiac surgery with cardiopulmonary bypass. The observed event proportions were 0.333 and 0.421, respectively. The estimated risk difference was -0.088, and its 95% confidence interval, from -0.231 to 0.055, includes zero. The unadjusted p value was 0.232. These results leave substantial uncertainty about the size and direction of the underlying group difference.

The result does not establish that the groups are equivalent. A non-definitive statistical comparison is not the same as evidence that any difference is absent or too small to matter. Conversely, the negative point estimate alone does not establish a reliable benefit. Interpretation should account for the interval, the endpoint definition, and the limitations in the registry's reporting.

The endpoint combines death, cardiac arrest, extracorporeal membrane oxygenation, renal insufficiency, hepatic insufficiency, and rising lactic acidosis. The overall count does not reveal how many participants experienced each component, whether multiple components occurred in the same participant, or which component drove the group comparison. Separate primary component results are not reported in the registry record.

The finding concerns this composite and the recorded follow-up through hospital discharge; the expected average hospital stay was 5 weeks. It does not answer questions about every secondary outcome or longer-term outcomes. Although ventilation duration, intensive care unit stay, hospital stay, and neurodevelopmental outcome are listed as secondary outcomes, their numerical results are not reported in the registry record.

These data describe a particular trial population: neonates with congenital heart disease requiring surgery with bypass in the first month of life. They do not by themselves determine how results apply to other patients, procedures, or settings. The registry's limited reporting of missing data, analysis populations, and analytic methods also constrains conclusions about the robustness of the posted estimate.

16. Why This Trial Matters Statistically

This trial illustrates why a clinical result needs to be read through its endpoint definition and its uncertainty, not only through the direction of the point estimate. The composite outcome is intended to capture serious postoperative morbidity as well as death, which the registry says rarely occurs in this population. A broader endpoint can make an outcome occur more often than death alone, but it combines events that may differ in severity and frequency. Without component-specific results, the overall contrast cannot show what kinds of events account for the observed counts.

The trial also offers a clear example of why a point estimate and a confidence interval answer different questions. The risk-difference estimate is negative, but its 95% confidence interval includes zero and extends into positive values. The estimate's direction is therefore not enough to establish a stable difference. Reporting the interval alongside the unadjusted p value helps readers focus on the range of plausible contrasts rather than treating a single threshold as a complete interpretation.

Finally, registry transparency shapes what can be assessed. The record identifies randomization, quadruple masking, the intervention, comparator, outcome, and posted group counts. It does not report the original sample-size rationale, missing-data procedures, analysis-population definitions, or numerical results for listed secondary outcomes. Such information is relevant when judging precision, the scope of the findings, and how closely the reported comparison reflects the planned analysis. The sample-size illustrations based on the observed effect are not a substitute for the trial's original design assumptions.

17. Limitations

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

The registry record does not report the original sample-size assumptions or rationale, so the planning illustrations based on the observed effect cannot show whether the trial's design anticipated a particular effect size or precision. Interim analyses and the detailed statistical analysis plan are also not reported. The record lists no analysis entries, although it posts the primary outcome counts and an unadjusted comparison.

The registry does not report missing outcome counts, reasons for missingness, the analysis population, or how participants were handled in the analysis. It lists enrollment as 190 and gives primary outcome denominators of 81 and 95, but does not reconcile those figures. This limits assessment of outcome completeness and of the population represented by the posted comparison.

Results for the listed secondary outcomes are not reported in the registry record. The primary composite combines events with different clinical meanings, and component-specific counts are not posted. The record also does not give detailed information about baseline characteristics, treatment adherence, protocol deviations, allocation procedures, or implementation of masking. These omissions limit assessment of comparability, potential bias, and the interpretation of individual components.

The primary follow-up extends through hospital discharge, with an expected average duration of 5 weeks; longer-term outcome information is not reported in the registry record. The posted results therefore have a defined population and follow-up scope, and generalization beyond that scope requires evidence not contained in this record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Corticosteroid Therapy in Neonates Undergoing Cardiopulmonary Bypass — NCT01579513.
• Registry record last updated 2019-12-09; status last verified 2019-11.
• Results first posted 2019-06-18.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT01579513 is a completed randomized, quadruple-masked, parallel-group trial sponsored by the Medical University of South Carolina. It compared one intraoperative intravenous dose of methylprednisolone, described in the arm title as methylprednisone, with placebo in neonates with congenital heart disease undergoing surgery with cardiopulmonary bypass in the first month of life.

The primary endpoint was a composite of death, cardiac arrest, extracorporeal membrane oxygenation, renal insufficiency, hepatic insufficiency, or rising lactic acidosis before hospital discharge. The posted counts were 27 of 81 in the methylprednisone group and 40 of 95 in the placebo group. The risk difference was -0.088, with a 95% confidence interval from -0.231 to 0.055; the unadjusted p value was 0.232.

The registry lists four secondary outcomes, but their numerical results are not reported in the registry record. It also does not report the original sample-size rationale, missing-data procedures, or a detailed analysis plan.