Study to Evaluate the Safety and Efficacy of High Dose Intravenous Immune Globulin (IVIG) Plus Standard Medical Treatment (SMT) Versus SMT Alone in Participants in Intensive Care Unit (ICU) With Coronavirus Disease (COVID-19): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Evaluate the Safety and Efficacy of High Dose Intravenous Immune Globulin (IVIG) Plus Standard Medical Treatment (SMT) Versus SMT Alone in Participants in Intensive Care Unit (ICU) With Coronavirus Disease (COVID-19) (NCT04480424), a randomized phase 2 study. The primary outcome is All-Cause Mortality Rate Through Day 29.

2. Clinical Question

The question is framed around an addition to usual care: both groups received standard medical treatment, while only one group also received GAMUNEX-C. The primary endpoint is a short-term mortality measure, rather than a measure of a particular cause of death or a longer-term outcome. The registry record identifies the study as a pilot and describes the purpose as evaluating whether adding IVIG could reduce all-cause mortality through Day 29. That stated purpose does not itself establish that a difference occurred.

The observed results were 28.0% in the GAMUNEX-C plus standard medical treatment group and 32.0% in the standard medical treatment group. The comparison is imprecise, and the sponsor’s reported confidence interval includes values on either side of no difference. These results describe the randomized groups in this trial; they do not, by themselves, settle the broader question of what would happen in other populations or settings.

3. Trial Design

This was a Phase 2, multicenter, randomized, open-label, parallel-group pilot study. The registry record lists an enrollment of 100 participants. The primary outcome results include 50 participants in each group: GAMUNEX-C plus standard medical treatment and standard medical treatment alone. Random allocation supports comparison of the groups, while the open-label design means masking was not used.

The intervention group received GAMUNEX-C with standard medical treatment. The record describes the GAMUNEX-C dose as 2 g/kg, with a maximum of 160 g for participants weighing more than 80 kg. Standard medical treatment was used in both groups. For the standard-treatment group, the record says that care was selected at the Principal Investigator’s discretion during hospitalization from Day 1 to Day 29. The registry description of the intervention’s infusion schedule is incomplete, so further schedule details are not reported in the registry record.

The primary analysis used the intent-to-treat population, defined in the record as all participants who were randomized. The endpoint was all-cause mortality up to Day 29. The study is listed as completed, with a start date of 2020-09-17 and a primary completion date of 2021-08-25. The sponsor is Grifols Therapeutics LLC.

The registry record does not report the original sample-size justification or the assumptions used to choose the enrollment target. It also does not report a detailed protocol-level statistical analysis plan. The planning calculations associated with the posted results are separate illustrations based on the observed effect, not evidence of the trial’s original design rationale.

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: Participants with Coronavirus Disease 2019 (COVID-19) were randomized in 1:1 ratio to receive Standard Medical Treatment (SMT) or SMT plus a net total dose of Gamunex-C of 2 grams per kilogram (g/kg) (body weight) administered in divided doses over 4 to 5 consecutive days at the Principal Investigator's discretion. Maximum dose was capped at 160 g.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The intent to treat (ITT) population included all participants who were randomized.

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.

Population: The intent to treat (ITT) population included all participants who were randomized.

6. Primary Endpoint

The registry lists the primary outcome as All-Cause Mortality Rate Through Day 29, measured over Up to Day 29.

The primary endpoint is the percentage of participants in each treatment group who experienced death from any cause up to Day 29. It is an event-based binary outcome: each participant either experienced the event during the specified follow-up period or did not. The primary population is the intent-to-treat population, including all randomized participants.

All-cause mortality is used when the outcome of interest is death regardless of its recorded cause. As a general statistical point, this avoids making the primary comparison depend on assigning deaths to particular causes. The endpoint is also directly interpretable as a proportion of participants, although a proportion over a fixed follow-up period does not describe when events occurred during that period.

The posted percentages were 28.0% for GAMUNEX-C plus standard medical treatment and 32.0% for standard medical treatment alone. The registry’s primary outcome timeframe is up to Day 29. These figures describe the participants included in the reported groups; the confidence interval around the sponsor’s comparison is important for understanding how uncertain the group difference remains. The endpoint does not measure every aspect of recovery, duration of intensive care, or longer-term status.

The record does not provide additional detail about how deaths were ascertained or how incomplete Day 29 follow-up was handled. Those details are not reported in the registry record.

7. Results Posted in the Registry

• Standard Medical Treatment: 32.0% (16/50) versus 28.0% (14/50) on control; risk difference 4.0 percentage points (95% CI -13.9 to 21.9), risk ratio 1.14 (0.63–2.08); unadjusted two-proportion z-test p = 0.663.

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.

Percentage of Participants With Actual Intensive Care Unit (ICU) Discharge Time

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Standard Medical Treatment: 62.0% (31/50) versus 64.0% (32/50) on control; risk difference -2.0 percentage points (95% CI -20.9 to 16.9), risk ratio 0.97 (0.72–1.31); unadjusted two-proportion z-test p = 0.836.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Standard Medical Treatment and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants With Actual Hospital Discharge Time

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Standard Medical Treatment: 56.0% (28/50) versus 62.0% (31/50) on control; risk difference -6.0 percentage points (95% CI -25.2 to 13.2), risk ratio 0.90 (0.65–1.25); unadjusted two-proportion z-test p = 0.542.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Standard Medical Treatment and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Achieving Clinical Response: NEWS ≤ 2 Maintained for 24 Hours

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Standard Medical Treatment: 28.0% (14/50) versus 32.0% (16/50) on control; risk difference -4.0 percentage points (95% CI -21.9 to 13.9), risk ratio 0.88 (0.48–1.60); unadjusted two-proportion z-test p = 0.663.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Standard Medical Treatment and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several aspects of the clinical course, including ICU and hospital discharge, mechanical ventilation, oxygen use, changes in ordinal status, severity categories, and acute respiratory distress syndrome. The posted numerical results include discharge measures and a Day 29 clinical-response measure. Taken together, the posted results do not show a single uniform pattern across all outcomes: some group percentages are numerically higher in the GAMUNEX-C plus standard medical treatment group, while the differences are uncertain.

These outcomes give context around the primary mortality result because they address different dimensions of the course of illness. They are not interchangeable with all-cause mortality, and a result for a discharge or clinical-response measure does not determine the primary endpoint. The primary result remains the randomized comparison of mortality through Day 29, with the sponsor’s confidence interval indicating substantial uncertainty.

Secondary findings generally deserve less weight than a prespecified primary result when many outcomes are examined. As a general statistical concern, testing multiple outcomes creates more opportunities for apparently notable results to arise by chance. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting secondary tests. The secondary analyses should therefore be treated as supportive or exploratory rather than as independent confirmation of the primary finding.

The record lists additional outcomes, but the statistical plan and details needed to assess every secondary analysis are not reported in the registry record. In particular, the approach to missing observations and the handling of competing events for discharge outcomes are not reported in the registry record. These gaps limit how fully the secondary findings can be compared or synthesized.

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

• Percentage of Participants With Actual Intensive Care Unit (ICU) Discharge Time
• Duration of Mechanical Ventilation
• Percentage of Participants With Actual Hospital Discharge Time
• Duration of Any Oxygen Use From Day 1 Through Day 29
• Mean Change From Baseline in Ordinal Scale
• Absolute Change From Baseline in Ordinal Scale at Day 29
• Percentage of Participants in Each Severity Category of the 7-Point Ordinal Scale
• Percentage of Participants Who Develop Acute Respiratory Distress Syndrome (ARDS)

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is binary: each participant is classified according to whether all-cause mortality occurred up to Day 29. A group percentage is the proportion of participants with the event, expressed as a percentage. A risk difference compares two such proportions by subtraction. Its sign indicates which group has the higher observed percentage only after the group order is known; reversing that order reverses the sign.

What does the confidence interval describe?

A confidence interval communicates uncertainty around an estimated group contrast. In general, it reflects a range of values reasonably compatible with the observed data under the method used. An interval containing zero for a risk difference includes no difference as one possibility. It does not show that the true difference is zero, nor does it mean that every value in the interval is equally likely. The sponsor’s 95% interval for the primary risk difference runs from -22.3 to 14.5, and includes zero.

Why do the reported and recalculated results differ?

The registry lists a sponsor analysis using Fisher Exact for the risk difference. The recalculated comparison is an unadjusted calculation from posted summary statistics. Its risk-difference direction is standard medical treatment relative to GAMUNEX-C plus standard medical treatment, whereas the sponsor’s reported value is expressed in the reverse direction. Thus, the signs should not be compared without accounting for the order of subtraction. The unadjusted recalculation also uses a different method from the sponsor’s analysis. The sponsor’s own analysis takes precedence for interpreting the trial’s reported result.

A p-value is a measure of how compatible the observed data are with a specified null model under a particular testing procedure. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of a difference. A p-value also does not express the precision of an estimate as directly as a confidence interval. Since the analyses use different methods, their p-values need not be identical.

What does randomization contribute?

Random allocation is intended to make treatment assignment independent of participant characteristics, on average, supporting a fair comparison between groups. It does not guarantee that every characteristic is balanced in a trial of this size. The registry record identifies the study as randomized and reports an intent-to-treat primary population consisting of all randomized participants. An intent-to-treat approach retains participants in their randomized groups for the primary comparison, which preserves the comparison created by random allocation.

The record also identifies the study as open-label, with no masking. As a general consideration, awareness of assigned treatment can influence care decisions, reporting, or outcome assessment for some types of outcomes. Death is a comparatively direct endpoint, but open-label status remains part of the trial context. The registry record does not report further information about blinded adjudication or outcome-assessment procedures.

Why can over-dispersion matter?

Over-dispersion is a general concern when observed variation is greater than a statistical model expects. If a model understates variability, standard errors and confidence intervals can be too small, making results appear more precise than they are. The primary outcome is a binary event, and the registry record does not report an over-dispersion adjustment. It would therefore be inappropriate to claim that such an adjustment was used or needed for this analysis.

More generally, the method used for the sponsor’s test and the method used for a simple unadjusted recalculation need not produce identical inferential results. The registry identifies Fisher Exact for the sponsor’s primary comparison. It does not provide enough detail to reconstruct every analysis choice, such as the full implementation details or handling of any missing outcome observations.

11. Confidence Intervals and Precision

The sponsor’s primary estimate is a risk difference of -4.0, with a 95% confidence interval from -22.3 to 14.5. Because the interval includes zero, the data do not isolate a difference in one direction. Its span also signals substantial uncertainty about the magnitude of any difference. The observed group percentages, 28.0% and 32.0%, are point estimates from this trial; they should not be mistaken for exact values of an underlying treatment effect.

In general, a confidence interval is useful because it shows a range of effect values compatible with the data and analysis method, rather than presenting only a single estimate. The interval does not assign equal probability to each value inside it, and it does not guarantee that the underlying value falls within the interval. Its interpretation depends on the model and procedure used to construct it.

The secondary results also illustrate why individual percentages should be read alongside uncertainty. For ICU discharge, the reported 95% confidence intervals for the groups are 48.9 to 75.7 and 46.8 to 74.0. For hospital discharge, they are 46.8 to 74.0 and 41.0 to 68.6. These intervals overlap substantially. Overlap alone is not a formal test of the difference, but it conveys that the group percentages are not estimated with high precision.

The modest group sizes and the pilot designation are important context when considering precision. The registry record does not report the original sample-size justification or a prespecified precision target. The observed estimates therefore should not be presented as if the trial had been designed to guarantee a particular width of confidence interval.

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 illustrations are planning calculations based on the observed effect, not the original design assumptions for this trial. For this binary primary endpoint, the figures are participants per arm, rather than total events. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The calculations consider detecting the stated fraction of the observed effect.

The 80% power column describes the number of participants per arm that the planning calculation indicates would be needed for an 80% chance of detecting the assumed effect under those assumptions. The 90% power column describes the corresponding planning target for a 90% chance. These are prospective design illustrations, not a measure of how likely the observed trial result was to be correct. This is not observed power.

The rows consider planning for 100%, 75%, and 50% of the observed effect. A smaller effect is harder to distinguish from random variation, so the planning calculation requires more participants per arm as the assumed effect becomes smaller. The estimates are sensitive to their assumptions: the effect used is derived from this trial’s observed result, and a different underlying effect or analysis approach would lead to different planning figures.

The registry record does not report the original rationale for enrolling 100 participants or the assumptions used in its initial design. The planning figures should therefore not be interpreted as a reconstruction of the trial’s original target. They are illustrations of how sample-size requirements can change under the stated planning assumptions.

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 = 0.280; treatment proportion p₁ = 0.320; average p̄ = 0.300.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6481 = 1.2702.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6475 = 0.5449.
4. n = (1.2702 + 0.5449)² / (0.0400)² = 2,059.2, rounded up to 2,060 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 <- 0.28                          # control proportion
p1 <- 0.32                          # 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(4480424)
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 = 2,060 (80% power), 2,757 (90% power)
 75% of observed effect: n per arm = 3,627 (80% power), 4,855 (90% power)
 50% of observed effect: n per arm = 8,080 (80% power), 10,816 (90% power)
power.prop.test: 2059.2 
Simulated power at n = 2,060 per arm: 0.798 (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 own primary analysis is the result to prioritize when describing the trial. The registry reports a Fisher Exact analysis of the risk difference, with an estimate of -4.0 and a 95% confidence interval from -22.3 to 14.5. The confidence interval includes zero and allows differences in either direction. The sponsor’s reported p-value is recorded in the registry, but it is not necessary to use a separately recalculated p-value to characterize the reported confidence interval.

The unadjusted recalculation uses the posted group summary statistics and expresses the comparison in the reverse group order. Its risk-difference estimate is 0.04, and its unadjusted p-value is 0.663. The reversed sign reflects the contrast order: the recalculation subtracts the GAMUNEX-C group percentage from the standard-treatment group percentage, while the sponsor’s estimate is oriented the other way. Both describe the same observed ordering of group percentages when read with their respective conventions.

The recalculation is not a replacement for the sponsor’s analysis. It is a simple check based on the posted summaries, while the registry identifies Fisher Exact as the sponsor’s method. Their inferential values may differ because the methods differ. The registry record does not report enough detail to explain every implementation difference. There is no discrepancy flag in the record.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes or comparisons are tested. As a general statistical principle, the more tests conducted, the greater the chance that at least one result may appear notable by chance, even when there is no underlying effect for the outcomes being tested. A prespecified primary endpoint helps identify the main comparison, but interpretation of secondary findings also depends on whether the analysis plan specified an order of testing or an adjustment for multiple comparisons.

The registry record identifies all-cause mortality through Day 29 as the primary endpoint and lists multiple secondary outcomes. It does not report a multiplicity adjustment, a testing hierarchy, or a complete statistical analysis plan. Accordingly, the secondary results should not be read as if each were a separate confirmatory finding with a controlled overall error rate.

The primary analysis population is reported as intent-to-treat and includes all randomized participants. That is useful information about which participants were intended to contribute to the primary comparison. However, the record does not describe how missing mortality observations, incomplete follow-up, or other missing outcome data were handled. It also does not report the amount or pattern of missing data. Those details are not reported in the registry record.

The registry record does not report whether interim analyses were planned or conducted, nor does it give the original sample-size justification or the protocol-level analysis plan. These omissions do not change the posted outcome values, but they constrain assessment of whether all analysis decisions were set before the results were known. They also limit the ability to reproduce or fully audit the sponsor’s analysis from the registry entry alone.

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: acute respiratory failure (16.0%), respiratory failure (12.0%), septic shock (8.0%), hypoxia (6.0%), cardiac arrest (4.0%).

The safety record reports serious adverse events affecting 27 of 50 participants in the GAMUNEX-C plus standard medical treatment group and 23 of 50 in the standard medical treatment group. Other adverse events affected 42 of 50 and 44 of 50 participants, respectively. These are descriptive counts from the registry record; they do not establish that treatment caused or prevented an event.

The listed serious adverse-event terms include acute respiratory failure at 16.0%, respiratory failure at 12.0%, septic shock at 8.0%, hypoxia at 6.0%, cardiac arrest at 4.0%, and multiple organ dysfunction syndrome at 4.0%. The registry record does not provide further detail in these figures about event timing, severity grading, or attribution to treatment.

The safety listing also reports 16 deaths in the GAMUNEX-C plus standard medical treatment group and 18 in the standard medical treatment group. These safety counts are presented separately from the primary endpoint percentages. The record does not explain the relationship between these safety counts and the primary endpoint analysis, so they should not be used to replace or reconcile the primary results without further information.

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

The posted data describe a randomized comparison of GAMUNEX-C plus standard medical treatment against standard medical treatment alone among ICU participants with COVID-19. For the primary endpoint, the observed mortality percentages through Day 29 were 28.0% and 32.0%, respectively. The sponsor’s risk-difference confidence interval extends from -22.3 to 14.5 and includes zero. The comparison is therefore uncertain, both about whether there was a difference and about its size.

That uncertainty does not establish that the groups were identical. A confidence interval containing zero is compatible with no difference, but it also includes values on either side of zero. Conversely, the observed difference in percentages is not enough to establish a reliable effect. Statistical interpretation depends on the estimate, its uncertainty, the analysis method, and the trial context.

The study is listed as a Phase 2 pilot with 100 participants enrolled. Pilot results can describe outcomes and inform future research, but the registry record does not establish that this study was designed to provide a definitive answer. The original sample-size justification and detailed statistical plan are not reported in the registry record. Planning illustrations based on the observed effect do not substitute for those original design assumptions.

The results also do not establish what would occur with different treatment schedules, different standard-care practices, longer follow-up, or other patient populations. The record describes standard treatment as selected at the Principal Investigator’s discretion and identifies the study as open-label. Those features are relevant when considering the scope of what the trial can show.

No treatment recommendation follows from these statistics. They describe the posted results and the degree of uncertainty in this trial; they do not prove that either strategy works or does not work.

18. Why This Trial Matters Statistically

This trial is statistically instructive because it places an easily understood endpoint—whether a participant died by a specified time—alongside a comparison whose uncertainty is substantial. The observed percentages differ, but the sponsor’s confidence interval includes no difference and extends to effects in either direction. This is a practical example of why a point estimate alone is not enough to interpret a trial.

It also illustrates why the direction of a contrast must be stated. Risk differences depend on which group is subtracted from which. The sponsor’s reported estimate and the unadjusted recalculation use opposite contrast orientations, so their signs differ even though they describe the same ordering of group percentages. Without stating the reference group, a reader could mistake a sign change for a conflict in the underlying data.

The record also distinguishes a sponsor analysis from a simple recalculation. A recalculation based on posted summaries can be useful as a check, but it does not replace the reported analysis, which uses Fisher Exact. When methods differ, their p-values and intervals may differ as well. Statistical reporting is clearer when the analysis method, group order, estimate, and uncertainty are considered together.

Finally, the study shows why sample-size illustrations should be read as planning tools. Calculations based on the observed effect can demonstrate how a smaller assumed effect requires a larger planned sample, but they do not reveal the original rationale for enrollment or the probability that the trial’s result is correct. Keeping those distinctions clear prevents planning scenarios from being mistaken for trial findings.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The primary endpoint is reported for follow-up up to Day 29. The registry record does not provide a longer-term mortality result, so the posted endpoint cannot describe outcomes beyond that timeframe. It also does not report detailed information on missing follow-up or how any missing primary outcome observations were handled.

The trial is described as a pilot, with 100 participants enrolled and 50 participants in each primary analysis group. The resulting estimates have substantial uncertainty, as reflected in the sponsor’s 95% confidence interval. The original sample-size justification is not reported in the registry record, so it is not possible to assess the initial precision target from this entry.

The study was open-label, with no masking. The registry record does not report whether outcome adjudication was blinded or provide detailed procedures for assessment. Standard medical treatment was selected at the Principal Investigator’s discretion, so the record does not define a single uniform treatment regimen across participants. The intervention description gives the dose and cap but does not fully report the infusion schedule.

The registry record does not report a complete statistical analysis plan, interim-analysis information, multiplicity handling, or detailed missing-data methods. These omissions limit assessment of how analysis decisions were specified and how the secondary findings should be interpreted. The record also lists multiple clinical outcomes, and secondary results should be considered in light of the absence of a reported multiplicity strategy.

These limitations affect the certainty and scope of interpretation; they do not alter the posted group percentages. They support reading the trial as a limited, short-term comparison rather than as a precise estimate that necessarily applies beyond the studied setting.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study to Evaluate the Safety and Efficacy of High Dose Intravenous Immune Globulin (IVIG) Plus Standard Medical Treatment (SMT) Versus SMT Alone in Participants in Intensive Care Unit (ICU) With Coronavirus Disease (COVID-19) — NCT04480424.
• Registry record last updated 2022-10-07; status last verified 2022-10.
• Results first posted 2022-10-07.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT04480424 is a completed, Phase 2, multicenter, randomized, open-label, parallel-group pilot study sponsored by Grifols Therapeutics LLC. It enrolled 100 participants with COVID-19 requiring ICU admission. The primary comparison was GAMUNEX-C plus standard medical treatment versus standard medical treatment alone.

The primary endpoint was all-cause mortality through Day 29 in the intent-to-treat population. The posted percentages were 28.0% and 32.0%, respectively. The sponsor reported a risk difference of -4.0 with a 95% confidence interval from -22.3 to 14.5 using Fisher Exact. The interval includes zero and indicates considerable uncertainty about the comparison.

The registry record lists 13 outcome measures and 11 analyses. Details of the original sample-size justification, complete statistical plan, missing-data handling, and multiplicity approach are not reported in the registry record.