SMaRT Blood: Single-unit Versus Multiple-unit Packed Red Blood Cell Transfusion in Non-acute Postpartum Anemia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for SMaRT Blood: Single-unit Versus Multiple-unit Packed Red Blood Cell Transfusion in Non-acute Postpartum Anemia (NCT03419780), a randomized na study. The primary outcome is Total Number of Units Transfused.

2. Clinical Question

The clinical question is about transfusion use under the two assigned protocols. The primary outcome does not directly measure all aspects of maternal recovery or morbidity; those concerns appear among the listed secondary outcomes, including length of stay, breastfeeding, depression, fatigue, maternal attachment, and infection.

The registry describes the trial as randomized and controlled, with parallel groups and no masking. Its summary states that the investigators sought to compare the protocols by total units transfused and maternal morbidity. The record does not report detailed eligibility criteria, so the population should not be taken to represent a more narrowly defined group than non-acute postpartum anemia.

The comparison is between protocol strategies, not simply between people who received different numbers of units after clinical decisions. The assigned approach in the single-unit arm includes reassessment after transfusion; the multiple-unit arm also includes reassessment after its stated transfusion. The registry record does not report further rules for subsequent transfusions or how clinical reassessment affected care.

3. Trial Design

The registry describes SMaRT Blood as a randomized, controlled, parallel-group trial with no masking. The study status is completed. The recorded enrollment is 66, and the posted primary outcome includes 33 participants in each arm. The registry lists the phase as NA. The sponsor is the University of Pennsylvania.

The study start date is 2018-03-01, and the primary completion date is 2020-06-01. The registry identifies the condition as postpartum anemia and the trial population as having non-acute postpartum anemia. More specific inclusion and exclusion criteria are not reported in the registry record. The registry also does not report the method used to generate the random allocation sequence or whether allocation was concealed before assignment.

The single-unit arm received a protocol beginning with 1 unit of packed red blood cells, with a planned blood count at 4-6 hours and clinical reassessment. The multiple-unit arm received 2 units, followed by a blood count at 4-6 hours and clinical reassessment. Masking is listed as none, so the record does not describe blinded treatment assignment or outcome assessment.

The primary outcome concerns total units transfused from randomization until discharge from the admission for delivery, described as an average of 2-3 days. Secondary outcomes listed in the record include length of stay, exclusive breastfeeding at 4-9 weeks postpartum, depression, fatigue, maternal attachment inventory scores, and infection. The registry reports results for some secondary outcomes, while results for others are not reported in the registry record.

The record does not report the original sample-size justification, planned recruitment target, or the statistical analysis plan in enough detail to assess them. It also does not report whether interim analyses were planned or performed. These absences limit what can be concluded about the design decisions beyond the randomized parallel-group structure and the posted outcome analyses.

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

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 Total Number of Units Transfused, measured over From randomization until discharge from admission for delivery, an average of 2-3 days.

The primary endpoint is the total number of blood units transfused, expressed as a mean with standard deviation. Its timeframe runs from randomization until discharge from the admission for delivery; the registry describes that admission as averaging 2-3 days. This endpoint directly measures the amount of transfused blood recorded under each protocol during the stated period.

The endpoint is relevant to the stated study question because the registry summary frames the comparison around whether a single-unit protocol can reduce the total number of units used. It therefore assesses transfusion use, rather than serving as a direct measure of symptoms, recovery, or maternal morbidity. Those other domains appear among the secondary outcomes.

A mean gives the average number of units in each group, while the standard deviation describes the spread of individual observations around that average. General statistical explanation: the mean is useful for comparing average resource use, but it does not show whether every participant received a similar amount or whether some observations were farther from the group average. The registry record does not provide the individual-level distribution or additional summaries such as medians and ranges.

The endpoint is defined over a specific clinical window, ending at discharge from the delivery admission. It does not describe transfusions after that point. The registry record does not report further operational details about how units were counted or whether any protocol deviations affected the endpoint.

7. Results Posted in the Registry

• Multiple-Unit Blood Transfusion Protocol: mean 2.10 versus 1.20 on control; difference 0.90 (95% CI 0.68 to 1.12), standardized effect d = 1.99; z-test p = <0.001.

8. Secondary Efficacy Endpoints

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

Number of Participants Exclusively Breastfeeding at 4-9 Weeks Postpartum

• 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:
  • Multiple-Unit Blood Transfusion Protocol: 55.6% (15/27) versus 55.2% (16/29) on control; risk difference 0.4 percentage points (95% CI -25.7 to 26.4), risk ratio 1.01 (0.63–1.61); unadjusted two-proportion z-test p = 0.977.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Multiple-Unit Blood Transfusion Protocol and the control. The interval gives the range of effects that remain compatible with the data.

Infection Rate

• 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:
  • Multiple-Unit Blood Transfusion Protocol: 3.0% (1/33) versus 6.1% (2/33) on control; risk difference -3.0 percentage points (95% CI -13.1 to 7.0), risk ratio 0.50 (0.05–5.25); unadjusted two-proportion z-test p = 0.555.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Multiple-Unit Blood Transfusion Protocol and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results cover exclusive breastfeeding at 4-9 weeks postpartum and infection through the 4-9 week postpartum visit. The registry lists additional secondary outcomes concerning length of stay, depression, fatigue, and maternal attachment inventory scores, but results for those outcomes are not reported in the registry record. The record therefore does not support a complete assessment of the pattern across every listed secondary outcome.

The available secondary comparisons do not add clear statistical evidence that the groups differ on those particular measures. Their estimates are imprecise, and the registry's own reported tests do not indicate a statistically clear difference. This broad pattern does not reverse or independently verify the primary finding: the secondary outcomes measure different aspects of care and postpartum experience from total transfused units.

Secondary results generally carry less weight than the primary endpoint when many outcomes are considered. Each additional comparison creates more opportunity for a chance finding, especially if no adjustment is made for multiple testing. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting the secondary outcomes. The posted secondary p-values are unadjusted recalculations, while the registry reports chi-squared tests for the two posted secondary comparisons.

General statistical explanation: an unadjusted p-value evaluates a single comparison without accounting for the number of other comparisons considered. When there are multiple outcomes, chance findings become more likely across the set. This does not make each secondary measure uninformative, but it means isolated secondary results should be treated as exploratory unless a prespecified analysis plan establishes otherwise. Such a plan is not reported in the registry record.

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

• Length of Stay
• Number of Participants Exclusively Breastfeeding at 4-9 Weeks Postpartum
• Rate of Depression
• Rate of Fatigue
• Maternal Attachment Inventory Scores
• Infection Rate

9. Statistical Interpretation

10. Statistical Methods Explained

General statistical explanation: the methods below describe what the named analyses mean in general and how they relate to the posted results. They do not imply that the registry record reports a more detailed analysis plan than it does.

What does a randomized parallel-group design mean?

Random assignment is intended to make treatment groups comparable, on average, with respect to factors that could affect outcomes. It does not guarantee that every characteristic will be balanced in a particular trial. A parallel-group design assigns participants to a protocol and compares outcomes between groups. Here, the registry identifies randomization, a parallel model, and no masking. The sequence-generation and allocation-concealment procedures are not reported in the registry record.

No masking means the registry does not describe blinding. Knowledge of the assigned protocol can matter for outcomes involving clinical decisions or participant reports, although the primary endpoint is a count of transfused units. The record does not report whether the outcome was independently assessed or whether anyone involved in recording it was masked.

Why compare means with a t-test?

General statistical explanation: a two-sample t-test evaluates whether the data provide evidence of a difference between group means, given a model for variation within groups. A two-sided test considers differences in either direction rather than testing only for a prespecified direction. The registry reports a two-sided t-test for the primary comparison, with p <0.001. The registry record does not report additional details about the test's variance assumptions or whether any covariates were included.

A mean difference expresses the estimated separation between group averages in the outcome's original units. For this outcome, the unit is units of blood. The posted recalculation compares the multiple-unit protocol with the single-unit protocol and gives a mean difference of 0.9. Because the outcome is a count summarized as a mean, the estimate need not describe the experience of every participant.

What does a standard deviation describe?

General statistical explanation: a standard deviation describes how spread out observations are around a group mean. It is a feature of the observed group data, not a measure of uncertainty in the mean difference. Uncertainty in a group comparison is represented by the standard error and confidence interval. The posted group standard deviations are 0.5 and 0.4, and the recalculation reports group standard errors of 0.087 and 0.070.

In general, a standard error reflects how precisely a statistic is estimated, taking account of variability and the amount of information available. The confidence interval for a mean difference uses this uncertainty to give a range of values compatible with the data under the analysis assumptions. It should not be read as containing a specified proportion of individual participants' outcomes.

Why does over-dispersion matter for count outcomes?

General statistical explanation: for count data, over-dispersion means that variability is greater than expected under a simple count model. If a model assumes less variation than the data contain, standard errors can be too small and inferential results can appear more precise than warranted. Different count-data models can account for different variance patterns. In this trial, the primary outcome is reported as a mean and standard deviation, and the sponsor's reported analysis is a t-test. The registry record does not report a count-regression analysis or a formal assessment of over-dispersion.

The choice of analysis should be understood in light of the outcome and the study's stated method, rather than inferred from the outcome label alone. The posted group summaries do not provide the individual observations or full distribution needed to assess alternative models independently. The registry record does not report a sensitivity analysis using another model.

How should secondary binary outcomes be analyzed?

General statistical explanation: a binary outcome records whether an event or status is present for each participant. A risk difference compares the proportions between groups in absolute terms. A confidence interval for a risk difference describes uncertainty in that comparison. When outcomes are sparse, such as events that occur infrequently, estimates can be imprecise and small changes in event counts can have a large effect on the estimated relative measure.

The registry reports chi-squared analyses for the posted breastfeeding and infection comparisons. The recalculations give unadjusted risk differences and confidence intervals. The record does not report whether the chi-squared analyses used a continuity correction or any alternative method for sparse data. General statistical explanation: a chi-squared test compares observed counts with counts expected under a no-association model, and its usual approximation may be less reliable when expected cell counts are small. That consideration is relevant when interpreting analyses with few events, but the record does not provide the expected cell counts.

What can and cannot be inferred from the posted analyses?

The primary recalculation uses the posted summary statistics and is unadjusted. It is not a replacement for the sponsor's own reported analysis. The sponsor reports a two-sided t-test and the same thresholded p-value as the recalculation; no discrepancy is flagged. The record does not report a prespecified statistical analysis plan, detailed model diagnostics, covariate adjustment, or the handling of protocol deviations. Those details therefore cannot be assumed.

The registry also does not report whether interim analyses were conducted or whether stopping rules were used. General statistical explanation: interim looks at accumulating data can affect how evidence is interpreted if they are not accounted for in the analysis. Since such procedures are not reported in the registry record, no conclusion about them can be drawn for this trial. Similarly, the statistical methods for any secondary endpoint whose results are not posted cannot be established from the available record.

11. Confidence Intervals and Precision

The primary mean difference is reported as 0.9 units, with a confidence interval that does not cross zero. This indicates that, under the assumptions of the unadjusted comparison, the data support a positive difference in the direction defined as multiple-unit protocol minus single-unit protocol. The posted interval provides a range of plausible values for that mean difference, not a range containing a specified proportion of individual outcomes.

General statistical explanation: a confidence interval reflects both the estimated effect and its sampling uncertainty. A narrower interval indicates greater precision for the estimate under the model, while a wider interval indicates more uncertainty. An interval that crosses zero for a difference measure includes no difference among the values compatible with the data at the stated confidence level. Whether an interval is clinically important is a separate judgment and is not established by its width or its position relative to zero alone.

The posted primary interval is much more informative about the mean difference than the p-value by itself, because the p-value does not show the range of effect sizes consistent with the data. The registry record does not report a sponsor confidence interval for the primary comparison, but the recalculated interval is posted with the unadjusted estimate. It is based on the available summary statistics rather than individual participant data.

The secondary comparisons are less precise. Their posted risk-difference intervals include zero, and the infection comparison is based on few observed events. General statistical explanation: sparse outcomes commonly produce broad uncertainty, so an estimate near zero does not rule out effects in either direction when the interval is wide. These secondary intervals should not be interpreted as proof of equivalence or as confirmation that the groups are identical.

All intervals and p-values depend on the analysis assumptions and the observed data. The registry record does not report additional sensitivity analyses or uncertainty estimates for outcomes whose results are not posted. Precision also does not resolve concerns about missing observations, outcome measurement, or how far the trial findings can be generalized.

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 illustrations based on the observed effect, not the trial's original design justification. For the outcomes with planning calculations, the figures are participants per arm; they are not total-event counts. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each calculation targets the stated fraction of the observed effect.

For the primary endpoint, the illustration for 100% of the observed effect gives 4 participants per arm for 80% power and 6 participants per arm for 90% power. For 75% of the observed effect, the figures are 8 and 10 participants per arm, respectively. For 50% of the observed effect, they are 16 and 22 participants per arm. Smaller effects need more participants to detect under the same assumptions, because the group difference is harder to distinguish from random variation.

The 80% power column describes the sample size that the calculation estimates would give an 80% chance of detecting the specified effect if that effect were present and the assumptions held. The 90% power column uses a higher chance of detection and consequently gives larger planning figures. These are planning illustrations, not observed power.

The enrollment recorded for the trial is 66. That figure should not be treated as a validation of the illustration or as evidence that the trial was designed for any particular power target. The original design assumptions and sample-size justification are not reported in the registry record. The posted planning figures do not account for any unreported design features, missingness, or analysis choices beyond the stated 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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 0.900; pooled standard deviation σ = 0.453.
2. n = 2 × (1.96 + 0.842)² × 0.453² / 0.900² = 4.0, rounded up to 4 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
delta <- 0.9                      # observed difference in means
sigma <- 0.452769256906871                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(3419780)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 4 (80% power), 6 (90% power)
 75% of observed effect: n per arm = 8 (80% power), 10 (90% power)
 50% of observed effect: n per arm = 16 (80% power), 22 (90% power)
power.t.test: 5.1 
Simulated power at n = 4 per arm: 0.651 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 reported primary analysis is a two-sided t-test with p <0.001. The recalculated unadjusted comparison of the posted group means also has p <0.001, and the registry record does not flag a discrepancy. The sponsor result and the recalculation therefore agree at the precision reported.

The recalculation uses posted group summary statistics to estimate an unadjusted mean difference of 0.9 units and its confidence interval. It is a simple re-analysis of those summaries, not a separate participant-level analysis and not a substitute for any fuller sponsor analysis. The registry record does not post a sponsor estimate or confidence interval for the primary comparison in its reported-analysis entry.

Because there is no discrepancy flagged, the two accounts do not conflict. If recalculated and sponsor results did conflict, the sponsor's own analysis would take precedence, but that circumstance is not indicated for this comparison. Details that would allow further evaluation of the sponsor's analysis, such as a complete statistical analysis plan or model diagnostics, are not reported in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The registry reports a primary endpoint and multiple secondary outcomes. It identifies a t-test for the primary result and chi-squared tests for the posted breastfeeding and infection analyses. The record does not report a family-wise error strategy, false-discovery procedure, adjustment of secondary p-values, or a prespecified hierarchy for testing outcomes. As a result, the secondary p-values should be read as unadjusted comparisons rather than as a set with a documented multiplicity-control plan.

The record lists length of stay, depression, fatigue, and maternal attachment inventory scores as secondary outcomes, but their results are not reported in the registry record. It is not possible to determine from the record whether those measures were collected, how they were analyzed, or why results are absent. The record also does not report whether the posted secondary outcomes represent all outcomes in the protocol.

Missing-data handling is not reported in the registry record. The breastfeeding outcome includes 29 participants in the single-unit group and 27 in the multiple-unit group, whereas the primary outcome summaries list 33 in each arm. The reason for the different reported counts is not stated. It would be inappropriate to infer why observations are unavailable or to assume that missingness had no effect on the comparison.

The registry does not report the analysis population definition, such as whether the primary analysis followed all randomized participants or another specified set. It also does not report imputation methods, sensitivity analyses for missing data, or details about exclusions after randomization. These omissions limit assessment of whether analyses preserve the benefits of random assignment and how robust the results are to missing observations.

Interim analyses, stopping boundaries, and monitoring procedures are not reported in the registry record. Nor are protocol deviations and their handling described. These matters are relevant to interpreting the conduct and analysis of a randomized trial, but their absence from the record does not establish that such procedures were or were not used.

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 non-serious adverse event terms

The registry reports serious adverse events for 33 participants at risk in each arm. It records 0 serious adverse events in the single-unit group and 0 in the multiple-unit group. The deaths field is 0 for each arm. No serious adverse event terms are listed.

For other adverse events, the registry reports 0 affected participants in the single-unit group and 1 in the multiple-unit group, with 33 participants at risk in each group. The record does not provide a term for that other event in the posted safety summary, so its nature and severity cannot be described from this information.

These figures are counts observed in the registry's safety reporting, not proof that serious harms cannot occur. General statistical explanation: when an event is uncommon, observing no events in a trial does not establish that the underlying risk is zero. The trial's safety figures should be interpreted within the recorded follow-up and the information available; the registry does not provide further detail about safety definitions or adjudication.

The safety counts are separate from the primary endpoint, which measures transfused units. They do not determine the meaning of the primary comparison and should not be taken as a complete account of all potential harms.

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

The primary result describes a difference in average total units transfused between the randomized protocols during the period from randomization until discharge from the delivery admission. The posted means are 1.2 units for the single-unit protocol and 2.1 units for the multiple-unit protocol; the recalculated mean difference is 0.9 units, with a confidence interval above zero and p <0.001.

This is evidence of a difference on the stated measure in this trial. It is not, by itself, evidence about differences in maternal recovery, symptoms, breastfeeding, depression, fatigue, attachment, or longer-term outcomes. Those are distinct measures, and results for several listed secondary outcomes are not reported in the registry record.

The result also does not establish that one protocol is appropriate for every clinical circumstance. The registry identifies non-acute postpartum anemia but does not report detailed eligibility criteria or enough information to characterize all circumstances represented. The results should therefore be understood in the context of the trial's enrolled population and protocol definitions, not generalized to populations or care situations that the record does not describe.

The confidence interval communicates uncertainty around the estimated average difference, while the p-value addresses compatibility with a null comparison under the analysis. Neither statistic answers questions about the importance of the difference in clinical practice. The registry record does not report a threshold for a clinically meaningful difference in total units or a formal benefit-harm assessment.

The posted safety information records no serious adverse events in either arm, but the trial's safety counts do not establish the absence of risk. The available secondary outcomes are limited and some results are missing from the registry record. Taken together, the evidence supports a conclusion about the primary transfusion-use endpoint, while broader claims about outcomes, harms, and applicability remain outside what the posted record establishes.

18. Why This Trial Matters Statistically

This trial asks a focused statistical question about a measurable resource-use outcome: whether assigned single-unit and multiple-unit transfusion protocols differ in mean total units transfused by discharge from the delivery admission. The endpoint matches the study's stated objective of comparing total units, and random assignment gives the comparison a design intended to reduce confounding between groups.

The primary result also illustrates why effect estimates and uncertainty are more informative together than a p-value alone. The mean difference is reported in the outcome's original units, and its confidence interval is entirely on the positive side of zero. The sponsor's two-sided t-test and the unadjusted recalculation agree at the posted p-value, so the principal statistical result is not dependent on a disagreement between those accounts.

The trial also demonstrates the distinction between a clear primary comparison and uncertain secondary evidence. The secondary outcomes address different domains, have less conclusive posted comparisons, and are subject to multiplicity concerns. Results for several listed measures are not reported, and the registry does not describe adjustment for multiple testing. These limitations make it important to keep conclusions tied to the outcome and analysis that are actually posted.

Finally, planning calculations based on an observed effect are not a substitute for the original design rationale. The registry record does not report the trial's own sample-size justification or analysis plan. Recognizing that distinction helps prevent post hoc planning illustrations from being mistaken for evidence about the trial's design intent or its observed power.

19. Limitations

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

The registry record leaves important design and analysis details unspecified. It does not report detailed eligibility criteria, the random-sequence generation method, allocation concealment, or the original sample-size justification. The registry's phase entry is NA, and no further phase information is reported.

The study is listed as unmasked. The record does not describe blinded outcome assessment, independent adjudication, or procedures to reduce the influence of treatment knowledge. It also does not provide the statistical analysis plan, covariate adjustment details, diagnostic checks, or sensitivity analyses for the primary result. The sponsor reports a two-sided t-test, but the record does not give enough detail to evaluate all assumptions or alternative analyses.

Missing-data methods and the analysis population are not reported. The breastfeeding outcome has fewer reported participants than the primary outcome summaries, and the reason for this difference is not stated. Results for length of stay, depression, fatigue, and maternal attachment inventory scores are not reported in the registry record, limiting interpretation of the full set of planned or listed outcomes.

The registry does not report whether secondary comparisons were adjusted for multiplicity, whether interim analyses occurred, or how protocol deviations were handled. It also does not provide individual observations or outcome distributions, which restricts independent assessment of the primary mean comparison and alternative models for count data.

Finally, the posted safety summary gives counts but little detail about the non-serious event, event definitions, or safety assessment procedures. These omissions do not negate the primary result, but they constrain how broadly the trial can be interpreted and what can be concluded about outcomes beyond total units transfused.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: SMaRT Blood: Single-unit Versus Multiple-unit Packed Red Blood Cell Transfusion in Non-acute Postpartum Anemia — NCT03419780.
• Registry record last updated 2020-11-04; status last verified 2020-11.
• Results first posted 2020-11-04.
• 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

SMaRT Blood is a completed randomized, controlled, parallel-group trial sponsored by the University of Pennsylvania. It compares a single-unit packed red blood cell transfusion protocol with a multiple-unit protocol in non-acute postpartum anemia. Masking is listed as none, and recorded enrollment is 66.

The primary endpoint is mean total units transfused from randomization until discharge from the delivery admission. The posted means are 1.2 units in the single-unit arm and 2.1 units in the multiple-unit arm. The recalculated unadjusted mean difference is 0.9 units, with p <0.001; the sponsor reports a two-sided t-test with p <0.001.

Secondary results are posted for exclusive breastfeeding and infection; results for several other listed secondary outcomes are not reported in the registry record. The record does not report the original sample-size justification, detailed missing-data methods, or multiplicity procedures. Safety reporting records no serious adverse events or deaths in either arm.