Preventing Excessive Gestational Weight Gain in Obese Women: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Preventing Excessive Gestational Weight Gain in Obese Women (NCT01545934), a randomized na study. The primary outcome is Weight Gain Per Week of Observation.

2. Clinical Question

The trial also listed secondary outcomes concerning offspring weight gain and dietary intake, daily calories, maternal glucose, exceeding IOM guidelines, and being at or below prepregnancy weight after delivery. These outcomes address related but distinct questions: the primary endpoint concerns the rate of maternal gestational weight gain, while the secondary measures include other maternal outcomes and outcomes concerning offspring. The registry record contains posted results for two of the listed secondary outcomes. It does not report results for the others in the posted outcome information.

3. Trial Design

This was a randomized, parallel-group trial with single masking. The registry record lists an enrollment of 264 and marks the study status as completed. Its phase is recorded as NA. The record identifies California Polytechnic State University-San Luis Obispo as the sponsor. The listed study start was 2012-11, and primary completion was 2016-05.

Participants were assigned to standard care or a lifestyle intervention. The posted primary outcome has arm results for 127 participants in standard care and 129 in the intervention arm. These are the denominators attached to that outcome; other outcomes use their own denominators. Random allocation is intended to make comparison groups similar on average at the point of assignment, although it does not ensure that every measured or unmeasured characteristic is balanced in a particular trial. The registry record does not report allocation concealment or the details of the randomization procedure.

Single masking indicates that the record describes the study as having one level of masking, but it does not identify who was masked. It is therefore not possible to say from this record whether participants, care providers, outcome assessors, or another group were unaware of assignment. The arm descriptions provide no further account of treatment delivery or standard care.

The primary outcome timeframe is described as 13 weeks gestation to 35 weeks gestation. The outcome description says that the rate was computed from the difference between study-entry weight and weight at gestational week 35, divided by the number of weeks observed between study entry and the final pregnancy assessment. If a week-35 weight was unavailable, the most proximal clinic-visit weight was to be used. Details about the original sample-size justification, planned statistical model, and intended analysis population are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

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: Participants who withdrew (N = 7) are not included in baseline analysis population table or in any results.

6. Primary Endpoint

The registry lists the primary outcome as Weight Gain Per Week of Observation, measured over 13 weeks gestation, 35 weeks gestation.

The primary endpoint is titled Weight Gain Per Week of Observation and is measured in kg/wk. It represents an average rate over the observation period rather than a single weight or the total amount gained over a fixed common duration. According to the registry description, it uses the difference between a participant’s weight at study entry and a later pregnancy assessment, divided by the number of weeks between those assessments. The target assessment was gestational week 35; when that measurement was unavailable, the description specifies using the most proximal clinic visit weight.

A rate is used because participants may enter the study at different gestational weeks or have different lengths of observation. Expressing gain per week makes the recorded change relative to each participant’s observation time. That can support a comparison of average rates between randomized groups, but it does not make the observation periods identical or remove all possible effects of missing or differently timed measurements.

The posted endpoint is characterized as a least-squares mean, with dispersion labeled as standard deviation. The registry record does not give the model or covariates used to obtain the least-squares means, nor does it describe how missing measurements were handled beyond the stated use of a proximal clinic weight when the week-35 weight was unavailable. These omissions limit what can be inferred about the exact construction of the endpoint and the adjustment, if any, in the posted arm means.

7. Results Posted in the Registry

• Lifestyle Intervention: mean 0.33 versus 0.39 on control; difference -0.06 (95% CI -0.12 to -0.00), standardized effect d = -0.25; z-test p = 0.046.

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 Women Exceeding IOM Guidelines as a Proportion of Total Number of Women in Each Group.

• 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:
  • Lifestyle Intervention: 41.1% (53/129) versus 54.3% (69/127) on control; risk difference -13.2 percentage points (95% CI -25.4 to -1.1), risk ratio 0.76 (0.58–0.98); unadjusted two-proportion z-test p = 0.034.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Lifestyle Intervention than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Women at or Below Prepregnancy Weight as a Proportion of the Total Number of Participants in Each Group

• 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:
  • Lifestyle Intervention: 31.8% (41/129) versus 29.7% (38/128) on control; risk difference 2.1 percentage points (95% CI -9.2 to 13.4), risk ratio 1.07 (0.74–1.55); unadjusted two-proportion z-test p = 0.716.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lifestyle Intervention and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address several dimensions beyond the primary rate of maternal weight gain, including dietary, glucose, offspring, guideline, and postpartum measures. The registry record lists six secondary outcomes, while posted arm results and comparisons are available for two. The outcomes differ in their definitions, measurement times, and denominators, so their results do not form a single unified measure of the intervention.

The overall pattern is not uniformly aligned across the posted secondary findings. The comparison for exceeding IOM guidelines points in a direction consistent with the lower primary rate in the intervention arm, whereas the comparison for being at or below prepregnancy weight after delivery is uncertain and does not show a clear group difference. This pattern may be considered alongside the primary result, but these outcomes are not direct substitutes for the primary rate endpoint. Nor do they establish why the groups differed or whether a change in gestational weight-gain rate leads to a later outcome.

Secondary findings generally carry less weight when their status in the analysis plan, ordering, and multiplicity handling are unknown. The registry record does not report a prespecified hierarchy or adjustment for multiple comparisons, and the posted p-values are unadjusted. In general, examining multiple outcomes can yield apparently notable results by chance even when no corresponding underlying effect exists. This concern does not make secondary results irrelevant; it means they are best treated as supportive or exploratory rather than as independent confirmation.

The registry record does not post results for the other listed secondary outcomes. Their absence should not be interpreted as evidence of no effect or as evidence of a particular direction. Overall, the secondary information adds context to the primary endpoint but does not remove uncertainty about the size, durability, or broader implications of the primary comparison.

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

• Offspring Weight Gain
• Kcals/Day
• Changes in Offspring Dietary Intake
• Changes in Maternal Glucose
• Number of Women Exceeding IOM Guidelines as a Proportion of Total Number of Women in Each Group.
• Number of Women at or Below Prepregnancy Weight as a Proportion of the Total Number of Participants in Each Group

9. Statistical Interpretation

10. Statistical Methods Explained

The endpoint is continuous: each participant’s outcome is a rate of weight gain, and the arm-level summaries report means in kg/wk. A mean describes the arithmetic center of a set of observations, while the standard deviation describes how spread out individual observations are around that center. The posted standard deviations are 0.23 in standard care and 0.25 in the intervention arm. They describe variation among observations; they are not confidence intervals for the means.

What does a mean difference describe?

The primary comparison is the intervention mean minus the standard-care mean. The estimate is -0.06 kg/wk, so the posted intervention mean is lower. A difference in means preserves the units of the outcome, which makes its direction and scale interpretable in kg/wk. The comparison does not say that every participant in the intervention arm had a lower rate, and it does not describe the distribution of individual responses.

The registry labels the primary arm summaries as least-squares means. In general, a least-squares mean is a model-based group mean, often adjusted for variables included in a statistical model. The registry record does not report the model specification or any adjustment variables. The posted comparison should therefore be read as the reported mean difference, without assuming which covariates or modeling choices produced it.

What does the confidence interval add?

A confidence interval gives a range of values compatible with the observed estimate under the statistical procedure used, reflecting sampling uncertainty. For the primary mean difference, the posted interval is -0.119 to -0.001 kg/wk. Because zero is outside that interval, it corresponds to a conventional two-sided finding against a zero difference at the associated confidence level. The registry record does not state the confidence level in the outcome information; it should not be inferred solely from the bounds. The interval is also not a range containing a fixed proportion of individual participants’ outcomes.

How should the p-value be read?

The primary p-value is 0.046 and is labeled unadjusted. In general, a p-value measures how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the statistical assumptions were true. It is not the probability that the null hypothesis is true, nor does it measure the probability that the result will replicate. It also does not quantify clinical importance. The record does not report the full test specification or model assumptions underlying the p-value.

Because the posted p-value is unadjusted, it does not account for testing other outcomes. The trial lists multiple secondary measures, and results are posted for two of them. When several outcomes are examined, the chance of obtaining at least one apparently notable result can increase. General statistical practice may address that issue through prespecified outcome hierarchies or multiplicity procedures, but the registry record does not report such a plan or adjustment. The unadjusted secondary p-values therefore need cautious interpretation.

What do the binary outcomes measure statistically?

The secondary outcomes concerning IOM guidelines and prepregnancy weight are counts of participants meeting a stated condition. Their comparisons are reported as risk differences: the intervention-arm proportion minus the standard-care proportion. A risk difference is an absolute contrast on the probability scale. A negative estimate means a lower observed proportion in the intervention arm; a positive estimate means a higher observed proportion. The confidence interval describes uncertainty in that contrast. For the guideline outcome, the reported interval excludes zero; for the postpartum outcome, it includes zero. These statements concern the posted unadjusted comparisons and do not establish a causal mechanism.

General statistical interpretation of a binary outcome depends on clear definitions of the event, denominator, and assessment time. Here, the registry provides outcome titles and timeframes, but does not provide detailed participant-level information or report analyses for these outcomes. The different denominators and timeframes should be kept in view when considering whether one result aligns with another.

What can randomization and masking contribute?

In general, random assignment helps support a causal comparison by balancing prognostic factors on average, while masking can reduce some forms of behavior or assessment influenced by knowledge of assignment. Those safeguards depend on how the study was implemented. The record says allocation was randomized and masking was single, but it does not report concealment procedures or identify who was masked. It is therefore not possible to assess those implementation details from the registry record.

The posted comparisons are not labeled as adjusted analyses, and no reported analysis details are listed. No assumptions about model selection, missing-data methods, subgroup analyses, or interim analyses should be added. A statistical estimate and its precision can be described from the posted results, while questions about analytic choices remain unanswered in the registry record.

11. Confidence Intervals and Precision

The primary mean difference is -0.06 kg/wk, with a confidence interval from -0.119 to -0.001 kg/wk. The interval lies below zero, but its upper end is close to zero. This means the posted data are compatible with a comparatively small difference as well as with a larger reduction in the rate. The interval conveys uncertainty more directly than the point estimate alone, while not identifying which value within the range is most likely or resolving whether any value is important to patients.

The p-value of 0.046 is consistent with the interval excluding zero for the posted primary comparison. Neither statistic indicates that the result is precise in an absolute sense. Precision depends on the width of the interval and the variability and amount of information in the analysis. The registry record gives arm-level outcome counts and standard deviations, but does not describe the exact analysis population or model used for the least-squares means.

For the secondary guideline outcome, the risk-difference interval excludes zero; for the postpartum outcome, the interval includes zero and spans differences in either direction. These interval patterns express different degrees of uncertainty about the respective group contrasts. They do not establish that one outcome is more important than another, and they should be interpreted in light of the fact that the comparisons are unadjusted.

Confidence intervals represent uncertainty under the method and assumptions used; they do not cover every possible source of bias. Missing outcome data, deviations from assigned intervention, measurement differences, or analytical choices can affect how well an interval reflects uncertainty in the underlying clinical question. The registry record does not report enough detail to evaluate all of those issues.

12. Planning a Similar Trial: Sample Size

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

The sample-size figures are planning illustrations based on the observed effect, not the trial’s original design assumptions. For these non-time-to-event outcomes, each figure is participants per arm, not a total across arms. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect being targeted is the stated fraction of the observed effect.

The 80% power column gives the planned number of participants per arm under those assumptions for an 80% chance of detecting the specified effect if that effect were the true effect and the assumptions held. The 90% power column describes the corresponding planning number per arm for a 90% chance. These are design calculations, not guarantees about what a future study will find. The sample size needed depends on the effect targeted and the assumptions used in the calculation.

The rows for 100%, 75%, and 50% of the observed effect illustrate planning around progressively smaller effects. Smaller effects are harder to distinguish from random variation, so the planning figures increase as the assumed effect gets smaller. The figures are illustrative and depend on treating the observed effect as a basis for planning; they do not establish that the observed effect is stable or that the original trial was designed around it.

This is not observed power. The original sample-size justification, power target, and design assumptions are not reported in the registry record. The figures should be read as hypothetical planning guidance under the stated assumptions, rather than as a retrospective measure of the trial’s success or as evidence that a particular result is certain.

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 = -0.060; pooled standard deviation σ = 0.240.
2. n = 2 × (1.96 + 0.842)² × 0.240² / -0.060² = 251.8, rounded up to 252 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 <- -0.06                      # observed difference in means
sigma <- 0.240286902005895                     # 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(1545934)
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 = 252 (80% power), 338 (90% power)
 75% of observed effect: n per arm = 448 (80% power), 600 (90% power)
 50% of observed effect: n per arm = 1,008 (80% power), 1,349 (90% power)
power.t.test: 252.7 
Simulated power at n = 252 per arm: 0.799 (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. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates more than one outcome or makes several statistical comparisons. Even if each test is interpreted using a conventional threshold, repeated testing can increase the chance that at least one result appears notable by chance. This is a general statistical concern, not a claim that any particular posted result is false.

The registry record lists a primary outcome and six secondary outcomes. Results are posted for the primary outcome and two secondary outcomes. The posted comparison p-values are unadjusted. The record does not report a multiplicity adjustment, an ordered testing strategy, or a hierarchy specifying how secondary results were to be interpreted relative to the primary endpoint. Consequently, the secondary p-values should not be read as though they were isolated tests selected in advance, and the primary p-value alone does not resolve questions raised by the multiple outcomes.

The record also does not report a detailed missing-data plan or the number of participants with missing measurements for each outcome. The primary endpoint description says to use the most proximal clinic visit weight if a gestational week-35 weight is unavailable. That rule describes a measurement substitution, but does not explain how all other missing information was handled, whether the substitute was used for every relevant case, or whether sensitivity analyses were conducted.

Analysis populations are another unreported area. The registry record does not say whether the results follow an intention-to-treat approach, whether participants were analyzed according to assigned group, or whether any exclusions occurred. It does not report adherence, treatment crossover, or losses to follow-up in a way that permits assessment of their effect on the estimates. The reported denominators vary by outcome, so denominators should be understood separately rather than assumed to represent identical analysis populations.

Finally, the registry record does not report interim analyses, stopping rules, or the detailed statistical analysis plan. These items are not grounds to infer a particular flaw; they are limits on how completely the posted estimates can be evaluated. The available summaries permit a description of the group results and their reported uncertainty, but not a full audit of analysis choices or missing-data sensitivity.

15. Safety Results

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

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The serious adverse event figures list zero serious adverse events in each arm. The number at risk for this reporting is 128 in standard care and 129 in the lifestyle intervention arm. These are safety denominators and should be kept distinct from the primary outcome denominators.

The registry record also lists five other adverse events in standard care and four in the intervention arm, with 128 and 129 participants at risk, respectively. These counts are descriptive. The record does not provide event terms, severity detail for these other events, exposure-adjusted rates, or a statistical comparison, so the counts alone do not show whether the groups differed in underlying risk.

Deaths are not reported in the registry record. A zero count for serious adverse events should not be taken to mean that all possible harms were absent; it refers to the reported serious-event count and the available safety information. These figures describe the safety entries in the registry and do not provide a complete clinical safety assessment.

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

The posted data show a lower average rate of gestational weight gain in the lifestyle intervention arm than in standard care: 0.33 kg/wk compared with 0.39 kg/wk. The estimated mean difference is -0.06 kg/wk, and the reported confidence interval lies below zero. These results describe the recorded trial outcomes and the unadjusted comparison; they do not establish that every participant had the same response or that the difference was clinically important.

The result does not, by itself, establish how the intervention affected outcomes not reported in the registry record, including the listed offspring, dietary, and glucose measures. Nor does it establish a mechanism, persistence beyond the recorded assessment, or generalizability to populations other than the women represented by this trial. The registry record does not describe enough eligibility and participant characteristics to determine how broadly the findings apply.

The comparison also does not show that the intervention is appropriate for any individual. A trial-level average cannot predict an individual outcome, and the information in the registry record is not a basis for personal treatment decisions. The results should be understood as statistical descriptions of groups assigned in this study.

The unadjusted primary p-value is 0.046, but statistical evidence against a zero difference is not the same as evidence of a meaningful benefit. The confidence interval gives a range of estimates compatible with the analysis, and its upper bound is close to zero. The lack of reported details on the analysis plan, missing outcomes, and multiplicity further limits certainty. The result is best characterized as a modest estimated difference with uncertainty, not as a definitive account of all maternal or offspring outcomes.

17. Why This Trial Matters Statistically

This trial illustrates why an endpoint’s definition matters. Weight gain per week is a rate derived from measurements taken over an observation period, rather than a single fixed-time measurement. That choice permits comparison when observation periods may differ, but also makes the timing and availability of measurements important to interpretation. The registry’s rule for using a proximal clinic weight when a week-35 weight was unavailable is therefore part of understanding what the endpoint represents.

The result also demonstrates the value of presenting an estimate with its interval rather than relying only on a thresholded p-value. The mean difference and its confidence interval describe direction, scale, and uncertainty. The p-value alone would not show that the interval’s upper end is close to zero or convey the range of compatible differences.

Multiple outcome families complicate the interpretation. The primary outcome concerns a continuous rate, while the listed secondary measures include participant counts and other maternal and offspring endpoints. A pattern across these measures can provide context, but unadjusted secondary tests do not carry the same evidential weight as a clearly specified primary comparison. The registry record’s lack of a reported multiplicity strategy makes that distinction especially important.

Finally, the record shows how a completed trial can have posted estimates while leaving important analysis details unreported. The means, standard deviations, comparisons, and safety counts support a clear description of the available results. They do not provide a complete account of model specification, missing-data handling, analysis populations, or the original design assumptions. Statistical interpretation depends both on the numbers and on knowing how those numbers were generated.

18. 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 gives limited detail about intervention delivery and the standard-care comparator. It identifies a multicomponent lifestyle intervention that included partial meal replacements, but does not describe the individual components, intensity, adherence, or delivery. Standard care is not further defined. This makes it difficult to determine what specific contrast the posted results represent in practice.

The primary endpoint description allows a proximal clinic weight to replace an unavailable week-35 measurement. The record does not report how many measurements required that substitution, the timing of those measurements, or whether other data were missing. Since the outcome is a rate divided by observation time, variation in measurement timing and completeness may matter. The posted record does not provide information to evaluate that issue fully.

The analysis details are sparse. The least-squares means are reported without the model specification or adjustment variables, and the registry does not describe analysis populations, exclusions, adherence, or sensitivity analyses. The original sample-size justification is also not reported in the registry record. These gaps prevent a full assessment of whether the posted comparison matches the intended analysis and how robust it is to alternative assumptions.

Single masking is recorded, but the record does not identify who was masked or describe how masking was maintained. Allocation concealment and the randomization procedure are also not described. These are reporting limitations; the available information does not establish that the procedures were inadequate.

Finally, results are not posted for all listed secondary outcomes, and the secondary comparisons that are posted are unadjusted. The record does not report a multiplicity plan. These limitations restrict interpretation of the broader outcome pattern and make secondary findings less conclusive than a prespecified, fully documented analysis would be.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Preventing Excessive Gestational Weight Gain in Obese Women — NCT01545934.
• Registry record last updated 2021-08-02; status last verified 2021-07.
• Results first posted 2021-01-28.
• 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.

22. Record Summary

The registry record describes a completed, randomized, parallel-group, single-masked trial comparing a lifestyle intervention with standard care in obese women. The primary outcome was weight gain per week of observation, measured in kg/wk. The posted means were 0.39 in standard care and 0.33 in the intervention arm, with a reported mean difference of -0.06 kg/wk and an unadjusted p-value of 0.046.

The primary confidence interval lies below zero but has an upper bound close to zero. Two secondary outcomes have posted comparisons, with different directions of evidential support; the other listed secondary outcomes do not have posted results in the registry record. Serious adverse event counts are zero in both arms, while other adverse-event counts are five and four. Deaths are not reported in the registry record.

The results support a description of the posted group comparisons, but the registry record does not report the original sample-size justification, detailed statistical plan, analysis populations, or comprehensive missing-data handling. Those omissions, along with unadjusted secondary comparisons, limit the strength and scope of conclusions that can be drawn.