mHealth Medication Safety Intervention: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for mHealth Medication Safety Intervention (NCT03247322), a randomized na study. The primary outcome is Number of Medication Errors.

2. Clinical Question

3. Trial Design

TRANSAFE Rx was a randomized, parallel-group clinical trial with 1:1 allocation. The registry reports a single masking designation but does not identify which people were masked. The trial included 136 participants, with 68 assigned to the intervention group and 68 to the control group. Its stated duration was 12 months. The registry lists the study as completed, with a start date of 2017-10-11 and primary completion date of 2020-02-03.

The intervention combined pharmacist-led medication therapy with an mHealth application. The intervention description emphasizes enhanced medication-safety monitoring and a tool for self-care monitoring and management, including reminders to take medication. The control group received usual follow-up care for kidney transplant patients. Further detail about the intervention's delivery, frequency of pharmacist contact, or participant use of the application is not reported in the registry record.

The primary outcome was the number of medication errors during 1 year. The registry defines a medication error as documentation that a patient is taking a medication in a manner that was not intended. It reports a mean and standard deviation for each group. Hospitalization rate, expressed as hospitalizations per patient-year over 1 year, is the posted secondary outcome. The registry lists six outcome measures overall, but only one secondary outcome is posted in the available results.

The record identifies the study as phase NA and lists Medical University of South Carolina as the sponsor. The trial's original sample-size justification, planned analysis population, intended covariate adjustments, and full protocol-level statistical methods are not reported in the registry record. Randomization is reported, but details about sequence generation, concealment, stratification, or implementation are not reported in the registry record. Those omissions limit how specifically the trial's design and analysis procedures can be reconstructed from the record alone.

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 Number of Medication Errors, measured over 1 year.

The primary endpoint is the number of medication errors observed over 1 year. The registry defines an error as documentation that a patient is taking a medication in a manner that was not intended. The outcome is summarized as a mean number of errors, with a standard deviation in each group. The posted means were 9.0 for the intervention group and 20.0 for the control group; each group included 68 participants.

Medication errors are relevant to the trial's stated aim of improving medication safety after kidney transplantation. Counting errors offers a way to describe the burden of documented medication use that does not match what was intended. Comparing the group means gives a summary of the average number of errors recorded in each randomized group over the same stated follow-up period. It does not show whether every participant experienced an error, how errors were distributed among participants, or the seriousness of each error. Those details are not reported in the registry record.

General statistical context: a mean is useful for summarizing a numeric outcome across a group, but it can conceal variation between participants. The standard deviations help describe that variation, while the estimated difference in means focuses on the contrast between groups. The outcome definition depends on documentation, so the endpoint reflects medication errors identified and recorded under the study's procedures. The registry record does not provide further detail about error ascertainment or adjudication.

7. Results Posted in the Registry

• Intervention Group: mean 9.00 versus 20.00 on control; difference -11.00 (95% CI -14.57 to -7.43), standardized effect d = -1.04; 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.

Hospitalization Rate

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, with the standard error taken from the posted confidence limits.
• Result:
  • mHealth Group: 0.65 versus 1.08 (Hospitalizations per patient-year) on control; rate ratio 0.60 (95% CI 0.31–1.15, derived from the posted confidence limits); p ≈ 0.126.
• Interpretation:
  • The 95% confidence interval includes no difference (a ratio of 1), so these data do not show a statistically significant difference between mHealth Group and the control. The interval gives the range of effects that remain compatible with the data.

The registry posts hospitalization rate as the secondary outcome. Its estimated rate ratio is below 1, while its confidence interval includes 1 and its unadjusted p-value is 0.126. This outcome therefore provides a less definitive statistical contrast than the primary medication-error result. It addresses healthcare use rather than the medication-error count itself, so the two outcomes describe related but distinct aspects of the study's stated goals.

The primary endpoint concerns documented medication use that did not match what was intended. Hospitalizations may reflect many factors and are not interchangeable with medication errors. A difference in one endpoint does not require a corresponding difference in the other, and the hospitalization result cannot be used on its own to confirm or refute the medication-error finding. The registry does not report analyses examining whether participant-level medication errors were associated with hospitalizations.

Only one secondary outcome is posted, although the registry lists six outcome measures in total. The other outcome results are not reported in the registry record. The registry also reports no analyses for the secondary outcome. This means the posted rate comparison should be understood as the available unadjusted result, rather than as a full account of all analyses that might have been planned.

General statistical context: when several outcomes are examined, the chance of at least one apparently notable result can increase if each is tested separately without adjustment. This is why unadjusted secondary findings generally carry less weight than a prespecified primary endpoint, especially when the analysis plan and multiplicity approach are not reported. The record does not state whether the hospitalization result was designated in advance as a confirmatory test, how the other listed measures were handled, or whether any multiplicity adjustment was planned. Accordingly, the secondary result adds context but should not be treated as independent confirmation of the primary result.

The direction of the secondary point estimate is consistent with a lower hospitalization rate in the mHealth group, but its interval remains compatible with a range that includes no rate difference. That uncertainty should be kept distinct from the more separated primary mean-difference interval. Neither result identifies the mechanism linking medication management to healthcare use, and the record does not provide enough information to assess such a pathway.

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

• Hospitalization Rate

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a continuous count summarized by its mean and standard deviation in each randomized group. The registry reports 68 participants per group. The mean is the arithmetic average of the recorded medication-error counts; the standard deviation describes how dispersed those counts were around the group mean. A standard deviation is not the uncertainty in the mean difference. The uncertainty in a comparison is represented separately by its confidence interval.

What does the mean difference represent?

The primary contrast is the intervention-group mean minus the control-group mean. The posted means are 9.0 and 20.0, respectively, and the unadjusted mean difference is -11.0. A negative estimate means the intervention-group mean is lower under this ordering. The registry does not report an adjusted primary analysis, so the posted comparison is an unadjusted contrast rather than an estimate adjusted for baseline characteristics or other variables. The registry record does not describe whether other analyses were planned or performed outside the posted results.

The reported p-value for this comparison is p < 0.001. General statistical context: a p-value measures how unusual data at least as discrepant from a specified null hypothesis would be if that null model and its assumptions held. It is not the probability that the null hypothesis is true, nor does it measure the size or practical importance of an effect. The size and uncertainty of the estimate are better read alongside the confidence interval and the outcome's units.

Why report a confidence interval?

General statistical context: a confidence interval gives a range of values compatible with the data under the estimation method and its assumptions. The primary 95% confidence interval runs from -14.57 to -7.434 medication errors for the mean difference. It conveys uncertainty about the group contrast, while the point estimate of -11.0 is one estimate within that range. The interval does not incorporate every possible source of uncertainty, such as unreported measurement limitations, protocol deviations, or missing-data assumptions.

How is the hospitalization comparison different?

The secondary outcome is a rate, not a mean error count. It is expressed as hospitalizations per patient-year, with posted rates of 0.65 for the mHealth group and 1.08 for usual care. The comparison is a rate ratio of 0.602. A ratio of 1 represents equal rates; values below 1 correspond to a lower rate in the numerator group relative to the denominator group. The 95% confidence interval is 0.314 to 1.153, and the unadjusted p-value is 0.126.

The registry identifies a Poisson approach for the rate comparison and derives the follow-up time from the outcome's 1-year timeframe. General statistical context: a Poisson model is commonly used for event counts over time or exposure, with the rate accounting for the time at risk. A key consideration is whether variability in the counts exceeds the model's assumptions, often called over-dispersion. If over-dispersion is present and not addressed, standard errors and confidence intervals may not adequately reflect uncertainty. The registry record does not report diagnostics for over-dispersion or a sensitivity analysis addressing it, so the record does not establish whether that issue was assessed.

The hospitalization result's confidence interval is based on the posted rate information. The registry reports event totals used in the comparison, but the count of events is not the same as the number of participants with at least one hospitalization. Participants may contribute different numbers of events, and the rate comparison uses the time-based outcome definition. The registry does not report participant-level event patterns or further details about recurrent-event handling.

What is not specified about the statistical plan?

The registry record does not report the trial's original sample-size calculation, the assumptions used for its design, or the planned statistical analysis methods in sufficient detail to verify them. It also does not report whether the analyses accounted for baseline covariates, departures from assigned treatment, clustering, or missing outcome data. The reported trial enrollment is not a substitute for those design assumptions. The record lists six outcome measures and posts one secondary result, but it does not report a multiplicity strategy. Accordingly, the posted p-values should be read as unadjusted and within the limits of the information available in the registry record.

The effect-based sample-size figures are separate planning illustrations calculated from observed effects under stated assumptions. They are not evidence that the original trial was designed using those exact assumptions. Their purpose is to show how a hypothetical future study's required enrollment would change if it aimed to detect a chosen fraction of an observed effect.

11. Confidence Intervals and Precision

The primary mean difference is -11.0 medication errors, with a 95% confidence interval from -14.57 to -7.434. The interval lies entirely below zero, so the posted data are more compatible with a negative mean difference than with no difference under the unadjusted comparison. Its width also matters: the estimate is not an exact count of errors avoided for every participant, and values across the interval represent different plausible magnitudes for the group-level difference under the method's assumptions.

General statistical context: a confidence interval communicates the precision of an estimate. A narrower interval indicates greater precision for the quantity being estimated, while a wider interval allows a broader range of values. Precision depends on factors including sample size, outcome variability, and the analysis method. It does not measure whether the outcome definition captures every relevant aspect of medication safety, and it does not correct for bias or unreported design limitations.

The group standard deviations were 5.4 in the intervention group and 14.0 in the control group. These describe variation in observed counts among participants, not confidence limits for the means. The registry does not provide the underlying participant-level values or the distribution of error counts, limiting assessment of skew, outliers, and the frequency of zero counts.

For hospitalization rate, the 95% confidence interval for the rate ratio is 0.314 to 1.153. The interval includes 1, the no-rate-difference value for a ratio, and the unadjusted p-value is 0.126. This result is less precise with respect to distinguishing a difference from no difference than a confidence interval that excludes 1 would be. It does not establish equal rates; rather, it leaves uncertainty about the size and direction of the rate contrast. General statistical context: confidence intervals describe uncertainty under a specified method and do not account automatically for multiplicity, missing-data bias, or model misspecification.

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 observed effects, not the trial's original design justification. The trial's own sample-size assumptions are not reported in the registry record. The listed assumptions for these illustrations are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The figures are participants per arm for 80% power and participants per arm for 90% power. They are not total event counts because the outcomes are not time-to-event outcomes in these planning calculations.

For the primary medication-error comparison, planning for 100% of the observed effect gives 15 participants per arm for 80% power and 20 for 90% power. Planning for 75% of the observed effect gives 26 participants per arm for 80% power and 35 for 90% power. Planning for 50% of the observed effect gives 59 participants per arm for 80% power and 79 for 90% power.

For the hospitalization-rate comparison, planning for 100% of the observed effect gives 76 participants per arm for 80% power and 101 for 90% power. Planning for 75% of the observed effect gives 124 participants per arm for 80% power and 166 for 90% power. Planning for 50% of the observed effect gives 259 participants per arm for 80% power and 346 for 90% power.

General statistical context: 80% power means that, under the planning assumptions and specified effect, a study would have an 80% chance of rejecting the null hypothesis if that effect were the true effect. The 90% column describes the corresponding 90% target. A smaller effect is harder to distinguish from random variation and therefore requires more participants under otherwise identical assumptions. These figures are not observed power; they are hypothetical planning values conditional on the listed assumptions and the observed-effect estimates.

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 = -11.000; pooled standard deviation σ = 10.610.
2. n = 2 × (1.96 + 0.842)² × 10.610² / -11.000² = 14.6, rounded up to 15 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 <- -11                      # observed difference in means
sigma <- 10.6103722837608                     # 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(3247322)
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 = 15 (80% power), 20 (90% power)
 75% of observed effect: n per arm = 26 (80% power), 35 (90% power)
 50% of observed effect: n per arm = 59 (80% power), 79 (90% power)
power.t.test: 15.6 
Simulated power at n = 15 per arm: 0.781 (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

The registry lists six outcome measures, while the posted results include the primary medication-error outcome and one secondary outcome, hospitalization rate. Results for the other listed measures are not reported in the registry record. The record does not report a multiplicity adjustment or explain how the family of outcomes was handled in the statistical analysis plan. This makes it difficult to determine whether the posted p-values were intended as isolated tests, part of a prespecified hierarchy, or one component of a broader set of comparisons.

General statistical context: testing several outcomes can increase the chance of at least one small p-value arising by chance if each test is interpreted independently. Prespecifying a primary endpoint and a multiplicity strategy can help clarify which findings are confirmatory and how secondary results should be interpreted. The registry identifies a primary outcome, but the full planned testing hierarchy and any procedures for controlling multiplicity are not reported in the registry record. The unadjusted secondary p-value should therefore be read with that uncertainty in mind.

The registry record does not report how missing outcome observations were handled, whether any participants discontinued follow-up, or whether analyses used imputation or another missing-data method. It also does not report the analysis population, such as whether participants were analyzed according to randomized assignment, treatment received, or availability of outcome data. The record reports 68 participants in each group for the posted outcomes, but that alone does not establish that every randomized participant contributed complete data throughout follow-up.

Other potentially important analysis details are not reported in the registry record, including protocol deviations, adherence to the intervention, baseline adjustment, sensitivity analyses, and the treatment of unusual or repeated outcome observations. The record reports a single masking designation without identifying who was masked. These absences do not show that procedures were not used; they mean the registry record does not document them. In consequence, the posted estimates can be interpreted as summaries of the reported results, but the available record is insufficient to reconstruct all choices that may affect the analysis or its uncertainty.

15. 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: laboratory abnormality (5.9%), nervous system disorder (4.4%), abnormal vital signs (4.4%), gi dysfunction (2.9%), musculoskeletal disorder (2.9%).

The registry reports serious adverse event figures for 68 participants in each group. Six participants in the intervention group and 16 in the control group were recorded as affected by serious adverse events. It reports other adverse events for all 68 participants in each group. No deaths were recorded in either group. These counts describe the registry's safety entries; they are not a complete account of event type, timing, duration, severity grading, or relationship to the intervention.

The registry lists the most frequent serious-event terms as Laboratory abnormality (5.9%), Nervous System Disorder (4.4%), Abnormal Vital Signs (4.4%), GI Dysfunction (2.9%), Musculoskeletal disorder (2.9%), and General Disorder (1.5%). These terms and percentages describe the entries reported in the record. The record does not provide enough detail to establish the cause of an event or whether it was related to study participation.

General statistical context: event counts are descriptive and can be difficult to compare when events are uncommon, follow-up differs, or event definitions and ascertainment are unclear. The registry record does not report a formal comparative safety analysis or confidence intervals for these counts. The figures should therefore be read as reported counts, not as proof of safety equivalence or a causal safety difference between groups.

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

The primary result describes a lower mean number of documented medication errors in the intervention group than in the usual-care group over 1 year. The unadjusted difference was -11.0, and its 95% confidence interval ranged from -14.57 to -7.434. The interval does not include zero, and the reported p-value is p < 0.001. These results indicate a clear statistical separation in the posted group means under the unadjusted comparison.

That statistical result does not show that every participant in the intervention group had fewer errors, or that the intervention eliminated errors. Group averages can conceal substantial differences among individuals, and the registry does not report the participant-level distribution. The endpoint is based on documentation of medication use that was not intended; the result therefore speaks to the recorded outcome as defined, not every possible aspect of medication safety.

The hospitalization comparison is less conclusive: its confidence interval includes the rate-ratio value of 1, and its unadjusted p-value is 0.126. It does not establish a hospitalization-rate difference or prove that the rates were equal. The primary and secondary findings address different outcomes and should be interpreted separately.

The results do not establish which elements of the pharmacist-led mHealth intervention were responsible for the observed primary contrast. The record does not report enough detail about intervention use, adherence, analysis populations, missing data, or adjustment to answer those questions. Nor do the posted results establish that the same pattern would apply outside the enrolled population, under other care arrangements, or over a different follow-up period. Such claims require evidence beyond the registry results.

General statistical context: statistical significance is not the same as clinical importance, and an estimated difference does not by itself identify its practical consequences. The registry does not report a threshold for a clinically meaningful change in medication-error counts. The most defensible reading is therefore specific: the posted randomized-group summaries show a lower mean count in the intervention group, with an interval excluding no mean difference, while the secondary hospitalization comparison remains uncertain.

17. Why This Trial Matters Statistically

This trial is statistically informative because it compares two randomized groups on a defined medication-safety outcome and reports group sizes, means, standard deviations, and a mean difference with a confidence interval. Those details allow readers to distinguish the size of the estimated group contrast from its statistical uncertainty. The result is not represented only by a p-value: the interval gives a range for the mean difference under the unadjusted method.

The contrast between the primary and secondary outcomes is also instructive. A comparatively clear difference in the mean number of documented medication errors coexists with a less precise hospitalization-rate comparison. This illustrates why endpoints should be interpreted according to what they measure, rather than assuming that a result on one outcome automatically carries over to another. The outcomes also use different statistical scales: a mean difference for error counts and a rate ratio for hospitalizations per patient-year.

The record's planning illustrations show how the required enrollment changes when the target effect is reduced or the desired power target is raised. These are useful for understanding the relationship between effect size, precision, and sample size, but they are not the original trial's design calculation. The record does not report the assumptions behind the original enrollment decision, so readers cannot determine from this entry how the observed enrollment related to the planned effect or power.

Finally, the registry highlights the importance of complete reporting. Multiplicity procedures, missing-data methods, analysis populations, and the full set of outcome results are not reported in the registry record. Such information helps readers assess whether estimates were prespecified, how uncertainty was handled, and how much weight secondary results should receive. The posted figures remain interpretable as reported summaries, while the unreported methods set limits on stronger conclusions.

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 does not provide detailed eligibility criteria, participant characteristics, or the participant-level distribution of medication-error counts. Although the primary outcome is defined and summarized by group, readers cannot assess the number of participants with no errors, the presence of extreme counts, or how the errors were distributed across individuals. Further information about how errors were identified, documented, or reviewed is not reported in the registry record.

Intervention delivery is also described only in broad terms. The record identifies pharmacist-led medication therapy and an mHealth application intended to support medication safety monitoring and self-care, but it does not report the extent of application use, pharmacist contact, participant adherence, or variation in delivery. These missing details limit evaluation of which parts of the intervention were received and how consistently they were implemented.

The registry does not report the original sample-size justification, detailed analysis plan, missing-data procedures, or analysis population. It also does not report whether the primary comparison included adjustments, whether sensitivity analyses were conducted, or how protocol deviations were handled. The record lists six outcome measures but posts only one secondary outcome, and it does not report a multiplicity strategy. These limitations restrict interpretation of the full range of planned results and the potential influence of analysis choices.

The hospitalization comparison is based on a rate, with a Poisson approach identified in the record. Diagnostics for model assumptions, including assessment of over-dispersion, are not reported in the registry record. The available information also does not describe participant-level recurrent hospitalizations or the handling of missing follow-up time. The confidence interval and p-value should thus be understood in light of the reported method and the absence of those additional details.

Finally, the registry reports a single masking designation but does not identify who was masked. It gives a study timeframe and completed status but does not provide enough information to assess all aspects of follow-up or generalizability. These are limits on what can be concluded from the registry entry, not evidence that procedures were absent or that the reported estimates are necessarily biased.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: mHealth Medication Safety Intervention — NCT03247322.
• Registry record last updated 2021-02-25; status last verified 2021-02.
• Results first posted 2021-02-25.
• 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 TRANSAFE Rx, a completed, 12-month, randomized parallel-group study of a pharmacist-led mHealth medication-safety intervention compared with usual post-transplant care. It reports 136 participants, with 68 in each group. The primary outcome was the number of medication errors over 1 year, defined as documentation that a patient was taking a medication in a manner that was not intended.

The intervention group's mean was 9.0, compared with 20.0 in the control group. The unadjusted mean difference was -11.0, with a 95% confidence interval from -14.57 to -7.434 and p < 0.001. The posted secondary outcome was hospitalization rate. Its rate ratio was 0.602, with a 95% confidence interval from 0.314 to 1.153 and an unadjusted p-value of 0.126.

The registry record does not report the original sample-size justification, a full analysis plan, missing-data procedures, analysis populations, or multiplicity methods. It lists six outcome measures but posts one secondary result. The reported estimates can be read as group-level summaries, with these reporting gaps limiting assessment of analyses and outcomes not documented in the record.