The INDORSE Study: Inhibition of Dipeptidyl Peptidase IV: Outcomes on Renal Sodium Excretion: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The INDORSE Study: Inhibition of Dipeptidyl Peptidase IV: Outcomes on Renal Sodium Excretion (NCT02406443), a randomized phase 4 study. The primary outcome is Percent Change in Fractional Excretion of Sodium (FENA).

2. Clinical Question

3. Trial Design

The INDORSE study is registered as a Phase IV, randomized, parallel-group trial with triple masking. Its brief summary describes a double-blind, randomized, placebo-controlled design. These descriptions differ on the masking label; further details about who was masked are not reported in the registry record.

The brief summary describes assignment in a 1:1 ratio to sitagliptin or placebo. Both treatments were oral tablets taken once daily for 28 days. The intended population was patients with type 2 diabetes and systolic hypertension, with the summary specifying HbA1c from 6.5% to 9% and systolic blood pressure from 120 to 160 mmHg.

The registry record gives enrollment as 36, while the brief summary describes a population of 32 patients. For the primary outcome, 16 participants are listed in each arm. The registry record does not explain the difference between the enrollment figure and the arm counts used for the posted result.

The study began in 2015-03, had primary completion in 2016-06, and is marked completed. The study’s objective was to evaluate acute effects after a single dose and effects after short-term treatment on renal sodium handling, renal hemodynamics and renal function. The primary endpoint compares fractional excretion of sodium at three hours after administration following one month with the measure at three hours after one dose. The full protocol, eligibility criteria beyond those summarized, and original design assumptions 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

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 Percent Change in Fractional Excretion of Sodium (FENA), measured over 3 Hrs post-administration after 1 month and after 1 dose.

The primary endpoint is percent change in fractional excretion of sodium (FENA). The description defines the comparison as FENA measured three hours after study-drug administration following one month, compared with FENA measured three hours after one dose, and contrasts sitagliptin with placebo. It therefore concerns the difference between responses at two treatment durations, rather than a simple comparison of a single post-dose measurement.

FENA is a continuous measure of how much of the sodium filtered by the kidneys is excreted in urine. In general, a measure of fractional excretion can help characterize renal handling of a substance in relation to filtration. This endpoint was selected to address the study’s stated question about renal sodium handling. It is not, by itself, a direct measure of a long-term clinical outcome.

The posted arm summaries report means and standard deviations for percentage change. The sitagliptin arm mean is 41.0, with a standard deviation of 43.0, and the placebo arm mean is -5.0, with a standard deviation of 31.0. The recalculated unadjusted mean difference is 46.0, with a confidence interval from 20.03 to 71.97. The sponsor’s reported analysis gives a mean difference of 46 and p =0.012; the registry record does not provide a confidence interval for that analysis.

Details about the endpoint’s clinical interpretation, measurement reliability and prespecified analysis beyond the posted description are not reported in the registry record.

7. Results Posted in the Registry

• Experimental Arm: mean 41.00 versus -5.00 on control; difference 46.00 (95% CI 20.03 to 71.97), standardized effect d = 1.23; 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.

Change in Glomerular Filtration Rate (GFR)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental Arm: mean 3.90 versus -1.80 on control; difference 5.70 (95% CI -7.57 to 18.97), standardized effect d = 0.30; z-test p = 0.400.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Experimental Arm and the control. The interval gives the range of effects that remain compatible with the data.

Change in Fractional Excretion of Lithium (FELi)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental Arm: mean 29.00 versus 7.00 on control; difference 22.00 (95% CI -12.51 to 56.51), standardized effect d = 0.44; z-test p = 0.212.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Experimental Arm and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in SDF-1alpha^1-67 (Intact) Measured by Immunoaffinity and Tandem Mass Spectrometry

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental Arm: mean 0.50 versus 0.00 on control; difference 0.50 (95% CI 0.40 to 0.60), standardized effect d = 3.54; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Experimental Arm than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes show a mixed pattern rather than a consistent difference across all measures. The recalculated comparisons for glomerular filtration rate and fractional excretion of lithium have intervals that include zero, while the intact SDF-1alpha comparison has an interval above zero. The registry’s own analyses report p =0.40, p =0.15 and p <0.001 for these outcomes, respectively.

These measures address distinct aspects of renal function, sodium handling and biomarker response. They are related to the study’s broader objective, but they do not directly confirm or negate the primary result because they are different outcomes. Six secondary outcomes are listed in the registry, but results are posted for only three. Results for fractional excretion of lithium and the two SDF-1alpha outcomes are not all available: the posted results include fractional excretion of lithium and intact SDF-1alpha, while no result is posted for truncated SDF-1alpha, systolic blood pressure or effective renal plasma flow.

In general, when multiple outcomes are tested, the chance of at least one apparently unusual result can rise unless the analysis accounts for the number of tests or prioritizes outcomes in advance. The registry record does not report a multiplicity adjustment or a detailed plan for interpreting secondary outcomes. Accordingly, unadjusted secondary p-values carry less weight than the prespecified primary outcome and should be treated as exploratory evidence rather than as a collection of independent confirmations.

The registry lists seven outcome measures overall but names six secondary outcomes, and six analyses are recorded. The record does not explain this accounting. It also does not establish whether the unposted outcomes were measured, analyzed but omitted, or unavailable for another reason.

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

• Change in Glomerular Filtration Rate (GFR)
• Change in Fractional Excretion of Lithium (FELi)
• Change From Baseline in SDF-1alpha^1-67 (Intact) Measured by Immunoaffinity and Tandem Mass Spectrometry
• Change From Baseline in SDF-1alpha^3-67 (Truncated) Measured by Tandem Mass Spectrometry With Antibody-based Affinity Enrichment
• Change in Systolic Blood Pressure (SBP), Non-invasive Cardiac Output Monitoring
• Change in Effective Renal Plasma Flow (ERPF)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference describe?

The primary outcome is continuous, and its posted arm summaries are means with standard deviations. A mean difference expresses the distance between the two group averages on the outcome’s scale. For the primary endpoint, the recalculated unadjusted mean difference is 46.0 percentage points as reported in the registry’s percentage-change scale. The direction is based on the arm means: the sitagliptin mean is 41.0 and the placebo mean is -5.0.

In general, a mean is useful for describing a group’s average, but it does not describe every participant’s response. A standard deviation describes the spread of participant values around the mean. It is not the same as a confidence interval, which expresses uncertainty about an estimated quantity. The observed standard deviations for the primary outcome are 43.0 and 31.0 in the two arms.

What does the confidence interval add?

In general, a confidence interval gives a range of values compatible with the data and the assumptions of the calculation. The recalculated unadjusted interval for the primary mean difference runs from 20.03 to 71.97. Its width conveys uncertainty: a wider interval indicates less precision than a narrower interval on the same scale. This interval is based on an unadjusted comparison of posted summary statistics, not the sponsor’s regression analysis.

For the secondary outcome of glomerular filtration rate, the recalculated interval runs from -7.566 to 18.97. For fractional excretion of lithium, it runs from -12.51 to 56.51. Both include zero, which means the ranges include no difference as well as differences in either direction. The intact SDF-1alpha interval, from 0.402 to 0.598, lies above zero. These intervals are recalculations; the registry’s own analysis does not report confidence intervals for these outcomes.

Why are the p-values different?

The sponsor’s primary analysis is described as linear regression, with a mean difference in final values and p =0.012. The simple recalculation compares the posted group means without adjustment and gives p <0.001. These analyses are not interchangeable: regression can use a model and adjustment choices that are not represented in a simple comparison of arm summaries. The registry record does not report the covariates, model specification or other details needed to reproduce the sponsor’s analysis. Since the discrepancy flag is true, the sponsor’s own result takes precedence when describing the reported trial analysis.

A p-value measures how incompatible the data are with a specified null hypothesis under the assumptions of a statistical test. In general, it is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. Its interpretation depends on the analysis method and the assumptions used.

Why does variability matter?

In general, greater variability makes a group mean less precise when sample size is held constant. The primary standard deviations are large relative to the group means, and the arm counts are 16 each. A mean difference can still be estimated, but its precision depends on both variability and sample size. The confidence interval provides a more direct account of the recalculated uncertainty than the p-value alone.

Over-dispersion is a general concern when variability is greater than assumed by a statistical model. If a model understates variability, standard errors can be too small and inferential results can appear more precise than warranted. The registry record does not report a dispersion assessment or enough detail to determine whether over-dispersion was relevant to the sponsor’s regression analysis. It would therefore be inappropriate to infer that the posted results used a particular correction.

What assumptions underlie the recalculations?

The recalculated comparisons are simple unadjusted calculations based on posted summary statistics. They are not reconstructions of the sponsor’s regression models. In general, such calculations rely on assumptions about the outcome distribution and the appropriateness of comparing group means. The planning illustrations use a normal approximation and equal allocation, as specified in the registry’s planning information. No further assumptions about the original trial design or its analysis should be inferred from those illustrations.

The primary endpoint compares measurements after one dose and after one month, but the posted analysis description does not explain whether the underlying analysis accounts for repeated measurements or baseline values. The sponsor result is described as a comparison of final values. The full analysis plan, handling of repeated measures, covariate adjustment, and missing-data methods are not reported in the registry record.

11. Confidence Intervals and Precision

The recalculated unadjusted primary mean difference is 46.0, with a 95% confidence interval from 20.03 to 71.97. This interval indicates that the point estimate is not exact: values across a range remain compatible with the summary data and calculation assumptions. The interval lies entirely above zero, but its width still matters when considering how precisely the difference has been estimated.

The sponsor’s reported analysis gives a mean difference of 46 and p =0.012, but no confidence interval is reported for that analysis. The recalculated interval should not be presented as if it were the interval from the sponsor’s regression model. The discrepancy between the sponsor’s p-value and the unadjusted recalculation also means that inferential statements should prioritize the sponsor’s own analysis.

For the posted secondary comparisons, the recalculated intervals are -7.566 to 18.97 for glomerular filtration rate, -12.51 to 56.51 for fractional excretion of lithium, and 0.402 to 0.598 for intact SDF-1alpha. The first two intervals span zero, whereas the intact SDF-1alpha interval does not. These are unadjusted recalculations, and the sponsor analyses do not report confidence intervals.

In general, confidence intervals reflect statistical uncertainty under a specified method; they do not account for every source of uncertainty. Small arm counts, unreported missing-data handling, model choices and the absence of a reported multiplicity plan all affect how cautiously the findings should be read. The record does not provide enough information to quantify those additional uncertainties.

12. Planning a Similar Trial: Sample Size

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

The sample-size illustrations give participants per arm, not a total across both arms and not a number of events. They are based on a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Each illustration uses the observed effect or a stated fraction of it as the effect to detect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column indicates the number of participants per arm that the planning calculation estimates would be needed for an 80% chance of detecting the specified effect under its assumptions, if that effect were the true one. The 90% power column expresses the corresponding planning target for a 90% chance. These are design illustrations, not guarantees about a future study’s result. This is not observed power.

The primary-outcome illustration estimates 11 participants per arm for planning for 100% of the observed effect at 80% power, and 14 per arm at 90% power. Planning for 75% of the observed effect gives 19 per arm for 80% power and 25 per arm for 90% power. Planning for 50% of the observed effect gives 42 per arm for 80% power and 56 per arm for 90% power. The figures show the general pattern: smaller effects require more participants to detect under the same planning assumptions.

These calculations use the observed effect as a starting point, so they are sensitive to how well that estimate represents the effect that might be seen in another study. They do not establish that the original trial was adequately powered, and they are not a substitute for a prospective design calculation based on a justified target effect and protocol 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 = 46.000; pooled standard deviation σ = 37.483.
2. n = 2 × (1.96 + 0.842)² × 37.483² / 46.000² = 10.4, rounded up to 11 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 <- 46                      # observed difference in means
sigma <- 37.4833296279826                     # 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(2406443)
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 = 11 (80% power), 14 (90% power)
 75% of observed effect: n per arm = 19 (80% power), 25 (90% power)
 50% of observed effect: n per arm = 42 (80% power), 56 (90% power)
power.t.test: 11.5 
Simulated power at n = 11 per arm: 0.785 (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 registry’s reported primary analysis used linear regression and gives a mean difference of 46 with p =0.012. It does not report a confidence interval for that analysis. The simple recalculation from the posted arm summaries is unadjusted: it estimates a mean difference of 46.0, a confidence interval from 20.03 to 71.97, and p <0.001.

The p-values differ, so the two results should not be treated as matching analyses. A regression analysis may depend on model details or adjustments that a calculation from group means cannot reproduce. The registry record does not report those details, so the reason for the discrepancy cannot be established from the posted information. The discrepancy flag is true; the sponsor’s own analysis takes precedence when reporting the trial’s inferential result.

The recalculated confidence interval describes uncertainty for the unadjusted comparison only. It should not be attached to the sponsor’s regression estimate as though it came from that model. The registry also does not report the sponsor model’s covariates, diagnostics, missing-data approach or full analysis plan. The recalculation can offer a transparent comparison of the posted summaries, but it cannot replace or resolve the sponsor analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies a primary endpoint and lists secondary outcomes, but a detailed statistical analysis plan is not reported in the registry record. The record does not say whether secondary analyses were prespecified in a hierarchy, whether multiplicity was controlled, or how secondary results were intended to support conclusions. Without this information, the secondary p-values should not be interpreted as if they were protected against the additional uncertainty created by testing multiple outcomes.

Missing-data methods are also not reported. The arm summaries for the primary outcome and the posted secondary comparisons each list 16 participants, but the record does not describe whether all randomized participants contributed data, whether any measurements were missing, or how missing measurements were handled. The overall enrollment is reported as 36, while the brief summary describes 32 patients and the primary outcome has 16 participants per arm. The reason for this difference is not reported.

The analysis populations are not described in enough detail to determine whether the posted results use an intention-to-treat population, a per-protocol population, or another set of participants. Details about exclusions after randomization, adherence, protocol deviations, and the handling of repeated measurements are not reported in the registry record.

The sponsor’s primary result is described as a linear regression analysis of final values. The model specification, covariates, assumptions, diagnostics and missing-data approach are not reported. Nor is there a reported account of interim analyses or stopping rules. These omissions limit independent assessment of the analysis and make it difficult to explain why the sponsor’s p-value differs from the unadjusted recalculation. They do not demonstrate that a particular method was or was not used.

16. 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 serious adverse event terms

Serious events with the highest arm-level rate: lower gi bleed (5.9%), dyspnea (5.6%), presyncope (5.6%).

The registry lists serious adverse events for 17 participants at risk in the experimental arm and 18 in the placebo arm. One serious adverse event is recorded in the experimental arm and two in the placebo arm. The reported serious-event terms include lower GI bleed, dyspnea and presyncope, with percentages of 5.9%, 5.6% and 5.6%, respectively. These terms and percentages are recorded in the registry, but the record does not provide enough context to assign each term to a particular treatment group or assess causality.

No other adverse events are recorded in the adverse-event fields for the 17 participants at risk in the experimental arm or the 18 at risk in the placebo arm. Death counts are not reported in the registry record. These counts describe events recorded during the study and should not be read as a complete assessment of comparative safety. The registry record does not provide event timing, severity detail beyond the serious-event designation, relatedness assessments, exposure-adjusted rates or enough information to evaluate uncommon events.

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

The posted primary results show different mean percentage changes in fractional excretion of sodium between the randomized arms, with a recalculated unadjusted mean difference of 46.0. The sponsor’s own analysis reports a mean difference of 46 and p =0.012. The statistical discrepancy means the sponsor result takes precedence for describing the trial’s reported analysis, while the recalculation remains a separate unadjusted comparison of the posted summaries.

This finding concerns a short-term renal sodium-handling measure, assessed at three hours after administration following one month and after one dose. It does not directly establish effects on long-term kidney function, cardiovascular outcomes, symptoms or other clinical outcomes. The registry record does not report those outcomes as the primary question.

The results do not show that every participant had a similar response, and the group averages do not describe the full distribution of individual outcomes. The small posted arm counts and the substantial variation in the primary outcome make precision relevant. The recalculated interval excludes zero, but the sponsor analysis has no reported interval, and the two methods yield different p-values.

Results from the secondary outcomes are incomplete and include a mixture of findings. Their interpretation is limited by the absence of a reported multiplicity plan and by the fact that three listed secondary outcomes have no posted results. The study record also does not report enough about missing data, analysis populations, or model details to resolve those limitations.

These results describe one completed randomized trial in the population and treatment setting summarized in the registry. They do not establish that the same pattern would occur in other populations, with longer treatment, or for outcomes not measured or posted. They are not a basis for individual treatment decisions.

18. Why This Trial Matters Statistically

INDORSE is statistically interesting because it focuses on a physiological outcome and contrasts an acute response with a response after short-term treatment. The primary endpoint is framed around renal sodium handling, while the listed secondary outcomes extend to filtration, renal plasma flow, blood pressure and biomarkers. This makes the trial’s question mechanistic and measurement-focused rather than centered on a long-term clinical event.

The registry also illustrates why the analysis method matters. A recalculation from arm-level summaries produces a different p-value from the sponsor’s regression analysis. The posted information is sufficient to describe that difference, but not to identify its cause. Stating which analysis is sponsor-reported and which is an unadjusted recalculation helps avoid treating distinct methods as interchangeable.

The number of participants per arm and the observed variability have practical implications for precision. The planning illustrations show how the participant requirement changes when the target effect is smaller than the observed effect. Those illustrations do not validate the original design, but they emphasize that a large-looking estimate from a small study should be read alongside uncertainty and the assumptions behind the calculation.

Finally, the incomplete posting of secondary results and unreported details about multiplicity, missing data and analysis populations matter for interpretation. A registered trial record can provide useful outcome-level information, but its value depends on distinguishing recorded findings from questions the record leaves unanswered. This trial is a clear example of why effect estimates, intervals, analysis methods and reporting completeness should be considered together.

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 has several trial-specific limitations. The brief summary describes 32 patients, the enrollment field reports 36, and the posted primary arms contain 16 participants each. The reason for these different counts is not reported. The record also labels masking as triple, whereas the brief summary calls the study double-blind; details resolving that difference are not reported.

The primary sponsor analysis has no confidence interval, and its p-value differs from the simple unadjusted recalculation. Model covariates, diagnostics and the full statistical analysis plan are not reported, so the discrepancy cannot be explained from the record. The sponsor’s analysis takes precedence, but independent reproduction is limited.

Only three of the six named secondary outcomes have posted results. The record does not explain the missing outcome results, report a multiplicity approach, or describe the analysis populations and missing-data handling. It also does not report whether interim analyses occurred or how the original sample size was justified.

The primary endpoint is a short-term physiological measure, and the posted description concerns assessments three hours after administration following one dose and one month of treatment. The record does not provide longer-term outcomes or enough detail to determine the clinical importance of the observed changes. The posted summaries also do not show individual participant data, which limits assessment of distributional shape, outliers and response heterogeneity.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: The INDORSE Study: Inhibition of Dipeptidyl Peptidase IV: Outcomes on Renal Sodium Excretion — NCT02406443.
• Registry record last updated 2018-04-05; status last verified 2018-01.
• Results first posted 2018-04-05.
• 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

The INDORSE study is a completed Phase IV randomized parallel-group trial comparing sitagliptin with placebo in people with type 2 diabetes and systolic hypertension. The primary outcome is percentage change in fractional excretion of sodium, comparing measurements three hours after administration following one month with measurements after one dose.

The posted primary arms each contain 16 participants. The sponsor reports a linear-regression mean difference of 46 with p =0.012. An unadjusted recalculation gives a mean difference of 46.0, a confidence interval from 20.03 to 71.97 and p <0.001; because these analyses differ, the sponsor’s own analysis takes precedence.

Three secondary outcomes have posted results, with mixed findings. The record does not report multiplicity handling, missing-data methods, analysis populations or the reason for differences between the enrollment and arm counts.