Study of How the Dose of Dialysis is Affected by Dialysate Flow Rate: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of How the Dose of Dialysis is Affected by Dialysate Flow Rate (NCT00962000), a randomized na study. The primary outcome is Delivered Single-pool Kt/Vurea (spKt/V) at Dialysate Flow Rates of 600 mL/Min and 800 mL/Min..

2. Clinical Question

The question concerns a continuous measure of delivered dialysis dose, rather than a clinical event or a patient-reported outcome. Kt/Vurea relates urea clearance during treatment to treatment time and the urea distribution volume. The primary comparison therefore asks whether the measured average dose differed between treatments at the two flow rates. It does not, by itself, address other aspects of dialysis or patient health.

The registry describes a randomized crossover arrangement. Each participant was assigned to start with one flow rate and then received treatment sequences at both rates. The sequence descriptions specify three consecutive treatments at one rate followed by three at the other, with the starting order varied between participants. This lets the comparison draw on observations at both settings within the study, while making sequence and period details important to interpretation. The registry record does not report further information about how those factors were handled in the analysis.

3. Trial Design

The registry record describes a completed randomized, unmasked crossover study sponsored by Vantive Health LLC. Enrollment was 42. The listed conditions are chronic kidney disease and chronic renal disease. The record gives a start date of 2009-09 and a primary completion date of 2010-06. A phase is listed as NA.

The treatment contrast was between dialysate flow rates of 600 mL/min and 800 mL/min. Participants in the 600 mL/min-start sequence received three consecutive treatments at 600 mL/min followed by three at 800 mL/min, described as an ABAB sequence. Participants in the 800 mL/min-start sequence received the reverse starting order, described as BABA. The registry does not report additional details about the timing between treatment periods, adherence, or whether any treatment periods were interrupted.

The primary outcome was delivered single-pool Kt/Vurea, measured at the final treatment session of each group or sequence period. Its stated timeframe is 4 weeks. The registry also lists equilibrated Kt/Vurea and Kt/V determined from ionic dialysance as secondary outcomes, each with a 4-week timeframe. Posted arm summaries for the primary and equilibrated outcomes include 42 observations at each flow rate; the ionic dialysance summaries include 28 at each rate. These are outcome-specific counts and should not be treated as proof that every enrolled participant contributed to every analysis.

Masking is listed as none. The registry record does not report the original sample-size justification, a detailed statistical analysis plan, the handling of sequence or period effects, or the approach to missing observations. Those omissions limit assessment of how the crossover structure informed the sponsor's analysis.

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.

Period 1 - 1 Week

Period 2 - 1 Week

Period 3 - 1 Week

Period 4 - 1 Week

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 Delivered Single-pool Kt/Vurea (spKt/V) at Dialysate Flow Rates of 600 mL/Min and 800 mL/Min., measured over 4 weeks.

The primary endpoint was delivered single-pool Kt/Vurea (spKt/V) at dialysate flow rates of 600 mL/min and 800 mL/min. Kt/Vurea expresses dialysis dose using three components: K, the clearance of urea; t, treatment time; and V, the urea distribution volume. In the single-pool formulation, urea removal is treated as occurring in a single compartment during dialysis. The registry describes estimating delivered Kt/Vurea from blood urea nitrogen concentrations measured before and after dialysis.

The endpoint was calculated for the final treatment session of each sequence period, described as the final session of the ABAB or BABA group. It therefore summarizes a biochemical measure of dose at a specified treatment session, not a direct measure of long-term health or a clinical event. The registry gives a timeframe of 4 weeks for the outcome.

A continuous outcome is useful for comparing average measured values across treatment conditions and for describing the spread of values among participants. The posted summaries report means and standard deviations. These quantities describe the observed outcome distribution, while the estimated difference and its confidence interval address how uncertain the comparison is. The registry record does not report an endpoint threshold or a clinically important difference, so the numerical comparison alone cannot establish whether a difference would be meaningful to patients or clinicians.

7. Results Posted in the Registry

• 800 mL/Min: mean 1.63 versus 1.66 on control; difference -0.03 (95% CI -0.13 to 0.07), standardized effect d = -0.13; z-test p = 0.552.

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.

Delivered Equilibrated Kt/Vurea (eKt/V at Dialysate Flow Rates of 600 mL/Min and 800 mL/Min.

• 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:
  • 800 mL/Min: mean 1.35 versus 1.37 on control; difference -0.02 (95% CI -0.10 to 0.06), standardized effect d = -0.11; z-test p = 0.630.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 800 mL/Min and the control. The interval gives the range of effects that remain compatible with the data.

Kt/V Determined From Measurements of Ionic Dialysance

• 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:
  • 800 mL/Min: mean 1.49 versus 1.46 on control; difference 0.03 (95% CI -0.13 to 0.19), standardized effect d = 0.10; z-test p = 0.708.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 800 mL/Min and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes follow the same broad pattern as the primary endpoint: the posted comparisons are small in magnitude, and the reported confidence intervals include zero. Across the outcomes, estimates do not all point in the same direction. Taken together, these results do not show a consistent separation between the two flow-rate conditions across all the measured dose indicators. They also do not establish that the measures are equivalent or that any possible difference is unimportant.

The secondary measures address related but distinct aspects or methods of estimating dialysis dose. Equilibrated Kt/Vurea is a related dose measure, while the ionic dialysance outcome is derived from a different measurement approach. Agreement across related measures can be informative, but correlation among endpoints means they are not independent confirmations. Their findings should be read in the context of the primary endpoint and the study's crossover design, not as separate definitive answers.

The registry does not report whether a multiplicity adjustment was planned or used. When several outcomes are examined, the chance of at least one seemingly notable result due to random variation can increase. Unadjusted secondary comparisons therefore carry less weight than a prespecified primary analysis, particularly when the analysis plan and hierarchy among outcomes are not reported. The posted secondary findings are useful as supporting descriptive evidence, but they should not be used to make a stronger claim than the primary result supports.

The record lists two secondary outcomes and does not report additional analyses that would clarify whether these were prespecified, exploratory, or subject to adjustment. The endpoint-level results and their uncertainty are best considered alongside these limitations, rather than counted as multiple independent votes for or against a difference.

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

• Delivered Equilibrated Kt/Vurea (eKt/V at Dialysate Flow Rates of 600 mL/Min and 800 mL/Min.
• Kt/V Determined From Measurements of Ionic Dialysance

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, and the registry reports it as a mean with a standard deviation in each flow-rate group. A mean describes the center of the observed values; a standard deviation describes how dispersed those values are around the mean. The two summaries answer different questions. Similar means do not imply identical individual values, while the standard deviations do not show how precisely the difference in means has been estimated.

What does the mean difference represent?

The comparison is expressed as the 800 mL/min mean minus the 600 mL/min mean. A negative estimate therefore indicates a lower observed mean at 800 mL/min, while a positive estimate indicates a higher observed mean at that setting. The simple unadjusted recalculation for spKt/Vurea is -0.03. This is a contrast between the posted group means, not a model-based adjustment for sequence or period. It should not be assumed to capture all features of the randomized crossover design.

The registry's sponsor analysis is reported as an ANOVA of final values. ANOVA is a general method for comparing means through a statistical model. However, the record does not describe the specific model terms, assumptions, or handling of within-participant observations. It is therefore not possible to tell from the registry record whether or how the reported ANOVA incorporated the crossover sequence and repeated treatment observations.

Why does crossover structure matter?

In a crossover study, participants receive both treatment conditions in an assigned order. This can make each participant's experience at one condition informative alongside that participant's experience at the other. The resulting observations are related rather than necessarily independent. A statistical analysis may need to account for that relationship as well as the order and period in which treatments occurred. If these features are ignored or modeled differently, the estimated uncertainty can differ. The registry record does not report enough detail to determine how these considerations were addressed.

The posted simple recalculations compare summary statistics and are explicitly unadjusted. They are useful as a transparent contrast based on the posted means, but they do not substitute for a fully described crossover analysis. The reported ANOVA and the recalculated comparison are distinct analyses with distinct estimates and intervals. Since the registry does not give full model specifications, the reason for their difference is not reported in the registry record.

What does a confidence interval add?

A confidence interval gives a range of values compatible with the estimate under the assumptions of the analysis. It communicates precision as well as direction. A narrow interval indicates more precision than a wide interval, while an interval spanning zero leaves uncertainty about the direction of the difference. It is not a guarantee that the true value lies within the particular interval, nor does it directly state whether the difference is clinically important.

The recalculated primary interval extends from -0.129 to 0.069. The posted sponsor interval extends from -0.064 to 0.024. Both include zero, but their widths differ. The record does not explain why the estimates and intervals differ, and it does not report a p-value for the sponsor ANOVA. The unadjusted p-value of 0.552 belongs only to the simple recalculation; it should not be attributed to the sponsor analysis.

Why is standard deviation relevant?

Variation among observed measurements affects how precisely a mean contrast can be estimated. Greater variability generally makes it harder to distinguish a small mean contrast from random variation, all else equal. In crossover data, within-participant variation and correlation can matter as well; the posted standard deviations alone do not provide those quantities. A standard deviation is not a standard error or a confidence interval, and it should not be read as uncertainty in the group mean.

The posted analyses are limited to the outcome summaries and reported estimates. The original analysis plan, model details, assumptions about the outcome distribution, treatment of missing data, and analysis population are not reported in the registry record. That missing methodological information constrains evaluation of whether the analyses match the design and whether the uncertainty estimates fully reflect it.

11. Confidence Intervals and Precision

Precision is conveyed by the range of values in a confidence interval, not by the point estimate alone. For the primary spKt/Vurea contrast, the simple unadjusted recalculation estimates a mean difference of -0.03, with a 95% confidence interval from -0.129 to 0.069. Because this interval includes zero and extends in both directions, the recalculation does not sharply determine whether the average value was lower or higher at 800 mL/min. It also does not rule out every difference that might matter in practice.

The sponsor's posted ANOVA estimate is -0.024, with a 95% confidence interval from -0.064 to 0.024. This is a separate reported analysis. Its interval also includes zero and is narrower than the recalculated interval. The record does not report the model details or explain the difference in precision, so the two intervals should not be blended or treated as the same calculation.

In general, a confidence interval describes uncertainty under the assumptions used to calculate it. It is not a range containing most participants' measurements, and it is not a direct probability statement about the true effect. A confidence interval that includes zero does not prove that the treatments are equivalent. Equivalence or non-inferiority requires a prespecified margin and a corresponding analysis; the margin is not reported in the registry record.

For this crossover study, interpretation of precision also depends on how related observations from the same participant and the treatment sequence were handled. The registry record does not report those details. Thus, the posted intervals quantify uncertainty for their respective analyses, while the adequacy of the underlying model cannot be fully assessed from the record.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total events. They are illustrations based on the observed effect and are not the trial's original design calculation. The assumptions stated for these illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario targets a stated fraction of the observed effect. The trial's own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect under those assumptions. The 90% power column gives the corresponding number for a 90% chance. These are prospective planning quantities: they describe what a future study might require under the stated assumptions, not what the completed trial achieved.

Rows for planning for 75% or 50% of the observed effect use smaller target effects than planning for 100% of the observed effect. Smaller effects are harder to distinguish from random variation, so the corresponding planning figures require more participants per arm. This relationship is a general feature of statistical planning and does not establish that any particular effect size is clinically important.

These figures are not observed power. Observed power is not a useful substitute for reading the estimated effect and its confidence interval after a study is completed. The planning illustrations depend strongly on the effect used as a target, and the observed estimate may be unstable. They should be interpreted as conditional planning examples, not as evidence that the study was adequately or inadequately designed.

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 = -0.030; pooled standard deviation σ = 0.231.
2. n = 2 × (1.96 + 0.842)² × 0.231² / -0.030² = 929.7, rounded up to 930 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 <- -0.03                      # observed difference in means
sigma <- 0.230867927612304                     # 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(962000)
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 = 930 (80% power), 1,245 (90% power)
 75% of observed effect: n per arm = 1,653 (80% power), 2,213 (90% power)
 50% of observed effect: n per arm = 3,719 (80% power), 4,979 (90% power)
power.t.test: 930.6 
Simulated power at n = 930 per arm: 0.801 (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 sponsor analysis for the primary endpoint uses ANOVA and reports a mean difference in final values of -0.024, with a 95% confidence interval from -0.064 to 0.024. A p-value is not reported for this analysis. The analysis is labeled in the registry as a legacy non-inferiority or equivalence analysis, but the record does not report the margin or decision rule needed to evaluate such a claim.

The simple unadjusted recalculation from the posted arm summaries gives a mean difference of -0.03, a 95% confidence interval from -0.129 to 0.069, and an unadjusted p-value of 0.552. This recalculation is not the sponsor's ANOVA and should not be presented as its result. The point estimates are close in direction and scale, while the reported intervals differ in width.

The registry does not provide the model specifications or other analysis details needed to explain the difference. It also does not state whether the sponsor's analysis accounted for sequence, period, or within-participant correlation. Since the record does not flag a discrepancy, neither estimate should be silently substituted for the other: the sponsor's analysis is the registry-reported analysis, and the recalculation is a separate unadjusted comparison. The missing detail limits independent assessment of the sponsor method.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary endpoint and two secondary outcomes, with three analyses posted. It does not report whether the investigators prespecified a hierarchy among outcomes, adjusted for multiple comparisons, or treated any secondary analyses as exploratory. Without that information, the statistical interpretation cannot assume that the reported comparisons were protected against multiplicity.

Multiplicity arises when several hypotheses are tested or several outcomes are analyzed. Even if each analysis uses a conventional threshold, making many comparisons can increase the chance that at least one result appears noteworthy by chance. This general concern does not mean that a particular result is false; it means that the context and analysis plan matter when judging how much weight to place on multiple results. No adjustment method or family of tests is reported in the registry record.

Missing-data handling is also not reported. The registry gives outcome-specific summary counts, including 42 observations at each flow rate for the primary and equilibrated measures and 28 at each flow rate for the ionic dialysance measure. It does not explain why those counts differ, whether there were missing measurements, how missingness was defined, or whether any imputation or sensitivity analysis was performed. The counts alone do not establish the reason for the difference.

The analysis population is not reported in the registry record. It is therefore unclear whether the posted results use all randomized participants, participants with complete measurements, or another population. The record also does not report how treatment sequence, period, or participant-level correlation were addressed. Those omissions are especially relevant to a crossover study, in which observations from the same participant may be related.

These gaps limit assessment of model adequacy, potential bias from incomplete data, and the role of secondary findings. They do not invalidate the posted estimates, but they constrain how confidently the analyses can be interpreted as complete evidence about the randomized comparison.

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 1% reporting threshold.

The registry reports serious adverse events for the sequence groups labeled 600 mL/min first and 800 mL/min first. Each group lists 21 participants at risk and zero serious adverse events. The record also lists 21 at risk and zero other adverse events in each group. These are the posted event counts for the stated groups and should be read as counts, not as proof that no adverse events could occur.

Deaths are not reported for either group in the registry record. The listing of zero events applies to the serious and other adverse event fields; it should not be extended to the unreported death field. The record does not provide event descriptions, timing, severity details beyond the serious-event classification, or an explanation of how safety information was collected.

Because the study is a crossover trial, the sequence-group safety figures do not by themselves describe exposure-specific event rates during each treatment period. The registry record does not provide treatment-period-specific safety summaries. These figures are therefore a concise account of the posted safety counts, with limited detail for assessing the timing or relation of events to either flow rate.

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

The posted results describe average delivered dialysis dose at two dialysate flow rates in a randomized crossover study. For the primary single-pool Kt/Vurea outcome, the group means are close, and both the simple recalculation and the sponsor's reported estimate are near zero in scale. Their confidence intervals include zero, leaving uncertainty about the direction of the difference. These results do not demonstrate that the settings are identical.

Nor does an interval that includes zero establish equivalence or non-inferiority. Such a conclusion requires a prespecified margin and an analysis designed to evaluate that margin. Although the registry labels the sponsor analysis as a legacy non-inferiority or equivalence analysis, it does not report the margin or decision rule. The label alone cannot establish that a formal criterion was met.

The outcome is a biochemical measure of delivered dose, measured from pre- and post-dialysis blood urea nitrogen concentrations. It does not directly represent all dimensions of dialysis or long-term patient outcomes. The registry record does not report a clinically important threshold for interpreting the observed contrast. Consequently, the statistical estimate should not be converted into a claim about clinical benefit or harm.

The findings are also bounded by the available analysis detail. The record does not explain the handling of crossover sequence and period, missing observations, or analysis populations. These are not minor labels: they affect how the comparison and its precision should be understood. The posted endpoint summaries remain descriptive evidence, but they cannot resolve those methodological questions.

The most defensible reading is that the registry reports modest mean contrasts with uncertainty for the primary and secondary dose measures. The results do not show a clear separation in the posted estimates, but they also do not rule out every potentially relevant difference. No treatment recommendation follows from these statistical summaries.

18. Why This Trial Matters Statistically

This trial is statistically interesting because it compares two treatment conditions within a randomized crossover framework. In a crossover design, observations can be related within participants, and sequence and period can matter to the analysis. That structure makes the distinction between an unadjusted contrast of posted summaries and a model-based analysis especially important.

The registry gives both a sponsor ANOVA result and enough summary information for a simple unadjusted recalculation. These estimates are similar in general scale, but their intervals differ. Seeing both makes clear that an estimate cannot be interpreted without knowing what analysis produced it. The registry does not report enough model detail to explain the difference or evaluate how the crossover structure was handled.

The record also illustrates why a nonsignificant or zero-spanning interval is not proof of equivalence. A non-inferiority or equivalence conclusion depends on a prespecified margin and a defined decision process. Although the sponsor analysis carries a legacy label in that category, the margin and decision rule are not reported. The distinction is central to sound interpretation.

Finally, the planning illustrations show how strongly future sample-size requirements depend on the target effect. They are not a retrospective verdict on this study, and they are not observed power. The original design assumptions are unavailable in the registry record. Together, these features make the trial a useful example of interpreting effect estimates, uncertainty, and incomplete analytic reporting without overstating what the data establish.

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.

Several limitations specific to this record affect interpretation. The study is described as randomized and crossover, with opposing treatment sequences, but the registry does not report how sequence, period, or within-participant correlation were represented in the analysis. Those details are important for interpreting both the point estimate and its uncertainty.

The primary endpoint was measured at the final treatment session of each sequence period. The record does not report whether measurements at earlier sessions were collected for analysis, whether there were washout periods, or how potential carryover was assessed. No assumptions about these design features can be made from the sequence description alone.

The outcome counts differ for the ionic dialysance measure compared with the primary and equilibrated outcomes. The registry does not explain the difference, describe missing-data handling, or identify the analysis population. It also does not report sensitivity analyses for incomplete observations.

The sponsor analysis is labeled as a non-inferiority or equivalence analysis, yet its margin and decision rule are not reported. The sponsor analysis has no posted p-value, and the record does not give a complete model specification. The simple recalculations are unadjusted comparisons based on posted summaries; they cannot resolve those omissions.

The record does not report the original sample-size justification, multiplicity strategy, or a clinically important difference for the dose measures. Safety reporting is limited to counts by starting sequence, with no deaths reported in the record and no treatment-period detail. These limitations do not erase the reported observations, but they narrow the conclusions that can be drawn from them.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study of How the Dose of Dialysis is Affected by Dialysate Flow Rate — NCT00962000.
• Registry record last updated 2025-07-24; status last verified 2025-07.
• Results first posted 2011-07-21.
• 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 registry record describes a completed randomized, unmasked crossover study of dialysate flow rates of 600 mL/min and 800 mL/min, with enrollment of 42. Participants followed one of two starting sequences, each including treatments at both flow rates. The primary outcome was delivered single-pool Kt/Vurea, measured at the final treatment session of each sequence period; equilibrated Kt/Vurea and ionic dialysance-derived Kt/V were also reported.

For the primary outcome, the posted means are 1.66 at 600 mL/min and 1.63 at 800 mL/min. The simple unadjusted recalculation and sponsor ANOVA report estimates near zero, with confidence intervals including zero. The record does not report the sponsor's non-inferiority or equivalence margin, full analysis details, sample-size justification, missing-data approach, or analysis population. The posted results are estimates with uncertainty, not proof of identical outcomes or equivalence.