Chronic Versus Acute Dosing of Sodium Citrate for Swimming 200m: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Chronic Versus Acute Dosing of Sodium Citrate for Swimming 200m (NCT01835912), a randomized phase 3 study. The primary outcome is Time.

2. Clinical Question

The underlying hypothesis in the registry summary is physiological: sodium citrate was described as an alkalizing agent, and the investigators proposed that inducing alkalosis before anaerobic exercise might affect muscle acidity and time to fatigue. That is the rationale for the trial, not a result established by the posted performance data. This statistical question concerns the measured swim time and how uncertain the observed comparisons are.

The trial has a crossover model, so the same trial population was studied under more than one condition. Crossover designs can make within-participant comparisons informative because participants can serve as their own controls. However, the posted summaries do not give participant-level paired results. The reported recalculations therefore should not be mistaken for a complete analysis of the crossover structure.

3. Trial Design

The registry describes a randomized, double-masked, crossover trial, listed as Phase 3, with an enrollment of 10. Its title specifies well-trained swimmers aged 13–17 and a 200-metre swim. The record lists a start of 2012-09, primary completion of 2013-03, and status Completed. The sponsor is Brock University. These administrative details describe the record; they do not establish how randomization, masking, or trial conduct were implemented in practice.

Four conditions appear in the posted results: acute sodium citrate, acute flavoured-water placebo, chronic sodium citrate, and chronic flavoured-water placebo. The acute sodium citrate dose was 0.5 g/kg of body mass dissolved in 500 milliliters of flavoured water. The chronic schedule was 0.1g/kg of body mass for 3 days, then 0.3 g/kg of body mass on the 4th day, also in 500 milliliters of flavoured water. Each placebo condition is described as 500 milliliters of flavoured water.

The registry record does not report the sequence of conditions, the interval between conditions, details of allocation concealment, or how masking was maintained. It also does not report whether any adjustment was made for period or sequence effects. These omissions matter when interpreting a crossover trial: the meaning of a condition comparison depends partly on how repeated conditions and their order were handled.

The primary outcome was mean time in seconds to complete a 200-metre swim, measured once each 200m performance. Participants chose their swim stroke and performed at maximal effort. Lactate, in mmol/L, was posted as a secondary outcome at 3 min post performance. Although the record lists three outcome measures, it provides posted summaries for the primary time outcome and one secondary outcome. The protocol, full outcome definitions, and reasons for any outcomes not posted 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 Time, measured over once each 200m performance.

The primary endpoint is time to complete a 200-metre swimming performance, measured in seconds. A lower time means a faster recorded swim; a higher time means a slower recorded swim. The registry describes a maximal-effort performance with stroke selected by each participant, and states that the time was recorded once each 200m performance.

Time is a continuous outcome: it can take a range of values rather than being limited to categories such as success or failure. Reporting a mean gives a summary of the group’s recorded times, while the standard error describes uncertainty around that estimated mean. Neither statistic shows the full distribution of individual swim times.

The endpoint is used to address the stated performance question directly: whether completion time differed across sodium citrate and placebo conditions. The physiological rationale in the registry summary proposes that sodium citrate could alter processes related to fatigue during anaerobic exercise. The swim time itself measures performance, not those proposed physiological mechanisms. Lactate was listed separately as a secondary measure, collected 3 min post performance; it does not replace the primary time outcome.

For the reported primary summaries, mean times were 144.2 seconds for acute flavoured-water placebo, 145.3 seconds for acute sodium citrate, 145.3 seconds for chronic flavoured-water placebo, and 144.8 seconds for chronic sodium citrate. The arm summaries report standard errors of 4.7, 5.3, 5.4, and 5.3 seconds, respectively. These are condition-level summaries, not participant-level trajectories, and they do not by themselves account for the repeated-condition structure of a crossover trial.

7. Results Posted in the Registry

• Sodium Citrate Dihydrate Acute: mean 145.30 versus 144.20 on control; difference 1.10 (95% CI -12.78 to 14.98), standardized effect d = 0.07; z-test p = 0.877.
• Flavoured Water Placebo for Chronic Dosing: mean 145.30 versus 144.20 on control; difference 1.10 (95% CI -12.93 to 15.13), standardized effect d = 0.07; z-test p = 0.878.
• Sodium Citrate Dihydrate Chronic: mean 144.80 versus 144.20 on control; difference 0.60 (95% CI -13.28 to 14.48), standardized effect d = 0.04; z-test p = 0.932.

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.

Lactate

• 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 errors.
• Result:
  • Sodium Citrate Dihydrate Acute: mean 10.40 versus 8.80 on control; difference 1.60 (95% CI -1.29 to 4.49), standardized effect d = 0.48; z-test p = 0.279.
  • Flavoured Water Placebo for Chronic Dosing: mean 9.50 versus 8.80 on control; difference 0.70 (95% CI -2.02 to 3.42), standardized effect d = 0.23; z-test p = 0.614.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sodium Citrate Dihydrate Acute and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Flavoured Water Placebo for Chronic Dosing and the control. The interval gives the range of effects that remain compatible with the data.

Lactate is the secondary outcome posted in the registry, measured in mmol/L at 3 min post performance. Across the listed conditions, its mean pattern differs from the pattern in swim times: the citrate-condition summaries and chronic placebo summary are above the acute placebo summary. The secondary measure therefore does not simply mirror the primary endpoint’s near-similar condition means.

This broad pattern should not be treated as evidence that lactate changed in a way that explains performance. The registry does not report an analysis linking an individual participant’s lactate result to that participant’s swim time, and it does not provide a mechanistic analysis. Lactate is a physiological measure recorded after the swim; it is not the primary performance outcome. A condition-level pattern across the two outcomes cannot establish mediation or causation.

The posted secondary comparisons are recalculated and unadjusted. They are not reported sponsor analyses, and the registry lists no reported analyses. The secondary intervals include zero, and the unadjusted p-values do not establish a difference. These comparisons also use acute placebo as the reference; the record does not report a sponsor analysis pairing each dosing schedule with its corresponding placebo.

Secondary outcomes generally carry less evidential weight than a prespecified primary endpoint because they may be numerous, exploratory, or analyzed without a planned adjustment for multiple testing. When several outcomes or contrasts are examined, the chance of obtaining an apparently notable result by chance can increase. The record lists three outcome measures but provides no multiplicity plan, no full outcome-analysis schedule, and no account of which analyses were prespecified. Therefore, an isolated secondary pattern should be considered supportive or exploratory at most, not decisive evidence about the trial’s primary question.

In relation to the primary result, lactate offers context about a separate measured response but does not resolve the imprecision in swim-time comparisons. The registry’s physiological rationale makes lactate relevant to the hypothesis, while the posted summaries remain insufficient to show whether any biochemical response corresponded to a meaningful performance difference.

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

• Lactate

9. Statistical Interpretation

10. Statistical Methods Explained

The posted primary measure is a mean of a continuous outcome. A mean summarizes the condition-level times by their arithmetic center; the posted standard errors express uncertainty in those mean estimates. Means are useful for describing the average condition result, but can conceal variation among participants. The registry provides no individual observations, distributions, or participant-level paired differences, so those features cannot be assessed from the summaries.

What does a mean difference describe?

A mean difference compares the mean time in one condition with the mean time in a reference condition. Its sign depends on the order of subtraction, so the interpretation follows the posted comparisons: positive estimates indicate longer mean times in the named condition than in the acute flavoured-water placebo reference. A difference of zero would correspond to equal means under that comparison. This is a general explanation of the statistic, not a claim that the conditions are equivalent when an estimate is near zero.

The recalculated comparisons use the posted means and standard errors. They are described as unadjusted because they do not incorporate adjustments for other factors or a reported trial model. The registry’s crossover designation makes this limitation especially relevant. A paired analysis would ordinarily use the fact that repeated outcomes come from the same participants; the posted summaries do not include the covariance or paired differences required to reconstruct that analysis. The recalculations are therefore simple summary-based comparisons, not a substitute for a suitable crossover analysis.

How should a p-value be read?

A p-value describes how incompatible the observed data would be with a specified null model, under the assumptions used for the calculation. Smaller p-values can indicate greater incompatibility with that null model, but a p-value is not the probability that the null hypothesis is true. It is also not a measure of the size or importance of an effect. The reported comparison p-values are unadjusted; the registry record does not report a multiplicity procedure or sponsor analysis to use instead.

All posted primary comparisons have p-values well above the conventional threshold of 0.05 used in the planning illustration. That observation does not establish absence of an effect. Interpretation must also consider the effect estimate, the interval around it, the small enrollment, and whether the calculation correctly represents the crossover design. Since the registry does not report the original analysis plan, it is unknown whether a different model or testing procedure was prespecified.

What does an interval add?

A confidence interval expresses uncertainty around an estimate under a statistical method and its assumptions. In general, an interval that includes zero for a mean difference allows both a no-difference value and values on either side of it. A broad interval indicates limited precision: many different effect sizes remain compatible with the data under the calculation. An interval is not a guarantee that the true effect lies within its endpoints, and its interpretation depends on the method used.

The registry does not state the confidence level or method for the recalculated intervals, and the posted means and standard errors do not permit a crossover-adjusted interval to be reconstructed. The intervals should therefore be treated as simple, unadjusted summaries rather than as definitive uncertainty estimates for a properly specified crossover model.

Why does the crossover model matter?

In a crossover trial, a participant may contribute measurements under multiple conditions. Statistical methods can account for this within-participant relationship and may also consider period and sequence. The relationship matters because measurements from the same person are generally not independent. Ignoring that structure can produce uncertainty estimates that differ from those of an appropriate paired analysis. The direction and size of that difference cannot be inferred without the participant-level data and design details.

The registry confirms the crossover model but does not report condition order, washout interval, period effects, sequence effects, or the sponsor’s model. It also does not report participant-level data. Consequently, no conclusion can be drawn about whether carryover or period effects were present or adequately handled. These are questions about the design and analysis, not evidence that such problems occurred.

What is the role of standard error?

The standard error estimates the sampling uncertainty of a mean, given a statistical model. It is distinct from a standard deviation, which describes variation among individual observations. The arm summaries label their spread as standard error, and the recalculated comparisons use those values. Without individual results, it is not possible to evaluate the distribution of times or verify assumptions such as approximate normality.

For a continuous measure, the mean and standard error can be a concise summary, but they do not show whether results are driven by a few unusually fast or slow swims. In a small crossover trial, the within-participant pattern could be particularly informative. The registry record does not provide enough information to examine it.

Finally, “recalculated” distinguishes these simple comparisons from analyses reported by trial investigators. The registry lists zero reported analyses. The absence of a reported sponsor result means the simple estimates and p-values should not be presented as the trial’s prespecified primary analysis. The posted record does not state whether a statistical analysis plan exists or what methods it specified.

11. Confidence Intervals and Precision

The recalculated intervals for the primary comparisons are broad. For acute sodium citrate versus acute flavoured-water placebo, the mean difference is 1.1 seconds, with an interval from -12.78 to 14.98 seconds. For chronic flavoured-water placebo versus acute flavoured-water placebo, the mean difference is 1.1 seconds, with an interval from -12.93 to 15.13 seconds. For chronic sodium citrate versus acute flavoured-water placebo, the mean difference is 0.6 seconds, with an interval from -13.28 to 14.48 seconds.

Every interval includes zero and allows differences in both directions. Thus, the point estimates alone should not be read as precise estimates of a longer swim time. The intervals also leave room for faster times under the named conditions. They do not show that either direction is likely, and they do not establish equivalence. A formal equivalence conclusion would require a prespecified margin and suitable analysis, neither of which is reported in the registry record.

In general, a confidence interval summarizes uncertainty around an estimated effect under the method used. Wider intervals indicate less precision, while narrower intervals indicate greater precision. Here, precision is limited: the range of values compatible with the simple recalculations is much broader than the point estimates. The registry does not report the confidence level or calculation method for these intervals, and the posted results do not include the paired data needed to produce a crossover-adjusted interval.

The small enrollment and absence of participant-level results further limit interpretation. The intervals are not a measure of individual variability, and the standard errors should not be confused with the spread of individual swim times. Their relevance depends on the statistical assumptions used, including whether the repeated conditions and within-participant dependence are handled appropriately. The record does not report enough detail to verify that.

Accordingly, the posted estimates are compatible with a range of performance differences and are not sufficiently precise to support a confident conclusion about the size or direction of an effect. A small p-value question and a precision question are related but distinct: the p-values do not cross a conventional threshold, while the broad intervals show why that finding should not be interpreted as proof of no difference.

12. Planning a Similar Trial: Sample Size

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

The planning figures are illustrations based on the observed effects in the posted comparisons, not the trial’s original design assumptions. For these continuous outcomes, the figures are participants per arm, not total events. The calculation assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It considers detecting the stated fraction of the observed effect. The original sample-size justification and assumptions are not reported in the registry record.

The 80% power column gives the planned number of participants per arm under those assumptions for an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column uses a higher target chance of detection and therefore generally requires more participants per arm. These are planning targets for a hypothetical future comparison, not a measure of what the completed trial achieved. This is not observed power.

Rows that plan for 100% of the observed effect use the observed estimate as the target effect; rows planning for 75% or 50% use smaller target effects. Smaller effects are harder to distinguish from random variation, so detecting them generally requires more participants. That is why the participant requirements increase as the target fraction decreases. The implications can vary by comparison because the observed effect and estimated variability differ.

The figures should be read as conditional illustrations, not recommendations or evidence that a particular sample size would be adequate for a crossover design. The calculation assumes equal allocation between two arms and does not reflect the paired structure, sequence, period, or other design details that may matter in this trial. The registry record does not report an original statistical plan or sample-size rationale against which to compare these illustrations.

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 = 1.100; pooled standard deviation σ = 15.840.
2. n = 2 × (1.96 + 0.842)² × 15.840² / 1.100² = 3,255.0, rounded up to 3,256 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 <- 1.10000000000002                      # observed difference in means
sigma <- 15.8398232313369                     # 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(1835912)
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 = 3,256 (80% power), 4,358 (90% power)
 75% of observed effect: n per arm = 5,787 (80% power), 7,747 (90% power)
 50% of observed effect: n per arm = 13,021 (80% power), 17,431 (90% power)
power.t.test: 3256 
Simulated power at n = 3,256 per arm: 0.798 (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 record does not report how multiplicity was handled. The listed record includes a primary time outcome, a secondary lactate outcome, several condition summaries, and multiple recalculated contrasts. Without a prespecified testing hierarchy or adjustment procedure, the unadjusted p-values should not be treated as if they account for all outcomes and comparisons considered during the trial. Examining many results can increase the chance of a seemingly unusual finding arising by chance. The record does not establish how many analyses were actually conducted beyond listing zero reported analyses.

Missing-data handling is not reported in the registry record. The arm summaries show an n of 10.0 for each condition, but the record does not explain whether these values represent complete outcome availability, how missing observations were handled, or whether any participants withdrew from particular conditions. It also does not report imputation, exclusion rules, or sensitivity analyses. These omissions prevent assessment of how missing outcomes may affect the estimates.

The analysis population is also not reported. The record does not state whether results were analyzed according to randomized condition, only among participants completing all conditions, or using another defined population. For a crossover design, the number of participants contributing paired data and the handling of incomplete condition sequences are important. Those details are not available in the registry record.

The registry identifies a randomized, double-masked crossover model, but does not describe the sponsor’s statistical analysis plan, treatment of period and sequence, carryover assessment, or model for within-participant correlation. Nor does it report interim analyses or stopping rules. These matters should be treated as unknown rather than inferred from the design label or from the posted summary statistics.

In consequence, the simple recalculations are useful for describing the posted condition means, but cannot answer whether the original analysis accounted for multiplicity, missing observations, or the repeated-measures structure. The registry record does not report a sponsor analysis against which those questions could be checked.

15. Safety Results

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

Other (non-serious) adverse events

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

The registry lists serious adverse events and other adverse events separately for each condition group. For acute placebo, acute sodium citrate, chronic placebo, and chronic sodium citrate, the record reports zero affected for serious adverse events and zero affected for other adverse events; each group lists 10 at risk for each category.

These figures mean that no affected participants are recorded in the posted adverse-event fields for those groups. They do not establish that no symptoms or events occurred in any broader sense, because the record does not provide event definitions, collection procedures, or further details about monitoring. The record also does not list serious-event terms.

Deaths are not reported in the registry record. The adverse-event summaries should be interpreted as descriptive entries for the listed conditions, not as a comprehensive safety analysis or as proof of safety. The crossover structure also means the condition-group entries should not be added together to infer a number of distinct participants.

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

The posted results describe mean 200-metre swim times that are similar in scale across the four conditions, alongside unadjusted recalculated comparisons with acute flavoured-water placebo. The estimated differences are small relative to their broad intervals, and each interval includes zero. The corresponding unadjusted p-values do not provide evidence against a no-difference null under these simple calculations.

That does not mean the trial established that acute or chronic sodium citrate has no effect on performance. The intervals allow differences in either direction, and their breadth reflects limited precision. Nor does the trial establish equivalence: the registry record does not report a prespecified equivalence margin or an analysis designed to demonstrate that differences are small enough to be unimportant.

The result also does not establish the proposed physiological mechanism. The registry summary discusses alkalosis and muscle acidity as rationale, while lactate is posted as a secondary outcome. The registry does not report a mechanistic analysis connecting lactate with swim time or demonstrating that the proposed biological changes occurred.

Several design and reporting details constrain the conclusion. This is a crossover trial, but the posted recalculations are based on condition summaries and do not account for paired participant data. The record does not report condition order, washout, period or sequence analyses, the sponsor’s statistical plan, missing-data handling, or analysis population. It lists no reported analyses. These limitations mean the recalculated summaries should be read as descriptive, not as a definitive substitute for the trial’s intended analysis.

The findings apply to the participants and conditions represented in this record; the title specifies well-trained swimmers aged 13–17. The registry does not report broader eligibility detail or support extrapolation to other populations, exercise settings, or dosing practices. No treatment recommendation follows from these statistical summaries. They describe what was posted and how uncertain the comparisons are, not whether any intervention should be used.

17. Why This Trial Matters Statistically

This trial is statistically interesting because it combines a crossover design with several dosing and placebo conditions, while the posted results are condition-level means and standard errors. That contrast highlights a central analytic point: the design may generate paired measurements, but the available recalculations do not use the participant-level pairing. The information needed to exploit that design is not reported in the registry record.

The example also shows why a non-significant p-value is not the same as evidence of no effect. The primary comparisons have small point estimates, but their intervals cover a broad range in both directions. Without sufficient precision, a result can remain inconclusive even when the observed means are close. Equivalence requires a different question and analysis than failure to reject a no-difference null.

A further lesson is the separation between a registry summary and a complete statistical report. The record names a randomized, double-masked crossover trial and posts outcome summaries, but lists no reported analyses. It does not explain the original analysis plan, missing data, multiplicity, or crossover-specific methods. Such details determine how well a reported estimate answers the study question.

Finally, the secondary lactate measure illustrates the distinction between mechanistic rationale and evidence of mechanism. A secondary physiological outcome may be relevant to a hypothesis, but its relationship to performance needs to be analyzed directly and interpreted in light of multiplicity and uncertainty. The posted record does not provide that analysis. The statistical lesson is not a verdict on sodium citrate; it is the importance of matching the analysis to the design and making uncertainty and analysis choices transparent.

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 principal limitation for interpretation is that the registry posts condition-level summaries but no participant-level results. Because this is a crossover trial, paired differences and within-participant correlation could be important to the precision of condition comparisons. The recalculated contrasts do not incorporate those features, and the record does not report a sponsor analysis or crossover model.

The comparator structure also limits direct interpretation. The recalculated contrasts use acute flavoured-water placebo as the reference for each condition, including chronic sodium citrate. Although the registry describes a chronic placebo condition, it does not post a sponsor analysis directly comparing chronic citrate with chronic placebo. Therefore, the simple contrasts do not isolate the chronic dosing comparison in the way a matched-condition contrast might.

The registry does not report condition sequence, washout duration, period effects, carryover assessment, missing-data methods, analysis population, multiplicity handling, or the original statistical analysis plan. These omissions prevent assessment of whether the intended crossover analysis addressed those issues. They are not evidence that a particular design problem occurred.

The enrollment is 10, and the intervals around the recalculated primary differences are broad. This limits precision and leaves a wide range of possible effects compatible with the posted summaries. The record does not report an original sample-size rationale, so the planning illustrations based on observed effects should not be interpreted as the trial’s own design justification.

Finally, the title’s population is well-trained swimmers aged 13–17, while detailed eligibility criteria and wider participant characteristics are not reported. Generalizability beyond the recorded setting is therefore uncertain. The posted lactate summaries are secondary and lack reported analyses linking them to swim performance. These limits call for cautious statistical interpretation rather than a clinical conclusion.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Chronic Versus Acute Dosing of Sodium Citrate for Swimming 200m — NCT01835912.
• Registry record last updated 2014-07-24; status last verified 2014-07.
• Results first posted 2014-07-24.
• 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 NCT01835912, titled “Chronic Versus Acute Dosing of Sodium Citrate for Swimming 200m.” It lists a randomized, double-masked crossover trial, Phase 3, with an enrollment of 10 and status Completed. The record gives a start of 2012-09 and primary completion of 2013-03; Brock University is listed as sponsor.

The primary outcome is mean time in seconds to complete a maximal-effort 200-metre swim, with participants choosing their stroke. Acute and chronic sodium citrate conditions and corresponding flavoured-water placebo conditions are described. Lactate at 3 min post performance is posted as a secondary outcome.

The posted primary summaries show mean times from 144.2 to 145.3 seconds across conditions. Recalculated unadjusted comparisons with acute placebo have broad intervals that include zero. The registry lists no reported analyses and does not report the original statistical plan, crossover-specific analysis, missing-data handling, or multiplicity approach. These gaps, together with the imprecision of the simple comparisons, limit conclusions about performance differences.