Hemodynamic Effects of Compression in POTS: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Hemodynamic Effects of Compression in POTS (NCT03484273), a randomized na study. The primary outcome is Orthostatic Heart Rate (HR) Change.

2. Clinical Question

POTS is described in the registry as a condition in which standing is associated with a substantial heart-rate rise and may be accompanied by symptoms. The study used head-up tilt testing to simulate the change from lying down to upright posture. Its stated hypothesis was that full compression would be associated with a smaller heart-rate increase than no compression. Participants also reported symptoms while upright.

The study included four ten-minute tilt tests, one for each configuration. Full compression secured all straps; abdominal and pelvic compression secured abdominal, pelvic, and upper-thigh straps; lower limb compression secured calf and ankle straps; and the no-compression condition left all straps unsecured. The registry also lists upright heart rate, symptom ratings, blood pressure, stroke volume, cardiac output, systemic vascular resistance, and cerebral blood-flow velocity as secondary outcomes.

The question is physiological and concerns responses during a controlled test. The registry record does not establish how these measurements translate to outcomes outside the test setting.

3. Trial Design

This was a randomized, unmasked crossover trial of LifeWrap compression configurations in people with postural tachycardia syndrome. The registry lists an enrollment of 32. For the primary outcome, it reports that 30 participants were analyzed. The trial status is completed. The listed study start was 2018-07-12, and the primary completion date was 2020-04-01.

Each participant was scheduled to undergo four ten-minute head-up tilt tests, with full compression, abdominal and pelvic compression, lower limb compression, and no compression. The garment configurations differed in which straps were secured. In a crossover design, participants experience multiple conditions, allowing responses to be compared across conditions within the study rather than relying only on separate groups of participants. The registry identifies the allocation as randomized and masking as none; it does not report further details about the order of conditions or how the sequence was generated.

The primary outcome was continuous: orthostatic heart-rate change, measured in beats per minute as maximum heart rate during minutes 5–10 of tilt minus pre-tilt baseline heart rate. The reported summary is the mean and standard deviation for each condition. The registry lists an analysis of variance (ANOVA) across all four conditions, with a reported p-value of <0.001.

The record does not report the original sample-size justification, the intended statistical analysis plan, interim analyses, or details of handling sequence, period, or carryover effects. These omissions matter when interpreting a crossover study because the conditions are experienced by the same participants and the order of exposure can be relevant to analysis. The registry’s reported overall analysis and the posted condition summaries therefore describe the available evidence, but do not fully document the analytic approach.

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.

Before assignment: This was a randomized cross-over trial. Participants were assigned to receive the 4 compressions interventions in a randomized order. There were a total of 24 potential sequence orders of the compression interventions.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: This was a crossover trial. A total of 30 participants were analyzed.

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 Orthostatic Heart Rate (HR) Change, measured over Maximum HR between 5-10min HUT MINUS the baseline (pre-tilt) HR.

The primary endpoint measures the change in heart rate associated with moving from a pre-tilt baseline to an upright head-up tilt. For each condition, the recorded value was the maximum heart rate between five and ten minutes of tilt minus the baseline heart rate before tilt. The unit is beats per minute. A larger positive change represents a greater rise from baseline during the test; a smaller change represents a more limited rise in that measurement.

The endpoint is used because the study’s stated question concerns orthostatic heart-rate response. Head-up tilt provides a standardized challenge that simulates standing, and the endpoint focuses on the heart-rate response during the later part of the test rather than on a single reading at the start of tilt. The registry reports a mean and standard deviation for each garment condition.

The primary endpoint is not the same as maximum upright heart rate alone. Maximum upright heart rate is separately listed as a secondary outcome, while the primary endpoint subtracts each participant’s pre-tilt baseline from the maximum recorded during tilt. That distinction matters: a change score incorporates the baseline measurement, whereas the upright rate alone does not.

The endpoint describes a short-term physiological measurement during testing. It does not, by itself, measure symptom burden, long-term response, or outcomes in everyday activities. The registry lists symptom ratings and other cardiovascular measures separately as secondary outcomes.

7. Results Posted in the Registry

• Abdominal and Pelvic Compression: mean 28.00 versus 23.00 on control; difference 5.00 (95% CI -0.57 to 10.57), standardized effect d = 0.45; z-test p = 0.078.
• Lower Limb Compression: mean 34.00 versus 23.00 on control; difference 11.00 (95% CI 4.63 to 17.37), standardized effect d = 0.87; z-test p = <0.001.
• No Compression: mean 39.00 versus 23.00 on control; difference 16.00 (95% CI 8.45 to 23.55), standardized effect d = 1.07; 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.

Maximum Upright Heart Rate

• 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:
  • Abdominal and Pelvic Compression: mean 97.00 versus 92.00 on control; difference 5.00 (95% CI -2.34 to 12.34), standardized effect d = 0.34; z-test p = 0.182.
  • Lower Limb Compression: mean 103.00 versus 92.00 on control; difference 11.00 (95% CI 3.39 to 18.61), standardized effect d = 0.73; z-test p = 0.005.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Abdominal and Pelvic Compression and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Lower Limb Compression than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Differences in Vanderbilt Orthostatic Symptom Score (VOSS) Symptom Rating

• 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:
  • Abdominal and Pelvic Compression: mean 15.00 versus 12.00 on control; difference 3.00 (95% CI -2.59 to 8.59), standardized effect d = 0.27; z-test p = 0.293.
  • Lower Limb Compression: mean 22.00 versus 12.00 on control; difference 10.00 (95% CI 2.94 to 17.06), standardized effect d = 0.72; z-test p = 0.005.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Abdominal and Pelvic Compression and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Lower Limb Compression than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Systolic Blood Pressure (SBP)

• 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:
  • Abdominal and Pelvic Compression: mean -7.00 versus -5.00 on control; difference -2.00 (95% CI -5.87 to 1.87), standardized effect d = -0.27; z-test p = 0.311.
  • Lower Limb Compression: mean -10.00 versus -5.00 on control; difference -5.00 (95% CI -9.44 to -0.56), standardized effect d = -0.58; z-test p = 0.027.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Abdominal and Pelvic Compression and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Lower Limb Compression than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary results with numerical summaries include maximum upright heart rate, Vanderbilt Orthostatic Symptom Score ratings, and change in systolic blood pressure. Across these available measures, the condition summaries generally show lower heart-rate and symptom-rating means in the more compressive configurations than with no compression. The blood-pressure change summaries do not follow the same simple ordering. This broad pattern is relevant to the primary result because it shows that the registry considered several related physiological and symptom measures, but secondary outcomes do not independently confirm the primary analysis.

The registry lists additional secondary outcomes: stroke volume, cardiac output, systemic vascular resistance, and cerebral blood-flow velocity. Their numerical results are not reported in the registry record. The record indicates seven secondary outcomes, but detailed arm summaries and analyses are available for only a subset in the material reported. This limits how comprehensively the secondary pattern can be assessed.

The registry reports overall repeated-measures ANOVA results for maximum upright heart rate and symptom ratings, each with p < 0.001, and for systolic blood-pressure change, with p = 0.01. The simple recalculations for selected comparisons are unadjusted. These secondary analyses should carry less weight than the primary endpoint because they are additional outcomes, several comparisons can be examined, and the record does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes.

Secondary findings can help show whether the primary pattern is accompanied by related measurements, but they should not be used to rescue or overturn the primary result on their own. Differences in measurement scale, variability, and completeness of reporting also make direct comparisons across outcomes inappropriate. The secondary data describe additional responses during tilt testing; they do not establish effects on unreported outcomes or on longer-term experience.

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

• Maximum Upright Heart Rate
• Differences in Vanderbilt Orthostatic Symptom Score (VOSS) Symptom Rating
• Change in Systolic Blood Pressure (SBP)
• Changes in Stroke Volume
• Change in Cardiac Output (CO)
• Change in Systemic Vascular Resistance (SVR)
• Change in Cerebral Blood Flow Velocity (CBFV)

9. Statistical Interpretation

10. Statistical Methods Explained

What does the reported ANOVA test?

ANOVA is a method for assessing whether the means across several conditions are compatible with a common mean or show evidence of variation among conditions. The registry reports an ANOVA across the four primary-outcome conditions, with p < 0.001. This is an overall result: it indicates evidence of differences somewhere among the conditions under the analysis used, but it does not, by itself, specify which pairs differ or how large those pairwise differences are. The registry does not post a parameter estimate or confidence interval for this overall analysis.

The record identifies the trial as a randomized crossover study. In a crossover design, measurements from different conditions come from the same participants. Analyses can use the within-participant structure, which may account for the fact that repeated measurements from one person are related. The registry does not describe the particular model terms, assumptions, or adjustments used in its primary ANOVA. It therefore is not possible to determine from the record how the reported analysis handled participant, sequence, or period effects.

What are the pairwise recalculations?

The pairwise comparisons are simple, unadjusted recalculations based on the posted condition means, standard deviations, and sample sizes. They compare each listed condition with full compression and express the estimate as a mean difference. The intervals and p-values are not the sponsor’s reported pairwise results. They are useful as a descriptive supplement, but they do not reproduce a crossover analysis that uses individual participant data and the dependence between measurements from the same participant.

This distinction is important because summaries for each condition do not reveal the within-person correlation between measurements. That correlation can affect the standard error of a paired or crossover comparison. A calculation based only on separate condition summaries may therefore have a different uncertainty estimate from an analysis that uses the trial’s participant-level data. The registry does not report the covariance information needed to reconstruct such an analysis from the posted summaries.

An unadjusted p-value assesses a comparison without accounting for the fact that several comparisons or outcomes may be examined. When many tests are considered, the chance of at least one apparently notable result can increase. Whether and how that issue was addressed in the sponsor’s analysis is not reported in the registry record. The reported overall ANOVA and the recalculated pairwise results answer different statistical questions and should not be treated as interchangeable.

What do means and standard deviations describe?

A mean gives the average measured value within a condition. The standard deviation describes how spread out individual measurements are around that mean. It is not a confidence interval for the mean, and it does not show the range of all individual responses. For the primary outcome, the condition means and standard deviations describe orthostatic heart-rate change among the participants included in the analysis.

Differences in means describe the size and direction of a contrast on the original measurement scale. Here that scale is beats per minute. A positive recalculated contrast for a condition compared with full compression means the posted mean for the other condition is higher. The estimate does not describe every participant’s response, and the group average may conceal variation between individuals.

How should a confidence interval be understood?

A confidence interval gives a range of estimates compatible with the data and the method used to calculate the interval. Wider intervals indicate less precision than narrower intervals, all else equal. An interval spanning zero is compatible with no mean difference as well as with differences in either direction under the calculation used. An interval that does not span zero still does not establish clinical importance or remove concerns about the analysis, multiplicity, or design.

The registry posts intervals for the summary-based recalculations, but it does not state their confidence level in the record presented. The interval should therefore be interpreted as the posted uncertainty range without assigning it a confidence percentage that is not documented. These intervals are distinct from the standard deviations reported for individual condition summaries.

Why does over-dispersion matter in general?

In general, over-dispersion means that observed variability is greater than a statistical model assumes. If a model understates variability, standard errors can be too small and intervals too narrow, making evidence look more precise than it is. This concept is especially relevant when a model’s distributional assumptions are not a good match for the data. The primary endpoint is continuous and summarized with means and standard deviations; the registry does not report an over-dispersion assessment, and the issue should not be assumed to have occurred.

Overall, the available statistics support a descriptive reading of the condition means and the sponsor-reported overall test. They do not permit a full independent reconstruction of the crossover analysis. The primary statistical plan, analysis details, and the sponsor’s pairwise estimates are not reported in the registry record.

11. Confidence Intervals and Precision

Precision concerns how tightly an estimate is determined by the data and analysis. The primary condition means are based on 30 analyzed participants per condition, and their standard deviations show appreciable variation among measured heart-rate changes. The posted recalculated intervals give an additional indication of uncertainty for specific contrasts, but they are simple unadjusted calculations from summary statistics rather than estimates from a documented participant-level crossover model.

For lower limb compression compared with full compression, the recalculated mean difference is 11.0 beats per minute, with an interval from 4.629 to 17.37. For no compression compared with full compression, the estimate is 16.0, with an interval from 8.451 to 23.55. Both posted intervals lie above zero. The abdominal and pelvic comparison has a mean difference of 5.0 and an interval from -0.567 to 10.57, which includes zero. The interval endpoints are not evidence that the true effects are confined to those exact values; they convey uncertainty under the calculation used.

The record does not state the confidence level of these intervals, so a particular coverage percentage should not be inferred. Nor do the intervals account for any unreported adjustment for multiple comparisons. The crossover design also means that within-participant dependence is relevant, while the summary-only recalculations do not use the underlying paired measurements.

Precision is not the same as importance. A narrow interval can still describe a difference that is not consequential for a particular purpose, while a wide interval can include both modest and larger effects. The registry does not report a threshold for an important change in orthostatic heart-rate response. The overall ANOVA p-value provides evidence of differences across conditions under the sponsor’s analysis, but it is not a measure of the precision or practical importance of each pairwise contrast.

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 for a two-arm comparison, not a restatement of this trial’s crossover design or its actual enrollment. For the primary comparisons, the figures use the observed contrast as a planning reference and show scenarios based on detecting 100%, 75%, or 50% of that observed effect.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The target effect is the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record. These planning figures are not observed power.

The 80% power column gives the estimated participants per arm for a design with an 80% chance of detecting the specified effect under those planning assumptions, if that effect were the true effect. The 90% power column gives the corresponding estimate for a design with a 90% chance under the same assumptions. They are prospective planning quantities, not a measure of the probability that this completed trial’s result is correct.

For example, when planning for 100% of the observed primary contrast between no compression and full compression, the illustration gives 14 participants per arm for 80% power and 19 per arm for 90% power. Planning for 75% of the observed effect gives 25 per arm for 80% power and 33 per arm for 90% power; planning for 50% gives 55 and 74 per arm, respectively. The pattern reflects a general statistical principle: smaller effects are harder to distinguish from random variation, so they require more participants for the same target power.

Because these illustrations are based on a simple two-arm normal approximation, they do not encode every feature of the actual crossover study. They should be read as planning aids tied to the stated assumptions, not as a claim about what the study was designed to detect.

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 = 5.000; pooled standard deviation σ = 11.000.
2. n = 2 × (1.96 + 0.842)² × 11.000² / 5.000² = 76.0, rounded up to 76 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 <- 5                      # observed difference in means
sigma <- 11                     # 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(3484273)
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 = 76 (80% power), 102 (90% power)
 75% of observed effect: n per arm = 136 (80% power), 181 (90% power)
 50% of observed effect: n per arm = 304 (80% power), 407 (90% power)
power.t.test: 76.9 
Simulated power at n = 76 per arm: 0.793 (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 sponsor’s reported primary analysis is an ANOVA across all four conditions, with p < 0.001. That is the registry’s own overall analysis result. The registry does not provide the sponsor’s pairwise estimates or confidence intervals for the individual condition contrasts.

The recalculated comparisons use the posted means, standard deviations, and sample sizes to estimate unadjusted differences against full compression. They are not a replacement for the sponsor’s analysis and do not reproduce a participant-level crossover model. In a crossover trial, the relation between measurements from the same participant can affect the uncertainty of a contrast; that information is not available in the posted condition summaries.

The record flags a discrepancy between the reported information and the simple recalculations. For that reason, the sponsor’s own analysis takes precedence. The recalculations can still help describe the size and direction of differences suggested by the condition means, but their p-values and intervals should not be treated as the definitive inferential results. The record does not explain the source of the discrepancy, so no particular cause should be presumed.

The distinction is also between an overall test and pairwise estimates: the sponsor’s reported result addresses whether there is evidence of variation across the conditions as a group, whereas the recalculated contrasts quantify selected comparisons with full compression. Neither result alone establishes the importance of a difference beyond the measured tilt-test response.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study makes several statistical comparisons or evaluates multiple outcomes. Even when each test is conducted using a conventional threshold, examining many tests can increase the chance of finding at least one result that appears notable by chance. This trial has four primary-outcome conditions, pairwise contrasts can be considered among them, and the registry lists multiple secondary outcomes. The record reports an overall primary ANOVA and selected secondary analyses, but does not state how multiplicity was handled.

The registry does not report a prespecified hierarchy for the secondary outcomes, a family of comparisons, or an adjustment method. The summary-based pairwise recalculations are explicitly unadjusted. Their p-values should therefore be interpreted as descriptive evidence for those specific comparisons, not as multiplicity-controlled findings. The overall ANOVA addresses the conditions collectively and is distinct from a sequence of individual pairwise tests.

Missing-data handling is also not reported in the registry record. The primary analysis includes 30 participants, while the enrollment is 32. The record does not explain why the analyzed number is lower than enrollment, whether all participants completed every condition, or how any incomplete measurements were handled. For the systolic blood-pressure summaries, 29 participants are listed per condition; the reason for that analysis count is not reported in the registry record.

The analysis populations are not described beyond the reported numbers analyzed for the primary outcome and the condition-specific counts. It is not reported whether analyses followed an intention-to-treat principle, how exclusions were defined, or whether participants with incomplete crossover periods were included in particular analyses. The sequence-generation details and handling of period or carryover effects are also not reported.

These omissions do not negate the recorded results, but they limit independent assessment of robustness. In particular, the reader cannot determine whether the sponsor’s model appropriately accounted for within-participant dependence, missing observations, multiple testing, or the sequence of test conditions from the registry record alone.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

The registry reports adverse-event figures for each of the four conditions. For each condition, 32 participants are listed as at risk for serious adverse events and 32 as at risk for other adverse events. The record lists zero serious adverse events, zero other adverse events, and zero deaths in each condition. No serious adverse-event terms are listed.

These figures indicate what was recorded in the registry for the study conditions. They do not establish that no adverse experiences occurred outside the categories or reporting approach represented in the record. The registry does not provide event narratives, event definitions, exposure-duration details, or information about how events were attributed across conditions. It also does not explain the relationship between the adverse-event denominators and the 30 participants analyzed for the primary outcome.

Because this was a crossover study, the same participants could experience multiple conditions. The condition-specific counts should not be added to infer a unique number of people in the study. The adverse-event record is a descriptive account, not a comparative safety analysis, and zero recorded events in these categories should not be interpreted as proof of absence of risk.

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

The registry results show that mean orthostatic heart-rate change differed across the four compression configurations under the sponsor’s reported overall analysis. The condition means follow a pattern in which full compression has the lowest reported mean change and no compression the highest. The sponsor-reported ANOVA result is p < 0.001. The simple recalculations also show larger mean changes for lower limb compression and no compression relative to full compression, while the recalculated abdominal and pelvic contrast is less precise and its interval includes zero.

These results concern a specific endpoint measured during head-up tilt testing. They describe group averages in a study of 30 participants analyzed for the primary outcome, not a guaranteed response for every participant. The registry does not report a threshold for judging whether a particular difference is important, nor does it establish how the test measurements correspond to everyday symptoms or longer-term outcomes.

The primary result should not be read as proof that every compression configuration produces the same response, or that a particular configuration is preferable for an individual. The trial compared defined garment conditions under testing procedures; the record does not report outcomes sufficient to draw conclusions about all compression garments or all settings.

The record also does not provide enough detail to reconstruct the sponsor’s analysis or explain the flagged discrepancy. The sponsor’s reported overall analysis takes precedence over the simple unadjusted recalculations. The recalculations are useful for understanding the posted means and selected contrasts, but they are not a substitute for the trial’s own analysis.

In short, the posted data describe condition-related differences in short-term heart-rate response during tilt testing and additional secondary measurements. They do not establish clinical benefit, individual suitability, or effects beyond the outcomes and setting recorded.

18. Why This Trial Matters Statistically

This trial is statistically interesting because a crossover design compares multiple conditions experienced by the same participants. Such a design can be efficient for studying short-term physiological responses, since each participant can contribute measurements under several configurations. At the same time, valid analysis must account for the repeated measurements and their dependence. The registry identifies the crossover structure but does not provide enough detail to assess how the reported model handled it.

The endpoint also illustrates why outcome definitions matter. Orthostatic heart-rate change is not simply the maximum upright heart rate: it is the maximum recorded during a specified portion of tilt minus the pre-tilt baseline. That definition focuses the analysis on change from baseline, while the secondary maximum-rate measure answers a related but distinct question.

The result shows the value of distinguishing an overall test from individual comparisons. A significant overall ANOVA indicates evidence of differences across the set of conditions, but it does not establish that every pair differs. The simple recalculations provide selected pairwise estimates, yet their summary-based, unadjusted nature and the record’s discrepancy flag limit their authority.

Finally, the registry record makes clear that sample-size planning illustrations based on observed effects are not the same as the original design justification or observed power. Keeping those concepts separate helps avoid overinterpreting a completed study’s results. The missing details on multiplicity, analysis populations, and incomplete measurements further show why transparent statistical reporting is important for evaluating a clinical trial.

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 primary analysis includes 30 participants, while 32 were enrolled. The registry does not report why the analysis count differs from enrollment or how missing or incomplete measurements were handled. The systolic blood-pressure summaries use 29 participants per condition, and the reason for that count is also not reported in the registry record.

The crossover design makes within-participant dependence, condition order, and possible period effects relevant. The registry identifies randomization and crossover structure but does not report the order-generation procedure, the analysis terms, or whether sequence and period effects were assessed. Carryover handling is not described.

The primary outcome has posted means and standard deviations, and the registry reports an overall ANOVA p-value. However, sponsor-reported pairwise estimates and confidence intervals are not posted. Simple unadjusted recalculations from the summaries do not use individual paired data, and the record flags a discrepancy; the sponsor’s own analysis therefore takes precedence.

The registry does not report the original sample-size justification, a complete statistical analysis plan, interim analyses, multiplicity handling, analysis-population definitions, or the confidence level for the posted intervals. These gaps prevent full independent evaluation of the analysis choices and their consequences.

Detailed numerical results are available for only some of the listed secondary outcomes. The registry does not report detailed results for stroke volume, cardiac output, systemic vascular resistance, or cerebral blood-flow velocity. The study outcomes concern measurements during tilt testing, so the record does not establish how the results generalize to other settings, longer-term outcomes, or different compression devices.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Hemodynamic Effects of Compression in POTS — NCT03484273.
• Registry record last updated 2021-10-22; status last verified 2021-09.
• Results first posted 2021-05-12.
• 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

NCT03484273, titled Hemodynamic Effects of Compression in POTS, is a completed randomized, unmasked crossover study sponsored by the University of Calgary. It enrolled 32 participants and tested four LifeWrap configurations during head-up tilt testing.

The primary endpoint was orthostatic heart-rate change, defined as maximum heart rate during minutes 5–10 of tilt minus pre-tilt baseline. The registry reports 30 participants analyzed and an overall ANOVA p-value of <0.001. The condition means were lowest with full compression and highest with no compression.

The registry also posts selected secondary results and adverse-event summaries. Important details about the original sample-size rationale, analysis plan, missing data, multiplicity, and crossover-specific modeling are not reported in the registry record. The record flags a discrepancy between reported information and simple recalculations; the sponsor’s own analysis takes precedence.