Effects of the Breathe Technologies Ventilation System in Subjects With Chronic Obstructive Pulmonary Disease: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of the Breathe Technologies Ventilation System in Subjects With Chronic Obstructive Pulmonary Disease (NCT01372462), a randomized na study. The primary outcome is Exercise Duration for Constant Work Rate Exercise Tests Under 4 Test Conditions.

2. Clinical Question

3. Trial Design

This was a randomized, double-masked, crossover pilot study. Crossover means participants receive or experience more than one study condition, so comparisons can draw on repeated measurements within the same person. Randomization concerns how study conditions are assigned; double masking means the registry classified the study as masked at two levels, but the registry record does not identify who was masked or how masking was maintained.

The study enrolled 15 stable male subjects with severe-to-very severe COPD. The primary outcome population is described as per protocol. The registry lists four conditions: NIOV powered by room air, NIOV powered by oxygen, nasal cannula oxygen, and no treatment. The oxygen used with NIOV and the nasal cannula was described as 100% medical oxygen; the room-air NIOV condition was powered by compressed air containing 21% oxygen. The control condition involved exercise without supplemental oxygen or NIOV.

The primary outcome was measured on study days 1, 2, 3 and 4, with condition availability varying by day. The listed schedule describes no treatment on day 1; no treatment, NIOV with room air and NIOV with oxygen on days 2 and 3; and NIOV with oxygen and nasal cannula oxygen on day 4. The posted timeframe does not provide a complete account of sequence allocation, washout periods or the handling of period and order effects. Those details are not reported in the registry record.

The registry identifies the study as completed and gives an enrollment of 15. The sponsor was Breathe Technologies, Inc. The original design rationale, sample-size justification and detailed statistical analysis plan 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.

NIOV - Room Air

NIOV - Oxygen

Oxygen Nasal Cannula

No Treatment Control

Analysis population for the primary outcome, as defined in the registry: Per protocol analysis

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.

Population: The primary endpoint is difference in endurance between cannula oxygen and NIOV+O2. Assuming 153 sec clinically important difference, 183 sec SD of increase and α=0.05, a sample size of 15 yields 85% power.

6. Primary Endpoint

The registry lists the primary outcome as Exercise Duration for Constant Work Rate Exercise Tests Under 4 Test Conditions, measured over Study days 1,2,3, and 4; Day 1 for no treatment; day 2 for no treatment and NIOV - Room Air and NIOV - oxygen; Day 3 for no treatment and NIOV - Room Air and NIOV - oxygen; Day 4 for NIOV - oxygen and Nasal Cannula Oxygen..

The primary endpoint was exercise duration, in minutes, during constant work rate exercise tests under four conditions. A constant work rate test holds the exercise workload steady while duration records how long exercise continues under that condition. It is therefore a direct measure of exercise endurance in the particular test setting, rather than a measure of everyday activity or long-term functioning.

The registry reports the mean and standard deviation for each condition. The listed means were 6.3 minutes with NIOV powered by room air, 17.5 minutes with NIOV powered by oxygen, 11.4 minutes with nasal cannula oxygen and 5.6 minutes with no treatment. These summaries describe the posted per-protocol results; the standard deviations describe variation among the recorded measurements, not uncertainty in the mean itself.

Comparing conditions addresses whether exercise duration differed during these tests. In a crossover study, within-person comparisons can be informative because each participant may contribute measurements under more than one condition. However, the registry record does not report the paired analysis details or the within-person covariance needed to reconstruct such comparisons from marginal means and standard deviations alone. The posted endpoint therefore needs to be interpreted in the context of both the registry’s reported analysis and the limits of a recalculation from summary statistics.

Exercise duration is useful for a short-term physiological study because it captures test performance during the assigned condition. It does not by itself establish effects on other outcomes, sustained use, daily life or health over a longer period.

7. Results Posted in the Registry

• NIOV - Oxygen: mean 17.50 versus 6.30 on control; difference 11.20 (95% CI 7.65 to 14.75), standardized effect d = 2.26; z-test p = <0.001.
• Nasal Cannula Oxygen: mean 11.40 versus 6.30 on control; difference 5.10 (95% CI 1.08 to 9.12), standardized effect d = 0.91; z-test p = 0.013.
• No Treatment: mean 5.60 versus 6.30 on control; difference -0.70 (95% CI -2.99 to 1.59), standardized effect d = -0.22; z-test p = 0.549.

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.

SpO2 During Constant Workrate Exercise at Isotime

• 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:
  • NIOV - Oxygen: mean 98.50 versus 87.90 on control; difference 10.60 (95% CI 8.61 to 12.59), standardized effect d = 3.82; z-test p = <0.001.
  • Nasal Cannula Oxygen: mean 92.70 versus 87.90 on control; difference 4.80 (95% CI 2.04 to 7.56), standardized effect d = 1.25; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for NIOV - Oxygen than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Nasal Cannula Oxygen than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Borg Dyspnea Score During Constant Workrate Exercise at Isotime

• 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:
  • NIOV - Oxygen: mean 1.80 versus 3.30 on control; difference -1.50 (95% CI -2.62 to -0.38), standardized effect d = -0.96; z-test p = 0.009.
  • Nasal Cannula Oxygen: mean 2.50 versus 3.30 on control; difference -0.80 (95% CI -2.05 to 0.45), standardized effect d = -0.46; z-test p = 0.211.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for NIOV - Oxygen than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Nasal Cannula Oxygen and the control. The interval gives the range of effects that remain compatible with the data.

Across the two posted secondary outcomes, the condition-level pattern is directionally consistent with the primary result: the NIOV-with-oxygen condition has higher mean oxygen saturation and lower mean Borg dyspnea score than the room-air NIOV condition. The posted summaries also place nasal cannula oxygen between the oxygen-powered NIOV condition and room-air NIOV for these outcomes. These are descriptive patterns during exercise at isotime, not separate evidence about longer-term outcomes.

The registry reports sponsor ANOVA comparisons for some, but not all, secondary contrasts. For oxygen saturation, sponsor comparisons are listed for NIOV with oxygen against nasal cannula oxygen and against NIOV with room air. For Borg dyspnea, the listed sponsor comparisons are also limited to selected conditions. The registry record does not provide a complete set of inferential results for every possible contrast, and no numerical sponsor estimates or confidence intervals are reported for these secondary analyses.

The secondary measures relate to the primary endpoint because they describe oxygen saturation and perceived dyspnea during the same general exercise-testing context. They can help characterize the observed physiological and symptom pattern alongside exercise duration, but they do not independently validate the primary result or establish a mechanism. The record does not report a prespecified hierarchy among endpoints or a plan for interpreting them together.

Unadjusted secondary results carry less weight when multiple outcomes and comparisons are examined. General statistical explanation: testing many hypotheses increases the chance that at least one result will appear notable by chance if no adjustment or prespecified hierarchy is used. The registry record does not report a multiplicity adjustment. Therefore, the secondary pattern is useful as descriptive context, while isolated significance claims should be treated cautiously. This caution is especially relevant in a pilot study with a small participant population and incomplete reporting of the statistical plan.

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

• SpO2 During Constant Workrate Exercise at Isotime
• Borg Dyspnea Score During Constant Workrate Exercise at Isotime

9. Statistical Interpretation

10. Statistical Methods Explained

The registry classifies the primary endpoint as a continuous measure reported as a mean with standard deviation. A mean describes the average recorded exercise duration in a condition. A standard deviation describes how spread out the recorded values are around that average. It is not a confidence interval and does not directly show how precisely the mean has been estimated.

What does a mean difference represent?

A mean difference expresses the difference between the average in one condition and the average in a reference condition. In the recalculated primary comparisons, NIOV powered by room air is the reference. A positive estimate means the mean in the named comparison condition is higher than the room-air mean; a negative estimate means it is lower. These differences are in minutes because the endpoint is exercise duration. The recalculations use the posted summary statistics and are unadjusted.

What is the role of a confidence interval?

General statistical explanation: a confidence interval conveys uncertainty around an estimated quantity under the assumptions of the method used to construct it. It is not a range containing a specified proportion of individual participants’ results. For the primary recalculated comparisons, the intervals describe uncertainty around the unadjusted mean differences. They do not incorporate information that is absent from the posted marginal summaries, such as the within-person correlation among measurements in a crossover study.

How should the p-values be read?

A p-value describes how compatible the observed data are with a specified null model, assuming the analysis model and its assumptions apply. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of an effect. The recalculated p-values are unadjusted. The registry also reports sponsor analyses using ANOVA, with p < 0.05 for three specified comparisons. The registry record does not report the full ANOVA model or its detailed inferential procedure.

General statistical explanation: an analysis of variance can compare means across conditions, but repeated observations require a method that reflects their dependence. In a crossover design, measurements from the same participant are typically related rather than independent. Accounting for that relationship can affect standard errors and tests. The registry’s brief method label alone does not show whether the sponsor’s analysis included participant, period, sequence or other terms.

Why does over-dispersion matter?

General statistical explanation: over-dispersion occurs when variability in the data exceeds what a model assumes. When a model underestimates variability, uncertainty may be understated and tests may appear more decisive than warranted. This trial reports continuous means and standard deviations, so a count-outcome over-dispersion model is not identified as the method for the primary endpoint. The broader lesson is to check whether a model’s variability assumptions fit the outcome and design rather than relying on a test label alone.

Why can the recalculation differ from the sponsor analysis?

The recalculated comparisons are based on posted means, standard deviations and condition-level sample sizes. They do not contain the paired participant-level information needed to reconstruct a crossover contrast, and they do not reproduce an ANOVA model from its name alone. The recalculated estimates and p-values are therefore descriptive checks, not a substitute for the sponsor’s analysis. A discrepancy is recorded for this study, so the sponsor’s own analysis takes precedence.

More generally, a statistical result depends on the estimand, analysis population, model, missing-data handling and multiplicity strategy, as well as the observed measurements. Several of these details are not reported in the registry record. This means that the posted summaries permit a transparent description of condition-level averages and limited unadjusted comparisons, but not a full independent audit of the trial’s inferential analysis.

11. Confidence Intervals and Precision

The primary recalculated comparison of NIOV with oxygen against NIOV with room air is 11.2 minutes, with a 95% confidence interval from 7.647 to 14.75. The interval lies above zero, indicating that the unadjusted summary-based estimate is positive under the calculation used. For nasal cannula oxygen against room air, the estimate is 5.1 minutes, with a 95% confidence interval from 1.082 to 9.118. For no treatment against room air, the estimate is -0.7 minutes, with a 95% confidence interval from -2.987 to 1.587; this interval includes zero.

General statistical explanation: an interval that includes zero is compatible, under the stated calculation, with a zero mean difference as well as with differences on either side of zero. An interval that does not include zero is not proof that the estimate is free from bias, nor does it address model misspecification, selective reporting or multiplicity. Interval width is one way to assess precision: narrower intervals indicate less sampling uncertainty under the same analysis assumptions.

The recalculated intervals use posted summary statistics and do not recover the within-participant dependence in this crossover study. Consequently, their apparent precision may not reflect the precision of the sponsor’s crossover analysis. The sponsor’s analyses report thresholded p-values rather than numerical confidence intervals in the registry record. Numerical sponsor confidence intervals are not reported in the registry record.

The outcome standard deviations also show that exercise duration varied within conditions. Such variability is distinct from uncertainty in the estimated mean difference. The small pilot population, per-protocol analysis and incomplete reporting of the crossover model limit the confidence that can be placed in the recalculated precision. These intervals should be read as conditional on the simplified recalculation, not as definitive precision estimates for the sponsor’s full analysis.

12. Planning a Similar Trial: Sample Size

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

The sample-size figures are planning illustrations based on the observed effects, not the original trial’s design assumptions. They are stated as participants per arm for each target power level, not as total events. The planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect defined as the stated fraction of the observed effect. The original trial’s own sample-size rationale is 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 the planning assumptions, if that effect and those assumptions were correct. The 90% power column uses a higher target chance of detecting the same specified effect, so it generally calls for more participants per arm. These are hypothetical design calculations; they are not observed power for this completed pilot study.

Each row scales the effect being planned for relative to the observed estimate. Planning for 100% of the observed effect uses the full observed estimate; planning for 75% or 50% uses a smaller target effect. Smaller effects are harder to distinguish from random variation, so they need more participants per arm to reach the same target power. This is why the figures increase as the planned effect becomes smaller.

The illustrations are based on simple two-arm assumptions. They do not account for crossover features such as repeated measurements within participants, nor do they establish what sample size would be appropriate under a fully specified crossover analysis. They are useful for showing how assumed effect size and target power relate to planning requirements, but should not be treated as a reconstruction of the study’s design process.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 11.200; pooled standard deviation σ = 4.965.
2. n = 2 × (1.96 + 0.842)² × 4.965² / 11.200² = 3.1, rounded up to 4 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- 11.2                      # observed difference in means
sigma <- 4.96487663492256                     # 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(1372462)
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 = 4 (80% power), 5 (90% power)
 75% of observed effect: n per arm = 6 (80% power), 8 (90% power)
 50% of observed effect: n per arm = 13 (80% power), 17 (90% power)
power.t.test: 4.3 
Simulated power at n = 4 per arm: 0.759 (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 reports sponsor analyses using ANOVA for NIOV with oxygen compared with nasal cannula oxygen, NIOV with room air and no treatment. Each reported comparison has p < 0.05. The record does not include numerical sponsor estimates or confidence intervals for these comparisons, nor does it provide the full ANOVA specification.

The posted-summary recalculations use condition-level means and standard deviations, with NIOV powered by room air as the reference. For comparisons with NIOV with oxygen and nasal cannula oxygen, these simple recalculations produce positive mean differences and intervals that do not include zero. For no treatment against room air, the recalculated estimate is -0.7 minutes, its interval includes zero, and its p-value is 0.549. This differs from the sponsor’s reported p < 0.05 for NIOV with oxygen versus no treatment.

The recalculation cannot recover the participant-level pairing or reproduce the reported ANOVA from the summary values alone. It also does not establish whether the sponsor’s model addressed study day, sequence or other crossover features. Since the registry record flags a discrepancy, the sponsor’s own analysis takes precedence. The recalculated results are best understood as a limited, unadjusted check, not a competing definitive analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary endpoint and two secondary outcomes, and the posted results include several conditions and selected pairwise analyses. The record does not report a prespecified multiplicity strategy, such as an adjustment across endpoints or comparisons, or a testing hierarchy that would determine which results are confirmatory. Without that information, the extent to which reported p-values account for multiple opportunities to find a statistically notable result is not reported in the registry record.

General statistical explanation: when many hypotheses are tested, the chance of at least one false-positive finding can increase if each test is interpreted at the same threshold without adjustment. Multiplicity does not make every result invalid, but it affects how strongly isolated p-values can support confirmatory claims. This is a particular consideration for secondary outcomes and for comparisons selected from several study conditions.

The registry identifies the primary analysis population as per protocol. It does not report whether an intention-to-treat analysis was also performed, how many participants were excluded from the per-protocol analysis, or the reasons for any exclusions. Condition-level entries show 15 for each arm, but the registry record does not explain missing observations, incomplete tests or whether every participant contributed data to every condition and endpoint.

The approach to missing data is not reported in the registry record. There is no reported description of imputation, sensitivity analyses, or assumptions about data missingness. The crossover schedule also means that missing measurements could affect within-person comparisons differently from condition-level summaries, but the record does not describe how that possibility was addressed.

The registry gives ANOVA as the sponsor method for selected comparisons, but the statistical analysis plan, model terms, handling of period or sequence, and model diagnostics are not reported. These omissions limit independent assessment of the inferential results. They also make it difficult to know how the sponsor accounted for repeated measurements and whether reported tests were planned in advance.

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 5% reporting threshold.

The posted adverse-event summaries list zero serious adverse events and zero other adverse events in each condition, with 15 at risk in each listed group. These are condition-level registry figures. In a crossover study, condition-level at-risk entries should not be added to infer a total number of unique participants, because the same participant may contribute to more than one condition.

Deaths are not reported in the registry record. The record also lists no serious adverse-event terms. The zero entries describe what was posted for the reported categories; they do not establish that no events occurred outside the collection or reporting definitions, nor do they show how completely safety events were monitored. The timeframe and detailed safety-collection procedures are not reported in the registry record.

These data are from a small pilot study and should be read as limited descriptive safety reporting. They do not provide a precise estimate of uncommon risks, and they do not establish comparative safety between conditions. No medical conclusion should be drawn from the absence of posted event counts alone.

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

The posted results describe short-term exercise testing under four conditions in stable male subjects with severe-to-very severe COPD. The mean exercise duration was highest in the NIOV-with-oxygen condition. Simple unadjusted recalculations using room-air NIOV as the reference show positive estimated mean differences for NIOV with oxygen and nasal cannula oxygen, while the no-treatment comparison is close to zero and imprecise by that calculation. The registry’s own ANOVA results report p < 0.05 for its listed comparisons, including NIOV with oxygen versus no treatment.

Because the summary-based recalculation conflicts with the sponsor result for the no-treatment comparison, the sponsor’s own analysis takes precedence. The recalculation does not recover the paired crossover information or reproduce the sponsor model. The registry record does not provide enough model detail to independently evaluate the reported ANOVA results fully.

The findings do not establish effects outside the constant work rate exercise tests, or on outcomes that were not measured. They do not demonstrate longer-term impact, everyday functioning or effects in populations not described by this pilot. The secondary measures add context about oxygen saturation and dyspnea at isotime, but the record does not report a multiplicity strategy and those results should be interpreted cautiously.

A statistically notable comparison is not by itself a measure of clinical importance. The study’s size, per-protocol analysis, incomplete details about missing data and limited reporting of the analysis plan all constrain interpretation. The posted values are evidence about the recorded measurements and specified comparisons; they are not a general treatment recommendation or proof of a broader effect. Whether a result is useful for a decision depends on questions and evidence beyond the short-term physiological comparisons reported in this registry record.

18. Why This Trial Matters Statistically

This study illustrates why the design and analysis must be read together. In a crossover study, each participant may contribute measurements under multiple conditions, so the association between those measurements is central to estimating uncertainty. Condition-level means and standard deviations summarize the results but do not retain the within-person covariance. A simple recalculation from those summaries can therefore differ from an analysis that uses the crossover structure.

The record also makes the distinction between a reported analysis and a reanalysis concrete. The sponsor reports ANOVA comparisons with p < 0.05, while the unadjusted summary-based recalculation for NIOV with oxygen versus no treatment yields a different result. Recognizing the discrepancy and giving precedence to the sponsor’s own analysis avoids presenting an incomplete reanalysis as a definitive correction. At the same time, the absence of a detailed model specification limits independent scrutiny.

The pilot setting matters statistically as well. Estimates from a small study can be imprecise and sensitive to individual observations, and observed effects can be optimistic when used as planning inputs. The planning illustrations show how required participants per arm change when the target effect is reduced, but they are not the original study’s justification or observed power.

Finally, the study reports several outcomes and condition comparisons. Without a reported multiplicity strategy, secondary and selected comparison p-values need careful interpretation. Together, the crossover structure, the discrepancy between analyses, and limited reporting of the statistical plan make this a useful example of why effect estimates, uncertainty, analysis population and design details should be considered alongside thresholded p-values.

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 are specific to this trial’s posted record. It is a pilot study in 15 stable male subjects with severe-to-very severe COPD. The small, narrowly described population limits how broadly the findings can be applied. The primary endpoint is a short-term exercise-test measure, and the registry does not report outcomes that would establish longer-term effects or performance in daily life.

The crossover design creates analytical requirements that cannot be met using condition-level means and standard deviations alone. The registry record does not give the full randomization sequence, washout details, period effects or participant-level data. Although the sponsor reports ANOVA, the model specification is not reported. The recalculated contrasts are therefore not a full independent reconstruction of the design.

The analysis population is described as per protocol, but exclusions, adherence rules and the relationship between the enrolled population and the analyzed observations are not described. Missing-data handling is not reported. The registry’s condition-level sample sizes do not explain whether all measurements were available for all conditions and outcomes.

The record does not report the original sample-size justification, an analysis plan, multiplicity procedures, or numerical sponsor confidence intervals. A discrepancy is flagged between the sponsor’s reported analysis and the simple recalculation for one primary comparison; the sponsor’s analysis takes precedence. Secondary results are also subject to uncertainty from multiple outcomes and selected comparisons. Safety summaries show zero events in the listed categories, but deaths are not reported and the safety ascertainment details are unavailable. These reporting limits should be considered alongside the numerical results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effects of the Breathe Technologies Ventilation System in Subjects With Chronic Obstructive Pulmonary Disease — NCT01372462.
• Registry record last updated 2016-10-12; status last verified 2016-08.
• Results first posted 2016-10-12.
• 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

The registry record describes a completed randomized, double-masked crossover pilot study of NIOV conditions, nasal cannula oxygen and no treatment during constant work rate exercise in stable male subjects with severe-to-very severe COPD. The primary outcome was exercise duration, with secondary outcomes of oxygen saturation and Borg dyspnea score at isotime.

The posted primary means are highest for NIOV powered by oxygen. Sponsor-reported ANOVA comparisons list p < 0.05 for selected contrasts. Simple unadjusted recalculations from the posted summaries differ from the sponsor result for NIOV with oxygen versus no treatment; the sponsor’s own analysis takes precedence. The registry record does not report sufficient detail to reproduce the crossover analysis, assess missing-data handling or determine a multiplicity strategy.

Safety entries show zero serious and other adverse events in the listed conditions; deaths are not reported in the registry record. The findings are limited to the short-term test setting and the population described.