Smartphone App-guided Inspiratory Muscle Strength Training for Lowering Systolic Blood Pressure: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Smartphone App-guided Inspiratory Muscle Strength Training for Lowering Systolic Blood Pressure (NCT06229873), a randomized na study. The primary outcome is Change From Baseline in Casual Systolic Blood Pressure.

2. Clinical Question

This is a comparison of two active training approaches; it is not a comparison with no training or usual care. Consequently, the between-group estimate addresses the relative outcomes of app and researcher guidance under the trial’s stated training schedule. It does not by itself identify the effect of IMST compared with receiving no IMST.

3. Trial Design

The record describes a randomized, double-masked, parallel-group trial of app-based and clinic-based inspiratory muscle strength training. The listed enrollment is 33. The arm-level primary outcome summaries include 17 participants in the app-guided group and 15 in the clinic-guided group. These outcome denominators do not add up to the listed enrollment, and the registry record does not explain the difference or report the reasons for any missing outcome data.

Both groups were described as using a handheld device for 30 breaths a day, six days a week, for six weeks. The app group received guidance through a smartphone application, while researchers guided the clinic group. The brief summary describes the training as 5 minutes a day, six days a week, for six weeks. The record does not explain how the duration description relates to the breaths-per-day description.

The trial status is completed. The recorded start date is 2024-06-27 and the primary completion date is 2025-12-31. The phase is listed as NA. The registry identifies the University of Colorado, Boulder as sponsor. Randomization is recorded, but the registry record does not report the sequence-generation procedure or allocation concealment. Although masking is recorded as double, the record does not identify which groups of people were masked or explain how masking was maintained.

A parallel design assigns participants to one of the trial groups and compares outcomes between groups. Random assignment can support a causal interpretation when the allocation process is implemented appropriately and the analysis preserves that comparison. The available record does not describe the full conduct of the trial, its analysis population, or the analysis plan, so these aspects cannot be assessed from the registry results alone.

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: 18 participants were assigned to the App-based group, and 15 participants were assigned to the Clinic-based group. Once enrolled, no participants were excluded from the study before assignment to a group.

Overall Study

Reasons for not completing this period:

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 Change From Baseline in Casual Systolic Blood Pressure, measured over 6 weeks.

The primary endpoint is change from baseline in casual systolic blood pressure measured at rest in the clinic setting, with the change assessed at 6 weeks and expressed in mmHg. The record reports each group’s mean change and standard deviation, alongside a between-group mean difference and an interval estimate.

Blood pressure is a continuous measure: a value can take a range of numeric measurements rather than being classified only as an event or no event. Mean change summarizes the average direction and amount of change within a group, while the between-group contrast addresses whether the average changes differ between the two training approaches. The sign of a change is meaningful: a negative value denotes a decrease from baseline in the reported measure, while zero denotes no average change.

In general, measuring change from baseline is one way to describe how an outcome differs over follow-up relative to its starting value. A clinic measurement at rest makes the endpoint specific to that measurement context; it should not be treated as a measure of every blood-pressure setting or time point. The registry record does not report the exact measurement procedures, the number of readings, or a clinical threshold for interpreting a difference. The endpoint therefore supports a statistical comparison of the reported group averages, but the record alone does not establish how a particular difference should be judged in clinical practice.

7. Results Posted in the Registry

• Clinic-Based Inspiratory Muscle Strength Training: mean 0.00 versus -2.00 on control; difference 2.00 (95% CI -3.20 to 7.20), standardized effect d = 0.26; z-test p = 0.451.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Change From Baseline in Endothelial Function

• 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:
  • Clinic-Based Inspiratory Muscle Strength Training: mean -0.70 versus -0.50 on control; difference -0.20 (95% CI -1.28 to 0.88), standardized effect d = -0.13; z-test p = 0.716.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Clinic-Based Inspiratory Muscle Strength Training and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Maximum Inspiratory Pressure

• 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:
  • Clinic-Based Inspiratory Muscle Strength Training: mean 28.00 versus 23.00 on control; difference 5.00 (95% CI -17.05 to 27.05), standardized effect d = 0.16; z-test p = 0.657.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Clinic-Based Inspiratory Muscle Strength Training and the control. The interval gives the range of effects that remain compatible with the data.

Difference in Adherence to Inspiratory Muscle Strength Training

• 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:
  • Clinic-Based Inspiratory Muscle Strength Training: mean 100.00 versus 97.00 on control; difference 3.00 (95% CI -2.77 to 8.77), standardized effect d = 0.37; z-test p = 0.308.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Clinic-Based Inspiratory Muscle Strength Training and the control. The interval gives the range of effects that remain compatible with the data.

The three secondary outcomes cover vascular function, inspiratory muscle performance, and adherence. Across these measures, the recalculated point estimates show differences of varying direction, while the reported confidence intervals include zero for each comparison. The associated unadjusted p-values also do not provide strong evidence of a between-group difference. Taken together, the secondary results do not present a clear, consistent pattern of separation between app-guided and clinic-guided training.

These outcomes can add context to the primary blood-pressure comparison because they address related aspects of vascular function, the trained muscle measure, and participation in the training schedule. However, they are not interchangeable with the primary endpoint. A change in a secondary measure does not establish a corresponding change in casual systolic blood pressure, and a lack of a clear secondary contrast does not resolve the uncertainty in the primary comparison.

The registry record lists the secondary outcomes but reports no analyses for them. The between-group comparisons are unadjusted recalculations from the arm summaries. There is no reported multiplicity procedure or prespecified hierarchy for interpreting the secondary outcomes. In general, when several outcomes are examined, the chance of finding an apparently notable result by chance can increase unless the analysis accounts for the number and structure of the comparisons. This is why unadjusted secondary results generally carry less confirmatory weight than a prespecified primary result.

The secondary outcomes are therefore most appropriately read as descriptive evidence about the range of measurements collected, rather than as independent proof for or against the primary finding. Their estimates and uncertainty may inform future research questions, but the registry record does not establish which secondary analyses were planned, how they were selected, or whether any adjustment was intended. No additional conclusion should be drawn from their combined pattern beyond the fact that the posted summaries do not show a precise, consistent between-group difference.

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

• Change From Baseline in Endothelial Function
• Change From Baseline in Maximum Inspiratory Pressure
• Difference in Adherence to Inspiratory Muscle Strength Training

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports continuous outcomes as group means with standard deviations. A mean is the arithmetic average of observed values, and a standard deviation describes how spread out individual values are around that average. These summaries answer different questions: the mean describes the group’s central level of change, while the standard deviation describes variation among participants. A standard deviation is not itself a confidence interval for the group mean or for the between-group difference.

What does the mean difference represent?

The primary comparison is expressed as clinic-based minus app-based. The reported estimate of 2.0 mmHg is formed from the clinic-group mean change of 0.0 mmHg and the app-group mean change of -2.0 mmHg. This direction matters when reading the sign: a positive estimate indicates a greater mean change in the clinic group under this subtraction convention. It does not mean that the clinic group had a higher blood pressure at every measurement, because the endpoint is change from baseline and the result is a group average.

In general, a between-group mean difference summarizes the average separation between two groups on a continuous outcome. It does not describe the outcome of every participant, and it can conceal variation within each group. For this comparison, the registry record gives an unadjusted estimate rather than a reported adjusted model result. No covariate-adjusted analysis is listed.

How should the confidence interval be read?

A confidence interval gives a range of estimates compatible with the observed data under the assumptions of the interval procedure. For the primary mean difference, the interval runs from -3.197 to 7.197 mmHg. Because zero lies within this range, the interval does not exclude no average difference between the groups. It also spans negative and positive values, so the data do not determine which group had the more favorable mean change with high precision.

In general, an interval’s width reflects the precision of an estimate: narrower intervals indicate less uncertainty, and wider intervals indicate more uncertainty. The interval is not a list of values that each have a separately established probability of being the true effect. It also does not account for uncertainty arising from unreported design or analysis choices, such as missing-data handling or selection among multiple outcomes.

What does the p-value add?

The unadjusted p-value for the primary comparison is 0.451. In general, a p-value measures how unusual the observed data, or data more extreme, would be under a specified null hypothesis and the assumptions of the statistical procedure. It is not the probability that the null hypothesis is true, and it does not measure the clinical importance of the observed estimate. A p-value alone also does not show the range of effects compatible with the data; that is why the estimate and confidence interval should be read together.

The registry record does not list a sponsor-reported inferential analysis for the primary outcome. The displayed primary contrast and interval are unadjusted recalculations from the arm-level summaries. The record indicates no discrepancy between the recalculation and a sponsor analysis; it does not report a sponsor analysis to compare against. Accordingly, these calculations should be understood as summary-statistic comparisons, not as a complete reconstruction of an unreported analysis plan.

Why does variation matter?

In general, greater variability among participants makes a group mean less precisely estimated when the sample size is held constant. The primary outcome standard deviations of 8.0 and 7.0 mmHg are larger than the absolute group mean changes, and the arm samples are limited. The consequence visible in the comparison is an interval that covers both sides of zero. This does not establish that the true difference is zero; it indicates that the observed data leave uncertainty about the difference.

The registry does not report whether the primary comparison was based on a particular model, whether assumptions were checked, or whether any adjustment was planned. For continuous outcomes, common analytic choices can include comparisons of means with or without adjustment for baseline measurements, but the choice used in the trial’s own analysis is not reported in the registry record. These are general possibilities, not claims about the trial’s protocol.

What is not established by the calculations?

The recalculated contrast uses the reported group means and standard deviations and is unadjusted. It does not account for unknown participant-level data, alternative analysis populations, missing outcomes, or any covariates that might have been included in an original model. The registry record reports zero analyses and does not provide analysis methods for the outcome. As a result, the posted summary statistics support a transparent descriptive comparison, while leaving the original statistical plan and any trial-level inferential analysis not reported in the registry record.

These distinctions are important because a numerical estimate can be calculated from summary data even when the original analysis is unavailable. The calculation should not be mistaken for evidence that the trial used the same method, or that all assumptions of a model can be checked. The appropriate reading is to consider the group summaries, the unadjusted estimate, its uncertainty, and the limits of the record together.

11. Confidence Intervals and Precision

The primary between-group estimate is 2.0 mmHg, with a confidence interval from -3.197 to 7.197 mmHg. The estimate is a single summary of the observed contrast, but the interval communicates that the data are also compatible with a range of other contrasts. Since zero is inside the interval, the posted primary summary does not exclude no average difference. Since the interval extends in both directions, it also does not settle the direction of the difference.

In general, precision is about how tightly the data locate an estimate, not whether the estimate is important. A confidence interval can be statistically compatible with zero while still including nonzero values that might matter. Whether any value is clinically important depends on a justified threshold and the clinical context. The registry record does not report such a threshold, so the interval cannot be divided into clinically meaningful and unimportant ranges on the basis of the record alone.

The arm-level sample sizes contributing to the primary summaries are 17 and 15, with standard deviations of 8.0 and 7.0 mmHg. Those summaries and the interval indicate that uncertainty remains around the estimated contrast. A point estimate close to zero should not be interpreted as proof of equivalence: an equivalence conclusion would require a prespecified margin and an analysis designed to assess it, neither of which is reported in the registry record.

The interval is an unadjusted recalculation from the posted summary statistics. It reflects sampling uncertainty under the calculation’s assumptions, but it cannot account for unreported design features, departures from the analysis assumptions, or unknown effects of missing data. It is most informative when read alongside the group means and the outcome context, rather than as a definitive statement about all possible effects.

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 a total across both arms and not total events. The calculations use the observed effect as a reference and show illustrations for detecting the full observed effect, 75% of the observed effect, and 50% of the observed effect. For the primary outcome, the display gives 224 participants per arm for 80% power and 300 participants per arm for 90% power when planning for 100% of the observed effect. The other rows illustrate the greater participant counts associated with planning for smaller fractions 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 effect to detect is the specified fraction of the observed effect. The registry record does not report the assumptions or justification used for the trial’s original design, so these planning figures should not be read as its original target or protocol calculation.

In plain terms, the 80% power column gives the illustrated participants per arm for a design with an 80% chance of detecting the specified effect under the listed assumptions, if that effect is the true effect and the assumptions hold. The 90% column gives the corresponding illustration for a higher chance of detection. Smaller effects are harder to distinguish from random variation and therefore require more participants under the same assumptions.

These figures are planning illustrations based on the observed effect, not observed power. They do not indicate the probability that the trial’s result is true, and they do not repair the uncertainty in the completed trial’s estimate. Because planning from an observed effect can be sensitive to the estimate in a small trial, the figures are best treated as conditional illustrations rather than as a definitive sample-size recommendation.

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 = 2.000; pooled standard deviation σ = 7.550.
2. n = 2 × (1.96 + 0.842)² × 7.550² / 2.000² = 223.7, rounded up to 224 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 <- 2                      # observed difference in means
sigma <- 7.54983443527075                     # 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(6229873)
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 = 224 (80% power), 300 (90% power)
 75% of observed effect: n per arm = 398 (80% power), 533 (90% power)
 50% of observed effect: n per arm = 895 (80% power), 1,198 (90% power)
power.t.test: 224.7 
Simulated power at n = 224 per arm: 0.794 (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 identifies one primary endpoint and three secondary outcomes. It does not report a multiplicity adjustment, a testing hierarchy, or a plan specifying how results across outcomes would be interpreted together. The registry record also lists zero analyses. It is therefore not possible to determine whether the trial’s original statistical plan controlled the chance of false-positive findings across multiple endpoints or whether the secondary outcomes were intended to be confirmatory or exploratory.

In general, multiplicity arises when investigators make several statistical comparisons or test several outcomes. If each is judged separately without accounting for the total set, the chance of at least one apparently positive result can increase. Methods for addressing this depend on the study objectives and the planned relationships among outcomes. No particular method should be attributed to this trial because one is not reported in the registry record. The unadjusted secondary p-values should consequently be interpreted cautiously and should not be treated as a set of independent confirmations.

The outcome summaries also do not explain whether every randomized participant was included in each analysis. The arm-level primary summaries include 17 and 15 participants, while the record lists overall enrollment as 33. Secondary outcome denominators vary by measure. The reasons for these differences, the extent of missing data, and any imputation or other missing-data procedures are not reported in the registry record. Missingness can affect both precision and the interpretation of a group comparison, particularly if the probability of having an observed outcome is related to the outcome itself or to group assignment.

The analysis populations are likewise not described. The record does not state whether the primary analysis followed an intention-to-treat approach, used a per-protocol population, or applied another definition. It also does not report how participants who did not complete training or follow-up were handled. These are not details that can be inferred from randomized allocation or from the arm summaries. Without this information, readers cannot assess how closely the reported outcome sample represents all randomized participants or whether the analysis followed the planned assignment groups.

15. 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 5% reporting threshold.

Most frequent non-serious adverse event terms

The adverse-event summaries report no serious adverse events in either group and no deaths. The number at risk for serious adverse events was 17 in the app-guided group and 15 in the clinic-guided group. The record separately reports other adverse events for 2 participants in the app-guided group and 7 participants in the clinic-guided group, among 17 and 15 at risk, respectively.

These figures are counts from the registry record, not a comparison adjusted for follow-up time, event severity beyond the serious-versus-other classification, or participants’ baseline characteristics. The record does not provide the types of other adverse events, their timing, their relationship to training, or an analysis comparing the groups. The absence of recorded serious events in this sample does not establish that serious events cannot occur; it describes what was recorded among the participants at risk in this trial.

In general, adverse-event counts are most informative when read with the number of participants followed, the duration and completeness of follow-up, and the event definitions. The registry gives the at-risk counts but does not report further detail about safety monitoring or ascertainment. The figures therefore provide a limited descriptive account and should not be interpreted as a definitive comparative safety assessment.

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

The result describes a randomized comparison of two ways of guiding the same stated IMST schedule. At 6 weeks, the observed mean change in casual systolic blood pressure was -2.0 mmHg with app guidance and 0.0 mmHg with researcher guidance. The estimated clinic-minus-app difference was 2.0 mmHg, with a confidence interval from -3.197 to 7.197 mmHg. This interval includes zero and values on either side of zero, so the estimate remains compatible with more than one direction and size of average difference.

The result does not establish that the approaches are equivalent. An equivalence conclusion requires a prespecified margin defining differences small enough to count as equivalent, plus an analysis designed around that margin. The registry record does not report such a margin or an equivalence analysis. Similarly, the result does not establish that the approaches have no difference simply because the interval includes zero or because the unadjusted p-value is 0.451.

Nor does the comparison answer whether IMST itself changes blood pressure compared with no training. Both groups received IMST, with the distinction being app versus researcher guidance and setting. The within-group averages describe observed change over time, but without an untreated comparison they cannot separate training effects from other changes over the same period.

The result is also not a conclusion about every participant or every blood-pressure context. It concerns an average change in casual systolic blood pressure measured at rest in a clinic setting at the stated follow-up. The registry does not report a clinically important difference threshold, detailed measurement procedures, or participant-level results. Thus the precision and practical importance of the estimated contrast cannot be fully judged from the registry summaries alone.

The most supportable reading is limited: the posted summaries show a modest estimated separation in group means, but considerable uncertainty around the between-group contrast. They do not provide a precise determination of the relative effects of the two delivery approaches, nor do they establish clinical benefit, harm, or equivalence.

17. Why This Trial Matters Statistically

This trial addresses a statistical question that is distinct from whether a training program can change an outcome: can app-based guidance produce a different result from guidance by researchers when the stated training schedule is otherwise similar? A randomized comparison of active approaches can be useful for evaluating delivery models, but it requires careful interpretation because there is no no-training group to estimate the effect of IMST itself.

The registry results are a useful example of why a point estimate should not be read in isolation. The mean difference is 2.0 mmHg, but the confidence interval extends from -3.197 to 7.197 mmHg. The interval communicates uncertainty about both the size and direction of the difference more directly than a binary reading of the p-value. The outcome summaries also illustrate how participant-level variation and modest group sizes can leave a broad range of effects compatible with the observed data.

The record additionally highlights the distinction between a completed trial and a fully documented statistical analysis. It lists randomized allocation, masking, outcomes, and group summaries, but does not report the analysis plan, analysis populations, missing-data methods, or multiplicity approach. Those omissions limit the ability to assess how the displayed summaries relate to the trial’s intended primary analysis.

Finally, the planning illustrations show how sample-size requirements depend on the effect a future study aims to detect. They are conditional calculations based on the observed effect and stated assumptions, rather than a report of the original design rationale. Separating this kind of planning information from evidence about the completed trial helps prevent sample-size calculations from being mistaken for a measure of the trial’s evidential strength.

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 is the uncertainty in the primary between-group estimate. The confidence interval spans zero and extends in both directions, so the registry summary does not precisely establish the direction or magnitude of the difference. The arm-level primary outcome counts are 17 and 15, and the record does not explain why those counts differ from the listed enrollment of 33.

Further limitations arise from incomplete reporting. The record does not describe missing outcomes, reasons for missingness, adherence to the planned analysis population, or the handling of participants with incomplete follow-up. It does not specify who was masked, how masking was maintained, how randomization was implemented, or whether allocation was concealed. The original statistical analysis plan and sample-size justification are not reported in the registry record.

The intervention descriptions state both 30 breaths a day and 5 minutes a day, each on six days a week for six weeks, without explaining how these descriptions correspond. The record also does not provide detailed measurement procedures for casual systolic blood pressure, the clinically important difference threshold, or the timing and number of measurements used to define the outcome.

The comparator is another active IMST approach, so the study does not estimate IMST versus no training. The secondary outcomes have no reported analyses, and the registry does not state whether multiplicity was addressed. Safety reporting is descriptive and does not include event types or further detail about ascertainment. These limits constrain interpretation of both the primary contrast and the broader pattern of outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Smartphone App-guided Inspiratory Muscle Strength Training for Lowering Systolic Blood Pressure — NCT06229873.
• Registry record last updated 2026-05-19; status last verified 2026-04.
• Results first posted 2026-05-19.
• 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 a completed randomized, double-masked, parallel-group trial sponsored by the University of Colorado, Boulder. It compares smartphone app-guided with researcher-guided inspiratory muscle strength training in adults 18 years and older with elevated blood pressure. Listed enrollment is 33, and the recorded dates are 2024-06-27 for trial start and 2025-12-31 for primary completion.

The primary outcome is change from baseline in casual systolic blood pressure at rest in the clinic setting at 6 weeks. The reported group means were -2.0 mmHg for app guidance and 0.0 mmHg for clinic guidance. The unadjusted recalculated mean difference was 2.0 mmHg, with a confidence interval from -3.197 to 7.197 mmHg and an unadjusted p-value of 0.451.

The record lists three secondary outcomes and adverse-event summaries, but no reported analyses. Important details—including the original analysis plan, missing-data handling, analysis populations, and multiplicity approach—are not reported in the registry record.