Stroke Telemedicine Outpatient Prevention Program for Blood Pressure Reduction: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Stroke Telemedicine Outpatient Prevention Program for Blood Pressure Reduction (NCT03923790), a randomized na study. The primary outcome is Daytime Ambulatory Systolic Blood Pressure.

2. Clinical Question

The clinical question is about a continuous blood-pressure measure, not a count of clinical events. The primary outcome was assessed using an ambulatory blood-pressure monitor and reported in millimeters of mercury (mmHg). The registry describes STOP as a pilot intended to compare post-stroke blood-pressure treatment approaches, assess implementation feasibility, and use pilot measures and outcomes to examine knowledge gaps.

The intervention description includes an educational packet, a discharge nurse navigator call, planned telehealth visits, educational messages, and a Bluetooth-enabled blood-pressure monitor with periodic data transmission. The STOP arm description also reports pharmacist evaluation before discharge. The two arms therefore share some elements: both descriptions include pharmacist evaluation, navigator contact, and an educational packet. Their recorded care descriptions are not identical, but the registry record does not define a single contrast limited to any one component.

The primary question is answered descriptively by the recorded arm means and by an unadjusted recalculation of their difference and interval. The registry record does not report a sponsor analysis for this outcome. The posted summaries can indicate the direction and precision of the observed contrast, but they do not by themselves establish why the groups differed or whether any particular component of the program was responsible.

3. Trial Design

STOP was a randomized, parallel-group pilot trial with single masking. The identity of the masked party is not reported in the registry record. The trial is listed as completed, with phase recorded as NA. The registry reports enrollment of 83 and identifies The University of Texas Health Science Center, Houston as sponsor.

The STOP Model was the intervention arm, and Usual Care was the comparator. The STOP description includes a pharmacist evaluation before discharge, a nurse navigator contact 72 hours after discharge, an educational packet, a Bluetooth-enabled blood-pressure monitor with an iPad, and a video telehealth visit 7 days after discharge attended by a nurse practitioner or physician. The listed interventions also specify telehealth visits at 1 month, 3 months, and 5 months after discharge; educational messages every other week; and periodic transmission of blood-pressure data from the monitor. The registry's arm description ends during its account of the telehealth visit, so additional detail beyond the recorded description is not reported in the registry record.

Usual Care included a pharmacist evaluation before discharge, a nurse navigator contact 72 hours after discharge, and an educational packet. The record does not provide further detail about usual-care procedures. Both arms therefore included some discharge-related contact and education, while the STOP arm description includes additional monitoring and telehealth elements.

The registry lists the trial start as 2019-03-04 and primary completion as 2021-10-14. The primary endpoint was mean daytime ambulatory systolic blood pressure at 6 months after enrollment. The outcome record says data were not collected for 16.0 participants in the STOP Model arm and 25.0 in Usual Care; the reported outcome summaries have 26.0 and 16.0 participants, respectively. The registry record does not report the original sample-size justification, the identity of the masked party, or a detailed statistical analysis plan.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Data for this outcome measure were not collected for 16 in the STOP Model arm and 25 in the Usual Care arm.

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 Daytime Ambulatory Systolic Blood Pressure, measured over 6 months after enrollment.

The primary endpoint was daytime ambulatory systolic blood pressure, measured in millimeters of mercury (mmHg) at 6 months after enrollment. The registry says blood pressure was assessed with an ambulatory blood-pressure monitor. Unlike a single reading taken at a clinic visit, ambulatory measurement is intended to capture blood pressure during a specified period of ordinary daytime activity. This makes it a continuous physiological measure that can be summarized by a group mean and standard deviation.

The endpoint is relevant to the trial's stated aim of comparing approaches to post-stroke blood-pressure care in people at risk for uncontrolled blood pressure. The registry's stated rationale also refers to general and stroke-related factors associated with racial disparities in blood-pressure control. The posted primary outcome is a measure of blood pressure itself; it is not a direct measure of recurrent stroke, other vascular events, patient experience, or implementation feasibility.

The recorded outcome uses a mean for each arm, with standard deviations describing variability among the observed measurements. The primary outcome record reports that data were not collected for 16.0 participants in the STOP Model arm and 25.0 participants in Usual Care. The analysis population represented in the posted outcome summaries is therefore not the full enrolled cohort as described by the enrollment field. How the missing outcome measurements were handled in any formal analysis is not reported in the registry record.

7. Results Posted in the Registry

• STOP Model: mean 123.60 versus 128.30 on control; difference -4.70 (95% CI -16.29 to 6.89), standardized effect d = -0.26; z-test p = 0.427.

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.

Daytime Ambulatory Diastolic Blood 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:
  • STOP Model: mean 75.10 versus 76.50 on control; difference -1.40 (95% CI -9.06 to 6.26), standardized effect d = -0.12; z-test p = 0.720.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between STOP Model and the control. The interval gives the range of effects that remain compatible with the data.

Night Time Ambulatory Systolic Blood 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:
  • STOP Model: mean 117.30 versus 119.30 on control; difference -2.00 (95% CI -14.53 to 10.53), standardized effect d = -0.12; z-test p = 0.754.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between STOP Model and the control. The interval gives the range of effects that remain compatible with the data.

Nighttime Diastolic Blood 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:
  • STOP Model: mean 69.40 versus 68.00 on control; difference 1.40 (95% CI -7.07 to 9.87), standardized effect d = 0.13; z-test p = 0.746.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between STOP Model and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary blood-pressure summaries follow a mixed directional pattern. The recalculated daytime diastolic and nighttime systolic mean differences favor a lower observed mean in STOP Model, while the nighttime diastolic difference is in the other direction. The uncertainty intervals for these comparisons are broad and include zero. Overall, the secondary blood-pressure findings do not present a consistently precise pattern across day and night measurements.

This pattern is compatible with the primary result in an important statistical sense: the primary and secondary comparisons all have substantial uncertainty, and none of these summary-based contrasts gives a sharply determined group difference. The secondary endpoints add context about related blood-pressure measures, but they do not independently confirm the primary estimate. They are also measured in subsets with different outcome counts, so their precision and available information differ across outcomes.

The registry lists additional secondary outcomes involving body mass index, recurrent vascular events, and acute healthcare utilization. Detailed numerical results for those outcomes are not reported in the registry record. The available record therefore does not support an overall quantitative assessment of every listed secondary outcome.

Unadjusted secondary comparisons carry less weight than a prespecified primary analysis because several outcomes may be examined, increasing the chance of apparently notable findings arising by chance. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes. These results are best treated as exploratory descriptions rather than as separate confirmatory evidence. The pilot's stated purpose included examining knowledge gaps, which is consistent with viewing secondary measures as informative for future research questions rather than definitive tests.

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

• Daytime Ambulatory Diastolic Blood Pressure
• Night Time Ambulatory Systolic Blood Pressure
• Nighttime Diastolic Blood Pressure
• Body Mass Index(BMI)
• Number of Participants With Recurrent Vascular Events (Stroke, Myocardial Infarction, Acute Cardiac Death)
• Number of Participants With Acute Healthcare Utilization

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, so the registry reports a mean and standard deviation for each arm. A mean locates the center of the observed measurements. A standard deviation describes how spread out measurements are around that mean; it is not the uncertainty interval for the mean or the group difference. The primary summaries are 123.6 mmHg with a standard deviation of 16.7 in STOP Model and 128.3 mmHg with a standard deviation of 19.7 in Usual Care.

What does the mean difference represent?

The recalculated comparison subtracts the Usual Care mean from the STOP Model mean. Its estimate is -4.7 mmHg, so the observed STOP Model mean is lower. The difference retains the endpoint's unit, mmHg, and is expressed on the same scale as the blood-pressure outcome. This simple contrast does not adjust for baseline measurements, participant characteristics, or other covariates. Whether the trial protocol planned an adjusted comparison is not reported in the registry record.

How should the interval be understood?

A confidence interval describes uncertainty around an estimate under the method used to construct it. It is not a range containing every individual participant's measurement, and it is not a guarantee that the true difference lies within the displayed endpoints. For the primary recalculation, the interval runs from -16.29 to 6.892 mmHg. Its span illustrates that the observed data are consistent with a range of differences, rather than pinning down a precise contrast. The interval includes zero, which is the value corresponding to no difference between the means.

What does the p-value add?

The unadjusted recalculated p-value is 0.427. In general, a p-value measures how incompatible the observed result, or a more extreme result, would be with a specified null model if that model and the calculation assumptions held. It is not the probability that the intervention has no effect, nor is it a measure of clinical importance. Here it accompanies a wide interval and a small observed outcome sample. It should be read alongside the estimate and interval rather than as a stand-alone verdict.

What does unadjusted mean in this comparison?

The recalculation uses the posted arm-level means, standard deviations, and outcome sample sizes to compare the groups without covariate adjustment. It is not a reconstruction of an individual-participant analysis. It also does not account for features of the trial or data that cannot be recovered from these summary values, such as baseline outcome values, repeated measurements, stratification, or missing-data procedures. Whether any of those approaches were used in a sponsor analysis is not reported in the registry record.

The posted p-value and interval are recalculated from the summaries rather than reported as a sponsor's analysis. The registry lists no reported analyses for the outcome. The standard interpretation of the recalculated result should therefore remain separate from any potential analysis based on participant-level data or a protocol-defined model.

Why do variation and sample size matter?

When measurements vary substantially within arms, the arm means are estimated less precisely for a given amount of observed data. The standard deviations describe this observed spread, while the standard errors in a comparison quantify the estimated sampling uncertainty of the arm means. In general, larger samples can improve precision, but they do not remove bias arising from missing data, measurement issues, or a mismatch between the analysis and the trial question.

Some statistical methods assume that the sampling distribution of the estimated mean difference is adequately approximated by a normal distribution. That is a general modeling idea, not a claim that the registry used a particular method. The planning illustrations explicitly use a normal approximation. The trial's own analysis method and assumptions are not reported in the registry record.

What is not documented?

The registry record does not report the original sample-size justification, an analysis population definition, the handling of missing primary measurements, or a formal primary analysis. It also lists no reported analyses. The recalculated comparison is consequently a transparent, unadjusted reading of the posted summaries, but it cannot substitute for a prespecified analysis with documented handling of missingness and other design features. The lack of such documentation should be treated as uncertainty about the analysis process, not as evidence that a particular method was or was not used.

11. Confidence Intervals and Precision

The primary recalculated difference is -4.7 mmHg, with an interval from -16.29 to 6.892 mmHg. The estimate points toward a lower observed mean in the STOP Model arm, but the interval is broad and crosses zero. It therefore does not narrowly determine the direction or magnitude of the underlying group difference. The posted result is more informative about the limits of precision than about a single definitive value.

The observed standard deviations, 16.7 mmHg in STOP Model and 19.7 mmHg in Usual Care, describe substantial spread in the measurements. The primary outcome summaries are based on 26.0 and 16.0 participants, respectively, while the record notes that measurements were not collected for 16.0 in STOP Model and 25.0 in Usual Care. A small observed outcome sample can make estimates more sensitive to the measurements of individual participants and can leave broad uncertainty.

Confidence intervals and p-values address sampling uncertainty under their calculation assumptions. They do not account automatically for missing data, measurement error, or bias from differences between participants with and without observed outcomes. The registry record does not state how missing measurements were handled in a formal analysis, so the interval from the summary-based recalculation should not be read as resolving that issue.

The interval is not evidence that the arms are equivalent. An equivalence conclusion would require a prespecified acceptable range for the difference and an analysis designed to test that question. Such a margin and analysis are not reported in the registry record. The uncertainty also means the estimate should not be treated as a precise prediction of the result in a future trial.

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 illustrations express the number of participants per arm for 80% power and the number of participants per arm for 90% power. These are not total events: the outcome is continuous, and the planning values are participants per arm. The illustrations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They use the observed effect as a starting point and consider detecting 100%, 75%, or 50% of that observed effect. The original trial's design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes a planning target in which the assumed study design would have an 80% chance of detecting the specified difference under the planning assumptions, if that difference were the true effect. The 90% power column uses a higher probability target under the same general framework. Neither column describes the probability that the completed pilot detected a real effect. These calculations are planning illustrations based on the observed effect, not observed power.

For the primary endpoint, planning for 100% of the observed effect gives 228 participants per arm for 80% power and 305 participants per arm for 90% power. Planning for 75% of the observed effect gives 405 participants per arm for 80% power and 541 participants per arm for 90% power. Planning for 50% of the observed effect gives 910 participants per arm for 80% power and 1,218 participants per arm for 90% power. The pattern reflects a general feature of power planning: smaller effects are harder to distinguish from random variation and therefore require more participants.

These figures do not establish what a future study should enroll. They depend on the observed effect used as the planning reference, the stated assumptions, and the outcome variability represented in this pilot. If the true effect differs from the observed estimate, or if a future design uses different methods or assumptions, the required sample size would differ. The registry does not report an original design calculation for STOP.

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 = -4.700; pooled standard deviation σ = 17.884.
2. n = 2 × (1.96 + 0.842)² × 17.884² / -4.700² = 227.3, rounded up to 228 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 <- -4.70000000000002                      # observed difference in means
sigma <- 17.8840711248865                     # 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(3923790)
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 = 228 (80% power), 305 (90% power)
 75% of observed effect: n per arm = 405 (80% power), 541 (90% power)
 50% of observed effect: n per arm = 910 (80% power), 1,218 (90% power)
power.t.test: 228.3 
Simulated power at n = 228 per arm: 0.799 (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 lists secondary endpoints that include additional ambulatory blood-pressure measures, body mass index, recurrent vascular events, and acute healthcare utilization. The number of outcome measures is reported as 11, while six secondary outcomes are posted. The registry record does not report a multiplicity adjustment, a testing hierarchy, or a rule for controlling the overall chance of false-positive conclusions across multiple outcomes. Consequently, secondary comparisons should not be interpreted as if each were an isolated confirmatory test.

For the primary endpoint, the registry states that data were not collected for 16.0 participants in STOP Model and 25.0 in Usual Care. The posted summaries include 26.0 and 16.0 participants, respectively. This incomplete outcome collection can affect both precision and the interpretation of the group comparison, especially if the probability of having a measured outcome is related to participant characteristics or blood pressure. The reason that data were not collected is not reported in the registry record.

The record does not state whether missing measurements were imputed, whether complete observed cases were analyzed, or whether a sensitivity analysis was conducted. It also does not define an intention-to-treat, per-protocol, or other analysis population for the primary endpoint. The enrollment field reports 83, but the relationship between enrollment, assigned arms, and the available endpoint measurements is not fully explained in the outcome record.

No reported analyses are listed. The registry therefore does not document the statistical model used for a sponsor analysis, any adjustment for baseline values, the handling of repeated measures, or prespecified covariates. These absences do not show that no such procedures were used outside the posted record; they mean that the analysis details are not reported in the registry record. The unadjusted recalculations should be interpreted with this limitation in mind.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hospitalization (11.8%), hospitalization due to injury from fall (3.7%), death (3.7%).

The adverse-event record lists serious events among 4 of 27 participants at risk in STOP Model and 2 of 17 at risk in Usual Care. For other, non-serious adverse events, it lists 1 of 27 at risk in STOP Model and 2 of 17 at risk in Usual Care. The death counts are 1 in STOP Model and 0 in Usual Care. These are the recorded counts and denominators; they do not establish that an event was caused by the intervention.

The listed serious-event terms include Hospitalization at 11.8%, Hospitalization due to injury from fall at 3.7%, and Death at 3.7%. These term-level percentages should be read as registry-reported adverse-event information, not as a comparison of causal risk between arms. The record does not provide enough detail to determine whether event categories overlap or how the listed term percentages relate to arm-specific denominators.

With a pilot trial and limited event counts, apparent differences in counts can be unstable. Safety interpretation also depends on event definitions, ascertainment, timing, and attribution, which are not fully described in the posted record. The figures are a descriptive account of reported events, not proof of safety or harm.

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

The posted primary summaries show a lower mean daytime ambulatory systolic blood pressure in STOP Model than in Usual Care at the recorded follow-up. The unadjusted recalculated contrast is -4.7 mmHg, but its interval ranges from -16.29 to 6.892 mmHg. This combination of a point estimate and a broad interval means the observed direction is not estimated precisely. The data do not establish a dependable difference in either direction.

A p-value of 0.427 does not show that the treatments are equivalent, and it does not mean there is a 42.7% chance that the null hypothesis is true. It reflects the compatibility of the observed contrast with a null model under the assumptions of the recalculation. A conclusion of no meaningful difference would require an explicit definition of what differences are acceptably small and an analysis designed to evaluate that criterion. The registry record does not report such a framework.

These results also do not show that STOP caused the observed difference. Randomization supports a comparative trial design, but interpretation still depends on complete outcome ascertainment, appropriate analysis, and the limitations of the available sample. The registry notes substantial missing outcome collection and does not report how it was handled in a formal analysis. The posted summary-based recalculation is unadjusted and cannot account for unavailable participant-level information.

The primary endpoint is a blood-pressure measure, not a direct measure of recurrent stroke, cardiovascular events, or quality of life. The registry lists some clinical-event outcomes among secondary measures, but detailed numerical results for them are not reported in the registry record. Therefore, the primary result alone cannot establish effects on those outcomes. Nor does it quantify the feasibility of implementing the full program, although feasibility was among the pilot's stated purposes.

The appropriate takeaway is a preliminary comparison with considerable uncertainty. The pilot provides an observed estimate and information about outcome collection, but it does not establish a definitive treatment effect. The sample-size illustrations may support future planning under their stated assumptions, but they cannot turn an imprecise pilot estimate into a confirmed result.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate should be read together with its uncertainty. The primary comparison has a directional estimate, but its interval includes differences both below and above zero. Looking only at the observed means could make the contrast seem more decisive than the data warrant; looking only at the p-value would also miss the range of plausible effects represented by the interval.

The endpoint data also highlight the distinction between enrollment and outcome availability. The registry reports enrollment of 83, while the primary outcome record notes that data were not collected for participants in both arms and provides smaller arm-specific outcome counts. Missing outcome collection is not merely a reporting detail: it can reduce precision, and, depending on why measurements are absent, can also affect the representativeness of the observed comparison.

The pilot framing matters for statistical interpretation. The registry describes feasibility and knowledge gaps among the aims, while the primary outcome offers an early estimate for a future research question. A pilot estimate can be useful for planning, but it may be unstable. Planning calculations based on an observed effect are particularly sensitive to that uncertainty, and their assumptions should be kept visible when interpreting the resulting participant targets.

Finally, the record demonstrates the value of distinguishing posted outcome summaries from a documented analysis plan. The summary-based recalculations are transparent comparisons, yet the registry does not report the original sample-size justification, an analysis population, missing-data procedures, or a multiplicity strategy. Those omissions limit how confidently readers can reconstruct the intended inferential framework. Clear reporting of these features would help readers separate exploratory signals from prespecified confirmatory conclusions.

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 primary outcome is available for fewer participants than the enrollment field reports, and the registry explicitly notes that data were not collected for 16.0 participants in STOP Model and 25.0 in Usual Care. The reasons for non-collection and the relationship between missingness and participants' blood pressure are not reported. If the availability of measurements was related to outcome values or other characteristics, an observed-case comparison could differ from a comparison among all randomized participants.

The posted primary comparison is an unadjusted recalculation from summary statistics. No sponsor-reported analysis is listed, and details of any protocol-defined model are not reported in the registry record. The available summaries do not allow adjustment for baseline measurements or other participant characteristics, nor do they show individual-level distributions. Means and standard deviations alone cannot reveal every feature of the data, such as skewness or influential observations.

The trial is described as a pilot, and the registry does not report the original sample-size justification. The outcome counts are limited, and the interval around the primary estimate is broad. The available secondary results also have uncertain precision, while detailed numerical values for some listed secondary outcomes are not reported. The registry does not report a multiplicity strategy, so secondary comparisons should be considered exploratory.

The intervention is a bundle of education, follow-up, telehealth, and monitoring elements. The comparator also includes some discharge-related contact and education. The comparison therefore cannot isolate the contribution of any individual program component. The single-masking designation does not identify who was masked, and further information about implementation, adherence, and outcome ascertainment is not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Stroke Telemedicine Outpatient Prevention Program for Blood Pressure Reduction — NCT03923790.
• Registry record last updated 2022-11-09; status last verified 2022-10.
• Results first posted 2022-11-09.
• 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

STOP was a completed, randomized, parallel-group pilot trial with single masking, sponsored by The University of Texas Health Science Center, Houston. It compared the Stroke Telemedicine Outpatient Program with Usual Care for post-stroke blood-pressure management. The primary endpoint was mean daytime ambulatory systolic blood pressure at 6 months after enrollment.

The posted primary means were 123.6 mmHg for STOP Model and 128.3 mmHg for Usual Care. The unadjusted recalculated difference was -4.7 mmHg, with an interval from -16.29 to 6.892 mmHg and p = 0.427. The interval indicates substantial uncertainty. The registry reports missing primary measurements in both arms and does not list a sponsor analysis or explain how missing data were handled.

Three secondary ambulatory blood-pressure outcomes have numerical summaries; detailed results for other listed secondary outcomes are not reported in the registry record. The sample-size illustrations are planning calculations based on the observed effect and stated assumptions, not observed power. Overall, the record offers a preliminary, imprecise comparison and does not establish a definitive effect.