Orthostatic Hypotension Treatment on Rehab Unit: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Orthostatic Hypotension Treatment on Rehab Unit (NCT01030874), a randomized na study. The primary outcome is Orthostatic Hypotension at Discharge.

2. Clinical Question

The clinical rationale in the registry record is that orthostatic hypotension may contribute to functional impairment during recovery, when standing, walking, climbing stairs, and taking part in therapy are important. The project proposed a multidisciplinary, multicomponent approach and identified functional outcomes including balance, falls, therapy participation, length of stay, transfer to acute care, and discharge location. The posted primary outcome is narrower: it records whether a participant met the blood pressure definition of orthostatic hypotension at discharge. The posted secondary outcome records participants with falls after discharge.

3. Trial Design

The registry describes a randomized trial conducted in a rehabilitation setting and lists 356 participants enrolled. The record is marked completed. It identifies the sponsor as the VA Office of Research and Development and gives the study period as 2011-10 to primary completion in 2016-05. The phase is listed as NA, which is consistent with the record not presenting this as a drug-development phase trial.

The interventions are described as medication review, nutrition or salt intake, education, exercise, and drug recommendations. The arm descriptions identify usual rehabilitation care and treatment for, and prevention of, orthostatic hypotension. The registry metadata also labels the model as single group, while separately identifying randomized allocation and listing two arms. These design descriptions are not fully aligned; the record does not explain the discrepancy. The posted outcomes and comparisons are presented for two groups, but the inconsistency in the metadata leaves some ambiguity about the registry’s design classification.

Masking is listed as single, but the record does not specify who was masked. The original sample-size justification, intended allocation ratio, and detailed protocol analysis plan are not reported in the registry record. The intervention is multicomponent, so the posted comparison does not isolate the contribution of any single component. The primary analysis is restricted to participants with sufficiently complete blood pressure assessments at baseline and discharge. The registry reports a variable rehabilitation stay; among participants included in the analysis, mean length of stay was 41.2 days, median length of stay was 31 days, and the range was 10 to 90 days.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Analyses were restricted to patients for which OH status could be determined at both baseline and discharge. This required at least four blood pressure assessments, with at least two assessments each in separate weeks.

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: Excluding one participant that withdrew and did not want data to be included.

6. Primary Endpoint

The registry lists the primary outcome as Orthostatic Hypotension at Discharge, measured over Duration in rehabilitation facility (time to discharge or transfer) varied for participants. For patients included in the analysis, mean length of stay was 41.2 days (median 31 days), with a range of 10 to 90 days..

The primary endpoint is the count of participants categorized as having orthostatic hypotension at discharge. The registry defines this status using a decrease in systolic blood pressure > 30 or diastolic pressure >15 mm Hg, measured at 1 or 3 minutes after standing compared with the mean of supine values. The criterion had to be present on two or more readings in the last week of admission.

This outcome captures whether orthostatic hypotension was present at the end of the rehabilitation stay under the registry’s operational definition. It is relevant to the study’s stated concern that orthostatic hypotension may accompany functional impairment during rehabilitation. However, it is a specific physiologic classification, not a direct measure of balance, therapy participation, length of stay, or discharge destination. The registry lists those functional outcomes as part of the project rationale, but they are not the posted primary endpoint described in these results.

The endpoint is assessed at discharge, but participants had varying lengths of stay. The analysis population was further restricted to people whose baseline and discharge status could be determined from a required set of blood pressure assessments. Thus, the reported count describes the analyzed participants meeting the defined discharge criterion; it does not by itself describe all enrolled participants or establish why an individual did or did not meet the criterion.

7. Results Posted in the Registry

• Arm 2: 29.3% (44/150) versus 25.8% (39/151) on control; risk difference 3.5 percentage points (95% CI -6.6 to 13.6), risk ratio 1.14 (0.79–1.64); unadjusted two-proportion z-test p = 0.496.

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.

Falls 30 Days After Discharge

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Arm 2: 12.6% (20/159) versus 11.2% (18/161) on control; risk difference 1.4 percentage points (95% CI -5.7 to 8.5), risk ratio 1.13 (0.62–2.05); unadjusted two-proportion z-test p = 0.699.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcome is falls 30 days after discharge. Its result follows the same broad statistical pattern as the primary outcome: the posted comparison does not establish a clear difference between groups, and the estimated effect is uncertain. This does not independently confirm the primary result, because falls and orthostatic hypotension at discharge are different outcomes, assessed at different times and with different measurement processes.

The primary outcome concerns a defined blood pressure classification at discharge. The secondary outcome concerns participants who experienced falls after leaving the rehabilitation facility. The latter may reflect events across the post-discharge period, while the primary outcome is measured during the admission. The registry notes that the stay varied, so 30 days after discharge corresponded to 40 days to 120 days from admission. This variation matters when interpreting how the secondary follow-up aligns with the time in rehabilitation.

Unadjusted secondary results generally carry less weight than a prespecified primary result because they are often interpreted among multiple outcomes or analyses. When multiple comparisons are considered, the chance of seeing an apparently notable result by chance can increase unless an appropriate strategy is planned and reported. The registry lists two outcome measures and two analyses, but a multiplicity strategy is not reported in the registry record. The secondary estimate should therefore be read as supporting descriptive information, not as a standalone confirmation of an intervention effect.

The registry identifies only one secondary outcome in the posted results. It does not provide a complete account of every outcome considered during the project or state whether the reported secondary analysis was prespecified. The pattern across the posted endpoints is broadly consistent in that neither comparison shows a clear between-group difference, but the endpoints should not be combined into a single conclusion: they measure distinct aspects of the study question.

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

• Falls 30 Days After Discharge

9. Statistical Interpretation

10. Statistical Methods Explained

What does a count endpoint represent?

The posted outcomes are counts of participants with an event or classification. For the primary endpoint, the event is meeting the registry’s definition of orthostatic hypotension at discharge. For the secondary endpoint, the event is a fall within 30 days after discharge. Counts are interpreted alongside the number of participants analyzed in each group: the same count can convey different information when group sizes differ. A count alone does not express the size or precision of the between-group contrast.

What is a risk difference?

In general, a risk difference compares the proportion with an outcome in one group with the proportion in another. A value of zero corresponds to equal observed proportions; positive and negative values indicate opposite directions according to the group ordering. The recalculated risk-difference estimate is a simple, unadjusted comparison derived from the posted counts and group sizes. Its confidence interval describes the uncertainty around that comparison. For both outcomes, the interval includes zero, so the recalculation does not distinguish the groups clearly.

What does an odds ratio describe?

An odds ratio compares the odds of an outcome between groups. An odds ratio of 1 corresponds to equal odds. Values on either side of 1 indicate different directions of association, but an odds ratio is not the same quantity as a risk difference. The registry reports logistic regression analyses as odds ratios. The record does not identify the covariates included in those regressions, so their adjustment details cannot be assessed from the registry entry alone.

The separate unadjusted recalculation uses only the posted summary counts. It does not reproduce a regression analysis that may incorporate participant-level information or covariates. The two approaches can therefore yield different estimates without either number being a direct arithmetic transcription of the other. The registry’s reported regression result remains the sponsor’s own analysis; the recalculation is a supplementary, unadjusted view of the posted summaries.

How should confidence intervals and p-values be read?

In general, a confidence interval gives a range of estimates reasonably compatible with the observed data under the statistical model and its assumptions. A wide interval signals limited precision: the data do not pin down the size or direction of the effect closely. When a confidence interval for a risk difference includes zero, or a confidence interval for an odds ratio includes 1, it includes the value corresponding to no between-group difference on that scale. This does not demonstrate equivalence. A p-value summarizes how unusual the observed data, or more extreme data, would be if the model’s null hypothesis were true. It is not the probability that the null hypothesis is true and does not measure clinical importance.

The reported p-values are 0.6 for the primary sponsor analysis and 0.3 for the secondary sponsor analysis. They are consistent with the corresponding confidence intervals including the no-difference value. Neither p-value establishes that the groups were identical, nor does either quantify the probability that the intervention had no effect.

Why might event data be over-dispersed?

General statistical context: over-dispersion occurs when variation in event counts is greater than a model expects. It can arise when participants differ substantially in their underlying event risks or when events cluster. For binary outcomes recorded as whether each participant had an event, the main interpretation is a participant-level proportion rather than a repeated event rate. These registry outcomes are recorded as counts of participants, not counts of repeated falls per participant. The record does not report a model that addresses over-dispersion, nor does it provide repeated-event counts.

What distinguishes the posted analysis from the recalculation?

The sponsor’s analysis is identified as logistic regression, with odds ratios and confidence intervals. The recalculation is a simple unadjusted comparison based on the group counts and denominators. It can help readers understand the direction and uncertainty in the aggregate data, but it cannot reconstruct a regression model, adjust for baseline characteristics, or account for any participant-level details absent from the registry summary. The record does not report the regression covariates or enough detail to reproduce that model.

Neither approach can resolve limitations caused by incomplete outcome ascertainment or selective availability of measurements. In the primary analysis, eligibility depended on having blood pressure assessments at baseline and discharge. The record does not give the number or outcomes of participants excluded for missing or insufficient assessments, nor does it describe imputation or sensitivity analyses. Statistical methods characterize the data analyzed; they do not remove uncertainty about participants outside that analysis population.

11. Confidence Intervals and Precision

The primary estimate is not precise enough to rule out effects in either direction. The sponsor reports an odds ratio of 1.16, with a 95% confidence interval from 0.67 to 1.99. That interval includes 1 and covers a broad range of possible odds ratios. The unadjusted risk-difference confidence interval runs from -0.066 to 0.136, also including zero. The interval therefore does not isolate a single direction of effect.

The secondary falls estimate is similarly uncertain. Its sponsor-reported odds ratio is 1.53, with a 95% confidence interval from 0.74 to 3.24. That interval includes 1 and is wide. The corresponding unadjusted risk-difference interval extends from -0.057 to 0.085, including zero as well. The counts are relatively limited, and the confidence intervals reflect that the observed data do not tightly determine the group contrast.

In general, a confidence interval is an uncertainty range under a specified analysis, not a guarantee that the true effect lies within it. Wide intervals mean that the data remain compatible with several effect sizes, including no difference. A non-significant result is therefore not evidence that the groups are equivalent. The registry does not report a prespecified equivalence margin or a non-inferiority margin. The precision of the posted estimates should be considered alongside the analysis-population restrictions, the variable follow-up timing, and the absence of reported details about missing-data handling.

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 for these binary outcomes, not total events. The calculations use 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 planning reference, with separate illustrations for detecting 100%, 75%, or 50% of that observed effect. The registry does not report the trial’s original sample-size justification or its original planning assumptions, so these calculations should not be mistaken for the study’s own design calculation.

The 80% power column gives the estimated participants per arm for a planning scenario designed to have an 80% chance of detecting the specified effect, if the assumptions used for the calculation hold. The 90% power column expresses the same idea with a higher target chance of detection. These are planning targets, not guarantees about what a future study would find. The figures are illustrations based on the observed effect and the stated assumptions, not a recommendation about an appropriate trial size.

Smaller effects require more participants to detect under the same general planning framework. Accordingly, the rows that plan for a smaller fraction of the observed effect have larger participant requirements. This does not mean that the smaller effect is more likely or more important; it shows the relationship between effect size and the amount of information needed for a given power target.

This is not observed power. It is a prospective planning illustration, not a measure of whether the completed trial had enough power after seeing its results. The record does not report the original design assumptions, so the posted planning estimates should be interpreted separately from the trial’s actual design and enrollment.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.258; treatment proportion p₁ = 0.293; average p̄ = 0.276.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6320 = 1.2388.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6316 = 0.5315.
4. n = (1.2388 + 0.5315)² / (0.0351)² = 2,550.3, rounded up to 2,551 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
p0 <- 0.258278145695364                          # control proportion
p1 <- 0.293333333333333                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1030874)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 2,551 (80% power), 3,414 (90% power)
 75% of observed effect: n per arm = 4,490 (80% power), 6,010 (90% power)
 50% of observed effect: n per arm = 10,001 (80% power), 13,387 (90% power)
power.prop.test: 2550.3 
Simulated power at n = 2,551 per arm: 0.803 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 logistic regression analyses for both outcomes. For orthostatic hypotension at discharge, the sponsor’s reported odds ratio is 1.16, with a 95% confidence interval from 0.67 to 1.99 and p = 0.6. For falls after discharge, the reported odds ratio is 1.53, with a 95% confidence interval from 0.74 to 3.24 and p = 0.3.

The recalculations use the posted counts and group sizes to make simple unadjusted comparisons. They are not substitutes for the sponsor’s regression analyses: an unadjusted risk difference and a regression odds ratio are different measures, and the registry does not identify which covariates, if any, were included in the regressions. The numerical estimates therefore need not match. The sponsor’s analyses are the reported trial analyses; the unadjusted calculations provide a separate description based only on summary counts.

Both sets of results are imprecise and include the no-difference value on their respective scales. The registry does not report enough detail to reproduce the regression models or assess their adjustment choices. No discrepancy between the posted sponsor analysis and recalculation is flagged in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and one secondary outcome in the posted results. It does not report whether the analyses were prespecified in a protocol or statistical analysis plan, whether other outcomes were assessed but not posted, or whether any multiplicity adjustment was planned. With more than one outcome or analysis, interpreting each p-value as though it were the only test can overstate the strength of evidence. The secondary result is accordingly best treated as supportive and descriptive rather than as an independent confirmatory finding.

The primary analysis was restricted to participants with orthostatic hypotension status determinable at both baseline and discharge. The stated requirement was at least four blood pressure assessments, including at least two assessments in separate weeks. This makes the analysis population narrower than the total enrollment. The registry does not report how many participants lacked the required measurements, why assessments were unavailable, or whether missingness differed between groups. It also does not report an imputation method, a sensitivity analysis, or an analysis including all enrolled participants.

The secondary outcome has its own analyzed group sizes, which differ from those for the primary endpoint. The record does not explain the participant-level reasons for this difference or provide a detailed account of missing fall information. The timing of assessment is also tied to discharge, which occurred after variable lengths of stay. These features can affect who contributes information and when follow-up takes place.

The registry’s single masking label does not specify who was masked. It does not report the regression covariates, model diagnostics, handling of protocol deviations, or a detailed analysis population definition beyond the primary blood pressure requirements. The record also contains inconsistent design labels: randomized allocation is listed, but the model is described as single group while two arms and comparisons are posted. These gaps limit assessment of bias and reproducibility. They do not prove that a particular analytic choice was inappropriate; they mean that the registry entry does not document enough detail to evaluate it fully.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hospitalization (14.6%).

The registry reports serious adverse events for 22 participants in Arm 1, among 177 at risk, and 26 participants in Arm 2, among 178 at risk. It also reports 13 deaths in Arm 1 and 14 in Arm 2. Hospitalization is listed as a leading serious adverse event term, at 14.6%. The record reports no other adverse events in the corresponding adverse-event fields.

These figures describe events recorded in the registry; they do not establish that the intervention caused or prevented an event. The serious adverse event denominators differ from the analyzed denominators for the primary endpoint, so they should not be treated as the same analysis population. The registry does not give event-level timing, relatedness assessments, individual participant overlap between categories, or an explanation of how the hospitalization percentage was calculated. It also does not provide a comparative statistical analysis of safety outcomes. The counts are therefore descriptive and should not be interpreted as a causal safety comparison.

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

The posted findings show that the analyzed groups had similar observed counts in the broad sense that the comparisons did not produce a clear statistical distinction. For the primary endpoint, the sponsor’s reported confidence interval includes the no-difference odds ratio, and the unadjusted risk-difference interval includes zero. The same general pattern appears for the secondary falls outcome. The estimates are not precise enough to determine the direction or size of any underlying effect confidently.

These results do not prove that the intervention and usual rehabilitation care are equivalent. No equivalence or non-inferiority margin is reported, and the confidence intervals allow effects in either direction. Conversely, the results do not demonstrate that the intervention improves or worsens either endpoint. The p-values are not probabilities that a treatment effect is absent; they summarize the data under a particular null model.

The primary outcome captures a blood pressure classification at discharge, not every aspect of functional recovery. The secondary outcome captures reported falls after discharge, with follow-up timing linked to a variable rehabilitation stay. Neither outcome alone answers all of the broader questions in the project rationale about balance, therapy participation, length of stay, transfers, or discharge location.

The findings also apply to the analyzed participants, which required sufficient blood pressure assessments for the primary outcome. Missing-data handling and the characteristics of participants excluded from that analysis are not reported in the registry record. The multicomponent intervention cannot be separated into individual effects from these comparisons. Overall, the posted estimates are best understood as uncertain group comparisons in this rehabilitation setting, rather than as definitive evidence for or against any one intervention component.

18. Why This Trial Matters Statistically

This trial illustrates several recurring challenges in clinical biostatistics. First, an outcome that sounds direct still depends on an operational definition. Orthostatic hypotension at discharge was classified using specified blood pressure changes, measurement times, and repeated readings. Those rules determine which participants count as having the endpoint and make the analysis population dependent on measurement availability.

Second, event counts need denominators and uncertainty measures. Counts alone can make group differences seem more or less compelling than they are. The confidence intervals clarify that the posted estimates do not tightly distinguish the groups, and that a non-significant result is not the same as evidence of equivalence.

Third, different statistical measures answer different questions. A risk difference describes a contrast in proportions, while an odds ratio describes a contrast in odds. An unadjusted calculation from summary counts is useful for transparency, but it cannot replace the sponsor’s regression analysis or reveal its covariate choices. Interpreting both requires attention to the estimand and model, not just the direction of a point estimate.

Finally, trial records are not always complete accounts of design and analysis. The discrepancy between randomized allocation and the single-group model label, the absence of reported multiplicity and missing-data plans, and the differing analysis populations all shape how confidently results can be interpreted. Recognizing those limits is part of statistical interpretation, not a reason to disregard the observations. The record supports a careful account of what was measured and estimated while leaving important design and analysis details unresolved.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record has a design-label inconsistency: it identifies randomized allocation and two arms but labels the model as single group. It does not explain the mismatch. Masking is described only as single, without identifying who was masked. These omissions limit a full assessment of the design from the registry entry.

The primary endpoint analysis includes only participants with enough blood pressure assessments to determine status at baseline and discharge. The number and characteristics of participants who did not meet this requirement are not reported, nor are the reasons for missing assessments or any missing-data sensitivity analyses. The secondary analysis uses different group sizes, but the record does not explain the difference in detail.

The intervention includes several components, so the posted comparison cannot distinguish the effects of medication review, nutrition or salt intake, education, exercise, or drug recommendations. The registry does not report the covariates in the logistic regression analyses, an analysis plan, or a multiplicity strategy. It also does not provide an original sample-size justification. These are limits on interpretation and reproducibility, not evidence that the analyses were necessarily conducted in a particular way.

Follow-up for falls is anchored to discharge, while length of stay varied. The registry indicates that 30 days after discharge ranged from 40 days to 120 days after admission. The record does not describe the method of fall ascertainment or how missing follow-up was handled. Finally, the posted primary measure is a defined discharge classification; it does not directly report all functional outcomes named in the study rationale.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Orthostatic Hypotension Treatment on Rehab Unit — NCT01030874.
• Registry record last updated 2021-07-01; status last verified 2021-06.
• Results first posted 2021-07-01.
• 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

NCT01030874, titled Orthostatic Hypotension Treatment on Rehab Unit, is listed as a completed randomized study with 356 participants enrolled. The record describes usual rehabilitation care and a multifaceted treatment and prevention approach for orthostatic hypotension, while also carrying a single-group model label that is inconsistent with its randomized, two-arm results.

The primary posted outcome is orthostatic hypotension at discharge among participants with sufficient blood pressure assessments. The sponsor’s logistic regression reports an odds ratio of 1.16, with a 95% confidence interval from 0.67 to 1.99 and p = 0.6. The secondary outcome is falls 30 days after discharge; the sponsor reports an odds ratio of 1.53, with a 95% confidence interval from 0.74 to 3.24 and p = 0.3. Both estimates are imprecise and do not establish a clear difference. The registry does not report the original sample-size assumptions, multiplicity plan, or detailed missing-data methods.