Mobilizing Evidence Into Action to Improve Outcomes of Vulnerable Seniors: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Mobilizing Evidence Into Action to Improve Outcomes of Vulnerable Seniors (NCT01254942), a randomized na study. The primary outcome is Short Physical Performance Battery.

2. Clinical Question

The trial also considered mobility, falls, sedentary behavior, strength, gait speed, and quality-of-life measures. These outcomes help describe areas that may accompany recovery after hip fracture, but the registry record identifies SPPB as the primary outcome. The primary comparison is therefore the most direct statistical response to the trial's stated main question. It does not by itself establish whether participants experienced changes in every other aspect of health or function.

The registry describes a randomized, parallel-group comparison and lists 53 participants as the enrollment. The primary outcome summaries include results for participants in both assigned groups, but the reasons for any difference between enrollment and outcome-specific numbers are not reported in the registry record. The record does not provide detailed eligibility criteria, recruitment setting, or participant-level characteristics, so the population to which the results may apply cannot be characterized beyond the description in the record.

3. Trial Design

The registry describes a randomized controlled trial with parallel groups and single masking. The intervention was a specialized Fracture Follow-up Clinic, named the B4 Clinic in the registry, compared with usual care after hip fracture. The trial is listed as completed, with enrollment of 53. The phase field is listed as NA. The start is recorded as 2010-12 and primary completion as 2014-08.

The primary outcome was the Short Physical Performance Battery (SPPB), measured at 12 months post-fracture. The reported group summaries are means with standard deviations. The primary outcome summary lists 25 participants in the usual-care group and 24 in the intervention group. Those outcome-specific numbers should not be treated as a complete account of the participant flow: the record does not describe losses to follow-up, exclusions, or reasons why the numbers may differ across outcomes.

Random assignment is intended, in general, to make groups comparable at the point of allocation, including with respect to factors that are measured and unmeasured. In a trial with limited enrollment, chance differences between groups can still occur, and the registry record does not provide enough participant-level information to assess baseline balance. It also does not report how the random sequence was generated, how allocation was concealed, or who was masked. “Single” masking is listed, but the masked role or roles are not identified in the registry record.

The brief summary says investigators would evaluate the effect of the clinic and exercise program on mobility and falls. The registry lists secondary outcomes spanning sedentary behavior, falls, quality of life, lower-extremity function, gait speed, grip strength, and leg strength. The record gives no detailed protocol, analysis plan, sample-size justification, or description of how follow-up was conducted. These omissions limit assessment of implementation and analysis choices, rather than changing the arithmetic of the posted outcome summaries.

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

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 Short Physical Performance Battery, measured over 12 months post-fracture.

The primary endpoint is the Short Physical Performance Battery (SPPB) score at 12 months post-fracture. According to the registry description, the SPPB combines three timed and categorized tests: standing balance, gait speed, and sit-to-stand performance. The subscales are combined into a score ranging from 0-12, with higher scores indicating better performance.

SPPB is used as a measure of physical performance that brings several functional tasks into one summary score. In general, a composite score can provide a concise way to compare overall performance across groups, while retaining information from several related domains. It can also obscure whether any group difference arises mainly from one component or is spread across components. Separate component results are not reported in the registry record.

The endpoint is relevant to the stated trial question because the intervention was designed around post-fracture management, mobility, fall risk, and exercise. The score does not directly measure falls, quality of life, or all aspects of recovery. Those topics are represented by separate secondary outcomes in the registry. Nor does the score, on its own, indicate whether a particular difference would be important to participants; a threshold for clinical importance is not reported in the registry record.

The posted primary summaries give group means and standard deviations. A mean describes the group average, while the standard deviation describes how dispersed individual scores are around that average. Comparing the means is a summary-level comparison; it does not show the distribution of individual responses or the trajectory of scores over time. Baseline SPPB scores and change-from-baseline results are not reported in the registry record.

7. Results Posted in the Registry

• Intervention: mean 9.08 versus 8.24 on control; difference 0.84 (95% CI -0.70 to 2.38), standardized effect d = 0.31; z-test p = 0.286.

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.

Quality of Life (ICECAP-O)

• 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:
  • Intervention: mean 0.78 versus 0.81 on control; difference -0.03 (95% CI -0.09 to 0.03), standardized effect d = -0.25; z-test p = 0.365.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Health Related Quality of Life (EQ5D-5L)

• 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:
  • Intervention: mean 77.20 versus 78.00 on control; difference -0.80 (95% CI -8.72 to 7.12), standardized effect d = -0.05; z-test p = 0.843.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Lower Extremity Measure

• 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:
  • Intervention: mean 88.72 versus 82.27 on control; difference 6.45 (95% CI -0.38 to 13.28), standardized effect d = 0.52; z-test p = 0.064.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes cover several related but distinct aspects of health and function after hip fracture, including quality of life, lower-extremity function, gait, strength, falls, and sedentary behavior. The available continuous-outcome summaries show that estimates do not all point in the same direction. This variation is not surprising when outcomes measure different constructs, have different scales and variability, and may be based on different outcome-specific participant counts.

These results add context to the primary SPPB comparison rather than serving as interchangeable measures of it. SPPB combines balance, gait speed, and sit-to-stand performance, whereas the secondary measures describe separate domains. A secondary estimate that appears more pronounced does not overturn the primary result, particularly when the analysis plan, outcome hierarchy, and role of each secondary endpoint are not reported in the registry record.

Each additional statistical comparison creates another opportunity for a result to look unusual by chance. In general, when many outcomes are tested, the chance of at least one apparently notable result can increase if no adjustment or prespecified interpretation strategy is used. The record does not report multiplicity control, a hierarchy for secondary outcomes, or which outcomes were confirmatory versus exploratory. Unadjusted secondary p-values and confidence intervals should therefore be interpreted cautiously and should not be treated as independent confirmation of the primary finding.

The registry lists more secondary outcomes than it posts numerical results for, and it does not report analyses for the outcomes with summaries. The absence of a reported analysis does not indicate that the outcome was not measured; it means that the registry record does not provide the corresponding analysis. Missing results and outcome-specific differences in the available counts make it difficult to assess whether the posted secondary findings represent the full set of measured outcomes.

Overall, the secondary pattern is best used to describe the range of domains considered, not to make a single broad claim about recovery. Their relationship to the primary result remains uncertain without a prespecified analysis plan, a full account of missing outcomes, and appropriate attention to multiple comparisons.

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

• Difference in Sedentary Behavior Minutes/Day
• Falls
• Quality of Life (ICECAP-O)
• Health Related Quality of Life (EQ5D-5L)
• Lower Extremity Measure
• Gait Speed (m/s)
• Grip Strength (Bilateral)
• Leg Strength (Fractured Leg)

9. Statistical Interpretation

10. Statistical Methods Explained

The posted continuous outcomes are summarized with group means and standard deviations. A mean is the arithmetic average of the measured values in a group. A standard deviation describes the spread of those values around the mean; it is not the uncertainty around the mean itself. The standard error, in contrast, describes the sampling variability of an estimated mean. In general, larger samples tend to give more precise mean estimates when other conditions are comparable.

What does a mean difference represent?

For the primary comparison, the mean difference is expressed as intervention minus usual care. A positive value therefore indicates a higher observed average in the intervention group, while a negative value indicates a lower observed average. This direction convention helps interpret both the estimate and its confidence interval. For SPPB, higher scores indicate better performance according to the registry description, but the estimate remains a comparison of group averages and does not describe every participant's outcome.

The primary mean difference is a simple unadjusted recalculation from the posted summaries. “Unadjusted” means that the comparison does not account for other variables, such as baseline score or participant characteristics. An adjusted analysis can sometimes improve precision or address chance imbalance, but whether that is appropriate depends on the protocol and analysis plan. Such an analysis is not reported in the registry record, so an adjusted result cannot be described.

How should the confidence interval be read?

A confidence interval gives a range of values compatible with the data under the statistical model and its assumptions. In repeated studies using the same method, the stated confidence procedure is designed to cover the true effect at its nominal rate. It is not a range containing a fixed probability that the true effect lies within it, and it does not account for every source of uncertainty, such as bias or missing data. The interval for the primary mean difference extends from -0.704 to 2.384, crossing zero. This signals that the posted summaries are compatible with effects in either direction as well as with no mean difference.

The unadjusted p-value for the primary comparison is 0.286. In general, a p-value measures how unusual data at least as incompatible with a null hypothesis would be under that hypothesis and the test assumptions. It is not an effect-size measure, a measure of clinical importance, or the probability that the null hypothesis is true. A p-value above a chosen threshold does not prove equivalence or demonstrate that any difference is absent. The registry's planning assumptions specify a two-sided significance level of 0.05, but the trial's own original analysis plan is not reported in the registry record.

Why do group sizes and variability matter?

Estimates are less precise when the observed data are highly variable or when the amount of information is limited. Here the standard deviations and outcome-specific sample sizes describe the scale of observed variability and the number contributing to the summary. They do not identify whether missing outcomes occurred, whether all randomized participants were analyzed, or why outcome-specific counts differ from the enrollment figure. Those participant-flow and analysis-population details are not reported in the registry record.

In general, randomization helps make a causal comparison credible by reducing systematic differences in assignment, but it does not guarantee balance in a particular trial. Allocation concealment, masking, adherence, follow-up, and analysis choices can also affect interpretation. The record identifies the design as randomized, parallel, and single-masked but does not describe sequence generation, concealment, masked roles, adherence, or the analysis population. Therefore, the statistical comparison should be read as an estimate based on the posted group summaries, not as a complete evaluation of trial conduct.

What does “recalculated” mean in this context?

Recalculated comparisons are simple unadjusted calculations from posted summary statistics. They are not evidence that the sponsor used the same method, nor do they replace a reported analysis. The registry record lists no reported analyses for the primary outcome. When a recalculation conflicts with the sponsor's own analysis, the sponsor's analysis takes precedence; no discrepancy is flagged for this record. Even without a discrepancy, the absence of a described analysis plan means that details such as covariate adjustment, missing-data handling, and multiplicity control remain unknown.

For continuous outcomes, a mean difference retains the original measurement scale, which can make the estimate easier to relate to the endpoint. Standardized effect measures, such as a difference expressed relative to pooled variability, answer a different question about magnitude relative to spread. They do not provide a substitute for the original scale or a clinical-importance threshold. The registry does not report a threshold for meaningful SPPB change, so the numerical estimate cannot be classified as clinically important or unimportant from this record alone.

11. Confidence Intervals and Precision

The primary mean-difference estimate is 0.84 points, with a 95% confidence interval from -0.704 to 2.384. The width of this interval indicates that the estimate is not highly precise: it permits a range of possible group differences, including values below zero, zero, and values above zero. The point estimate alone should not be read as the definitive size of an underlying effect.

In general, a confidence interval reflects sampling uncertainty under the statistical method used. It does not automatically capture systematic bias, measurement error, departures from the model, or the effect of missing data. The registry does not report enough detail to assess those sources of uncertainty. The interval is based on a simple unadjusted recalculation from the posted summaries, rather than a reported sponsor analysis.

The interval crossing zero is consistent with the unadjusted p-value of 0.286: the data do not provide a clear separation from zero under this comparison. This does not establish that the groups are equivalent or that a difference is absent. Equivalence requires a prespecified margin and an analysis designed to test whether the full range of plausible effects falls within that margin. Such a margin and analysis are not reported in the registry record.

Interpretation also depends on the SPPB scale and on what difference would matter to patients or clinicians. The registry describes the score range and direction but does not identify a minimal important difference or another threshold for practical importance. Consequently, the interval can be described statistically, but the record does not establish which values within it would be meaningful in practice.

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 report participants per arm for 80% power and participants per arm for 90% power. They are not totals across both arms and are not total event counts. In general, power is the chance that a statistical test will detect an effect of a specified size under the assumed model and design, if that effect is truly present. The 80% and 90% columns represent different target chances of detecting the specified effect: the higher target generally requires more participants.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The planning rows therefore illustrate scenarios based on 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. Smaller effects are harder to detect and require more participants under these assumptions. The trial's own original design assumptions and sample-size justification are not reported in the registry record.

These figures are planning illustrations, not observed power. They describe hypothetical participant requirements under the stated assumptions and use the observed effect as a reference for scenarios. They do not tell how likely the completed trial was to obtain a statistically significant result, and they do not establish that the observed effect is the true effect. Planning from an observed effect can be particularly uncertain when the estimate itself is imprecise.

For non-time-to-event outcomes, the stated convention is participants per arm; time-to-event planning figures, if present, use total events. The outcomes discussed in these continuous-measure comparisons are read as participants per arm. In general, such illustrations depend on assumptions about the target effect, variation, allocation, significance threshold, and statistical model. They should not be mistaken for the trial's actual enrollment plan or for a guarantee about the result of a future study.

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 = 0.840; pooled standard deviation σ = 2.745.
2. n = 2 × (1.96 + 0.842)² × 2.745² / 0.840² = 167.6, rounded up to 168 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 <- 0.84                      # observed difference in means
sigma <- 2.74461600616126                     # 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(1254942)
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 = 168 (80% power), 225 (90% power)
 75% of observed effect: n per arm = 298 (80% power), 399 (90% power)
 50% of observed effect: n per arm = 671 (80% power), 898 (90% power)
power.t.test: 168.6 
Simulated power at n = 168 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 record does not report a statistical analysis plan, a strategy for controlling multiplicity, or a hierarchy defining how the primary and secondary outcomes were to be interpreted. This matters because the trial considers multiple outcomes, and repeated testing can increase the chance of apparently noteworthy results arising by chance. An adjustment is not always required for every analysis, but the intended role of each outcome and the approach to multiplicity should be clear before results are interpreted. Those details are not reported in the registry record.

The record lists 11 outcome measures and posts numerical summaries for the primary outcome and some secondary outcomes. It lists no reported analyses. The presence of group summaries and recalculated comparisons does not establish whether the analyses were prespecified, whether other analyses were conducted, or whether all measured outcomes are represented. The registry record does not describe any changes to outcomes or analysis methods over the course of the trial.

Missing-data handling is also not reported. The outcome-specific group counts differ across the posted summaries, and the reason for those differences is not given. The record does not state how many participants were missing each measurement, why data were missing, whether missing values were imputed, or whether a sensitivity analysis was conducted. In general, missing outcomes can affect estimates if the participants with available measurements differ systematically from those without them.

The analysis population is not reported in the registry record. It is therefore unclear whether the posted summaries follow an intention-to-treat approach, include only participants with observed outcomes, or use another population definition. The record also does not describe adherence to the intervention or how participants who did not follow their assigned care were handled in analysis.

These omissions do not change the arithmetic of the posted group summaries, but they limit evaluation of bias, robustness, and confirmatory status. A complete interpretation would benefit from a protocol or analysis plan, participant-flow information, an account of missingness, and a description of the analysis populations and multiplicity approach. Those details are not reported in the registry record.

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

Serious events with the highest arm-level rate: possible adverse event (3.8%).

The registry reports serious adverse event counts for participants at risk in each group. In usual care, 0 serious adverse events are listed among 27 at risk. In the intervention group, 1 serious adverse event is listed among 26 at risk. The registry also lists 0 deaths in each group. For other adverse events, 0 affected participants are listed among 27 at risk in usual care and among 26 at risk in the intervention group.

The serious-event term listed is “Possible adverse event,” with a reported value of 3.8%. The registry record does not provide further detail about the event, its timing, severity assessment, relationship to the intervention, or the group assignment associated with that term. The counts therefore should be read as the registry's posted safety summaries, not as proof that the intervention caused or did not cause an event.

These figures are descriptive. With a limited number of participants and no detailed event narratives or follow-up information, they do not precisely characterize uncommon risks or establish comparative safety. The registry record does not describe how adverse events were collected or adjudicated.

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

The primary result describes an observed difference in average SPPB scores at 12 months post-fracture: the intervention group's mean was higher than the usual-care group's mean, and the unadjusted recalculated mean difference was 0.84 points. The confidence interval extends from -0.704 to 2.384, and the unadjusted p-value is 0.286. Taken together, these statistics indicate substantial uncertainty about the direction and size of the group difference.

The result does not establish that the clinic and exercise program improved physical performance, nor does it establish that the intervention had no effect. A non-significant result is not evidence of equivalence. The interval allows values on either side of zero, and the registry does not report a threshold for a clinically meaningful SPPB difference. Statistical compatibility with a range of values is not the same as proof that each value is equally likely or clinically important.

The randomized parallel design is relevant because random assignment can support a comparison of assigned groups. However, the registry record does not report allocation concealment, the identity of masked roles, adherence, missing-data methods, analysis populations, or a detailed statistical plan. The posted comparisons are simple unadjusted recalculations, while no analyses are reported in the registry record. These limitations affect confidence in interpretation and prevent a full appraisal of whether the analysis matched the intended design.

The secondary outcomes address other domains and have their own estimates and uncertainties. They should not be combined into a broad statement that the intervention did or did not alter recovery. The record does not report multiplicity control or the status of secondary outcomes as confirmatory or exploratory. Safety figures are also descriptive and do not support a definitive conclusion about uncommon harms.

The appropriate conclusion is narrow: the posted summaries show a higher mean SPPB score in the intervention group, but the unadjusted estimate is imprecise and compatible with effects in either direction. The registry information does not establish clinical importance, equivalence, or a comprehensive benefit-harm profile.

17. Why This Trial Matters Statistically

This trial is statistically instructive because it illustrates why an estimated difference should be read together with its uncertainty. The intervention group's observed mean SPPB score is higher, but the confidence interval crosses zero and includes values in either direction. Focusing only on the point estimate or only on whether a p-value crosses a threshold would lose important information about the range of effects compatible with the posted data.

The record also illustrates the distinction between trial results and planning calculations. Planning illustrations can show how participant requirements change when the target effect changes, but they are hypothetical scenarios based on stated assumptions. They are not observed power and do not substitute for the trial's original design rationale, which is not reported in the registry record.

Multiple outcome domains create another important interpretive issue. A trial may measure mobility, falls, strength, and quality of life, but those results do not all answer the same question. Without a reported outcome hierarchy and multiplicity strategy, secondary findings are more appropriately treated as supportive description than as decisive evidence. This is especially relevant when the registry posts several outcomes but does not report its analyses or missing-data approach.

Finally, the registry record shows how the availability of group summaries can permit a basic unadjusted comparison while leaving important analytical questions open. Participant flow, masking roles, analysis population, missingness, and the original statistical plan all contribute to judging credibility and generalizability. Statistical interpretation is not just a matter of calculating a difference; it also depends on knowing what was planned, measured, and included in the analysis.

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.

Several trial-specific limitations are apparent from the registry record. Enrollment is listed as 53, while the outcome summaries have different group-specific participant counts across outcomes. The record does not explain participant flow, losses to follow-up, exclusions, or the reasons for outcome-specific count differences. This makes it difficult to assess completeness of follow-up or whether the available summaries represent all randomized participants.

The design is listed as single-masked, but the registry does not identify who was masked. Details of sequence generation and allocation concealment are also not reported. These omissions limit assessment of the protections against selection and measurement bias. The record does not provide participant characteristics or baseline outcome scores, so baseline comparability cannot be evaluated from the posted summaries.

The registry lists secondary outcomes but does not report analyses. The analysis plan, multiplicity approach, analysis populations, adherence, and missing-data methods are not reported in the registry record. As a result, it is not possible to determine whether the displayed comparisons were prespecified, how missing measurements were handled, or whether the results are robust to alternative assumptions.

For the primary endpoint, no threshold for a clinically important SPPB difference is reported. The available comparison is a simple unadjusted recalculation from summary statistics, and its confidence interval is broad enough to include effects on either side of zero. The outcome-specific summaries do not provide individual-level distributions, component-level SPPB results, or change from baseline. Each of these omissions constrains interpretation of magnitude, clinical relevance, and potential sources of variation.

The safety information is limited to counts and a brief serious-event term. Event descriptions, timing, attribution, and collection methods are not reported. These limitations mean that the posted safety counts are descriptive and cannot characterize the full range of possible adverse outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Mobilizing Evidence Into Action to Improve Outcomes of Vulnerable Seniors — NCT01254942.
• Registry record last updated 2023-09-25; status last verified 2023-09.
• Results first posted 2023-09-25.
• 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 describes a completed randomized, single-masked, parallel trial of a Fracture Follow-up Clinic, also called the B4 Clinic, versus usual care following hip fracture. Enrollment is listed as 53, and the primary outcome is SPPB score at 12 months post-fracture.

The posted primary means were 8.24 for usual care and 9.08 for the intervention. A simple unadjusted recalculation gives a mean difference of 0.84, with a 95% confidence interval from -0.704 to 2.384 and an unadjusted p-value of 0.286. The interval includes zero and leaves uncertainty about the direction and size of the difference.

The registry lists secondary outcomes and descriptive adverse-event counts, but reports no analyses. Details about missing data, analysis populations, multiplicity, masking roles, and the original sample-size justification are not reported in the registry record. The results therefore support a cautious description of the posted summaries, not a definitive conclusion about clinical importance or overall benefit and risk.