Impact of Pharmaceutical Care in Diabetics Patients: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Impact of Pharmaceutical Care in Diabetics Patients (NCT01580904), a randomized na study. The primary outcome is Glycated Hemoglobin.

2. Clinical Question

The trial record frames pharmacist follow-up as a way to monitor treatment and measures laboratory outcomes rather than reporting a patient-reported quality-of-life result. Quality of life is mentioned in the rationale, but a quality-of-life outcome is not listed among the posted outcome results. The registry description also mentions baseline glucose, while the posted secondary results are for total cholesterol and LDL cholesterol.

The statistical question is about the difference between group averages, not whether every participant experienced the same change. Group means and standard deviations describe the observed distributions in broad terms; an estimate and its confidence interval describe the uncertainty around the group comparison. They do not by themselves establish why any difference arose. Details of the exact analysis population, missing data, and the trial's prespecified analysis plan are not reported in the registry record.

3. Trial Design

The registry describes a randomized, controlled, single-blind clinical trial with a factorial model designation. It lists the condition as type 2 diabetes mellitus and the intervention as pharmaceutical care. The study summary says the trial was conducted in two pharmacy units in Brazil. The record marks the study completed, gives an enrollment of 100, and lists a start in 2009-09 and primary completion in 2011-12.

The two posted groups were the control group and the intervention group. The control description says participants were not followed by a pharmacist. In the intervention group, participants received pharmacist follow-up described as pharmacotherapeutic monitoring, including dosing parameters such as glucose and glycated hemoglobin. The registry summary says the intervention was intended to identify and resolve medication-related problems. Further details about the content, frequency, or delivery of follow-up are not reported in the registry record.

Randomization indicates that allocation was intended to be by chance, but the sequence-generation method and allocation-concealment procedures are not reported in the registry record. The masking field says single blind; which people were masked and how masking was maintained are not reported in the registry record. Although the model is labeled factorial, the factors, their levels, and any interaction analyses are not reported in the registry record. The record lists phase as not applicable.

The primary outcome is glycated hemoglobin, expressed as a percentage, with an outcome period up to 24 weeks. The summary describes follow-up for 24 weeks and says outcomes would be assessed up to 24 weeks. Total cholesterol and LDL cholesterol are listed as secondary outcomes over the same stated period. The registry does not report detailed visit schedules, outcome-assessment procedures, or whether all participants had measurements at the same time points.

The enrollment entry is a registry figure, while the posted primary-outcome group summaries give group-specific counts. The registry does not explain the difference between the enrollment entry and those outcome counts. It also does not report whether participants were analyzed according to assigned group, how withdrawals were handled, or the original sample-size justification.

4. Participant Flow and Accounting

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

Before assignment: The exclusion criteria were (i) to have an infectious disease during the study, (ii) to miss three consecutive appointments, (iii) to stop the use of the hypoglycemic drugs by order of the doctor, and (iv) to deny the acceptance of the term of free and informed consent (TFIC).

Overall Study

Analysis population for the primary outcome, as defined in the registry: Data are glycated hemoglobin means of all patients per group.

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 Glycated Hemoglobin, measured over Up to 24 weeks.

Glycated hemoglobin is the primary endpoint. The registry reports it as a continuous measure expressed in percent, summarized by a mean and standard deviation. It describes the outcome as the average glycated hemoglobin over 24 weeks and gives the timeframe as up to 24 weeks. The population description says the data are glycated hemoglobin means of all patients per group.

As a general clinical-statistical explanation, glycated hemoglobin is used as a measure of blood glucose exposure over time, rather than a single glucose reading at one moment. A group mean can therefore provide a summary of this measure across participants. The standard deviation describes how spread out participant measurements are around the group mean; it is not the uncertainty interval for the difference between groups.

The primary comparison asks whether the average value differed between the intervention and control groups during the stated period. The posted means are 7.2 for the control group and 7.1 for the intervention group. The recalculated unadjusted mean difference, defined as intervention minus control, is -0.1, with a 95% confidence interval from -0.765 to 0.565. The interval includes zero, so the posted summaries do not estimate the group difference precisely enough to rule out no difference at the conventional 5% level using this unadjusted comparison.

The registry does not explain how measurements across the follow-up period were combined to form the reported average, whether baseline measurements were included, or how missing measurements were handled. Those details matter for interpreting what the average represents in practice.

7. Results Posted in the Registry

• Intervention Group: mean 7.10 versus 7.20 on control; difference -0.10 (95% CI -0.76 to 0.56), standardized effect d = -0.06; z-test p = 0.768.

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.

Total Cholesterol

• 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 Group: mean 191.10 versus 209.90 on control; difference -18.80 (95% CI -35.43 to -2.17), standardized effect d = -0.47; z-test p = 0.027.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Intervention Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

LDL Cholesterol

• 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 Group: mean 110.80 versus 131.00 on control; difference -20.20 (95% CI -33.82 to -6.58), standardized effect d = -0.62; z-test p = 0.004.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Intervention Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes concern total cholesterol and LDL cholesterol. Their group mean comparisons have the same direction: the intervention-group means are lower than the control-group means. The corresponding unadjusted confidence intervals exclude zero, unlike the primary glycated hemoglobin interval. This describes a pattern across the posted measures, not proof that the intervention caused those differences.

The secondary pattern should be considered alongside, not in place of, the primary outcome. Glycated hemoglobin was identified as primary, while the cholesterol measures were secondary. Different outcomes can show different estimates because they measure different things and have different variability. The secondary findings do not establish that the primary outcome changed, and the primary comparison does not erase the separate observed cholesterol pattern.

Unadjusted secondary results carry less weight because testing several outcomes creates more opportunities for a nominally notable result to occur by chance. A multiplicity procedure or prespecified outcome hierarchy can address that issue, but neither is reported in the registry record. The record also does not say whether the secondary outcomes were specified before the data were examined or whether other analyses were conducted.

The registry summary mentions baseline glucose as an outcome to be measured, but posted secondary results are listed only for total cholesterol and LDL cholesterol. A baseline glucose result is not reported in the registry record. Quality of life is discussed in the summary rationale, but no posted quality-of-life result is listed. These gaps mean the available secondary pattern is limited to the two cholesterol measures, and should not be generalized to outcomes without posted results.

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

• Total Cholesterol
• LDL Cholesterol

9. Statistical Interpretation

10. Statistical Methods Explained

For the primary outcome, the posted data are continuous measurements summarized as group means and standard deviations. A mean is the arithmetic average of observations in a group. A standard deviation describes how far individual observations typically vary around that group average. These answer different questions: the mean describes the location of the measurements, while the standard deviation describes their spread.

What does the mean difference represent?

The recalculated comparison subtracts the control mean from the intervention mean. A negative estimate therefore means the posted intervention-group mean is lower. For glycated hemoglobin, the estimate is -0.1. This is a difference between group averages, not a difference experienced by every participant, and it does not show individual trajectories or changes from baseline.

The group counts and standard deviations contribute to the uncertainty of a difference in means. A larger spread generally makes an estimate less precise, while more observations can make it more precise, all else being equal. This is a general statistical principle. The registry does not report participant-level data, so the posted summary statistics cannot show the shape of each outcome distribution or whether unusual observations influenced the means.

What does a confidence interval add?

A confidence interval expresses uncertainty around an estimate. In general, a 95% confidence interval is produced by a procedure that, under its assumptions, would contain the underlying value in 95% of repeated samples. It is not a 95% probability statement about the fixed value in this particular trial. For the primary comparison, the interval runs from -0.765 to 0.565. Its inclusion of zero indicates that the data are compatible with no group difference under the unadjusted calculation, as well as with differences in either direction within the interval.

A p value measures how incompatible the observed data are with a specified null hypothesis, assuming the analysis model and its assumptions hold. It is not the probability that the null hypothesis is true, nor does it measure clinical importance. The primary unadjusted p value is 0.768. The registry summary states a significance threshold of p < 0.05, but the record does not report a sponsor analysis for comparison with this recalculation.

Why distinguish a recalculation from the trial analysis?

The estimates and tests discussed in the statistical summaries are simple, unadjusted recalculations from the posted means, standard deviations, and group counts. Such calculations cannot reproduce analyses that require participant-level observations, such as models with covariates, repeated measurements, or particular rules for missing data. They also do not reveal whether the investigators used a different analysis population or a different distributional assumption. No reported endpoint analyses are listed in the registry record.

The registry summary states that Student t tests, chi-square analysis, analysis of variance, and other tests if necessary would be used. This is a description of intended methods, not a report of which test was actually applied to each outcome. The summary does not specify a detailed statistical analysis plan. The primary and secondary posted outcomes are continuous means, but that alone does not establish which test or model the investigators used.

What does over-dispersion mean in general?

Over-dispersion arises when observed variability is greater than a statistical model expects. It is especially relevant to count outcomes, where a simple model may assume a particular relationship between the mean and variance. If over-dispersion is ignored, standard errors can be too small and confidence intervals too narrow. It is not a central feature of the posted mean comparisons for glycated hemoglobin and cholesterol, and the registry record does not report a specific over-dispersion assessment.

For continuous outcomes, other assumptions may matter, including whether the analysis adequately represents the distribution of measurements and whether observations are independent. A basic comparison of group means does not automatically account for clustering by pharmacy unit or repeated measurements from the same participant. The registry record does not report whether such features were considered in the actual analysis.

What remains unknown about the analysis?

The factorial designation is recorded, but its factors and analysis are not reported in the registry record. There is no report of adjustment for baseline values, prespecified subgroup analyses, treatment-by-factor interactions, or corrections for examining multiple outcomes. Handling of missing observations, withdrawals, and protocol deviations is also not reported. The original sample-size justification and any interim analyses are not reported in the registry record.

These omissions limit how far summary-statistic calculations can be taken. They do not invalidate the arithmetic comparison of the posted numbers, but they mean that the recalculated result should be read as a transparent, unadjusted description rather than as a full reconstruction of the trial's intended inferential analysis.

11. Confidence Intervals and Precision

The primary estimate is a mean difference of -0.1 percentage points in glycated hemoglobin, with a 95% confidence interval from -0.765 to 0.565. This interval is wide relative to the point estimate and includes zero. It therefore reflects considerable uncertainty about both the direction and size of the underlying group difference. The point estimate alone gives a much narrower impression than the interval and should not be interpreted in isolation.

In general, confidence intervals help separate the estimated effect from its precision. An estimate near zero can be precise if its interval is narrow, or imprecise if the interval covers a broad range of values. In this comparison, the interval includes values that would represent a negative difference and values that would represent a positive difference under the intervention-minus-control convention. The data do not sharply locate the group difference.

The displayed interval is an unadjusted recalculation from the posted summary statistics. It does not include adjustment for baseline measurements, multiple outcomes, the factorial model designation, pharmacy unit, or other possible analysis features. Whether any of those adjustments were part of the investigators' analysis is not reported in the registry record. A confidence interval also does not account for bias from missing outcomes or problems with measurement and implementation.

The registry summary says confidence intervals of 95% were planned, but a sponsor-reported primary analysis is not listed. The precision described by the recalculated interval is therefore the precision of this simple comparison, not a claim that all sources of uncertainty have been accounted for. The separate cholesterol intervals have their own precision and should be interpreted in light of their secondary-outcome status and the absence of reported multiplicity 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 sample-size figures are planning illustrations for continuous outcomes and are expressed as participants per arm, not as total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The scenarios plan for the full observed effect, 75% of the observed effect, or 50% of the observed effect. The trial's original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that a planning calculation estimates would give an 80% chance of detecting the specified effect if that effect were truly present and the assumptions held. The 90% power column uses a higher target chance of detecting that effect, so it generally calls for more participants per arm. These are design-planning quantities, not measurements of what happened in this trial.

Smaller effects are harder to distinguish from random variation. Under otherwise similar assumptions, planning to detect a smaller fraction of the observed effect requires more participants per arm. The rows therefore illustrate how the required sample size changes when the target effect is reduced; they should not be read as evidence that the trial was designed around those scenarios.

This is not observed power. The figures are not a retrospective score of whether the completed trial had enough power, and they do not change the uncertainty in the posted outcome estimates. The observed estimates and their confidence intervals remain the relevant description of the trial's results. The registry record does not report the original effect size, variance assumptions, or other inputs used by investigators to choose the study's 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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.100; pooled standard deviation σ = 1.609.
2. n = 2 × (1.96 + 0.842)² × 1.609² / -0.100² = 4,063.2, rounded up to 4,064 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 <- -0.100000000000001                      # observed difference in means
sigma <- 1.60884766357716                     # 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(1580904)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 4,064 (80% power), 5,440 (90% power)
 75% of observed effect: n per arm = 7,224 (80% power), 9,671 (90% power)
 50% of observed effect: n per arm = 16,253 (80% power), 21,758 (90% power)
power.t.test: 4064.2 
Simulated power at n = 4,064 per arm: 0.796 (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 lists one primary outcome and two posted secondary outcomes, but it does not report a multiplicity-adjustment procedure or a hierarchy for interpreting tests. When several outcomes are tested, the chance of at least one apparently unusual result can increase. This is a general statistical issue, not evidence that any particular finding is false. Because the secondary comparisons are unadjusted, their nominal p values should be interpreted cautiously and alongside the primary result.

The record says a significance level of p < 0.05 and a 95% confidence interval were planned. It also refers to Student t tests, chi-square analysis, analysis of variance, and other tests if necessary. The specific tests used for each endpoint, whether any were adjusted, and whether the stated threshold applied to each separate outcome or to a family of outcomes are not reported in the registry record.

Missing-data methods and the number of participants with available measurements at each assessment are not reported in the registry record. The primary outcome description says the data are means of all patients per group, but it does not specify whether this means all randomized participants, all participants with a measurement, or another analysis population. The registry does not describe imputation, complete-case analysis, or sensitivity analyses for missing outcomes.

The record also does not report participant flow, reasons for withdrawal, protocol deviations, or whether analyses followed assigned group. These details affect how group comparisons should be interpreted, particularly if outcome availability differs between groups. The posted group counts should not be assumed to describe the same analysis population at every time point.

The registry labels the model factorial, but factors and any interaction analyses are not described. Baseline adjustment, clustering, and repeated-measures handling are also not reported. Interim analyses and stopping rules are not reported in the registry record. As a result, the unadjusted summary-statistic comparisons do not resolve these uncertainties about the trial's full analysis plan.

15. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: stomach pain (73.8%).

The registry lists serious adverse event figures for the control group as 31 affected among 42 at risk and for the intervention group as 34 affected among 47 at risk. It also lists other adverse event figures as 30 among 42 at risk in the control group and 32 among 47 at risk in the intervention group. These are the posted counts and denominators; they should be read as separate group summaries, not added together.

The most frequent serious adverse event term listed is stomach pain, at 73.8%. The record does not provide the denominator or further context for that percentage in the posted entry. The deaths field is null for both groups. A null entry does not establish that there were no deaths; it means a death count is not reported in the registry record.

These figures alone do not establish whether an event was caused by the intervention, how events were defined, or how severity and timing were assessed. The registry does not report further event narratives or an analysis comparing adverse-event risks. The counts are descriptive safety information and should not be treated as a causal comparison.

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

The primary posted comparison describes a small difference between the group means for glycated hemoglobin, with the intervention-group mean lower under the intervention-minus-control convention. Its unadjusted confidence interval includes zero and extends in both directions. Thus the posted summary does not provide a precise estimate of the direction or size of the primary group difference.

This is not the same as demonstrating equivalence or proving that there is no difference. Evidence for equivalence would ordinarily require a prespecified equivalence margin and an analysis designed to assess it; neither is reported in the registry record. Nor does a p value above the stated threshold show that the groups were identical. The estimate and confidence interval are the more informative way to describe the range of uncertainty in the posted primary comparison.

The secondary cholesterol outcomes show lower posted intervention-group means and unadjusted intervals that exclude zero, but they remain secondary analyses without reported multiplicity handling. They should not be used to replace the primary outcome or to make claims about outcomes that are not posted. In particular, the registry summary mentions glucose and quality of life, but does not provide corresponding posted results for those outcomes.

The trial record supports describing the design, intervention contrast, posted group summaries, and their recalculated unadjusted comparisons. It does not provide enough detail to verify the full analysis plan, assess missing-data bias, or determine whether the estimates account for baseline values or the factorial designation. The findings should therefore be understood as results reported in a limited registry record, not as a complete account of all trial analyses.

Statistical results also do not, on their own, determine clinical importance. That judgment would require context about meaningful differences, measurement and care settings, and other evidence. Such thresholds and evidence are not reported in the registry record. No treatment recommendation follows from these summary statistics.

17. Why This Trial Matters Statistically

This trial raises practical statistical questions common to clinical research: how to distinguish a group mean difference from its uncertainty, how to interpret a confidence interval that includes zero, and how to treat secondary outcomes when several measurements are examined. The primary estimate is close to zero, but its interval is broad enough to include differences in either direction. That combination makes precision central to interpretation.

The registry also illustrates why a planned analysis description and an analysis report are not interchangeable. It names several statistical procedures, but does not identify which procedures were actually applied to the posted endpoints. A simple recalculation can make the summary comparison transparent, yet it cannot reconstruct adjustments that need participant-level information or a detailed analysis plan.

The factorial model label is another reminder that a design description can be incomplete for statistical interpretation. Without information about the factors or their analysis, readers cannot determine whether interaction questions were intended or whether the posted comparisons reflect the full design. The same issue applies to masking: the single-blind designation does not identify who was masked.

Finally, the difference between the enrollment entry and the outcome-specific group counts emphasizes the importance of reporting participant flow and analysis populations. Counts at the outcome level affect precision and can help readers understand missingness. The record does not explain how its enrollment figure relates to the available primary-outcome summaries.

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 registry record leaves several trial-specific details unclear. It lists a factorial model but does not describe the factors, their levels, or whether analyses considered interactions. It labels the study single blind without identifying who was masked or how masking was maintained. Random sequence generation and allocation concealment are also not reported.

The record gives an enrollment of 100, while the posted outcome summaries report group-specific counts for the primary and secondary measures. It does not explain participant flow, why the outcome counts differ from the enrollment entry, or how many participants contributed at each assessment. The handling of missing measurements and withdrawals is not reported, limiting assessment of possible bias from incomplete follow-up.

The primary endpoint is described as an average over 24 weeks, but the record does not explain how measurements across that period were combined, whether baseline was included, or whether measurements were repeated at common scheduled visits. It does not report participant-level distributions, adjusted estimates, or a full statistical analysis plan. The method used to analyze each posted outcome is therefore unclear.

The registry summary mentions baseline glucose and quality of life in its description, but does not list posted results for these measures. Only total cholesterol and LDL cholesterol are listed as posted secondary results. A multiplicity strategy is not reported, so unadjusted secondary findings require caution. The sample-size justification, interim analyses, and stopping rules are not reported in the registry record.

Lastly, the adverse-event entries do not give further definitions, timing, event-level context, or an explanation of the null death fields. These limitations constrain interpretation of the safety summaries as well as the efficacy comparisons.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Impact of Pharmaceutical Care in Diabetics Patients — NCT01580904.
• Registry record last updated 2017-02-10; status last verified 2016-12.
• Results first posted 2017-02-10.
• 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, controlled, single-blind trial with a factorial model designation, studying pharmacist-led pharmaceutical care for people with type 2 diabetes in two pharmacy units in Brazil. The control group was not followed by a pharmacist; the intervention group received pharmacotherapeutic monitoring. The primary outcome was mean glycated hemoglobin up to 24 weeks, with total cholesterol and LDL cholesterol listed as secondary outcomes.

The posted primary group means were 7.2 for control and 7.1 for intervention. The recalculated unadjusted difference was -0.1, with a 95% confidence interval from -0.765 to 0.565 and p = 0.768. The interval includes zero and reflects uncertainty about the direction and size of the difference. Secondary cholesterol comparisons showed a different directional pattern, but multiplicity handling was not reported.

Important details—including the full analysis plan, missing-data handling, analysis populations, factorial factors, and original sample-size justification—are not reported in the registry record. The recalculations therefore offer a limited statistical reading of posted summaries rather than a reconstruction of the complete trial analysis.