The Effects of the Dietary Supplement CardioFlex Q10 on Reducing Cardiovascular Disease Risk Factors in Adults: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effects of the Dietary Supplement CardioFlex Q10 on Reducing Cardiovascular Disease Risk Factors in Adults (NCT03826914), a randomized na study. The primary outcome is Change From Baseline of Total Cholesterol After 90 Days.

2. Clinical Question

The registry record identifies the study as randomized, triple masked, and parallel group. Those design features describe allocation and masking, but the record does not explain how masking was implemented or how randomization was generated. The clinical question concerns a measured risk factor over the stated study period; it is not a question about cardiovascular events such as heart attack or stroke. Those conditions appear in the record’s list of conditions, but the primary outcome is total cholesterol change.

3. Trial Design

The registry record describes a completed, randomized, triple-masked, parallel study sponsored by the University of Manitoba. Enrollment is listed as 69. The record gives a start date of 2018-11-06 and a primary completion date of 2019-06-01. The study is marked completed, and its phase is listed as NA.

Participants were assigned to Cardioflex or placebo. The experimental-group description specifies one 10g serving of Cardioflex each day. The control-group description specifies a flavoured 10g placebo intended to look and taste exactly like Cardioflex. Triple masking indicates that the record characterizes the study as masked at three levels, but the identities of those levels and the practical masking procedures are not reported in the registry record. The method used to generate the random allocation sequence and the allocation-concealment procedure are also not reported in the registry record.

The primary endpoint was change in total cholesterol between baseline and day 90. The record posts 34 participants in the Cardioflex group and 33 in the placebo group for that outcome. Separate safety figures give 35 at risk in the experimental group and 34 in the control group. The record does not explain the difference between these outcome and safety counts, so they should be read as the counts posted for their respective analyses rather than reconciled by assumption.

The registry record names heart rate variability as a secondary outcome and posts results for it. It lists two outcome measures and two analyses, while one secondary outcome is posted. Further details about eligibility, recruitment, follow-up completion, adherence, protocol amendments, and analysis populations are not reported in the registry record. The planned enrollment target and the original design assumptions are likewise not reported in the registry record.

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:

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: 69 participants started the clinical trial, 35 in the Cardioflex group and 34 in the Placebo group.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline of Total Cholesterol After 90 Days, measured over Baseline and 90 days.

The primary endpoint is change from baseline in total cholesterol after 90 days, measured in mmol/L. The registry record defines the change as the day 90 score minus the baseline score. A negative change therefore represents a lower measured total cholesterol value at day 90 than at baseline; a positive change represents a higher value at day 90. The endpoint is a continuous measure, and the posted group summaries are means with standard deviations.

Total cholesterol is described in the record as the total amount of cholesterol in the blood. It is used as a cardiovascular risk factor, consistent with the study’s stated objective of examining changes in risk factors rather than cardiovascular events. The outcome therefore describes a laboratory measure over the study period; it does not directly count heart attacks, strokes, or other clinical events.

For the Cardioflex group, the mean change was -0.57 mmol/L, with a standard deviation of 1.06, among 34 participants. For the placebo group, the mean change was -1.09 mmol/L, with a standard deviation of 1.05, among 33 participants. These summaries describe average within-group changes. A comparison between the groups addresses whether their average changes differed, but does not by itself explain individual responses or establish what happened beyond the stated measurement period.

The registry record also reports an analysis of covariance for the primary outcome, with a median difference labelled net. Its reported measure is not the same summary as the difference between the posted group means. The registry record does not provide further detail about the covariates used or the precise contrast sign convention.

7. Results Posted in the Registry

• Cardioflex Group: mean -0.57 versus -1.09 on control; difference 0.52 (95% CI 0.01 to 1.03), standardized effect d = 0.49; z-test p = 0.044.

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.

Heart Rate Variability

• 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:
  • Cardioflex: mean 3.49 versus -6.27 on control; difference 9.76 (95% CI 4.63 to 14.89), standardized effect d = 0.91; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Cardioflex than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Heart rate variability is the only secondary outcome with results posted in the record. Its recalculated change comparison has a mean difference of 9.76 ms, with an interval from 4.633 to 14.89 and an unadjusted p-value of <0.001. The registry analysis reports a mean difference in final values of -6.772, with a 95% confidence interval from -11.2 to -2.24 and p = 0.04. The reported analyses use different descriptions of the outcome contrast, so their estimates should not be treated as interchangeable.

At a broad level, both the primary and posted secondary outcomes have reported comparisons whose intervals exclude zero and p-values below 0.05. That pattern is a description of the posted statistical results, not independent confirmation of a single underlying effect. The primary outcome is total cholesterol change; the secondary outcome is heart rate variability. They are distinct measures and have different analysis summaries in the registry record.

The secondary result carries less weight as confirmatory evidence because it is secondary and its reported comparison is unadjusted for multiplicity according to the information available in the record; a multiplicity plan is not reported in the registry record. When several outcomes or analyses are examined, the chance of obtaining at least one apparently strong result by chance can increase unless the analysis plan accounts for that multiplicity. The record does not report how many outcomes were originally planned beyond its count of outcome measures, or whether any adjustment strategy was prespecified.

The record lists two outcome measures and posts one secondary outcome. It does not report whether other outcomes were collected but not posted, or whether the listed secondary measure was the sole planned secondary endpoint. These uncertainties make selective reporting difficult to assess. The secondary finding can be considered alongside the primary result, but should not be treated as a substitute for the primary analysis or as a standalone basis for broad conclusions.

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

• Heart Rate Variability

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference represent?

A mean is an average across participants. For this endpoint, each participant’s change is defined as the day 90 measurement minus the baseline measurement, and the posted arm summaries report the mean of those changes. Comparing the two means gives a contrast between the groups’ average changes. The recalculated contrast uses the Cardioflex mean minus the placebo mean, so its sign follows that ordering. The reported estimate is 0.52 mmol/L. This is an unadjusted comparison based on the posted summary statistics, rather than a model that accounts for baseline values or other covariates.

The standard deviation describes how spread out participant-level changes are around a group mean. It is not the uncertainty of the group mean itself. Uncertainty in an estimated mean or contrast is often summarized with a standard error and a confidence interval. The registry record’s displayed comparison includes standard errors for the arm means, while the reported arm summaries include standard deviations. Those quantities serve different purposes: standard deviations describe observed variability, while standard errors describe sampling uncertainty in an estimate.

What is the purpose of a confidence interval?

A confidence interval gives a range of values compatible with the data and the assumptions of the estimation method. It communicates both the estimated contrast and its precision. A narrower interval indicates less statistical uncertainty about the contrast than a wider interval, all else equal. An interval that includes zero is compatible with no difference under the specified contrast, while an interval entirely on one side of zero indicates that the corresponding set of values excludes zero. This does not establish clinical importance, and it does not capture every source of uncertainty, such as limitations in study design, measurement, or reporting.

The recalculated interval for the mean difference is 0.015 to 1.025. The registry-reported primary analysis instead gives a 95% confidence interval from -0.846 to -0.015 for its median difference (net). The estimate and interval from the registry analysis should be interpreted together, using that analysis’s measure and contrast convention. The registry record does not report enough detail to reconstruct the adjusted analysis independently.

Why do the two primary estimates differ?

The recalculation compares posted means of change without adjustment. The registry record reports an analysis of covariance and labels its measure as a median difference (net). A mean contrast and an adjusted median contrast need not have the same numerical value or sign when the comparison is coded in a different order. The registry record does not report the covariates, model specification, or sign convention, so the exact reason for the numeric difference cannot be established from the record. The recalculated analysis is not a replacement for the trial’s own analysis.

The reported p-values, 0.044 for the unadjusted recalculation and 0.042 for the registry analysis, summarize how compatible the respective results are with a null contrast under their statistical assumptions. A p-value is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. A small difference between these p-values does not make the analyses equivalent; the estimands, adjustment, and summary measures remain distinct.

Why can variation and over-dispersion matter?

For a continuous endpoint, the standard deviation helps show how much participant-level results vary. When variation is large relative to the contrast, estimates tend to be less precise unless there are more observations or other design features that improve precision. In settings where outcomes are counts, over-dispersion means that the observed variation exceeds what a model’s simplest assumptions allow. It can lead to uncertainty estimates that are too small if not handled appropriately. That general issue is not a description of this primary endpoint, which is continuous, and the registry record does not report an over-dispersion assessment.

The posted primary standard deviations are 1.06 and 1.05 mmol/L, and the recalculation uses a pooled standard deviation of 1.055. A pooled standard deviation combines within-group variability for the unadjusted comparison under its assumptions. It does not imply that participant-level outcomes are identical across groups, nor does it remove uncertainty about the estimated contrast.

What assumptions apply to the planning illustrations?

The sample-size planning figures are illustrations based on the observed effect, not the trial’s own original design. Their stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. These assumptions describe those planning calculations only. The original sample-size justification and the assumptions used when designing this trial are not reported in the registry record.

Planning calculations translate a chosen effect size and statistical assumptions into a participant requirement for a target probability of detecting that effect under the model. They do not establish what the trial’s observed probability of detection was. The observed study results, the planned design, and a hypothetical future study calculation are separate quantities. The planning illustrations use the observed contrast as their reference, so they are sensitive to how large that estimate happens to be and should not be read as proof that the same effect would recur.

In general, the analysis method should be interpreted alongside the design, endpoint definition, missing-data handling, and analysis population. The registry record gives the primary outcome definition, arm summaries, and the named analysis method, but does not report full model details, missing-data methods, or the analysis-population definition. Those absences limit how far an independent reader can reproduce or evaluate the reported adjusted result.

11. Confidence Intervals and Precision

The unadjusted mean-difference estimate for primary total cholesterol change is 0.52 mmol/L, with a recalculated interval from 0.015 to 1.025. The interval is asymmetric around the rounded estimate as posted, so its endpoints should be quoted as recorded rather than reconstructed or altered. Its lower endpoint is close to zero, while the upper endpoint allows a larger positive contrast. That span conveys uncertainty about the magnitude of the unadjusted difference; a point estimate alone would hide that uncertainty.

The registry-reported primary result is a median difference (net) of -0.43, with a 95% confidence interval from -0.846 to -0.015. This interval is entirely below zero under the registry analysis’s reported contrast convention. Because its summary measure and adjustment differ from the recalculated mean contrast, the two intervals are not alternate versions of one identical estimate. The contrast sign convention and covariates for the registry analysis are not reported in the registry record.

Confidence intervals describe sampling uncertainty conditional on the method and its assumptions. They do not account automatically for every limitation, such as incomplete outcome data, measurement quality, selective reporting, or departures from the analysis model. The registry record does not report enough information to assess all of those possibilities. A confidence interval also does not indicate whether a difference is important in practice; that requires context not established by the statistical interval alone.

The primary outcome groups include 34 and 33 participants, and the posted standard deviations are 1.06 and 1.05 mmol/L. These summaries and the interval help characterize the precision of the comparison, but they do not reveal the individual distribution of change. The record does not report a prespecified threshold for a meaningful change or a minimum clinically important difference. Therefore the precision can be described statistically, while the practical importance cannot be determined from the interval alone.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total event counts. The calculation is a planning illustration based on the observed effect, with a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to 100%, 75%, or 50% of the observed effect. These are planning assumptions for the illustration; the original design assumptions and sample-size justification for the trial are not reported in the registry record.

The 80% power column gives the calculated participants per arm for an assumed study to have an 80% probability of detecting the selected effect under the stated assumptions, if that effect and model assumptions hold. The 90% power column gives the corresponding requirement for a 90% probability. These are not guarantees for a particular study, and they are not estimates of the power achieved by the completed trial. The figures are planning illustrations, not observed power.

For the primary outcome, planning for 100% of the observed effect gives 65 participants per arm for 80% power and 87 participants per arm for 90% power. Planning for 75% of the observed effect gives 115 participants per arm for 80% power and 154 participants per arm for 90% power. Planning for 50% of the observed effect gives 259 participants per arm for 80% power and 347 participants per arm for 90% power.

The pattern reflects a general feature of power calculations: smaller effects are harder to distinguish from random variation, so more participants are needed to achieve the same target power when other assumptions are held constant. These figures do not show what enrollment should have been for the original trial, because its design assumptions are not reported. They also depend on the observed effect used as the reference, which may not be a stable estimate of the effect in another 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 = 0.520; pooled standard deviation σ = 1.055.
2. n = 2 × (1.96 + 0.842)² × 1.055² / 0.520² = 64.6, rounded up to 65 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 <- 0.52                      # observed difference in means
sigma <- 1.0550887676837                     # 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(3826914)
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 = 65 (80% power), 87 (90% power)
 75% of observed effect: n per arm = 115 (80% power), 154 (90% power)
 50% of observed effect: n per arm = 259 (80% power), 347 (90% power)
power.t.test: 65.6 
Simulated power at n = 65 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. Analyses Reported by the Sponsor

The registry record’s own primary analysis is an analysis of covariance. It reports a median difference (net) of -0.43, with a 95% confidence interval from -0.846 to -0.015 and p = 0.042. The recalculated result is an unadjusted difference between the posted mean changes: 0.52 mmol/L, with an interval from 0.015 to 1.025 and an unadjusted p-value of 0.044.

These estimates are not directly interchangeable. One is the registry-reported adjusted median difference, while the recalculation is a simple unadjusted mean difference. The registry record does not identify the covariance model’s covariates, explain the sign convention, or give enough detail to reproduce that analysis. The primary reported estimate’s negative sign therefore should not be interpreted as contradicting the positive recalculated contrast without knowing how the registry analysis coded the groups.

The estimates differ in value and sign, but the registry record does not flag a discrepancy, and the results have similar p-values. Each interval excludes zero under its own reported contrast. The registry analysis remains the trial’s own reported analysis; the recalculation is a separate, unadjusted check using the posted arm summaries. Neither comparison alone establishes clinical importance.

15. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity strategy for the primary and secondary outcomes, or for any additional analyses. Multiplicity arises when several statistical hypotheses are tested: even if each test uses the same nominal threshold, the chance of at least one result crossing that threshold can rise as the number of tests increases. A prespecified hierarchy, adjustment procedure, or clearly designated primary analysis can help readers understand how to interpret multiple results. No such details are reported in the registry record, so the unadjusted secondary p-value should be treated as exploratory rather than as conclusive confirmation.

The record identifies total cholesterol change as the primary outcome and heart rate variability as a secondary outcome. It lists two outcome measures and two analyses, but does not provide a complete statistical analysis plan or establish whether all planned analyses are posted. The trial’s original sample-size justification, planned interim analyses, and any stopping rules are not reported in the registry record. It would be inappropriate to infer that these procedures were or were not used.

Missing-data handling is also not reported. The outcome summaries include 34 participants for Cardioflex and 33 for placebo, while the safety counts list 35 and 34 at risk. The registry record does not explain these distinct counts, report the number of missing primary measurements, or describe an imputation or other missing-data method. It also does not state whether the analysis followed intention-to-treat, per-protocol, or another population definition. Without those details, the impact of missing observations and analysis-set selection cannot be assessed from the posted summaries.

The record gives the name analysis of covariance for the primary analysis, but does not report its covariates, assumptions, model diagnostics, or handling of baseline values. It also does not report whether the method was specified before examining the results. These omissions limit independent reproducibility. They do not establish that the analysis was inappropriate; they mean that the registry entry does not contain the information needed to evaluate those aspects 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.

The safety figures are presented separately from the primary outcome counts. The experimental group has 35 participants at risk for serious adverse events and 35 at risk for other adverse events; zero are listed as affected in each category, and deaths are listed as zero. The control group has 34 at risk for serious adverse events and 34 at risk for other adverse events; zero are listed as affected in each category, and deaths are listed as zero. No top serious-event terms are listed.

These are counts recorded in the registry, not estimates of comparative risk with confidence intervals. The record does not provide event descriptions, severity grading for non-serious events, duration of safety follow-up, or further detail about how events were collected and classified. The absence of recorded events in these categories should not be taken to mean that no adverse experiences of any kind occurred, since the record does not give that broader information.

The safety denominators differ from the primary outcome counts of 34 and 33. The registry record does not explain the difference. The safety figures therefore should be read using their own at-risk counts, without assuming that they correspond to the same analysis population or outcome availability as the primary endpoint.

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

The results describe a randomized comparison of CardioFlex Q10 and placebo on measured cardiovascular risk factors over the study’s stated 90-day period. For total cholesterol, both posted group means changed downward from baseline, and the unadjusted mean changes differed. The registry analysis also reports a primary comparison with an interval that excludes zero under its stated contrast. These are statistical findings about the posted endpoint and analysis; they do not by themselves establish the practical importance of the difference.

Total cholesterol and heart rate variability are measurements, not cardiovascular events. The record does not report whether supplementation changed the incidence of heart attack, stroke, or other clinical outcomes. Nor does it provide results beyond the stated measurement period. It is therefore not possible to infer long-term effects or effects on disease events from these outcome summaries.

The study objective says the supplement’s effect was to be assessed independently of other dietary or physical activity changes. The registry record does not describe how those changes were assessed, controlled, or incorporated into the analysis. The posted data also do not provide enough detail about adherence, missing outcomes, or analysis populations to establish how those issues influenced the results. Statistical associations in this trial should be read in the context of those reporting gaps.

The uncertainty intervals indicate a range of estimates compatible with the analyses, but they do not resolve questions about clinical meaning, generalizability, bias, or reproducibility. The registry record does not report an eligibility profile detailed enough to characterize which adults the results may best represent. It also does not report a threshold for a clinically meaningful change. The statistics therefore support a careful description of the observed comparisons, not medical advice or a universal conclusion about the supplement.

18. Why This Trial Matters Statistically

This trial illustrates why an estimated contrast should be read alongside its definition and analysis method. The primary endpoint is a change score, and the simple recalculation compares group means of that change. The registry analysis is described as an analysis of covariance and reports a median difference (net). Those approaches can yield estimates with different scales or signs, particularly when the contrast convention is not stated. Readers need the analysis details to determine exactly how results map onto the treatment ordering.

The record also shows why p-values alone are incomplete. The reported p-values are close, but neither communicates the full range of plausible contrast values or establishes whether a difference matters clinically. The recalculated interval and the interval for the registry analysis accompany different estimands and must be interpreted separately. Precision, endpoint definition, and the distinction between adjusted and unadjusted analyses are central to understanding the evidence.

Planning calculations based on an observed effect also demonstrate how sample-size requirements depend on the effect a future study aims to detect. Smaller assumed effects require more participants under the stated calculation assumptions. Because these are illustrations rather than the original trial’s design justification, they should not be used to infer why the trial enrolled its observed number of participants or whether its original design was adequate.

Finally, the registry record leaves several evaluation questions open: missing-data handling, analysis populations, multiplicity, full model specification, and the original sample-size rationale are not reported. Clear reporting of these elements helps readers distinguish a confirmatory analysis from exploratory comparisons and assess how much confidence to place in estimates. The posted statistics are interpretable, but their limitations in reporting should remain visible alongside the findings.

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 primary outcome groups include 34 and 33 participants, while the safety summaries list 35 and 34 at risk. The registry record does not explain why the counts differ. It also does not report the number of participants with missing baseline or day 90 values, the handling of missing data, or the population used for each analysis. These details matter because the posted summaries cannot show whether unavailable measurements or analysis-set decisions affected the estimated contrasts.

The adjusted primary analysis is named as analysis of covariance, but its covariates, model specification, assumptions, and diagnostics are not reported. The registry record labels its estimate a median difference (net), but does not describe the sign convention. Consequently, the adjusted estimate cannot be fully reconstructed from the record, and its direction should not be inferred by comparing its sign directly with the unadjusted mean difference.

The record does not report a multiplicity plan, interim analyses, stopping rules, protocol changes, or the original sample-size justification. It lists two outcome measures and posts one secondary outcome, but does not establish whether all outcomes planned or collected are represented. The absence of these details prevents a full assessment of outcome selection and analysis flexibility.

Descriptions of eligibility, participant characteristics, adherence, and follow-up beyond day 90 are not reported in the registry record. The stated objective concerns supplement use independently of other dietary or physical activity changes, but the record does not explain how such changes were measured or handled. Finally, the primary and secondary measures are risk-factor outcomes rather than reported cardiovascular events, and the registry record does not provide evidence about effects beyond the measured period.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: The Effects of the Dietary Supplement CardioFlex Q10 on Reducing Cardiovascular Disease Risk Factors in Adults — NCT03826914.
• Registry record last updated 2020-10-29; status last verified 2019-12.
• Results first posted 2020-10-29.
• 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

NCT03826914 is a completed randomized, triple-masked, parallel study sponsored by the University of Manitoba, with enrollment listed as 69. It compared daily CardioFlex Q10 with a flavoured placebo and assessed cardiovascular risk factors in adults. The primary endpoint was change in total cholesterol from baseline to day 90, measured in mmol/L.

The posted mean changes were -0.57 for 34 Cardioflex participants and -1.09 for 33 placebo participants. The unadjusted mean-difference recalculation is 0.52, with an interval from 0.015 to 1.025 and p = 0.044. The registry’s analysis of covariance reports a median difference (net) of -0.43, with a 95% confidence interval from -0.846 to -0.015 and p = 0.042. One secondary outcome, heart rate variability, has results posted.

The record does not report the original sample-size justification, missing-data methods, analysis-population definition, or multiplicity plan. Its safety figures list zero serious adverse events, zero other adverse events, and zero deaths in the posted group counts; further safety details are not reported.