A Study to Evaluate the Effect of Lipid Infusion on Toll Like Receptor 4 (TLR4) Signaling: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate the Effect of Lipid Infusion on Toll Like Receptor 4 (TLR4) Signaling (NCT01740817), a randomized na study. The primary outcome is Muscle Insulin Sensitivity-M Value.

2. Clinical Question

3. Trial Design

The registry describes a randomized, crossover study with no masking. Enrollment was 12, and the trial status is completed. The record lists Diabetes and Obesity as conditions and identifies The University of Texas Health Science Center at San Antonio as the sponsor. The recorded start was 2008-01 and primary completion was 2013-12. Phase is listed as NA.

The study used two infusion conditions: Intralipid 20% and saline. One sequence began with lipid infusion, followed after a washout period of 4-6 weeks by saline infusion; the other began with saline and then used the lipid infusion. Each infusion is described as 30ml/h x48h. This sequence structure is the basis for calling the design a crossover rather than a parallel-group comparison.

The primary outcome was Muscle Insulin Sensitivity-M Value, measured 48 hr after the lipid or saline infusion. The registry describes the M value as the exogenous glucose infusion rate at steady state, when that rate equals the rate of whole body glucose disposal. An insulin clamp was used to measure it. The secondary outcomes were TLR4 Messenger Ribonucleic Acid (mRNA) in Muscle and ERK Phosphorylation in Muscle, measured pre-clamp 48 hr following infusion.

The posted results give a mean and standard error for each condition and an unadjusted mean difference. They do not report an analysis of the paired crossover structure, such as a participant-level treatment contrast, or a model accounting for sequence or period. The registry record does not report the original statistical analysis plan, sample-size justification, handling of missing measurements, or analysis population definitions. These omissions limit how completely the posted comparisons can be connected to the design.

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: 12 of 52 participants were randomized. Of those not randomized, 40 did not meet inclusion criteria.

First Intervention (48 h)

Washout (4-6 Weeks)

Second Intervention (48 h)

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 Muscle Insulin Sensitivity-M Value, measured over 48 hr after lipid/saline infusion.

The primary endpoint is Muscle Insulin Sensitivity-M Value, reported in mg/kg.min. The M value is defined in the registry as the exogenous glucose infusion rate at steady state, when the exogenous glucose infusion rate is equal to the rate of whole body glucose disposal. Measurement was by insulin clamp, with the endpoint collected 48 hr after lipid or saline infusion.

The endpoint is intended to quantify muscle insulin sensitivity under the study conditions. The registry’s stated comparison asks whether lipid infusion reduces muscle insulin sensitivity compared with saline infusion. In statistical terms, the posted result compares the condition means and expresses their difference as Intralipid minus saline. The posted means are 8.3 for Intralipid and 9.9 for saline, with a mean difference of -1.6.

A continuous endpoint preserves the measured values rather than reducing them to categories. Its interpretation depends on the measurement procedure, timing, and analysis. Here, timing is specified as 48 hr after infusion, and the measurement method is described, but details such as the exact analysis model and how within-participant measurements were handled are not reported in the registry record. The mean difference therefore describes the posted summaries; it should not be treated as a complete account of the crossover analysis.

7. Results Posted in the Registry

• Intralipid: mean 8.30 versus 9.90 on control; difference -1.60 (95% CI -3.54 to 0.34), standardized effect d = -0.66; z-test p = 0.106.

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.

TLR4 Messenger Ribonucleic Acid (mRNA) in Muscle

• 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 errors.
• Result:
  • Intralipid: mean 1.60 versus 1.00 on control; difference 0.60 (95% CI 0.11 to 1.09), standardized effect d = 0.98; z-test p = 0.016.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Intralipid than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Extracellular Signal-regulated Kinase (ERK) Phosphorylation in Muscle

• 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 errors.
• Result:
  • Intralipid: mean 1.95 versus 1.00 on control; difference 0.95 (95% CI 0.26 to 1.64), standardized effect d = 1.11; z-test p = 0.007.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Intralipid than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The two secondary outcomes share a directional pattern: their posted means are higher following Intralipid than following saline. Their unadjusted confidence intervals exclude zero, and their unadjusted p-values are below 0.05. This describes the observed secondary measurements; it does not establish that the same pattern would appear in a larger study or under an analysis accounting for the crossover design.

These measures concern muscle signaling, whereas the primary outcome measures muscle insulin sensitivity by insulin clamp. The secondary findings therefore provide biological measurements related to the study’s stated interest in TLR4 signaling and insulin resistance, but they are not interchangeable with the primary endpoint. In particular, a directional change in a signaling measure does not settle the uncertainty around the primary mean difference. The primary result remains an unadjusted comparison with a confidence interval that includes zero.

Unadjusted secondary results carry less weight because more than one outcome is examined, and the chance of finding at least one apparently notable result can increase when several tests are considered. General explanation: multiplicity procedures are used in some analyses to control the overall error rate or to organize confirmatory testing. The registry record does not report such a procedure, a prespecified hierarchy, or adjusted secondary results. The secondary comparisons should therefore be treated cautiously and should not be read as independently confirmatory evidence.

The registry reports no secondary analyses beyond the posted summary comparisons. It does not report whether the secondary outcomes were prespecified in a detailed statistical plan, whether all planned measures were collected, or how missing measurements were handled. The pattern is informative as a description of the posted results, but incomplete analysis reporting and multiplicity uncertainty limit the strength of conclusions that can be drawn across endpoints.

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

• TLR4 Messenger Ribonucleic Acid (mRNA) in Muscle
• Extracellular Signal-regulated Kinase (ERK) Phosphorylation in Muscle

9. Statistical Interpretation

10. Statistical Methods Explained

For continuous outcomes, a mean describes the arithmetic average of the observed measurements. The posted results report means for each infusion condition. The primary means are 9.9 for saline and 8.3 for Intralipid. The corresponding unadjusted mean difference is expressed as Intralipid minus saline, giving -1.6. The sign tells the direction of the contrast: a negative value means the Intralipid mean is lower than the saline mean. It does not, by itself, establish the cause of that difference.

The registry reports standard errors alongside the means. A standard error describes the precision of an estimated mean, rather than the spread of individual participant measurements. General explanation: it reflects how much a sample mean would vary across repeated samples under an assumed sampling process. A smaller standard error generally indicates a more precise estimate, but it does not describe every participant’s value. The registry lists standard errors of 0.7 for both primary condition means.

The comparison also includes a confidence interval. General explanation: a confidence interval gives a range of values compatible with the data and the method used to construct it. Its long-run coverage interpretation depends on the statistical assumptions and repeated use of that method. It is not a guarantee that the true value lies in the interval, and it is not a range containing a specified proportion of individual responses. For the primary difference, the interval extends from -3.54 to 0.340 and includes zero. The interval therefore does not rule out a zero difference under the calculation used.

A p-value is a measure of how surprising data at least as incompatible with a null hypothesis would be if that hypothesis and the model assumptions held. The unadjusted primary p-value is 0.106. The secondary p-values are 0.016 for TLR4 mRNA and 0.007 for ERK phosphorylation. A p-value is not an effect size or a measure of clinical importance. It is also not the chance that a result is false. Because the secondary p-values are unadjusted and the record does not report a multiplicity procedure, they should be interpreted as exploratory indicators rather than definitive tests across a family of outcomes.

The crossover structure matters for analysis. General explanation: in a crossover study, the same participant can contribute measurements under more than one condition. An analysis can compare those within-participant measurements, often accounting for their paired nature. Such an approach can distinguish treatment-condition differences from stable differences among participants. It may also need to consider period and sequence effects, depending on the design and analysis plan. Those features cannot be evaluated from condition means and standard errors alone.

The registry record reports n 12 for each condition, but does not provide a participant-level paired contrast, its standard error, or a crossover model. The posted comparison is an unadjusted summary-statistic calculation. It may not capture the precision available from paired measurements, and its assumptions may differ from those used in a trial’s intended analysis. The record does not report the trial’s own statistical analysis plan or whether the original investigators used a paired procedure. No reported analyses are listed, so there is no registry-reported analysis to compare with the summary-based calculation.

For general context, over-dispersion occurs when variability is greater than the statistical model expects. If a model assumes less variability than is present, standard errors can be too small and confidence intervals too narrow. The posted outcomes are continuous means, and the record does not report a model-based analysis of dispersion. There is no basis in the registry record for asserting that over-dispersion occurred in this trial; the concept is relevant only as a general reminder that the uncertainty estimate depends on model assumptions.

The standard errors and mean differences do not communicate the complete distribution of the measurements. For example, means alone do not show whether individual responses were similar or varied widely, whether the data were skewed, or whether any observations were influential. Those features require information beyond the posted summaries. The registry record does not report raw outcome data or participant-level plots.

Planning calculations use the observed effect as a reference and illustrate sample sizes for specified fractions of that effect. The assumptions listed for these calculations are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. This is a planning illustration and is not the trial’s own design calculation. The original sample-size justification and statistical assumptions are not reported in the registry record. The crossover design also means that an illustration framed as equal allocation between two arms is not a substitute for a design-specific calculation using a paired treatment contrast.

11. Confidence Intervals and Precision

Precision concerns how tightly the data estimate a quantity, not whether the result is important in practice. The primary unadjusted mean difference is -1.6 mg/kg.min, with a confidence interval from -3.54 to 0.340. The interval includes zero and spans values consistent with a lower Intralipid mean, a near-zero difference, and a higher Intralipid mean. This range indicates uncertainty about both the direction and magnitude of the underlying difference under the calculation used.

The primary standard errors are 0.7 for each condition mean. Those values describe uncertainty in the estimated means, not the distribution of participant-level outcomes. Precision of a difference depends on the variability and relationship between measurements, especially in a crossover design. Since the registry record does not report the paired covariance, paired standard error, or a crossover model, the condition-level standard errors do not show how much a paired analysis might change the uncertainty.

The confidence interval should be read together with the point estimate. A point estimate is a single summary from the observed data; the interval communicates a range of values compatible with those data and the calculation’s assumptions. The interval is not proof that every value in it is equally plausible, and it does not guarantee that values outside it are impossible. Its interpretation also depends on whether the unadjusted summary-based method is appropriate for the study’s crossover structure.

The secondary confidence intervals are above zero for the reported unadjusted comparisons, but their interpretation is affected by the absence of a reported multiplicity plan and analysis model. The registry record does not report adjusted confidence intervals or a prespecified hierarchy for outcomes. Precision in a statistical sense is therefore only one part of interpretation; design, analysis assumptions, and the number of outcomes considered also matter.

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 expressed as participants per arm. They are not total event counts. The assumptions listed for the illustration are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is a stated fraction of the observed effect. The original trial’s own sample-size justification and design assumptions are not reported in the registry record.

The 80% power column means the illustrated number of participants per arm intended to give an 80% chance of detecting the specified effect under the planning assumptions, if that effect and those assumptions are correct. The 90% power column describes the corresponding illustration for a 90% chance. These are planning probabilities for a hypothetical repeated study, not probabilities that the posted result is true. This is not observed power.

The rows for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect represent progressively smaller target effects. Smaller effects generally require more participants to detect with the same planned power and significance level, because they are harder to distinguish from random variation. The figures differ by outcome because the observed effects and variability differ.

The illustrations use an equal-allocation, two-arm framing and a normal approximation. They should not be read as a reconstruction of the study’s original design process, which is not reported in the registry record. In particular, the trial is described as crossover, while the planning presentation is stated in per-arm terms; the record does not provide the paired-variance assumptions that would be needed to interpret a design-specific crossover calculation.

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 = -1.600; pooled standard deviation σ = 2.425.
2. n = 2 × (1.96 + 0.842)² × 2.425² / -1.600² = 36.1, rounded up to 37 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 <- -1.6                      # observed difference in means
sigma <- 2.42487113059643                     # 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(1740817)
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 = 37 (80% power), 49 (90% power)
 75% of observed effect: n per arm = 65 (80% power), 86 (90% power)
 50% of observed effect: n per arm = 145 (80% power), 194 (90% power)
power.t.test: 37 
Simulated power at n = 37 per arm: 0.801 (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 lists a primary endpoint and secondary outcomes, but it does not report a multiplicity adjustment, a testing hierarchy, or an analysis plan identifying which comparisons were intended to be confirmatory. The secondary p-values are therefore unadjusted. When several outcomes are examined, the chance of observing at least one apparently small p-value can rise even if none of the underlying effects is real. This general concern makes unadjusted secondary findings less conclusive than results supported by a prespecified multiplicity strategy.

The record lists no reported analyses. It therefore does not give a sponsor-reported model, adjusted estimates, or a clear account of the analysis population. Although enrollment and condition-level sample sizes are posted, the registry record does not state whether all enrolled participants contributed measurements to each outcome, whether any observations were excluded, or whether missing values occurred. The recorded null values for deaths are not a description of missing outcome data.

Missing-data methods matter because results can depend on why values are missing and how the analysis handles them. General explanation: complete-case analysis uses only participants with the required measurements, while other approaches may use assumptions or models to account for incomplete records. The appropriate approach depends on the missingness pattern and analysis question. The registry record does not report a missing-data method, reasons for missingness, or sensitivity analyses, so none can be inferred.

The crossover design also raises questions about period, sequence, and paired observations. The record describes the sequence and washout, but it does not report whether the analysis accounted for those features or how it handled a participant who might not have complete measurements in both periods. These omissions prevent a full assessment of how the posted estimates relate to the randomized crossover design. They do not establish that the original study failed to address these issues; they mean the registry record does not report the details needed to assess them.

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.

The adverse-event figures list 0 serious adverse events among 12 at risk for saline and 0 among 12 at risk for Intralipid. The registry also lists 0 other adverse events for each condition, with 12 at risk in each. These figures describe the posted event counts for the recorded groups; they do not show that no adverse events of any kind occurred beyond the categories and recording represented in the registry.

The death counts are null for both conditions. A null entry is not a reported zero, so the registry record does not report death counts. The list of top serious adverse-event terms is empty. This should be read as no terms listed in that field, rather than as evidence that every possible event category was assessed and ruled out.

These adverse-event summaries are limited by the small study enrollment and the absence of detailed event descriptions, collection methods, or follow-up information in the registry record. They cannot establish the absence of risk. They are a narrow account of the counts posted for the listed study conditions and categories.

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

The posted results describe a small randomized crossover study comparing lipid infusion with saline infusion. For the primary measure, the mean after Intralipid is lower than the mean after saline, and the unadjusted mean difference is -1.6 mg/kg.min. The confidence interval includes zero, leaving substantial uncertainty about the size and direction of the underlying difference under the summary-based calculation. The result does not establish a definitive difference between conditions.

The secondary signaling measures have higher posted means following Intralipid than saline, with unadjusted intervals excluding zero. These findings describe the recorded data, but the registry does not report multiplicity adjustment or a detailed analysis plan. They should not be treated as proof that the primary outcome changed, nor do they establish a mechanism or clinical consequence.

General explanation: statistical significance and practical importance are different questions. A p-value does not measure the size of an effect, and a confidence interval does not say whether a difference matters to patients or to clinical decisions. The registry record does not provide a threshold for a clinically important M value difference or context for judging clinical importance.

The crossover format may allow comparisons within participants, but the registry does not report a paired estimate or the model used to account for repeated conditions. The available unadjusted summaries do not reveal how the relationship between each participant’s measurements affected the uncertainty. Therefore, the posted comparisons should be interpreted as descriptive summary-based evidence, not as a complete analysis of the trial design.

The registry record does not report detailed baseline characteristics, missing-data handling, the original statistical analysis plan, or the sample-size justification. Those gaps, along with the absence of reported analyses, restrict assessment of bias, precision, and reproducibility. The findings do not establish whether lipid infusion improves or worsens health, and they should not be used as medical advice. They characterize the posted outcomes under the study conditions only.

17. Why This Trial Matters Statistically

This study is statistically notable because its crossover design and posted results invite different levels of analysis. A crossover study can compare conditions within participants, potentially accounting for stable individual variation. Yet the registry presents condition means and an unadjusted difference without reporting the paired analysis or model. The distinction matters: an estimate based only on group summaries may not reflect the precision or assumptions of the intended crossover analysis.

The primary and secondary outcomes also illustrate why endpoints must be interpreted separately. The primary measure concerns insulin sensitivity, while the secondary outcomes assess muscle signaling. The posted secondary pattern is directional, but it does not eliminate uncertainty in the primary comparison. Unadjusted testing across multiple outcomes makes it particularly important to know whether an analysis hierarchy or multiplicity procedure was prespecified; that information is not reported in the registry record.

The confidence interval gives a more informative account of uncertainty than the point estimate alone. The primary interval includes zero and spans values in both directions, so the posted result does not narrowly identify the condition difference. Its interpretation is further limited by the lack of reported crossover-model details. This is a useful example of why statistical reporting needs to connect the design, estimand, model, and uncertainty measure.

Finally, the planning illustrations are not observed power and do not explain the original enrollment decision. They show how planned participant counts vary with target effect under stated assumptions, while the trial’s own justification is not reported. Separating descriptive results, analysis assumptions, and planning calculations helps prevent a small study’s numerical outputs from being mistaken for a complete evidentiary conclusion.

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 contains limited detail on the analysis relative to the crossover design. It does not report a paired treatment estimate, the statistical model, or whether sequence and period were considered. The posted condition summaries cannot show the within-participant relationship between measurements, which can be important for estimating uncertainty in a crossover study.

Enrollment was 12, and the posted condition summaries list n 12 for each condition. The record does not report a sample-size justification or clarify how the original design assumptions were set. The planning illustrations are based on the observed effect and stated generic assumptions, not on the trial’s documented design rationale.

The record does not report baseline characteristics, eligibility details, analysis population definitions, missing-data handling, or sensitivity analyses. It is therefore not possible from the registry record to assess the influence of incomplete measurements or exclusions. Nor does it report a detailed statistical analysis plan, multiplicity procedure, or adjusted secondary comparisons.

The outcomes were collected at the specified post-infusion time, and the record gives means and standard errors rather than participant-level distributions. That limits assessment of variability, outliers, and response patterns. The adverse-event listing is also sparse: serious and other event counts are posted, but death counts are null and detailed follow-up or event ascertainment information is not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Study to Evaluate the Effect of Lipid Infusion on Toll Like Receptor 4 (TLR4) Signaling — NCT01740817.
• Registry record last updated 2016-01-25; status last verified 2015-12.
• Results first posted 2016-01-25.
• 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

NCT01740817 is a completed randomized, unmasked crossover study sponsored by The University of Texas Health Science Center at San Antonio. The registry lists enrollment of 12 and conditions of Diabetes and Obesity. Participants received Intralipid 20% and saline in different sequences, with a 4-6 weeks washout period.

The primary outcome was muscle insulin sensitivity measured as the M value by insulin clamp 48 hr after infusion. The posted means were 8.3 mg/kg.min for Intralipid and 9.9 mg/kg.min for saline, with an unadjusted mean difference of -1.6 and a confidence interval that includes zero. The secondary outcomes were TLR4 mRNA and ERK phosphorylation in muscle.

The registry record does not report trial analyses, the original statistical plan, a multiplicity procedure, or missing-data methods. The posted results support descriptive comparisons but leave important details of the crossover analysis and outcome interpretation unresolved.