Time Limited Eating in Adolescents (Time LEAd): a Pilot Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Time Limited Eating in Adolescents (Time LEAd): a Pilot Study (NCT03954223), a randomized na study. The primary outcome is Percent Change in BMI in Excess of the 95th Percentile (%BMIp95).

2. Clinical Question

The registry describes a randomized, parallel-group pilot study with three treatment groups. Its primary outcome is a continuous measure, and the posted arm results report the mean change and standard deviation for each group. The central statistical question is not whether a particular group’s mean change differs from zero, but how precisely the groups differ from one another and what range of between-group differences remains compatible with the posted data.

The group descriptions distinguish two components: time-limited eating and access to real-time continuous glucose monitor feedback. Comparisons can therefore address the diet-only group against each combined intervention group, but they should not be read as isolating every component independently. In particular, the posted pairwise comparisons do not constitute a separate estimate of the effect of monitor feedback among otherwise identical groups unless the comparison is specifically between the two time-limited-eating groups.

The brief summary describes a proposal for 90 participants, while the registry record lists enrollment of 50. The relationship between that proposed number and the final enrollment is not reported in the registry record. The posted arm counts are 15, 19, and 16, respectively. The record labels the study completed, but the primary outcome results alone do not establish how well the findings generalize beyond this pilot population.

3. Trial Design

The registry identifies NCT03954223 as Time Limited Eating in Adolescents (Time LEAd): a Pilot Study, sponsored by Children's Hospital Los Angeles. It is classified as a randomized, single-masked, parallel-group study. The record lists the study as completed, with a start date of 2020-03-01 and primary completion date of 2022-01-30. The phase is listed as not applicable.

The brief summary describes a randomized controlled trial with three groups and a 12-week intervention. The first group received a low-sugar and carbohydrate diet, defined in the summary as <90 gm carbohydrate per day and <25 gm added sugar per day, plus a blinded continuous glucose monitor. The second received the same diet with time-limited eating, described as a 16-hour fast and 8-hour eating period for 3 days per week, and a blinded monitor. The third received the diet and time-limited eating with real-time monitor feedback. The intervention records identify the behavioral components as the diet and time-limited eating, and the device component as the continuous glucose monitor.

The registry lists enrollment of 50. The three posted arm counts are 15 for the diet with blinded monitor group, 19 for the time-limited-eating group with blinded monitor, and 16 for the time-limited-eating group with real-time feedback. These are the group counts accompanying the primary outcome results; the registry record does not explain the difference between the enrollment figure and the 90 participants described in the brief summary as proposed.

The primary endpoint was the change in percent BMI in excess of the 95th percentile from baseline to Week 12. The record also lists Average Glucose as a secondary outcome. It reports two outcome measures and two analyses, but details of the other measure and its results are not included in the posted results. The record does not report the randomization procedure, masking details, or the original statistical design assumptions.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Percent Change in BMI in Excess of the 95th Percentile (%BMIp95), measured over %BMIp95 at Week 12 minus %BMIp95 at baseline.

The primary endpoint is percent change in BMI in excess of the 95th percentile, abbreviated in the registry as %BMIp95. It is based on BMI relative to the 95th percentile for a child’s sex and age, using CDC extended SAS equations. The registry defines the measured value as %BMIp95 at Week 12 minus %BMIp95 at baseline. Thus, the endpoint is a change score over the intervention period, rather than a single BMI measurement at Week 12.

A measure expressed relative to the 95th percentile can describe how far BMI lies beyond that reference point while accounting for age and sex. This can be useful in a population where BMI values are above the usual 95th-percentile threshold, because it focuses on the amount in excess of that threshold rather than only reporting the percentile itself. This is a general description of the measure; the registry does not report a separate rationale for choosing it as the primary endpoint.

Because the outcome is continuous, the posted arm summaries use means and standard deviations. The reported mean change was -3.27 in the low-sugar and carbohydrate diet with blinded monitor group, -3.76 in the group adding time-limited eating with a blinded monitor, and -4.85 in the group adding time-limited eating with real-time feedback. A negative change indicates that the Week 12 value was lower than the baseline value under the registry’s subtraction definition. The group means describe the observed changes, but they do not by themselves show whether the between-group differences are precise or distinguishable from chance variation.

The registry includes a technical description of the calculation, including an illustrative example, but it does not report a minimal important difference or a threshold for interpreting a change as clinically meaningful. The posted endpoint should therefore be read as a statistical measure of change, not as a standalone judgment about clinical importance.

7. Results Posted in the Registry

• LSC+TLE + Blinded CGM: mean -3.76 versus -3.27 on control; difference -0.49 (95% CI -3.58 to 2.60), standardized effect d = -0.10; z-test p = 0.756.
• LSC+TLE+ Real Time Feedback Via CGM: mean -4.85 versus -3.27 on control; difference -1.58 (95% CI -4.59 to 1.43), standardized effect d = -0.37; z-test p = 0.303.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous, and the registry reports a mean and standard deviation for each treatment group. A mean is the arithmetic average of participants’ measured changes. The standard deviation describes how spread out individual changes were around the group mean. These measures answer different questions: the mean describes the group’s average change, while the standard deviation describes variability among participants.

What does a mean difference compare?

A mean difference subtracts one group’s mean from another group’s mean. The recalculated comparisons use the low-sugar and carbohydrate diet with blinded monitor as the reference group. The estimated difference of -0.49 compares that group with the group adding time-limited eating and using a blinded monitor. The estimated difference of -1.58 compares it with the group adding time-limited eating and using real-time feedback. The negative signs follow the order of subtraction used in the calculation; they do not independently establish a benefit or a meaningful effect.

The pairwise estimates are labelled recalculated because they are simple, unadjusted calculations from the posted arm-level summaries. They are not adjusted for baseline characteristics, nor do they incorporate a model beyond the stated calculation. The registry’s own reported analysis is an analysis of variance across all three groups. The record does not provide adjusted pairwise estimates or a detailed model specification.

What does the analysis of variance test?

Analysis of variance, often abbreviated ANOVA, is a general method for comparing the means of multiple groups. An overall ANOVA test evaluates whether the observed pattern of group means is inconsistent with a common mean under the model. A small p-value can indicate evidence against that common-mean hypothesis, but the overall test does not say which groups differ or quantify a specific pairwise contrast. The registry reports p = 0.4 for its three-group ANOVA. It does not report the test statistic, degrees of freedom, or an interval for the overall comparison.

How should the p-values be read?

A p-value measures how incompatible the observed data are with a specified null hypothesis, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The recalculated pairwise p-values are unadjusted: they do not account for testing multiple pairwise comparisons. The registry’s p = 0.4 is the reported result for the overall ANOVA, not a p-value for either pairwise recalculation. The registry record does not report a multiplicity plan.

The p-values should be interpreted alongside the effect estimates and confidence intervals. A p-value alone cannot show whether a difference is practically important, nor can a result that does not provide strong evidence against a null hypothesis establish that two groups are equivalent. Equivalence requires a prespecified range of differences that would count as sufficiently similar; such a range is not reported in the registry record.

Why does variability matter?

The spread of participant outcomes affects how precisely a group mean or group difference can be estimated. General statistical principle: greater variability makes it harder to distinguish a group difference from random variation when other design features are held fixed. The standard deviations differ across the three arms, and the posted group counts are modest, so the pairwise estimates have broad confidence intervals. The registry does not report a variance model or a plan to accommodate unequal variability.

Over-dispersion is a concern in some types of data when observed variability exceeds what a simple model expects. This endpoint is a continuous change measure, and the registry reports standard deviations; it does not report an over-dispersion analysis. General statistical principle: where an assumed model understates variability, standard errors can be too small and intervals too narrow. That is a general reason to examine model assumptions, not a claim that over-dispersion occurred in this trial.

What can the recalculations add?

Unadjusted recalculations from arm summaries can make pairwise contrasts and their uncertainty easier to interpret when the registry reports only an overall test. They are limited to the means, standard deviations, and group counts posted for the outcome. They cannot reproduce an analysis using participant-level data, account for covariates or missing observations unless those details are included, or verify the assumptions used by the original analysis. The registry record does not report enough information to assess those details.

The calculations use a pooled standard deviation for the pairwise effect-size summaries, and the posted standard errors for each arm are also shown in the underlying statistical output. A pooled standard deviation is a common scale for describing a mean difference relative to within-group variation. It is a descriptive standardization, not a clinical threshold. The effect-size values are -0.101 for the comparison with the blinded-monitor time-limited-eating group and -0.365 for the real-time-feedback group comparison. Their interpretation depends on the assumptions behind the pooled spread and should not replace the mean differences in the endpoint’s original units.

Finally, the study is identified as a pilot. General statistical principle: pilot studies can be useful for describing feasibility and generating estimates, but estimates from small groups are often imprecise. The record does not report a formal feasibility endpoint or a prespecified sample-size justification, so the pilot label alone does not establish the study’s specific design purpose.

10. Confidence Intervals and Precision

A confidence interval describes a range of values for a population quantity that are reasonably compatible with the observed data and the method used to calculate the interval. A 95% confidence interval is a procedure that, across repeated studies under its assumptions, would capture the target quantity 95% of the time. It is not a probability statement that the particular interval has a 95% chance of containing the true difference.

For the comparison of the diet-only group with the time-limited-eating group using a blinded monitor, the recalculated mean difference was -0.49 and the 95% confidence interval ran from -3.583 to 2.603. For the comparison with the real-time-feedback group, the estimated difference was -1.58 and the 95% confidence interval ran from -4.589 to 1.429. Both intervals include zero, so the estimates do not rule out no difference under the unadjusted calculation. They also extend to values on both sides of zero, leaving uncertainty about direction.

The intervals are wide relative to the point estimates. That width signals limited precision: the data are consistent with a range of possible between-group differences rather than a narrowly determined effect. The posted group sizes are 15, 19, and 16, and the standard deviations are 3.34, 5.76, and 5.08. General statistical principle: with a fixed level of variability, smaller groups usually yield less precise estimates than larger groups. The observed spread also contributes to the uncertainty.

The registry’s own three-group ANOVA reports p = 0.4 but does not report a confidence interval for the overall comparison. The pairwise intervals are recalculated from the posted summaries, not intervals reported by the sponsor. They are unadjusted for multiplicity and should not be treated as simultaneous confidence intervals covering all possible comparisons.

Confidence intervals show statistical uncertainty, not whether a difference is important to patients or clinically meaningful. The registry record does not report a threshold for a meaningful change in %BMIp95. It also does not provide enough detail to assess the effect of missing outcome data or other model choices on precision.

11. 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 illustrations translate an observed pairwise difference into hypothetical group sizes for future planning. They are not the trial’s observed enrollment and do not indicate how many participants were actually analyzed. For these continuous-outcome comparisons, every listed figure is participants per arm, not a total number of events. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses the stated fraction of the observed effect as the effect to detect.

The 80% power column gives the number of participants per arm under the stated assumptions for a design with an 80% chance of detecting the chosen effect if that effect is the true one. The 90% power column makes the corresponding calculation for a 90% chance. These are design targets, not guarantees that a future study will produce a particular result. The illustrations are not observed power.

For the comparison between the diet-only group and the time-limited-eating group with blinded monitor, planning for 100% of the observed effect gives 1,540 participants per arm for 80% power and 2,061 for 90% power. Planning for 75% of the observed effect gives 2,737 and 3,664 per arm, respectively; planning for 50% gives 6,157 and 8,243 per arm.

For the comparison with the real-time-feedback group, planning for 100% of the observed effect gives 118 participants per arm for 80% power and 158 for 90% power. Planning for 75% gives 210 and 281 per arm; planning for 50% gives 472 and 631 per arm. Across both comparisons, the smaller-effect scenarios require more participants because a smaller difference is harder to distinguish from variation under the same assumptions.

These are illustrations based on the observed effects, not the original trial’s design calculation. The trial’s own sample-size assumptions and justification are not reported in the registry record. Estimates derived from a pilot can be unstable, so the displayed scenarios are best read as conditional planning examples rather than definitive recruitment targets.

12. 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 = -0.490; pooled standard deviation σ = 4.852.
2. n = 2 × (1.96 + 0.842)² × 4.852² / -0.490² = 1,539.2, rounded up to 1,540 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 <- -0.49                      # observed difference in means
sigma <- 4.85211036560382                     # 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(3954223)
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 = 1,540 (80% power), 2,061 (90% power)
 75% of observed effect: n per arm = 2,737 (80% power), 3,664 (90% power)
 50% of observed effect: n per arm = 6,157 (80% power), 8,243 (90% power)
power.t.test: 1540.2 
Simulated power at n = 1,540 per arm: 0.803 (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.

13. Analyses Reported by the Sponsor

The registry reports the sponsor’s own primary-outcome analysis as an analysis of variance across all three groups, with p = 0.4. This is an overall test of the group means. The registry does not report a sponsor-generated pairwise estimate, confidence interval, or p-value for either comparison against the diet-only group.

The pairwise estimates discussed for the diet-only group versus the two time-limited-eating groups are unadjusted recalculations from the posted arm means, standard deviations, and counts. They answer focused comparison questions that differ from the sponsor’s overall three-group test. The recalculated estimates are -0.49 for the blinded-monitor comparison and -1.58 for the real-time-feedback comparison; their 95% confidence intervals are -3.583 to 2.603 and -4.589 to 1.429, respectively.

The registry record does not flag a discrepancy between a sponsor result and a recalculation. The results should still be distinguished by source and scope: the ANOVA p-value is the sponsor-reported overall analysis, while the pairwise results are summary-statistic recalculations. The record does not include the sponsor’s model details, analysis population, missing-data handling, or any adjusted pairwise analyses, so the recalculations cannot be treated as a reproduction of the full sponsor analysis.

14. Multiplicity, Missing Data and Analysis Populations

The registry reports a primary endpoint and lists Average Glucose as a secondary outcome. It also reports an overall three-group analysis for the primary endpoint, while the summary-statistic results allow two pairwise comparisons of the diet-only group with the other groups. Testing several outcomes or contrasts can increase the chance of observing a nominally notable result by chance. General statistical principle: multiplicity procedures can control that risk, but they may also affect the interpretation of p-values and confidence intervals.

The registry record does not report a multiplicity adjustment or a prespecified hierarchy for the outcomes and comparisons. The recalculated pairwise p-values are unadjusted, and their confidence intervals are not simultaneous intervals. They should therefore be read as individual exploratory comparisons rather than as a family-wise adjusted set of confirmatory tests. The sponsor-reported ANOVA is an overall test, but the record does not explain how it fits into a broader testing strategy.

The registry lists Average Glucose as a secondary outcome but does not report its numerical results in the posted results. Details for the second outcome measure are not reported in the registry record. As a result, the outcome-level picture cannot be assessed from the primary endpoint alone.

Missing-data methods and the number of participants contributing to each outcome analysis are not reported in the registry record. The registry gives arm counts for the primary outcome results, but it does not describe whether all randomized participants had Week 12 measurements, how missing measurements were handled, or whether any imputation was used. The analysis population, such as intention-to-treat or per-protocol, is also not reported in the registry record.

Other elements needed to assess statistical conduct are not reported in the registry record, including the randomization sequence method, allocation concealment, any prespecified covariate adjustment, interim analyses, and detailed model assumptions. Their absence from the record does not establish that they were not performed; it means their methods cannot be evaluated from the registry information. The original sample-size justification and design assumptions are also not reported.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

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

The registry’s safety fields show zero serious adverse events affected in each group: 0 of 15 in the low-sugar and carbohydrate diet with blinded monitor group, 0 of 19 in the time-limited-eating group with blinded monitor, and 0 of 16 in the time-limited-eating group with real-time feedback. The recorded number of deaths is 0 in each group. The fields for other adverse events also list zero affected participants in each group.

These figures describe the adverse-event counts recorded in the registry for the listed groups. They should not be interpreted as proving that an intervention has no safety risks. The groups are small, and the registry record does not provide event descriptions, follow-up details for safety collection, or information about how adverse events were assessed. Zero recorded events in these groups therefore gives limited information about the frequency of uncommon events.

The record lists 15, 19, and 16 participants at risk in the respective groups for the serious and other adverse-event fields. It does not report additional detail on exposure time or whether every participant completed the full intervention. The safety figures are descriptive counts, not comparative safety estimates adjusted for differences in follow-up or other factors.

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

The posted primary-outcome results describe mean decreases from baseline in %BMIp95 in all three groups over the measured period. The group means were -3.27 for the low-sugar and carbohydrate diet with blinded monitor, -3.76 for the same diet plus time-limited eating with blinded monitor, and -4.85 for the diet plus time-limited eating with real-time feedback. These values describe the observed group averages; they do not by themselves establish that the intervention components caused the changes.

The recalculated pairwise comparisons do not estimate the effects precisely. Both 95% confidence intervals include zero and span differences in either direction. The sponsor’s overall ANOVA reports p = 0.4. Taken together, the reported analysis and the unadjusted pairwise estimates do not provide clear evidence of a difference between the groups in the primary endpoint, but they also do not establish equivalence or rule out potentially meaningful differences. The registry does not report a threshold for clinical importance.

The trial compares a diet-only group with two groups that add time-limited eating, with different monitor-feedback arrangements. The posted primary endpoint results cannot be used to make claims about every intervention component separately. In particular, the primary results do not provide a reported estimate for Average Glucose, even though it is listed as a secondary outcome, and they do not describe other outcomes or mechanisms.

The registry identifies this as a pilot study and lists 50 enrolled participants. The observed arm sizes are 15, 19, and 16. With these group counts and the reported variability, the uncertainty around the group differences is substantial. These results are best treated as estimates from a small randomized study, not as a definitive test of whether the groups are the same or different.

The findings apply to the endpoint and time frame recorded: change in %BMIp95 from baseline to Week 12. They do not establish persistence beyond that follow-up, effects in populations not represented in the study, or safety beyond the adverse-event information recorded. Those outcomes and populations are not reported in the registry record.

17. Why This Trial Matters Statistically

This pilot illustrates why a randomized comparison should be interpreted through both the estimated differences and their uncertainty. The three group means are all negative, but within-group change does not answer whether the treatment strategies differ from one another. The pairwise mean differences directly address those comparisons, and their confidence intervals show how much uncertainty remains.

The study also separates treatment components in a way that raises useful statistical questions. The groups differ in whether time-limited eating is included and whether monitor feedback is available in real time. A comparison of the two time-limited-eating groups is relevant to the feedback contrast, while comparisons with the diet-only group address a broader difference in strategy. Clear identification of the contrast matters because a group difference cannot automatically be attributed to one component when interventions differ in more than one respect.

The results show the value and limits of pilot estimates for planning. The sample-size illustrations change substantially according to the comparison and the fraction of the observed effect selected for planning. Smaller target effects require larger per-arm samples under the stated assumptions. At the same time, observed effects from small pilot groups can be imprecise, so planning from them alone may produce unstable projections. The original sample-size rationale is not reported in the registry record.

Finally, the registry’s overall ANOVA and the pairwise recalculations answer different statistical questions. An overall test can summarize evidence across multiple groups, while pairwise estimates show the magnitude and uncertainty for specific contrasts. Separating these methods helps avoid treating one p-value as a complete account of the trial. The record’s missing detail on multiplicity, analysis populations, missing data, and model specification also shows why transparent reporting is important when interpreting a clinical study.

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 primary outcome results are based on modest arm counts: 15, 19, and 16 participants. The reported standard deviations are 3.34, 5.76, and 5.08, and the pairwise confidence intervals are broad. The point estimates are therefore uncertain and should not be treated as precise estimates of the differences between strategies.

The registry record contains a difference between the brief summary’s proposed 90 participants and the listed enrollment of 50. The record does not explain this difference. It also does not report the original sample-size justification, the randomization sequence method, allocation concealment, or the specific masking procedures. These omissions limit assessment of the design and the relationship between the intended and enrolled populations.

The sponsor’s posted statistical result is an overall three-group ANOVA with p = 0.4. Detailed model specifications, degrees of freedom, test statistic, covariate adjustments, analysis population, and missing-data handling are not reported in the registry record. The pairwise estimates are unadjusted recalculations from summary statistics and do not substitute for a fully specified participant-level analysis.

The registry lists Average Glucose as a secondary outcome but does not report numerical results for it. The registry record also does not report a multiplicity plan, a clinically meaningful threshold for %BMIp95, or an equivalence margin. Consequently, the results cannot establish equivalence, and the clinical importance of a given difference cannot be judged from the registry information alone.

Follow-up for the primary endpoint is defined at Week 12. Longer-term outcomes are not reported in the registry record. The safety data list zero serious adverse events and zero deaths in each arm, but the record does not provide detailed event narratives or safety follow-up methods. These limitations restrict conclusions to the posted short-term endpoint and recorded safety counts.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Time Limited Eating in Adolescents (Time LEAd): a Pilot Study — NCT03954223.
• Registry record last updated 2024-03-04; status last verified 2024-02.
• Results first posted 2023-04-06.
• 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

NCT03954223 is a completed, randomized, single-masked, parallel-group pilot study sponsored by Children's Hospital Los Angeles. The registry lists enrollment of 50 and three groups: low-sugar and carbohydrate diet with blinded continuous glucose monitor; the same diet with time-limited eating and blinded monitor; and the diet with time-limited eating and real-time monitor feedback.

The primary endpoint was change from baseline to Week 12 in percent BMI in excess of the 95th percentile. The respective group means were -3.27, -3.76, and -4.85. The sponsor reports an overall three-group ANOVA with p = 0.4. Unadjusted pairwise recalculations have wide 95% confidence intervals that include zero.

Average Glucose is listed as a secondary outcome, but numerical results are not reported in the registry record. The record lists zero serious adverse events and zero deaths in each group. Details on missing-data methods, analysis populations, multiplicity, and the original sample-size justification are not reported in the registry record.