Additional Insulin for Fat and Protein in Children With Diabetes Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Additional Insulin for Fat and Protein in Children With Diabetes Study (NCT02680054), a randomized phase 4 study. The primary outcome is Peak Glucose Level Following Test Meal.

2. Clinical Question

The study is registered as a randomized, unmasked crossover trial. A crossover design means participants may receive more than one study condition at different times, so each participant can contribute observations under different conditions. The registry record does not report the sequence of conditions, washout arrangements, or the analysis method used to account for repeated observations within a participant.

The clinical question is about glucose response to a specific test-meal situation and the timing of an additional insulin dose. It is not a comparison of different insulin products: the listed intervention is insulin Asp(B28)-, and the arm descriptions name insulin Aspart. The registry record also identifies hypoglycaemia following dosing as a secondary outcome and posts adverse-event summaries. These outcomes provide additional context, but the primary registered outcome is peak glucose.

3. Trial Design

This is a phase 4, randomized, unmasked crossover study sponsored by Oxford University Hospitals NHS Trust. The registry record lists Type 1 Diabetes as the condition and describes children using multiple daily injections. Enrollment is recorded as 38. The study status is terminated; the reason for termination is not reported in the registry record.

The three conditions differ in when the additional insulin for meal fat and protein is given. Arm 1, identified as usual treatment, gives that dose before the meal at the same time as insulin for carbohydrate. Arm 2 gives it one hour after the meal, and Arm 3 gives it two hours after the meal. The dose is calculated individually according to the child's usual insulin-to-carbohydrate ratio. The registry record describes the study as a crossover, but it does not report the order in which participants received conditions or how the crossover periods were organized.

The primary outcome is peak glucose following the test meal, measured by continuous subcutaneous glucose monitoring and assessed up to 12 hours after the meal. Each posted primary arm summary lists 27.0 participants. Those arm-level figures should not be added together to infer a number of unique participants: in a crossover study, an individual may contribute to more than one condition. The registry record does not explain the relationship between enrollment and the arm-level outcome counts or specify the analysis population.

The registry record lists five outcome measures, but only one secondary outcome is posted in the results presented. That secondary outcome counts participants with hypoglycaemia events following insulin dosing. The record contains no reported analyses and does not describe the trial's original sample-size rationale, planned statistical model, handling of missing data, or multiplicity procedure.

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: Study was closed before target could be reached due to exhaustion of eligible participants

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 Peak Glucose Level Following Test Meal, measured over assessed up to 12 hours following the test meal.

The primary endpoint is the mean peak glucose level following a test meal. Glucose is measured using a continuous subcutaneous glucose monitor, with the endpoint assessed up to 12 hours after the meal. A peak summarizes the highest glucose measurement during the stated assessment period; it therefore focuses on the maximum recorded response rather than an average across all measurements in that period.

The registry record reports the endpoint in mmol/l and describes the result as a mean with standard deviation. The posted mean is 10.93 for Arm 1 (usual treatment), 11.49 for Arm 2, and 11.49 for Arm 3. The standard deviations are 0.951, 0.831, and 0.863, respectively. Each arm summary lists 27.0 participants.

As a general statistical point, a continuous endpoint such as peak glucose retains information about the measured amount, rather than reducing it to a yes-or-no category. A mean gives a concise summary of the group values, while a standard deviation describes how spread out those values are around the mean. The endpoint is relevant to the stated research question because the study aims to compare glucose levels after varying the timing of the additional insulin dose.

The posted endpoint does not by itself describe the full glucose profile, the timing of the peak, or the duration of glucose changes. Those details are not reported in the registry record. Nor does a group mean identify the experience of any individual participant.

7. Results Posted in the Registry

• Arm 2: mean 11.49 versus 10.93 on control; difference 0.56 (95% CI 0.08 to 1.04), standardized effect d = 0.63; z-test p = 0.021.
• Arm 3: mean 11.49 versus 10.93 on control; difference 0.56 (95% CI 0.08 to 1.04), standardized effect d = 0.62; z-test p = 0.023.

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.

Number of Participants With Hypoglycaemia Events Following the Insulin Dosing

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Arm 2: 51.9% (14/27) versus 51.9% (14/27) on control; risk difference 0.0 percentage points (95% CI -26.7 to 26.7), risk ratio 1.00 (0.60–1.67); unadjusted two-proportion z-test p = 1.000.
  • Arm 3: 59.3% (16/27) versus 51.9% (14/27) on control; risk difference 7.4 percentage points (95% CI -19.0 to 33.8), risk ratio 1.14 (0.71–1.85); unadjusted two-proportion z-test p = 0.584.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2 and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 3 and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcome concerns participants with hypoglycaemia events following insulin dosing, assessed up to 12 hours after the test meal. Its overall pattern is not as clearly separated across timing conditions as the primary mean peak-glucose comparisons. The unadjusted risk-difference intervals include zero, leaving uncertainty about whether the event frequency differs between conditions.

This secondary result addresses a different aspect of the study question from peak glucose. Peak glucose is a continuous measure of the maximum glucose level during the assessment period; the hypoglycaemia outcome counts participants with an event. The outcomes should therefore not be treated as interchangeable or as if one confirms the other. The primary result describes the posted group means, while the secondary outcome adds information about reported hypoglycaemia events.

The registry record posts only one secondary outcome, although it lists five outcome measures overall. It gives no reported analyses for the secondary endpoint beyond the unadjusted comparisons, and no procedure for adjusting across outcomes or comparisons. As a general statistical point, examining multiple outcomes or contrasts increases the chance that at least one unadjusted result appears notable by chance. This is why unadjusted secondary findings generally carry less confirmatory weight than a prespecified primary analysis with an adequately reported plan.

The absence of a clear difference in these secondary comparisons should not be read as proof that the conditions have the same event risk. The intervals include a range of effects in either direction, and the registry record does not report a non-inferiority or equivalence analysis. Conversely, the numerical event pattern alone cannot establish a difference. The secondary result is best treated as contextual, exploratory evidence alongside the primary endpoint, with its uncertainty and the missing analysis details kept in view.

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

• Number of Participants With Hypoglycaemia Events Following the Insulin Dosing

9. Statistical Interpretation

10. Statistical Methods Explained

The registry presents a continuous primary outcome and a binary secondary outcome. The primary endpoint is a mean peak glucose level, whereas the secondary endpoint counts participants with hypoglycaemia events following dosing. These require different descriptive summaries and different interpretations. The posted primary comparisons use mean differences; the secondary comparisons use risk differences.

What does a mean difference describe?

A mean difference subtracts one group's mean from the comparator group's mean, with the direction depending on the stated comparison. In the primary comparisons, the registry gives Arm 2 versus usual treatment and Arm 3 versus usual treatment. Both reported mean differences are 0.56 mmol/l. A value above zero in these comparisons corresponds to a higher reported mean in the delayed-dose arm. The mean difference is expressed in the endpoint's original unit, which makes it directly interpretable on the glucose scale.

The standard deviation describes variability among observed values within an arm. The posted standard deviations are 0.951 for usual treatment, 0.831 for Arm 2, and 0.863 for Arm 3. As a general statistical point, the standard deviation is not the uncertainty interval for the mean difference. It describes spread in individual measurements, whereas an interval around a comparison describes uncertainty in the estimated contrast.

What does a comparison interval communicate?

A confidence interval is a range of values compatible with the data and the assumptions of the method used to calculate it. As a general statistical explanation, narrower intervals indicate greater precision, while wider intervals indicate less precision. The primary comparison intervals are entirely above zero, consistent with the positive mean differences. The intervals for the secondary risk differences include zero, so those data do not distinguish clearly between no difference and differences in either direction. The registry record does not state the confidence level for these intervals, so no confidence percentage should be inferred from the posted information.

A p-value is a measure of how unusual data at least as inconsistent with a specified null model would be if that model were true. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of a difference. The primary unadjusted p-values are 0.021 and 0.023. The registry identifies them as unadjusted; the record does not report an adjustment for the multiple comparisons or a complete prespecified statistical analysis plan.

How should the binary outcome be understood?

The secondary outcome is the number of participants with hypoglycaemia events, reported as a count of participants rather than as a continuous measurement. A risk difference compares the proportions with the event in two groups. For Arm 2 versus usual treatment, the posted point estimate is 0.0, and the reported interval includes zero. For Arm 3 versus usual treatment, the point estimate is positive, while the interval also includes zero. The associated unadjusted p-values are 1.0 and 0.584, respectively. These comparisons do not show a clear difference, but they also do not establish that the underlying risks are identical.

As a general statistical point, the uncertainty of a binary comparison depends on the number of participants and the event pattern. A small dataset can produce wide intervals, particularly when estimates are based on few observations. Here, the posted intervals are wide enough to include both decreases and increases for the secondary comparisons. That makes the point estimates less conclusive than a single number alone might suggest.

Why does the crossover design matter?

In a crossover design, participants receive more than one condition, so observations from the same participant can be related. As a general statistical principle, an analysis should account for that dependence when estimating comparisons and uncertainty. Treating observations as independent when they are paired can misstate precision. The registry record does not report the sequence of conditions, period-specific results, washout arrangements, or the model used to account for within-participant correlation. The posted comparisons can be described, but their relationship to a crossover-adjusted analysis is not reported.

The arm summaries list 27.0 participants for each primary outcome condition, while the registry enrollment is 38. These values cannot be combined to infer the number of unique participants contributing to the crossover comparisons. The record does not explain the analysis population, whether every enrolled participant contributed to every condition, or how missing measurements were handled.

What can planning calculations tell a reader?

Sample-size planning calculations illustrate the number of participants per arm that a future study might require under stated assumptions. They are not a measurement of the statistical power achieved by this trial. The posted planning assumptions use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set as a stated fraction of the observed effect. The trial's original sample-size assumptions are not reported in the registry record.

As a general statistical point, power is the probability that a study will detect a specified effect under a particular model and assumptions. A planning calculation is tied to the effect size selected, the variability or event rates assumed, and the chosen testing approach. Smaller target effects generally require more participants to detect than larger target effects. A planning figure based on an observed effect is especially dependent on that estimate and should not be treated as an independent estimate of what the trial was designed to detect.

For continuous outcomes, standard errors and intervals quantify uncertainty around mean estimates. For binary outcomes, risk differences and their intervals describe uncertainty in the event contrast. Both types of interval are important: a point estimate alone does not convey how precisely the underlying contrast has been estimated. The registry provides no reported inferential analysis beyond the unadjusted comparisons described, and does not report whether the final analysis followed a prespecified plan.

11. Confidence Intervals and Precision

The primary mean differences are 0.56 mmol/l for Arm 2 versus usual treatment and 0.56 mmol/l for Arm 3 versus usual treatment. The registry comparison intervals for both contrasts lie above zero, but their widths also show that the estimates are not exact. The reported unadjusted p-values, 0.021 and 0.023, summarize evidence against a zero-difference null under the method used for those comparisons; they do not express how likely the estimates are to be correct or whether the difference is important.

As a general statistical explanation, a confidence interval conveys both the estimated direction and the uncertainty around an effect. An interval that excludes zero is consistent with a nonzero contrast under the interval's method, while a wide interval allows a broader range of plausible effects. The registry record does not state the confidence level for its intervals. It also does not report whether the comparison intervals account for the paired nature of the crossover design, which may affect their precision.

For hypoglycaemia, the registry intervals around the risk differences include zero and extend to differences in both directions. This indicates limited precision for the secondary comparisons: the observed data are compatible with no difference as well as with potentially meaningful differences. The unadjusted p-values do not remove that uncertainty. The arm-level event counts are also modest, and the record does not provide a more detailed model-based analysis.

Precision is not the same as clinical importance. The registry record does not state a threshold for a meaningful change in peak glucose or a margin for equivalence. The posted estimates and intervals therefore describe statistical uncertainty, but they do not establish whether any difference would be important to patients or clinicians.

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 planning figures are expressed as participants per arm, not as total events. They use two-sided significance level 0.05, equal allocation between the two arms, and a normal approximation. The target effect is set to 100%, 75%, or 50% of the observed effect. These are planning assumptions for illustrations; the trial's own original design assumptions are not reported in the registry record.

For the primary comparison of Arm 2 with usual treatment, planning for 100% of the observed effect gives 40 participants per arm for 80% power and 54 participants per arm for 90% power. For 75% of the observed effect, the corresponding figures are 71 and 96 participants per arm; for 50%, they are 160 and 214. For Arm 3 compared with usual treatment, the figures are 42 and 56 for 100% of the observed effect, 74 and 99 for 75%, and 166 and 222 for 50%.

The secondary planning figures apply to the Arm 3 comparison and use participants per arm: 706 for 80% power and 944 for 90% power when planning for 100% of the observed effect; 1,260 and 1,686 for 75%; and 2,845 and 3,807 for 50%.

In plain terms, 80% power is the planned chance of detecting the chosen effect under the stated assumptions if that effect is present; 90% power uses a higher detection probability and therefore requires more participants in these illustrations. Smaller effects need more participants to detect than larger effects. The planning figures are not observed power for this trial; observed power is not a substitute for interpreting the estimates and their uncertainty.

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 = 0.560; pooled standard deviation σ = 0.893.
2. n = 2 × (1.96 + 0.842)² × 0.893² / 0.560² = 39.9, rounded up to 40 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 <- 0.56                      # observed difference in means
sigma <- 0.893017916953518                     # 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(2680054)
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 = 40 (80% power), 54 (90% power)
 75% of observed effect: n per arm = 71 (80% power), 96 (90% power)
 50% of observed effect: n per arm = 160 (80% power), 214 (90% power)
power.t.test: 40.9 
Simulated power at n = 40 per arm: 0.791 (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 identifies the primary endpoint and posts unadjusted pairwise comparisons of Arm 2 and Arm 3 against usual treatment. It does not report whether those comparisons were the only planned primary tests, whether a hierarchy was specified, or whether p-values or intervals were adjusted for multiplicity. No multiplicity procedure is reported in the registry record.

Multiplicity matters when more than one statistical question is tested. As a general statistical explanation, repeated testing can increase the chance of at least one result appearing notable even when the corresponding underlying effects are absent. The posted primary p-values are explicitly unadjusted. They should not be interpreted as multiplicity-controlled results. The registry lists five outcome measures and posts one secondary outcome; it does not state how the other measures relate to the primary question or whether they were included in a planned testing strategy.

The record contains no reported analyses. It does not specify the statistical model, analysis population, handling of crossover periods, or whether within-participant pairing was incorporated. The sequence of conditions, period effects, and any washout arrangements are also not reported in the registry record. These details are relevant because the design is identified as crossover, and observations from one participant may be related across conditions.

Missing-data methods are not reported in the registry record. Although the enrollment is 38 and each primary arm summary lists 27.0 participants, the record does not explain which participants contributed to each outcome, why the arm-level count differs from enrollment, or how missing or unusable glucose measurements were handled. It does not identify an intention-to-treat, per-protocol, or other analysis population. These omissions prevent a reader from assessing attrition, exclusions, or sensitivity to missing observations from the registry entry alone.

The study status is terminated, but the reason is not reported in the registry record. The record also does not report the original sample-size rationale or any interim-analysis plan. None of those missing details can be inferred from the posted outcome summaries.

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 serious adverse-event summaries list 27 participants at risk in each arm and zero serious adverse events affecting participants in each arm. The summaries also list zero other adverse events affecting participants in each arm and zero deaths in each arm. These are the posted counts; the registry record does not give further descriptions of events or event definitions.

As a general statistical point, observing no events in a group does not prove that the underlying risk is zero. The amount of uncertainty depends on the number observed and the study size, and a small study may not detect uncommon harms. The record's zero counts should therefore be read as no serious or other adverse events reported in these summaries, not as evidence that no risk exists.

The registry record does not report a detailed safety analysis, follow-up duration beyond the stated outcome assessment period, or how adverse events were collected and adjudicated. The posted summaries alone cannot establish comparative safety or support a treatment recommendation.

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

The posted primary summaries show mean peak glucose of 10.93 mmol/l with usual treatment and 11.49 mmol/l in each delayed-dose arm. The reported unadjusted mean differences are 0.56 mmol/l for both comparisons with usual treatment, with intervals above zero. This describes the direction and estimated size of the posted contrasts for the measured endpoint. It does not, by itself, establish a causal or clinical conclusion.

The registry record identifies a randomized crossover design, but does not report whether the analysis accounts for the relationship between measurements from the same participant. It also does not provide the condition sequence, missing-data approach, or analysis population. These matters affect how confidently the arm summaries and comparison intervals can be interpreted. Enrollment is recorded as 38, while the primary arm summaries each list 27.0 participants; the record does not explain this relationship.

The secondary hypoglycaemia comparisons are imprecise and do not establish that event risks are equal or different. The adverse-event summaries report zero serious events, zero other adverse events, and zero deaths in each arm, but these counts do not show that a risk is absent. The registry does not give enough safety detail to characterize uncommon events or make a complete safety comparison.

The result does not answer every question about glucose response. The primary endpoint is peak glucose within the specified period, not the full glucose trajectory, duration of excursions, or an individual's response. The record does not report those details or a threshold for a clinically meaningful difference. It also does not report a direct comparison between the two delayed-dose arms.

These posted findings should be understood as trial results with important reporting gaps, rather than as medical advice. The registry record does not provide a complete statistical analysis plan or the reason the study was terminated. The findings do not establish that one timing strategy should be used, nor do they establish equivalence between strategies.

17. Why This Trial Matters Statistically

This trial raises a useful statistical question because its design and outcomes require interpretation at more than one level. The randomized crossover structure means participants may contribute observations under multiple conditions. As a general statistical principle, within-participant dependence can affect the estimated uncertainty of contrasts. The registry identifies the design but does not report how the analyses handled that dependence, making the reporting of the statistical model especially important.

The primary endpoint is a continuous glucose measure, while the posted secondary endpoint is a participant count for hypoglycaemia events. The two outcomes capture different features and use different comparison measures. Their combined interpretation illustrates why one statistically notable primary contrast cannot stand in for a complete assessment of all outcomes, and why a secondary result with wide uncertainty should not be treated as proof of no difference.

The reported primary p-values are unadjusted, and the registry does not report a multiplicity plan. This highlights the distinction between a result that appears notable in an individual comparison and a conclusion supported by a prespecified analysis strategy. The record also does not provide the original sample-size rationale, limiting the ability to judge how the study was planned relative to its intended effect.

Finally, the gap between the registered enrollment and the arm-level outcome counts makes transparent reporting of analysis populations and missing data essential. The record's status is terminated, but the reason is not given. These limitations do not erase the descriptive information in the posted results; they define what can responsibly be inferred from it.

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 does not state why the study was terminated. It records enrollment of 38, while each primary arm summary lists 27.0 participants; the relationship between those figures, the number contributing to each crossover condition, and any exclusions are not explained. The analysis population and handling of missing glucose measurements are not reported.

Although the design is identified as crossover, the record does not describe treatment sequence, period structure, washout arrangements, or whether the reported comparisons account for repeated observations within participants. It also does not report a direct comparison between Arm 2 and Arm 3. The published pairwise summaries therefore do not answer whether the one-hour and two-hour timings differ from each other.

The record does not report the original sample-size rationale, a statistical analysis plan, the confidence level for the comparison intervals, or a multiplicity procedure. The primary p-values are unadjusted. No reported analyses are listed, so the registry does not clarify whether the posted summary-based comparisons correspond to the intended crossover analysis.

The primary endpoint describes peak glucose during the stated assessment window, not the full glucose profile or other measures of glucose control. The secondary outcome counts participants with hypoglycaemia events, but the record does not provide more detailed event data or analysis. The adverse-event summaries are limited to counts and do not report definitions, event descriptions, or detailed collection methods. These reporting limitations constrain interpretation without establishing that unreported outcomes or methods were absent from the study itself.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Additional Insulin for Fat and Protein in Children With Diabetes Study — NCT02680054.
• Registry record last updated 2020-02-05; status last verified 2020-01.
• Results first posted 2020-02-05.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a phase 4 randomized, unmasked crossover study of additional insulin timing for fat and protein in meals among children with type 1 diabetes using multiple daily injections. Enrollment is recorded as 38, and the status is terminated; the reason is not reported in the registry record.

The primary outcome is mean peak glucose measured by continuous subcutaneous glucose monitoring up to 12 hours after a test meal. Posted means are 10.93 mmol/l for usual treatment and 11.49 mmol/l for each delayed-dose arm. Both unadjusted comparisons against usual treatment report a mean difference of 0.56 mmol/l, with intervals above zero.

The posted secondary outcome concerns hypoglycaemia events. The registry also reports zero serious adverse events, zero other adverse events, and zero deaths in each arm. The record does not report the original analysis plan, the crossover-adjusted methods, the analysis population, missing-data handling, or the reason for termination.