Extended Bolus for Meals in a Closed-loop System: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Extended Bolus for Meals in a Closed-loop System (NCT05454891), a randomized na study. The primary outcome is Glucose Area Under Curve [AUC].

2. Clinical Question

The clinical question concerns the post-meal glucose trace in a specific meal context, rather than glucose control in every setting. The registry describes high-fat, high-protein meals and a closed-loop system. It does not describe other meal types or other treatment contexts. The primary outcome is an integrated measure over a stated post-meal period, while secondary outcomes describe time in glucose ranges, average glucose, insulin dosage, and timing-related measures.

The study was randomized and unmasked. Its crossover format means the two bolus strategies were administered in a sequence: one sequence used an extended bolus on the first day and a standard bolus on the second day, while the other sequence reversed that order. The record does not report details about how the sequence was generated or how the analysis accounted for repeated observations from the same participant. Those details matter when interpreting how closely the comparison estimates the effect of bolus strategy.

3. Trial Design

The registry describes a randomized, unmasked crossover study sponsored by the University of California, San Francisco. Its title is “Extended Bolus for Meals in a Closed-loop System,” and its official title specifies postprandial glucose control using an extended bolus for high-fat, high-protein meals in a closed-loop system in patients with type 1 diabetes. The phase is listed as not applicable. The study is marked completed.

The record lists enrollment as 30. In the arm descriptions, participants received breakfast with one bolus strategy on the first study day and the other strategy on the second study day. One sequence was extended then standard; the other was standard then extended. Randomization and crossover are stated, but the method of randomization, sequence allocation details, washout procedures, and handling of possible period or carryover effects are not reported in the registry record.

The primary outcome is glucose area under the curve, expressed in mg/dL* min, over 0 to 5 hours post-meal onset. The posted primary summaries report a mean and standard deviation for the standard-bolus condition and for the extended-bolus condition. Each condition has an outcome sample size of 18.0. These condition-level counts should not be interpreted as a count of distinct participants, since the study is described as a crossover and the record does not explain the relationship between enrollment and the posted outcome sample sizes.

The study start date is 2022-07-15, and primary completion is listed as 2024-12-19. The registry lists 12 outcome measures, with 11 secondary outcomes posted. It does not report the trial’s original sample-size justification, the planned primary analysis, a statistical analysis plan, or a description of the analysis population. The status and dates describe the registry record; they do not resolve these missing design and analysis details.

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: A total of 30 participants were enrolled. Three participants were screen failures. Of the remaining 27 eligible participants, 22 were randomized and 5 withdrew or were withdrawn prior to randomization.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Glucose Area Under Curve [AUC], measured over 0 to 5 hours post-meal onset.

The primary endpoint is glucose area under the curve between the glucose trace and the starting glucose, measured from 0 to 5 hours after meal onset. Its unit is mg/dL* min, and the registry describes the endpoint as a mean with standard deviation. In general, an area-under-the-curve measure combines information across the measurement period: the glucose trace’s position relative to the starting value and the duration of that pattern both contribute to the summary. It can therefore represent the accumulated post-meal glucose excursion rather than glucose at a single time point.

The outcome is relevant to a question about how glucose changes after a high-fat, high-protein meal under a closed-loop system. The time window is explicitly stated, so the reported mean should be understood as a summary of that post-meal interval, not as a measure of glucose control over the full day or over a longer period. The registry does not report details such as the frequency of glucose measurements, the precise computational handling of the trace, or whether the area calculation used a signed or another convention. Interpretation should therefore stay close to the recorded endpoint definition.

The standard-bolus condition had a mean of 45370.0 mg/dL* min, and the extended-bolus condition had a mean of 48640.0 mg/dL* min. The posted mean difference for extended compared with standard was 3270.0 mg/dL* min, with a confidence interval from -3003.0 to 9543.0. These summaries describe the observed endpoint values; by themselves, they do not establish that a bolus strategy causes better or worse glucose control.

7. Results Posted in the Registry

• High Fat High Protein (HFHP) Meal With Extended Insulin Bolus: mean 48,642 versus 45,372 on control; difference 3,270 (95% CI -3,003 to 9,543), standardized effect d = 0.34; z-test p = 0.307.

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.

Percentage of Time Between 70-180 mg/dL

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • High Fat High Protein (HFHP) Meal With Extended Insulin Bolus: mean 71.30 versus 73.60 on control; difference -2.30 (95% CI -20.83 to 16.23), standardized effect d = -0.08; z-test p = 0.808.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between High Fat High Protein (HFHP) Meal With Extended Insulin Bolus and the control. The interval gives the range of effects that remain compatible with the data.

Average Glucose

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • High Fat High Protein (HFHP) Meal With Extended Insulin Bolus: mean 161.70 versus 151.10 on control; difference 10.60 (95% CI -10.14 to 31.34), standardized effect d = 0.33; z-test p = 0.316.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between High Fat High Protein (HFHP) Meal With Extended Insulin Bolus and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Time in Hyperglycemic Range (Defined as ≥180 mg/dL);

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • High Fat High Protein (HFHP) Meal With Extended Insulin Bolus: mean 28.70 versus 26.00 on control; difference 2.70 (95% CI -15.83 to 21.23), standardized effect d = 0.10; z-test p = 0.775.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between High Fat High Protein (HFHP) Meal With Extended Insulin Bolus and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several views of post-meal glucose response: time in the stated glucose ranges, average glucose, insulin dosage, and measures of timing such as time to target, time to baseline, and time to peak glucose. The record reports posted numerical results for three continuous secondary outcomes. Across those outcomes, the mean differences are modest in relation to the uncertainty intervals, and the intervals include values on either side of no mean difference. Taken together, the posted results do not form a clear, consistent pattern that changes the primary endpoint interpretation.

Secondary measures can help describe whether an observed pattern is concentrated in a particular aspect of glucose response. They do not automatically serve as independent confirmation: several outcomes may reflect related features of the same glucose trace, and the record does not report the correlations among them. The registry lists 11 secondary outcomes posted, but does not provide numerical comparisons for every listed secondary measure in the posted outcomes represented by these summaries.

The secondary comparisons carry less weight than the primary comparison for confirmatory interpretation because their multiplicity handling and prespecified priority are not reported. When many outcomes are examined, the chance of seeing an apparently unusual result somewhere among them can increase. An adjustment, hierarchical testing approach, or clearly specified exploratory status can help guide interpretation, but the registry record does not describe such a plan. The displayed secondary p values are unadjusted, so they should be treated as descriptive rather than as stand-alone evidence.

These outcomes are most useful as context for the primary result. They indicate that the observed summaries do not provide a clearly decisive or uniformly aligned secondary signal, but they cannot establish that the strategies have identical effects on each measure. The absence of reported estimates for some listed outcomes and the lack of analysis details further limit the strength of conclusions from the secondary set.

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

• Percentage of Time Between 70-180 mg/dL
• Percentage of Time in Hypoglycemic Range (Defined as < 70 mg/dL)
• Average Glucose
• Percentage of Time in Hyperglycemic Range (Defined as ≥180 mg/dL);
• Insulin Dosage
• Time to Target (110mg/dL)
• Time to Baseline
• Time to Peak Glucose

9. Statistical Interpretation

10. Statistical Methods Explained

The primary comparison is expressed as a difference in means: the mean for the extended-bolus condition compared with the mean for the standard-bolus condition. A mean gives the average value of a continuous outcome, while the standard deviation describes how spread out the observed values are around that average. In this study, the endpoint is glucose area under the curve, so each mean summarizes the recorded area over the stated post-meal interval. The arm summaries are descriptive; the comparison and its uncertainty are needed to assess how clearly the observed means differ.

A confidence interval gives a range of values compatible with the observed data under the assumptions of the analysis method. It communicates uncertainty around the estimated mean difference, rather than the spread of individual observations. For the primary comparison, the interval extends from -3003.0 to 9543.0 mg/dL* min. Because this range includes both a negative and a positive difference, the record does not establish a clear direction for the underlying mean difference. The interval is also broad, which indicates limited precision.

The unadjusted p value for the primary comparison is 0.307. In general, a p value describes how unusual data at least as incompatible with a specified no-difference model would be, if that model and the analysis assumptions were true. It is not the probability that the no-difference model is true, nor a measure of clinical importance. “Unadjusted” means that the displayed value has not been adjusted for the multiple outcome comparisons described in the record. The registry does not report a multiplicity strategy.

The crossover design has an important analysis implication. Each sequence receives both bolus strategies on different days, so outcomes may be related within a participant. A method that accounts for within-participant pairing can use that relationship; a method that treats all condition observations as independent may not represent the design in the same way. The record does not report whether the primary comparison was paired, whether it included period or sequence effects, or how possible carryover was considered. The posted condition-level means and standard deviations are not enough to reconstruct a crossover analysis, because the within-participant relationship is not given.

Standard deviations and standard errors serve different purposes. A standard deviation describes variation among observations. A standard error describes uncertainty in an estimated mean, given the analysis assumptions and information used. The registry record includes condition-level standard deviations and comparison-level standard errors, but it does not describe the calculation or model for those standard errors. In a crossover study, the standard error for a comparison may depend on the covariance between a participant’s outcomes under the two conditions. That covariance is not reported, so the analysis cannot be independently checked as a paired comparison from the summary values alone.

The secondary outcomes use the same general type of summary: continuous outcomes are reported as means and standard deviations, with a mean difference, confidence interval, and unadjusted p value. General interpretation of these quantities is the same as for the primary endpoint, but secondary findings require extra caution when many outcomes are examined. If many tests are considered, some may appear notable by chance even when no corresponding effect exists. Adjustment methods or a prespecified testing order can address that concern, but neither is reported in the registry record.

The registry lists 12 outcome measures and 11 secondary outcomes posted, while the reported analyses count is 0. The posted numerical comparisons nevertheless include mean differences, confidence intervals, and unadjusted p values. The record does not clarify the distinction between those posted comparison statistics and its analysis count, nor does it give the model specifications or analysis populations. The statistical analysis plan, approach to missing observations, and handling of departures from the intended sequence are not reported.

The sample-size illustrations use a normal approximation, equal allocation between the two arms, a two-sided significance level of 0.05, and effects set to stated fractions of the observed effect. These are planning assumptions for the illustrations, not documented assumptions for the original trial. General power calculations estimate how often a specified analysis would detect a specified effect under stated conditions. They do not show whether the observed result is true or whether the trial had a particular probability of finding an effect after the data were collected.

There is no indication in the registry record of over-dispersion modeling or a count-data model, and the primary outcome is continuous rather than a count. In general, over-dispersion matters when count outcomes vary more than a model’s assumptions allow, because ignoring it can make uncertainty look too small. That general issue does not substitute for a description of the actual model used for this continuous endpoint. The registry’s lack of model detail is the main reason to avoid attributing a specific analytic method to the posted comparison.

11. Confidence Intervals and Precision

The primary mean difference is 3270.0 mg/dL* min, with a confidence interval from -3003.0 to 9543.0. The interval contains both negative and positive values, so the data are compatible with a mean area under the curve that is lower under the extended-bolus condition, as well as one that is higher. The point estimate alone should not be read as a definitive direction or as the size of an established effect.

In general, a confidence interval conveys precision: a narrower interval would indicate a more tightly estimated comparison, while a wider interval leaves more uncertainty about the possible values. This interval is wide relative to the point estimate and spans a substantial range of possible differences. The unadjusted p value of 0.307 is consistent with the interval’s lack of a clear separation from no mean difference, but neither statistic proves that the conditions are the same.

The condition-level standard deviations are 6737.0 for standard bolus and 11790.0 for extended bolus. These describe observed dispersion, not the precision of the comparison. The posted outcome sample size is 18.0 in each condition, but because the study is a crossover and the record does not describe the paired analysis, those counts alone do not show how much within-participant information contributed to the confidence interval.

Precision is also limited by missing methodological details. The analysis model, analysis population, missing-data handling, and adjustment for period or sequence are not reported in the registry record. The confidence interval should therefore be interpreted as the interval attached to the posted comparison, not as proof that every feature of the crossover design was accounted for.

12. Planning a Similar Trial: Sample Size

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

The planning table and curve translate an observed comparison into illustrative future study sizes. The figures are participants per arm, not total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes a planning scenario in which a study with the listed participants per arm would have an 80% chance of meeting the specified statistical decision rule if the assumed effect and model conditions were true. The 90% column uses a higher chance of detection under those same planning conditions, and therefore calls for more participants per arm. These are design illustrations, not observed power.

For the primary comparison, the planning table lists 136 participants per arm for 80% power and 182 participants per arm for 90% power when planning for 100% of the observed effect. When planning for 75% of the observed effect, it lists 241 participants per arm for 80% power and 323 participants per arm for 90% power. When planning for 50% of the observed effect, it lists 542 participants per arm for 80% power and 725 participants per arm for 90% power. Smaller effects require more participants because they are harder to distinguish from random variation.

These figures inherit uncertainty from the observed effect, which itself is imprecise. They are not a reconstruction of the completed study’s design and do not show that the trial was adequately or inadequately powered. The crossover structure is another reason to treat them as planning illustrations: the stated assumptions use equal allocation between two arms and a normal approximation, while the registry does not report how within-participant correlation was handled in the 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 = 3269.700; pooled standard deviation σ = 9601.733.
2. n = 2 × (1.96 + 0.842)² × 9601.733² / 3269.700² = 135.4, rounded up to 136 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 <- 3269.7                      # observed difference in means
sigma <- 9601.73299566281                     # 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(5454891)
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 = 136 (80% power), 182 (90% power)
 75% of observed effect: n per arm = 241 (80% power), 323 (90% power)
 50% of observed effect: n per arm = 542 (80% power), 725 (90% power)
power.t.test: 136.3 
Simulated power at n = 136 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.

14. Multiplicity, Missing Data and Analysis Populations

The record lists a primary endpoint and multiple secondary outcomes, but does not report how the analysis plan handled multiplicity. Multiplicity arises when statistical tests are conducted across several outcomes: even if each test is interpreted using the same nominal threshold, a result may appear notable by chance somewhere in the collection. A prespecified hierarchy, family-wise error control, false-discovery approach, or explicit exploratory framing could guide interpretation, but none is described in the registry record. The posted secondary p values are unadjusted and should not be treated as if they were adjusted confirmatory tests.

The registry lists 12 outcome measures, with 11 secondary outcomes posted. It does not report the rationale for the outcome set or whether all planned outcomes were measured and analyzed. The reported analyses count is 0, although numerical summaries and comparisons appear in the posted results. The record does not explain that distinction, so the analysis count should not be interpreted as meaning that no statistical calculations are displayed.

Missing-data methods are not reported in the registry record. It does not say whether measurements were missing, how any missing glucose readings were handled, whether an outcome required a minimum amount of data, or whether any imputation method was used. The analysis population is also not reported: the record does not state whether summaries include all randomized participants, only participants with usable measurements, or another defined population.

For a crossover study, relevant additional details include how incomplete sequences, withdrawals, period effects, sequence effects, and possible carryover were handled. These details are not reported. The registry also does not describe whether the primary comparison used a paired method or another model accounting for repeated observations. Without these methods, it is difficult to assess whether the uncertainty estimates reflect the design and all available data in the intended way.

The original sample-size justification, interim-analysis plan, and statistical analysis plan are not reported in the registry record. Their absence does not establish that no such plans existed; it means the registry record does not document them. Interpretation should therefore focus on the posted outcome summaries and explicitly retain uncertainty about unreported analysis choices.

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.

Most frequent non-serious adverse event terms

The serious adverse event summaries list 22 at risk in each bolus condition and 0 serious adverse events in each. Deaths are listed as 0 in both conditions. For other adverse events, the record lists 1 affected in the standard-bolus condition and 0 in the extended-bolus condition; each condition has 22 at risk.

These are event counts, not estimates of comparative risk, and the registry does not report a statistical comparison for safety. The record does not describe the event terms, severity criteria for non-serious events, ascertainment process, or the relationship between the safety groups and the crossover exposure periods. The at-risk counts should not be combined or interpreted as distinct-participant totals from the crossover information available.

No serious events or deaths are listed in these summaries, but that descriptive finding does not establish that the strategies have identical safety profiles or that uncommon harms are excluded. The record’s safety information is limited to the posted counts and does not provide enough detail for a broader safety assessment.

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

The results describe glucose outcomes after a high-fat, high-protein meal in a closed-loop system, comparing a standard bolus with an extended bolus. On the primary endpoint, the observed mean was 45370.0 mg/dL* min with standard bolus and 48640.0 mg/dL* min with extended bolus. The estimated mean difference was 3270.0 mg/dL* min, with a confidence interval from -3003.0 to 9543.0 and an unadjusted p value of 0.307. The interval leaves substantial uncertainty about the direction and size of the comparison.

The finding does not demonstrate that extended and standard boluses are equivalent. Equivalence requires a prespecified range of differences considered unimportant and an analysis designed to assess whether the data exclude effects outside that range. No equivalence margin or such framework is reported. Nor does the result establish that the extended bolus is better or worse: the confidence interval includes values on either side of no mean difference, and the record does not report the analysis plan needed to assess the crossover comparison in detail.

The observations also do not establish a general effect beyond the study context. The registry concerns a specific meal type, a specified post-meal interval, and a closed-loop system. It does not report outcomes for other meals or settings. The posted secondary summaries give additional descriptive context, but they are unadjusted and do not yield a clear overall pattern that overturns the primary result.

The safety counts show no serious adverse events and no deaths in either condition, with one other adverse event listed in the standard-bolus condition and none in the extended-bolus condition. These counts do not rule out uncommon harms or establish comparative safety.

In short, the registry documents a randomized crossover comparison with uncertain estimates and incomplete statistical reporting. The data are informative as a record of the measured outcomes, but they do not settle whether one bolus strategy produces a different glucose response, how large any difference might be, or how broadly the findings apply.

17. Why This Trial Matters Statistically

This trial is statistically instructive because its crossover design makes the unit of comparison important. In a crossover study, the same participant may contribute outcomes under both conditions. If those observations are related, accounting for the pairing can change the estimated uncertainty compared with treating condition summaries as unrelated. The registry gives condition-level means and standard deviations, but does not describe the analysis model or the within-participant relationship. Readers therefore cannot determine from the record whether the comparison fully reflects the design’s repeated-measures structure.

The primary endpoint also illustrates the distinction between an estimate and its precision. The mean difference is a single point estimate, while the confidence interval shows that a broad range of differences remains compatible with the posted data. A non-significant unadjusted p value should not be recast as proof of no effect, just as a point estimate in one direction should not be treated as conclusive evidence of that direction.

The multiple secondary outcomes demonstrate why outcome hierarchy and multiplicity matter. The record lists a broad outcome set, but does not report an adjustment plan or a prespecified order for interpreting the comparisons. A collection of unadjusted results can be useful descriptively, yet it is less secure as confirmatory evidence when the testing strategy is unknown.

Finally, the registry distinguishes neither the original design assumptions nor the details of missing-data and analysis-population choices. The sample-size illustrations are based on the observed effect and stated planning assumptions, not on documented original design calculations. This makes the study a useful example of why effect estimates, uncertainty, design structure, and reporting completeness all need to be considered together rather than reduced to a single p value.

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 main trial-specific limitation in interpreting the posted comparison is the lack of a reported crossover analysis method. The study assigns participants to different treatment sequences, but the registry does not state whether the primary comparison accounted for within-participant pairing, period effects, sequence effects, or possible carryover. The condition-level summaries alone do not provide the information needed to evaluate those choices.

The posted outcome sample size is 18.0 in each condition, while enrollment is listed as 30. The registry does not explain this difference or state whether the outcome counts represent participants with complete measurements, observations used in an analysis, or another quantity. Because the trial is a crossover, these counts should not be added or assumed to represent separate participant groups.

The endpoint definition identifies an area between the glucose trace and starting glucose over 0 to 5 hours post-meal onset, but further computational details are not reported. The registry does not specify measurement frequency, missing trace handling, or the exact area calculation convention. Those details may affect how readers understand the measure and reproduce the analysis.

The trial focuses on high-fat, high-protein meals in a closed-loop system. The registry does not describe evidence across other meal types or broader settings, so generalization beyond that context is uncertain. The primary estimate is imprecise, and the record does not report a formal equivalence or noninferiority framework. Secondary comparisons are unadjusted, and outcome hierarchy is not reported.

Finally, the analysis population, missing-data approach, original sample-size rationale, and statistical analysis plan are not reported in the registry record. These gaps limit assessment of potential selection, missingness, and analysis-choice effects. They do not prove that any particular bias occurred, but they constrain how confidently the reported summaries can be interpreted.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Extended Bolus for Meals in a Closed-loop System — NCT05454891.
• Registry record last updated 2026-05-12; status last verified 2026-04.
• Results first posted 2026-05-12.
• 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 completed, randomized, unmasked crossover study sponsored by the University of California, San Francisco. It enrolled 30 people with type 1 diabetes and compared standard and extended insulin bolus strategies for high-fat, high-protein meals in a closed-loop system.

The primary endpoint was mean glucose area under the curve over 0 to 5 hours post-meal onset. The posted mean difference for extended compared with standard bolus was 3270.0 mg/dL* min, with a confidence interval from -3003.0 to 9543.0 and an unadjusted p value of 0.307. The estimate is uncertain and does not establish a clear difference or equivalence.

The record also lists secondary glucose outcomes and safety counts, but does not report the analysis plan, crossover-specific modeling details, missing-data methods, analysis population, or multiplicity approach. These reporting gaps limit interpretation of the posted comparisons.