Sleep Optimization to Improve Glycemic Control in Adults With Type 1 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Sleep Optimization to Improve Glycemic Control in Adults With Type 1 Diabetes (NCT04506151), a randomized na study. The primary outcome is Sleep Variability Week 6.

2. Clinical Question

The question concerns a sleep measure rather than a direct measure of blood glucose. The registry summary links insufficient sleep with poor blood glucose control and describes improving sleep and glycemic control as aims of Sleep-Opt. However, the primary outcome reported for this comparison is sleep variability at Week 6. The posted primary result therefore addresses whether the groups differed on that sleep measure, not whether they differed in glycemic control, diabetes complications, or quality of life.

The comparison is between two active behavioral programs, not between Sleep-Opt and no contact. Healthy Living included weekly telephone contact and didactic material matched in time and attention. That comparator helps frame the question as one about the relative outcomes of the two programs. The registry record does not report further details about the intended causal contrast or how the primary hypothesis was specified.

3. Trial Design

The registry describes a randomized, double-masked, parallel-group study of Sleep-Opt and Healthy Living. The study is marked completed, and the registry lists enrollment as 144. Its listed start date is 2021-01-19 and its primary completion date is 2024-12-21. The registry lists phase as NA, which is consistent with the record not assigning a drug-development phase to these behavioral interventions.

Both interventions lasted 12 weeks. Sleep-Opt included self-monitoring, goal setting, and motivational enhancement. The registry summary also describes wearable sleep tracking technology, telephone coaching, and informational content. Healthy Living included weekly telephone contact and didactic content matched to the intervention group in time and attention. The registry record does not describe the procedures used to mask participants or staff, so the practical implementation of double masking is not reported in the registry record.

The primary result gives outcome summaries for 59 participants in Sleep-Opt and 56 in Healthy Living. These are the group counts associated with the posted Week 6 primary outcome, not a statement of the total number randomized or a complete account of follow-up. The registry lists enrollment as 144, but the record does not explain the relationship between enrollment, randomization, and the analysis counts for this endpoint. Nor does it state why the endpoint counts differ from the enrollment figure.

The record lists 36 outcome measures and 35 analyses, and it reports 24 secondary outcomes. It gives three secondary diabetes-distress outcomes at Week 6, Week 12, and Week 24 in the posted results. The other listed secondary domains include self-management behavior and quality of life. The registry record does not report the full analysis populations, allocation procedures, concealment methods, or a detailed schedule of outcome collection. It also does not report the original protocol's sample-size justification or the statistical analysis plan.

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: After those who met study criteria by initial phone screening and informed consent was obtained, participants completed a 1-week run-in period and a confirmation of inclusion criteria, which served as baseline (week 0) data collection.

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 Sleep Variability Week 6, measured over Week 6.

The primary endpoint is Sleep Variability Week 6, measured in minutes. It is described as the standard deviation of total sleep time for one week. A standard deviation describes how spread out repeated sleep-duration measurements are around their average: a larger value indicates more variation across the measured period, while a smaller value indicates less variation. This endpoint therefore characterizes consistency of sleep duration, rather than the amount of sleep alone.

Using a week of sleep measurements gives the endpoint a within-person variability interpretation. A person's total sleep time could differ from night to night even when their average sleep duration is similar to someone else's. The standard deviation captures that fluctuation; it does not identify its cause or indicate whether the average sleep duration is adequate. The registry record does not report the specific measurement device, data-processing rules, or minimum amount of valid sleep data required for the endpoint.

The endpoint is relevant to an intervention that aims to optimize sleep, and the registry summary describes wearable tracking as part of Sleep-Opt. But variability in total sleep time is not itself a direct measure of glycemic control. Although the study summary discusses glycemic control as an intended area of benefit, the posted primary endpoint is a sleep measure. The Week 6 comparison can therefore describe the groups' reported sleep variability at that time point; it cannot, by itself, establish a difference in blood glucose outcomes or longer-term clinical consequences.

7. Results Posted in the Registry

• Healthy Living: mean 63.74 versus 65.92 on control; difference -2.18 (95% CI -14.27 to 9.91), standardized effect d = -0.07; z-test p = 0.724.

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.

Diabetes Distress Week 6

• 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:
  • Healthy Living: mean 2.13 versus 1.83 on control; difference 0.30 (95% CI 0.04 to 0.56), standardized effect d = 0.41; z-test p = 0.026.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Healthy Living than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Diabetes Distress Week 12

• 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:
  • Healthy Living: mean 2.01 versus 1.88 on control; difference 0.13 (95% CI -0.17 to 0.43), standardized effect d = 0.15; z-test p = 0.400.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Healthy Living and the control. The interval gives the range of effects that remain compatible with the data.

Diabetes Distress Week 24

• 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:
  • Healthy Living: mean 1.99 versus 1.83 on control; difference 0.16 (95% CI -0.13 to 0.45), standardized effect d = 0.20; z-test p = 0.273.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Healthy Living and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results include diabetes-distress scores at Week 6, Week 12, and Week 24. They do not form a uniformly consistent pattern across all listed time points: the Week 6 comparison differs in its statistical summary from the later comparisons, while the Week 12 and Week 24 intervals include zero. The reported median-based summaries likewise vary over time. These data should be read as time-specific findings rather than as a single sustained effect.

The secondary outcomes address a different domain from the primary endpoint. Diabetes distress can add information about participants' reported experience, but it does not measure sleep variability or directly establish a change in glycemic control. The registry also lists self-management behavior and quality of life among the secondary outcomes, but results for those domains are not part of the posted secondary findings described in this record. The record lists 24 secondary outcomes overall.

Secondary results carry less weight when many outcomes and time points are examined, especially if the analysis plan does not state how multiplicity was handled. The registry record does not report an adjustment for multiple comparisons, a hierarchy of outcomes, or a prespecified distinction between confirmatory and exploratory analyses. Without that information, an isolated nominal result can be less persuasive than a result supported by a prespecified testing strategy and consistent evidence across related measures.

These secondary findings do not overturn or replace the primary result. They provide additional, limited context, but the record does not support a broad conclusion about the overall effect of Sleep-Opt across distress, self-management, quality of life, sleep, and glycemic control. Each domain requires its own careful consideration of the measure, time point, analysis, and uncertainty.

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

• Diabetes Distress Week 6
• Diabetes Distress Week 12
• Diabetes Distress Week 24
• Self-management Behavior Week 6
• Self Management Behavior Week 12
• Self Management Behavior Week 24
• Quality of Life Week 6
• Quality of Life Week 12

9. Statistical Interpretation

10. Statistical Methods Explained

The primary measure is continuous: it is a numerical outcome expressed in minutes. The posted group summaries give a mean and standard deviation for each arm. The mean describes the group's average reported sleep variability, while the standard deviation describes the spread of individual outcome values around that group average. These are distinct quantities: the endpoint itself is a within-week standard deviation of sleep time, and the group-level standard deviation describes variation in that endpoint across participants.

What does the recalculated mean difference represent?

The recalculated contrast is the Healthy Living mean minus the Sleep-Opt mean. Its estimate is -2.18 minutes. Under that orientation, a negative estimate means that the posted mean was lower in Healthy Living than in Sleep-Opt. This is a simple, unadjusted comparison of the posted summaries. It does not account for possible baseline differences, repeated measurements, covariates, or any other modeling features. The registry record does not report whether the sponsor's own analysis used such adjustments.

The standard error describes the uncertainty of an estimated group mean or contrast due to sampling variation under a statistical model. The posted recalculation includes group standard errors of 4.05 and 4.652 minutes. A standard error is not the same as a standard deviation: it reflects uncertainty in an estimate, not the spread of individual participant outcomes. The recalculated confidence interval for the mean difference uses the posted group summaries and is an approximate, unadjusted interval.

How should a confidence interval be read?

A confidence interval gives a range of values compatible with the observed data under the method used to construct it. In repeated studies using the same procedure, intervals constructed this way would cover the underlying value at the stated rate. For this result, the 95% confidence interval for the recalculated mean difference runs from -14.27 to 9.909 minutes. Because the interval includes zero, it is compatible with no mean difference as well as with differences in either direction. The interval does not assign a probability that the true value lies within this particular range.

The registry also reports a median difference for final values, with its own 95% confidence interval. A mean is sensitive to the magnitude of all values, whereas a median represents the middle of an ordered distribution. The two measures can differ when outcome distributions are asymmetric or contain extreme values. The record does not give enough information to determine why the sponsor reported a median-based contrast, how it was estimated, or how it relates to the trial's original analysis plan.

What does the unadjusted p-value say?

The recalculated p-value is 0.724. In general, a p-value describes 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 clinical importance of a difference. Here it accompanies a simple, unadjusted mean comparison. The registry's own reported median analysis has no p-value recorded, and the trial's prespecified testing procedure is not reported in the registry record.

Statistical significance alone would not determine whether an observed difference matters clinically. That judgment would require an interpretable clinical threshold, context about the outcome, and the planned inferential framework. The registry record does not report a threshold for a meaningful change in sleep variability. It also does not report whether the primary analysis was adjusted, whether there were interim analyses, or whether a particular test was selected before the results were known.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a statistical model expects. When a model assumes less variability than the data contain, standard errors can be too small and confidence intervals can be too narrow, making results appear more precise than they are. The posted primary outcome is continuous and its group standard deviations are reported, but the record does not identify a model that assumes a particular variance structure or report an over-dispersion assessment. This concept is therefore general context, not a claim that over-dispersion occurred in this trial.

The reported analysis and the recalculation also differ in what they summarize. The sponsor reports a median difference, while the simple recalculation uses means and standard deviations. Neither should be silently substituted for the other. The available record does not include participant-level distributions, so it is not possible to determine whether the mean or median better represents the outcome distribution, or to reproduce a model-based analysis from the posted information.

All of these methods describe different aspects of uncertainty and comparison. The group summaries show the observed values and their spread; the mean difference gives a direction and scale for a simple contrast; the confidence interval conveys its precision; and the p-value is tied to a null model. None of these, on its own, supplies information about missing observations, adherence, allocation concealment, or the broader clinical effects of the interventions. Those details are not reported in the registry record.

11. Confidence Intervals and Precision

The recalculated primary contrast is -2.18 minutes, with a 95% confidence interval from -14.27 to 9.909 minutes. This interval is wide relative to the point estimate and includes zero. It is therefore compatible with a range of possible differences, including values on either side of zero. The point estimate alone should not be mistaken for a precise estimate of the underlying group difference.

The sponsor's reported median difference is -2.12, with a 95% confidence interval from -13.75 to 9.59. This interval also includes zero. The registry record does not report a p-value for this analysis. Because the sponsor's contrast is based on medians and the recalculation is based on means, their intervals refer to different estimands and should be interpreted in their own terms rather than combined.

A confidence interval expresses statistical precision, not clinical importance. The registry record does not report a threshold for a meaningful difference in sleep variability, so these intervals cannot be classified against a stated clinical benchmark. Nor does an interval containing zero prove equivalence. To support equivalence, an analysis would need a prespecified margin and an appropriate design and interpretation; neither is reported in the registry record.

Precision also depends on the analysis population and assumptions used to construct an interval. The record gives endpoint-specific group counts and summary statistics, but does not explain missing data, exclusions, or the primary model. The intervals should therefore be read as summaries of the posted analyses, not as a complete assessment of every uncertainty in the study.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total participants or total events. They are illustrations based on the observed effect and use the stated planning assumptions: a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row considers detecting the stated fraction of the observed effect. The figures are planning illustrations, not a report of the trial's original design calculation.

The 80% power column gives the number of participants per arm that the illustration estimates would be needed for an 80% chance of detecting the specified effect under those assumptions, if that effect were the true one. The 90% power column gives the corresponding per-arm estimate for a higher chance of detection. Higher target power generally requires a larger planned sample for the same effect and assumptions.

The planning rows include 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. In this illustration, smaller effects require more participants per arm. For example, the row for 100% of the observed effect lists 3,589 participants per arm for 80% power and 4,805 for 90% power; the row for 50% lists 14,356 and 19,219, respectively. These large values reflect the small observed standardized contrast used in the calculation, not a claim about what the trial's own protocol required.

This is not observed power. It is a prospective-style calculation using the observed effect as a planning input, and it does not show the probability that the completed study detected a real effect. The registry record does not report the original sample-size justification, its target effect, or its design assumptions. The posted planning assumptions are known, but they should not be attributed to the trial's original design.

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 = -2.180; pooled standard deviation σ = 32.963.
2. n = 2 × (1.96 + 0.842)² × 32.963² / -2.180² = 3,589.0, rounded up to 3,589 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 <- -2.18                      # observed difference in means
sigma <- 32.9628038292131                     # 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(4506151)
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 = 3,589 (80% power), 4,805 (90% power)
 75% of observed effect: n per arm = 6,381 (80% power), 8,542 (90% power)
 50% of observed effect: n per arm = 14,356 (80% power), 19,219 (90% power)
power.t.test: 3590 
Simulated power at n = 3,589 per arm: 0.802 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry reports the sponsor's primary analysis as a median difference in final values of -2.12, with a 95% confidence interval from -13.75 to 9.59. The record does not include a p-value or name the method used for that analysis. This sponsor-reported result should be kept distinct from the simple recalculation of the means.

The recalculation uses the posted group means and standard deviations and expresses the contrast as Healthy Living minus Sleep-Opt. It gives a mean difference of -2.18 minutes, a 95% confidence interval from -14.27 to 9.909 minutes, and an unadjusted p-value of 0.724. A median contrast and a mean contrast are not interchangeable, even when their point estimates are numerically similar. They can respond differently to the distribution of participant values and may rely on different methods.

The recalculation is not a reproduction of the sponsor's analysis. It uses only summary statistics and does not incorporate unreported modeling decisions, adjustments, or missing-data methods. The registry record does not establish whether the sponsor's analysis was prespecified or how it handled the endpoint. There is no flagged discrepancy between the posted result and the recalculation, but that does not make the calculations methodologically identical. For interpretation of the trial's own findings, the sponsor's reported analysis takes precedence; the recalculation is a separate descriptive check.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 36 outcome measures, 35 analyses, and 24 posted secondary outcomes. Multiple outcomes and time points create a multiplicity issue: when many statistical comparisons are made, the chance of finding at least one apparently unusual result can increase, even if there is no real effect across the family of outcomes. In general, multiplicity can be handled through prespecified testing hierarchies or adjustments, but those choices depend on the trial's goals and analysis plan.

The registry record does not report whether multiplicity was addressed, which outcomes were designated confirmatory, whether the primary endpoint had a formal testing hierarchy, or how secondary analyses were intended to be interpreted. The unadjusted p-values from recalculations should therefore not be treated as multiplicity-adjusted evidence. A nominal result among several outcomes may be exploratory, but the record does not state that these outcomes were formally designated exploratory.

Missing-data information is also limited. The posted endpoint counts differ across outcomes and time points, and the primary outcome counts are 59 for Sleep-Opt and 56 for Healthy Living. The registry record does not explain the reasons for the counts, the amount or pattern of missingness, any exclusions, or whether missing values were imputed. It does not describe sensitivity analyses to assess how missing outcomes might affect the estimates. Differences in observed counts alone do not reveal why data are unavailable or whether missingness could bias a comparison.

The registry record also does not report the analysis populations, such as whether participants were analyzed according to their randomized assignment, nor does it provide a detailed statistical analysis plan. These omissions limit assessment of the inferential framework and the robustness of the results. They do not establish that a particular method was or was not used; the appropriate conclusion is that these details are not reported in the registry record.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

The safety record lists zero serious adverse events and zero other adverse events in the at-risk groups for both interventions. For serious adverse events, the listed at-risk counts are 73 for Sleep-Opt and 71 for Healthy Living; the recorded event counts are zero in each group. The record also lists zero deaths in each group and no top serious adverse event terms.

These figures describe what was recorded in the registry, not proof that no adverse event of any kind occurred. The safety at-risk counts differ from the primary endpoint analysis counts, and the registry record does not explain the populations or observation periods used for these safety summaries. It also does not provide event definitions, collection procedures, severity grading, or a detailed account of whether events were actively solicited. Zero recorded events should therefore be interpreted within the scope of the registry's reporting, rather than as a complete statement about all possible harms.

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

The primary result describes sleep variability at Week 6 in the two intervention groups. The posted means were 65.92 minutes for Sleep-Opt and 63.74 minutes for Healthy Living, and the simple recalculation estimates a mean contrast of -2.18 minutes when expressed as Healthy Living minus Sleep-Opt. Its 95% confidence interval includes zero and covers differences in either direction. The sponsor's median-based analysis also has a confidence interval that includes zero. These estimates do not provide a precise separation between the groups on the primary measure.

The result does not establish that the interventions are equivalent. Equivalence requires a prespecified margin and an analysis designed to assess whether differences remain within that margin; the registry record does not report either. Nor does the result prove that there is no possible effect. The confidence interval reflects uncertainty and retains a range of values, while the analysis itself depends on its assumptions and the available endpoint data.

The endpoint is sleep-duration variability, not blood glucose. Although the registry summary discusses glycemic control as an aim, the primary result cannot establish an effect on glycemic control, development of diabetes complications, or quality of life. The record includes some secondary diabetes-distress findings, but does not provide results for every listed secondary domain. It also does not report enough information to assess the overall effect across all outcomes.

These findings apply to the reported comparison of Sleep-Opt and Healthy Living, both described as behavioral programs. They do not answer how either program compares with no intervention or usual care. They also should not be generalized beyond the population and implementation described in the registry without further information about eligibility, participant characteristics, and follow-up. The record does not report those details in sufficient depth to support broader claims.

The appropriate interpretation is bounded: the registry reports a Week 6 sleep-variability comparison with an imprecise estimate, alongside other outcomes with their own limitations. The results do not by themselves justify a treatment recommendation or a claim of clinical benefit or lack of benefit.

18. Why This Trial Matters Statistically

This trial raises an important statistical distinction between a measure that fits an intervention's target and a measure that represents a broader clinical goal. Sleep variability is relevant to sleep optimization, but it is not interchangeable with glycemic control. Keeping the endpoint in view prevents conclusions about blood glucose or complications from being inferred from a sleep outcome alone.

The comparison also illustrates why the choice of summary measure matters. The registry reports a median difference, while the recalculation uses a mean difference. Means and medians describe different aspects of a distribution, so their estimates should be interpreted according to their respective methods. The posted information does not include participant-level data or enough method detail to determine how the two summaries relate beyond their reported values and intervals.

Precision is another central issue. The primary confidence intervals include zero and allow a range of possible differences. That uncertainty matters more than a binary reading of a p-value: an estimate can be compatible with no difference while also leaving meaningful differences unresolved. Without a stated clinical threshold or equivalence margin, statistical uncertainty cannot be translated into a definitive judgment about practical importance.

Finally, the registry includes multiple outcomes and time points, but does not report the multiplicity strategy or full analysis plan. That makes it important to distinguish the primary comparison from secondary findings and to avoid over-weighting isolated results. The record is useful for understanding the posted estimates, but its limits on analysis methods, missing data, and outcome interpretation are also part of the statistical picture.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several trial-specific details needed to assess the results are not reported in the registry record. The primary endpoint is defined as the standard deviation of total sleep time for one week, but the measurement device, scoring rules, valid-data requirements, and handling of incomplete sleep records are not described. Those details can affect how a sleep-variability measure is constructed and how comparable measurements are across participants.

The record does not provide participant characteristics, eligibility criteria in detail, the randomization sequence or concealment procedures, or the practical approach to double masking. It describes the two behavioral programs and their intended contact structure, but does not report adherence, intervention exposure, or whether participants followed the self-monitoring and coaching elements. These omissions limit assessment of implementation and of how broadly the findings may apply.

The primary outcome counts are smaller than the registry enrollment figure, but the record does not explain the difference or report reasons for missing endpoint values. There is no reported missing-data method, analysis-population definition, or sensitivity analysis. The sponsor's method is also not identified, and the record does not provide a detailed prespecified analysis plan, multiplicity approach, or original sample-size justification.

The posted primary endpoint concerns Week 6 sleep variability. The registry's summary discusses glycemic control and other possible aims, but the primary result cannot establish effects on those outcomes. The record lists secondary domains, yet only a subset of secondary findings is included in the posted results. These limitations counsel against treating the available outcome summaries as a complete account of the study's clinical results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Sleep Optimization to Improve Glycemic Control in Adults With Type 1 Diabetes — NCT04506151.
• Registry record last updated 2026-08-27; status last verified 2026-08.
• Results first posted 2026-08-27.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry describes a completed, randomized, double-masked, parallel-group behavioral study comparing Sleep-Opt with Healthy Living in adults with type 1 diabetes. Enrollment is listed as 144. Sleep-Opt and Healthy Living were each described as 12-week programs, with the latter designed to match telephone contact and didactic content in time and attention.

The primary outcome was sleep variability at Week 6, defined as the standard deviation of total sleep time for one week and measured in minutes. The posted group means were 65.92 for Sleep-Opt and 63.74 for Healthy Living. The recalculated mean difference was -2.18, with a 95% confidence interval from -14.27 to 9.909 and an unadjusted p-value of 0.724. The sponsor reported a median difference of -2.12, with a 95% confidence interval from -13.75 to 9.59.

The record also includes diabetes-distress outcomes at several time points and lists other secondary domains. It reports zero serious adverse events, zero other adverse events, and zero deaths in the safety groups. Details about the original sample-size justification, analysis plan, multiplicity, missing data, and analysis populations are not reported in the registry record.