Continuous Glucose Monitoring in Patients With End-Stage Kidney Disease and Burnt-Out Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Continuous Glucose Monitoring in Patients With End-Stage Kidney Disease and Burnt-Out Diabetes (NCT05741489), a non-randomized na study. The primary outcome is Percent of Time in Range (TIR) Between 70-180 mg/dL.

2. Clinical Question

3. Trial Design

The registry lists this as a completed, parallel, non-randomized study with no masking. The study start date is 2022-08-10, and the primary completion date is 2023-03-09. The listed phase is NA. Emory University is the sponsor. The enrollment is 40, described as 20 participants with ESKD and burnt-out diabetes and 20 non-diabetic participants with ESKD.

Participants in both groups wear a CGM device for 10 days. The registry describes the groups as ESKD with burnt-out diabetes and ESKD without diabetes. Since allocation is non-randomized, group membership is not assigned by random allocation. Differences between groups could therefore reflect characteristics other than diabetes status; the registry record does not report an adjustment strategy that would address such differences.

The groups are parallel in the sense that each group is observed as a separate group during the study. The record does not describe masking, which is consistent with its listing of masking as none. It does not report additional details about recruitment, eligibility criteria, the CGM device model, participant adherence, or the handling of CGM readings that may be unavailable or unusable. Those details are not reported in the registry record.

The primary endpoint is percent of time in the 70-180 mg/dL range, measured by CGM over up to 10 days. Listed secondary outcomes are mean daily blood glucose concentration and glycemic variability calculated by mean amplitude of glycemic excursions (MAGE). The registry lists 14 outcome measures, but it records no analyses. Without numerical outcome summaries or analysis results, the design can be described, but the size and precision of any group difference cannot be assessed from the registry record.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Percent of Time in Range (TIR) Between 70-180 mg/dL, measured over Up to 10 days.

The primary endpoint is the percentage of time in range (TIR) between 70 and 180 mg/dL, measured by CGM over up to 10 days. It expresses the share of monitored time during which glucose readings fall within the specified interval. The registry describes the endpoint as a mean, with standard deviation as the dispersion measure.

TIR is a summary of glucose readings across the monitoring period, rather than a single reading. In general, a measure of time within a stated range can convey information about glucose patterns that a measure based on a single blood sample may not capture. The study brief specifically raises the question of whether CGM is a better tool than HbA1c for assessing glycemic control in people with ESKD on dialysis. The record does not describe a direct comparison of CGM and HbA1c results, however; the listed primary endpoint is CGM-derived TIR between the two participant groups.

The endpoint's interpretation depends on how readings were collected and summarized, including the amount and completeness of monitoring data. Those details, along with the group means and standard deviations, are not reported in the registry record. It therefore does not establish the observed TIR in either group or the precision of a comparison.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record characterizes the primary outcome as a continuous measure summarized by a mean and standard deviation. It does not report the actual means or standard deviations, or any analysis estimates. The general statistical concepts below explain how such summaries and comparisons are commonly interpreted; they do not describe an analysis result from this record.

What does a mean describe?

For a continuous outcome such as percentage of time in range, a mean is a summary of the observed values in a group. It provides a measure of the group's average outcome, but it does not show how individual values are distributed. Two groups can have similar averages but different degrees of variability, or different averages with substantial overlap among individual observations.

The standard deviation describes the spread of observations around the mean. A larger standard deviation indicates more variability in the measured values within a group. It is not the same as the standard error, which describes uncertainty in an estimated mean, and it is not itself a confidence interval. The registry identifies standard deviation as the dispersion measure for the primary outcome but does not report its values.

How would a group comparison be read?

A comparison of group means would usually be expressed as an estimated difference, with an uncertainty interval such as a confidence interval. In general, a confidence interval gives a range of values compatible with the data and the analysis assumptions at the stated confidence level. Its width reflects precision: a narrower interval indicates greater precision than a wider interval. A confidence interval is not a guarantee that the true value lies within the interval, and it does not remove bias from study design or measurement.

A p-value, when reported, is a measure of how compatible the data are with a specified null model under the assumptions of the statistical test. It is not the probability that the null hypothesis is true, nor does it measure the clinical importance of a difference. A small p-value alone does not establish causation or show that an estimate is precise. The registry record does not report a p-value or a test for the primary comparison.

Why does the design matter?

Random allocation is one way to balance measured and unmeasured characteristics between study groups in expectation. This study is listed as non-randomized. Therefore, a group comparison could reflect diabetes status, other differences between participants, or a combination of factors. Statistical adjustment can address some measured differences if appropriate data and methods are available, but it cannot automatically remove unmeasured confounding. The registry record does not report an adjustment plan or adjusted estimates.

The study is also listed as unmasked. In general, masking can reduce the influence of knowledge about group assignment on aspects of study conduct or outcome assessment. CGM produces device-based readings, but this does not mean every source of bias is eliminated: decisions about data collection, handling, or analysis may still matter. The registry record does not report procedures for masking anyone involved in data handling or analysis.

What does monitoring duration contribute?

TIR summarizes readings across the monitoring interval, rather than describing glucose at just one instant. Its interpretation depends on the frequency and quality of readings and on how much of the intended monitoring period is represented in the analysis. General statistical practice distinguishes the number of participants from the number of observations within each participant: repeated CGM readings from one participant are not automatically independent observations. Analyses that treat correlated readings as independent can understate uncertainty. The registry record does not report the analytic unit, the handling of repeated readings, or details of CGM data completeness.

Over-dispersion is a general concern when observed variability is greater than a statistical model assumes. If a model understates variability, uncertainty estimates can be too small and tests can appear more decisive than warranted. Whether over-dispersion is relevant depends on the outcome distribution and the chosen model. The record does not identify a model or report diagnostics, so no claim can be made about over-dispersion in this study.

How should planning illustrations be understood?

The record describes a planning illustration based on the observed effect, using a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. It says that the effect to detect is a stated fraction of the observed effect. These assumptions describe an illustration for planning, not the trial's own design or a reported analysis. The resulting sample-size values are not reported in the registry record.

In general, sample-size planning asks how many participants per arm might be needed to detect a chosen effect under specified assumptions about variability, significance level, and power. Any such estimate depends on those assumptions. Planning for a fraction of an observed effect changes the target effect used in the illustration; it does not establish that the effect is real or reproducible. It is not observed power. The record also states that the planning calculation uses equal allocation, but that assumption should not be confused with proof that the study was designed or analyzed according to the illustration.

Because the registry does not report the primary outcome summaries or an analysis estimate, the underlying observed effect and its uncertainty cannot be independently evaluated from this record. Nor can the illustration be used to recover those missing results. The appropriate interpretation is limited to the study's stated design and endpoint, with no reported numerical inference about the group comparison.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("ESKD With Burnt-out Diabetes", "ESKD Without Diabetes")
n   <- c(20, 18)
m   <- c(80.4, 94)
sp  <- c(14, 6.4)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  ESKD With Burnt-out Diabetes  20  80.400  14.000  73.848  86.952
CARM  ESKD Without Diabetes  18  94.000  6.400  90.817  97.183

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 14 outcome measures, including the primary TIR endpoint and secondary outcomes of mean daily blood glucose concentration and MAGE. It records zero analyses. Numerical results, statistical tests, and confidence intervals for these outcomes are not reported in the registry record.

Multiplicity arises when several outcomes, comparisons, or statistical tests are considered. In general, evaluating many tests can increase the chance of at least one apparently notable finding under a null model. Common approaches include identifying a primary outcome in advance and applying an adjustment or a hierarchical testing strategy, but the appropriate approach depends on the analysis plan. The registry record does not report whether multiplicity was addressed or which outcomes were included in any analysis.

The record also does not report a statistical analysis plan, analysis populations, or criteria for including participants in analyses. It does not specify how missing or incomplete CGM data were handled, whether all enrolled participants contributed to each outcome, or whether any imputation was used. These omissions prevent assessment of how missing measurements might affect estimates or their uncertainty. They also make it impossible to determine whether reported outcomes, had they been available, were based on consistent participant sets.

These are reporting gaps, not evidence that a particular analysis or missing-data method was or was not used. The absence of such information means that the robustness and reproducibility of any outcome analysis cannot be judged from the registry record.

12. 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 entries list the two study groups separately. For ESKD with burnt-out diabetes, the record lists zero participants with serious adverse events, zero with other adverse events, and zero deaths. For ESKD without diabetes, it likewise lists zero participants with serious adverse events, zero with other adverse events, and zero deaths.

These entries describe what is recorded in the registry; they do not establish that no adverse events occurred in any broader sense. The record does not provide event terms, event narratives, severity details beyond the serious-event classification, or additional information about how adverse events were collected. The list of serious adverse event terms is empty.

Safety figures depend on the period and procedures used to collect and report events, as well as the number of participants with available follow-up. The registry record does not report further details about safety surveillance or completeness of reporting. The zero entries should therefore be read narrowly as the posted counts, not as proof of absence of risk or as a comparison establishing a safety difference between groups.

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

The registry record describes a study of CGM-derived glucose patterns in participants with ESKD, comparing those with burnt-out diabetes with non-diabetic participants. It specifies TIR between 70 and 180 mg/dL as the primary endpoint, measured over up to 10 days. That information establishes the study's question and measurement approach, but it does not provide the outcome values needed to answer the comparison.

The record does not report the primary endpoint mean for either group, the standard deviations, an estimated group difference, or an interval or test for that difference. It therefore does not show whether the groups had similar or different TIR, nor how precisely any comparison was estimated. Secondary outcome values are also not reported. No result about CGM's performance relative to HbA1c can be drawn from the listed endpoint alone; the record does not report a direct comparative analysis of those measures.

Even if group results were available, the non-randomized design would constrain causal interpretation. A difference between groups would not, by itself, show that diabetes status caused the difference. Participant characteristics other than diabetes status may also differ, and the registry does not report an adjustment strategy.

The study's monitoring period is up to 10 days. The registry does not report whether readings were complete or how well the recorded period represents glucose patterns over other periods. The listed zero adverse-event counts likewise do not establish that no events occurred outside the registry's reported entries.

Accordingly, the record supports a description of the intended comparison and outcome, not a conclusion about the direction, size, statistical significance, or clinical importance of a result. Those aspects are not reported in the registry record.

14. Why This Trial Matters Statistically

This study asks a measurement question in a population for whom the registry brief specifically raises whether CGM may be a better tool for assessing glycemic control than HbA1c. The primary endpoint makes the question concrete by defining a glucose range and measuring the percentage of time readings fall within it. The secondary outcomes broaden the stated measurement focus to mean daily glucose and glycemic variability.

Statistically, the study also illustrates why a clearly named endpoint is only part of the evidence needed for interpretation. Readers need outcome summaries, an estimate of the group contrast, and information about its uncertainty. Without these, neither the direction nor the precision of the comparison can be assessed. The registry lists the outcome measures but records no analyses, so the central inferential evidence is absent from this record.

The non-randomized design makes transparent reporting of participant characteristics and analysis methods especially relevant. If groups differ in other ways, a crude contrast may combine those differences with any relationship between diabetes status and TIR. The registry record does not report adjustment methods or results that would help examine that issue.

The short CGM monitoring period and the need to account for repeated readings are also statistically important. A participant's readings over time are related measurements, and the approach to summarizing them affects the interpretation of variability and uncertainty. The record does not provide the details needed to evaluate those choices.

Thus, the record is informative about the intended clinical question and design, while leaving the numerical evidence needed to assess the observed comparison unreported. That distinction matters: endpoint definitions and study completion do not substitute for estimates and uncertainty.

15. 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 most important limitation of interpretation is that the registry does not report results for the primary endpoint. It gives no group means, standard deviations, contrast, confidence interval, or p-value. It also records zero analyses. As a result, the observed association and its precision cannot be assessed.

The non-randomized allocation limits causal interpretation. Group membership is based on diabetes status, rather than random assignment, and the registry does not report whether potential differences between groups were measured or adjusted for. Any observed contrast, if available, could reflect factors other than the group label.

The monitoring interval is described as up to 10 days, but completeness of CGM data and the handling of missing readings are not reported. The record does not state how repeated measurements were summarized or modeled, or how participants with incomplete monitoring contributed to analyses. These details affect the interpretation of a time-based endpoint and its uncertainty.

The registry lists 14 outcome measures, but does not report analysis results or a multiplicity approach. It also does not report analysis populations or a statistical analysis plan. This limits assessment of selective reporting, consistency of analysis sets, and reproducibility.

Additional information about eligibility criteria, recruitment, participant characteristics, device details, and safety collection is not reported in the registry record. These omissions constrain assessment of how broadly the findings might apply and how completely outcomes were captured. No inference about a result can be made from the design information alone.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Continuous Glucose Monitoring in Patients With End-Stage Kidney Disease and Burnt-Out Diabetes — NCT05741489.
• Registry record last updated 2024-04-05; status last verified 2024-02.
• Results first posted 2024-04-05.
• 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.

19. Record Summary

NCT05741489 is a completed, non-randomized, unmasked, parallel study sponsored by Emory University. It lists enrollment of 40 and compares participants with ESKD and burnt-out diabetes with non-diabetic participants with ESKD. Both groups wear a CGM device for 10 days.

The primary endpoint is mean percent of time in the 70-180 mg/dL range over up to 10 days, with standard deviation specified as the dispersion measure. Mean daily blood glucose concentration and MAGE are listed as secondary outcomes. The record lists 14 outcome measures and zero analyses.

Primary and secondary outcome results, statistical comparisons, confidence intervals, and p-values are not reported in the registry record. The posted safety entries list zero serious adverse events, zero other adverse events, and zero deaths in each group. The design and endpoint are described, but the numerical evidence needed to interpret the glucose comparison is not reported.