Obtain a Good Blood Glucose Control With the Paradigm Real Time System: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Obtain a Good Blood Glucose Control With the Paradigm Real Time System (NCT00441129), a randomized na study. The primary outcome is Difference in HbA1C From Baseline and 6 Months.

2. Clinical Question

This is a question about comparative change, not simply whether either group’s HbA1C changed over time. A difference between the groups is the key quantity for the randomized comparison. The posted information gives group-level means and standard deviations, but it does not provide participant-level results or adjusted estimates. The primary comparison is consequently interpreted as an unadjusted comparison derived from the posted summary statistics.

3. Trial Design

The registry describes NCT00441129 as a completed, randomized, parallel-group trial with no masking. The recorded enrollment is 115. The study began in 2006-06 and its primary completion was 2008-05. The registry lists the phase as NA. The sponsor is Medtronic MiniMed, Inc. These details characterize the recorded trial design; they do not establish how the trial was conducted beyond what the registry states.

Participants were assigned to conventional insulin pump therapy or the MiniMed Paradigm Real-Time System. The registry lists 60 participants in the conventional pump group and 55 in the real-time system group for the primary outcome. The two interventions are both listed as devices. In the brief summary, the real-time system is described as an insulin pump that can receive and display data from a separate glucose sensor, while the comparator is conventional continuous subcutaneous insulin infusion.

The primary endpoint timeframe is baseline and 6 months. The posted primary outcome is the mean change in HbA1C, with standard deviation as the measure of spread. Two secondary outcomes are also posted: change in mean blood glucose calculated from continuous glucose monitoring recordings, and change in total daily dose. Their stated timeframe is also baseline and 6 months.

Randomization is relevant because, in general, assigning participants by chance is intended to make treatment groups comparable on average, including factors that may not have been measured. It does not guarantee that every relevant characteristic is balanced, and the registry record does not provide baseline characteristics or details of the randomization procedure. The open-label designation means masking was recorded as none. Whether or how awareness of assigned treatment affected measurement, behavior, or care is not reported in the registry record.

The registry does not report the original sample-size justification, allocation procedure details, participant flow, or analysis-population definition. It also does not give a fuller account of follow-up or treatment adherence. These omissions limit how far the recorded design can be reconstructed from the registry entry alone.

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

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 Difference in HbA1C From Baseline and 6 Months, measured over Baseline and 6 months.

The primary endpoint is the difference in HbA1C from baseline to 6 months, defined as the 6-month value minus the baseline value. HbA1C is recorded as a percentage of HbA1C, and the registry reports the mean change and standard deviation for each group. Because the endpoint is expressed as a change, a negative group mean indicates that the average 6-month value was below the average baseline value for that group.

As a general clinical-trial concept, HbA1C is used as a measure of longer-term glycemic status, so a change from baseline provides a way to assess whether average status shifted during follow-up. A comparison of changes between randomized groups addresses whether those shifts differed between the assigned treatment strategies. It is more informative for the comparative question than examining change within one group alone, because changes within a group can reflect factors other than the intervention.

The endpoint does not, by itself, describe every aspect of glucose control or the participant experience. It does not show how individual values varied, how changes were distributed, or whether particular subgroups had different results. Those details are not reported in the registry record. The six-month timeframe also defines the period represented by this outcome; longer-term outcomes are not reported in the posted primary result.

For the posted primary result, the conventional pump group mean change was -0.57 percentage points and the real-time system group mean change was -0.81 percentage points. The unadjusted between-group mean difference was -0.24 percentage points, defined as the real-time system group minus the conventional pump group. The interval for that difference includes zero, so the estimate does not resolve whether the underlying between-group contrast is positive or negative.

7. Results Posted in the Registry

• Minimed Paradigm Real Time Sytem: mean -0.81 versus -0.57 on control; difference -0.24 (95% CI -0.61 to 0.13), standardized effect d = -0.24; z-test p = 0.208.

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.

Change From Baseline in Mean Blood Glucose Value Calculated From CGMS Recordings.

• 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:
  • Minimed Paradigm Real Time Sytem: mean -30.60 versus -10.80 on control; difference -19.80 (95% CI -37.24 to -2.36), standardized effect d = -0.42; z-test p = 0.026.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Minimed Paradigm Real Time Sytem than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Total Daily Dose (TDD)

• 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:
  • Minimed Paradigm Real Time Sytem: mean 1.50 versus 6.80 on control; difference -5.30 (95% CI -10.29 to -0.31), standardized effect d = -0.38; z-test p = 0.038.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Minimed Paradigm Real Time Sytem than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The two secondary outcomes provide additional measures related to glucose control and treatment dose, but they address different questions from the primary HbA1C comparison. The posted mean glucose outcome comes from continuous glucose monitoring recordings, whereas total daily dose describes insulin use. Their results can offer context for the primary endpoint, but they are not interchangeable measures and do not independently establish the primary comparison.

Both secondary point estimates are more negative in the real-time system group relative to the conventional pump group under the stated subtraction direction. Their posted unadjusted confidence intervals exclude zero, unlike the primary endpoint interval. This pattern is compatible with differences on the secondary measures, but it does not resolve the uncertainty in HbA1C change. It should also not be treated as confirmation that every aspect of glucose control changed in the same way.

As a general statistical issue, evaluating several outcomes creates multiple opportunities for a result to appear unusual by chance. If multiple tests are considered without an adjustment or a prespecified hierarchy, the chance of at least one apparently notable result can increase. The registry record does not report a multiplicity strategy, a testing hierarchy for primary and secondary outcomes, or adjusted secondary analyses. The posted secondary p-values are therefore unadjusted, and they carry less inferential weight than a clearly prespecified primary result.

The fact that the secondary comparisons have confidence intervals excluding zero does not itself establish their clinical importance. The units and meanings differ, and the registry does not state thresholds for meaningful change. Nor does it provide participant-level relationships among HbA1C, monitored glucose, and daily dose. It is not possible from group summaries to determine whether changes in one outcome tracked changes in another for individual participants.

Overall, the secondary results add descriptive context: the observed group contrasts point in a similar direction across the posted measures, but the primary comparison remains imprecise and the secondary inferences are unadjusted. This is a pattern to interpret cautiously rather than a reason to replace the primary endpoint or treat secondary findings as definitive.

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

• Change From Baseline in Mean Blood Glucose Value Calculated From CGMS Recordings.
• Change From Baseline in Total Daily Dose (TDD)

9. Statistical Interpretation

10. Statistical Methods Explained

The posted outcomes are continuous measures summarized by group means and standard deviations. The principal comparison is a difference in mean change between the randomized groups. For the primary endpoint, the contrast is the real-time system group’s mean HbA1C change minus the conventional pump group’s mean change. A negative contrast indicates a more negative average change in the real-time system group, using the stated change definition. The same general interpretation applies to the secondary mean differences, in their respective units.

What does a mean difference represent?

As a general statistical explanation, a group mean condenses a set of measurements into an average, while a standard deviation describes how spread out measurements are around that average. A mean difference compares two group averages on the endpoint’s original scale. It is not a percentage change unless the endpoint itself is expressed that way, and it does not tell how many individuals experienced a particular change.

For the primary outcome, the posted group means are -0.57 and -0.81 percentage points. The reported unadjusted mean difference is -0.24 percentage points. The comparison is based on summary statistics and is not identified as an adjusted model estimate. The registry does not report a model specification, covariate adjustment, or a detailed statistical analysis plan. Consequently, it is not possible to determine from the record whether the trial’s original analysis used a different approach.

Why is a confidence interval useful?

As a general statistical explanation, a confidence interval describes a range of values compatible with the estimate under the method’s assumptions. It conveys precision as well as direction: a narrower interval represents greater precision than a wider interval. For the primary contrast, the posted 95% interval includes zero. This means the summary does not distinguish the observed contrast from no difference at the conventional interval level. It does not mean that every value in the interval is equally plausible, nor that the true effect has a particular probability of lying within this one calculated interval.

The unadjusted p-value for the primary comparison is 0.208. In general, a p-value measures how inconsistent the observed data are with a specified null hypothesis under a statistical model; it is not the probability that the null hypothesis is true. The registry does not report whether the primary comparison was tested using a particular model, nor does it report a multiplicity adjustment. The posted comparison is therefore best described as unadjusted, not as a fully documented reproduction of the trial’s original inferential analysis.

What does randomization contribute?

In general, random allocation aims to reduce systematic differences between groups at the start of a trial. It supports a causal comparison when combined with sound follow-up and analysis, but does not eliminate uncertainty or automatically address missing outcomes, non-adherence, or departures from the assigned treatment. The registry records randomized allocation, but it does not report the sequence-generation method, concealment process, baseline balance, or analysis population. The posted outcome summaries alone cannot verify those features.

Why does spread matter?

As a general statistical point, greater variability makes it harder to estimate a group mean and a between-group contrast precisely when other conditions are comparable. The primary group standard deviations were 0.94 and 1.09 percentage points. For the secondary outcomes, the reported standard deviations were 39.6 and 54.0 mg/dL for mean blood glucose change, and 17.3 and 9.1 units/day for total daily dose change. These are measures of dispersion, not confidence limits. They describe spread in the observed group outcomes and should not be confused with uncertainty in the estimated between-group difference.

Over-dispersion is a general concern when a statistical model assumes less variability than the data contain. Underestimating variability can make uncertainty appear too small. The registry reports standard deviations for these continuous outcomes, but it does not report a model checking procedure or a discussion of distributional assumptions. The reported planning illustration uses a normal approximation; it is not evidence that the trial’s original analysis used that approximation.

What is not documented?

The registry lists no reported analyses for the posted outcomes. The original statistical plan, handling of missing outcome measurements, analysis population, treatment of protocol deviations, and any adjustments for baseline values are not reported in the registry record. Neither are interim analyses or stopping rules. Those absences prevent a complete assessment of whether the posted comparison follows a prespecified analysis and how sensitive the result might be to alternative choices.

The standard deviations and group means can support simple unadjusted comparisons, but they cannot reproduce participant-level analyses or account for factors not included in the summaries. The reported comparisons are therefore useful as transparent summaries of the posted results, while their scope should not be mistaken for a complete statistical report of the trial.

11. Confidence Intervals and Precision

Precision is conveyed by the uncertainty around the estimated difference, not only by the point estimate. The primary unadjusted mean difference in HbA1C change was -0.24 percentage points. Its 95% confidence interval extends from -0.614 to 0.134. Since the interval includes zero, the posted primary estimate is compatible with no difference as well as with differences in either direction. The interval’s width indicates that the estimate does not pinpoint a narrow range of plausible contrasts.

As a general statistical explanation, a confidence interval reflects both the observed contrast and the uncertainty in estimating it. An interval does not guarantee that the true effect is contained within its endpoints, and it does not describe the range of outcomes for individual participants. The posted standard deviations describe outcome variability; the confidence interval describes uncertainty in the group comparison. These are related but distinct quantities.

The primary group sizes were 60 for conventional pump therapy and 55 for the real-time system. The standard deviations were 0.94 and 1.09 percentage points. These summaries give context for the precision of the mean comparison, but the registry does not report individual-level data or an adjusted estimate. It is therefore not possible to assess how baseline adjustment, missing measurements, or a different analysis population would alter the interval.

The secondary outcome intervals for mean blood glucose change and total daily dose exclude zero, while the primary interval includes zero. That contrast in statistical uncertainty should not be interpreted as a ranking of clinical importance. The outcomes use different units and measure different aspects of the study, and the registry does not report a plan for interpreting them jointly. In general, multiple intervals viewed together also raise the possibility of chance findings, particularly when there is no reported multiplicity procedure.

The primary interval should be read alongside the mean difference and the endpoint definition. Its negative point estimate describes the direction of the observed average contrast, while the interval shows that the direction is not determined precisely. Neither the interval nor the p-value establishes whether a difference is important to participants; a threshold for clinical importance is not reported in the registry record.

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 event counts. They are planning illustrations based on the observed effect, not the trial’s original sample-size calculation. The stated 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 trial’s own original design assumptions are not reported in the registry record.

The 80% power column describes a planning target under which a study of the stated size would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column uses a higher chance of detection as its target. Power is not a guarantee that a future study will reach a statistically significant result, and it does not describe the probability that the treatment effect is true.

For the primary endpoint, planning for 100% of the observed effect gives 281 participants per arm for 80% power and 376 participants per arm for 90% power. Planning for 75% of the observed effect gives 499 participants per arm for 80% power and 668 participants per arm for 90% power. Planning for 50% of the observed effect gives 1,122 participants per arm for 80% power and 1,502 participants per arm for 90% power.

Smaller effects require more participants to detect under the same assumptions, because a smaller difference is harder to distinguish from random variation. The declining fractions of the observed effect therefore correspond to larger planned group sizes. These figures are not observed power: they are prospective illustrations calculated from the observed effect, and the observed estimate itself is uncertain. The original trial’s sample-size rationale is not reported in the registry record.

For a confidence-interval curve, the general reading is that greater precision is represented by a narrower interval around the estimated difference. Planning for more participants can generally improve precision when other assumptions remain comparable, but the estimates shown depend on their stated assumptions. The planning illustration does not establish what sample size would be appropriate for a future study without a separate design decision about the effect of interest.

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 = -0.240; pooled standard deviation σ = 1.014.
2. n = 2 × (1.96 + 0.842)² × 1.014² / -0.240² = 280.5, rounded up to 281 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 <- -0.24                      # observed difference in means
sigma <- 1.01445220406695                     # 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(441129)
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 = 281 (80% power), 376 (90% power)
 75% of observed effect: n per arm = 499 (80% power), 668 (90% power)
 50% of observed effect: n per arm = 1,122 (80% power), 1,502 (90% power)
power.t.test: 281.4 
Simulated power at n = 281 per arm: 0.800 (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 identifies one primary endpoint and two secondary outcomes. It does not report how the statistical analysis addressed the possibility of multiple comparisons. That matters because testing several outcomes can increase the chance of finding one result that appears statistically unusual even when the underlying differences are absent. This is a general statistical concern, not evidence that any particular posted result is spurious.

The two secondary p-values are described as unadjusted. The registry does not report a family-wise error adjustment, a false-discovery approach, a hierarchical testing procedure, or another multiplicity plan. It also does not state whether these secondary outcomes were prespecified in a protocol or analysis plan. Their nominal p-values should therefore be read without assuming that the overall error rate was controlled.

The registry lists no reported analyses for the posted outcomes. It does not say whether the primary endpoint analysis used an intention-to-treat population, a per-protocol population, or another analysis set. The number of participants with outcome data at 6 months, reasons for missing data, and the method used to handle missing measurements are not reported in the registry record. The outcome group sizes are reported, but those numbers alone do not establish the amount or handling of missing data.

As a general statistical point, missing outcomes can affect an estimated treatment contrast if availability of measurements is related to treatment assignment or to the outcome itself. Different assumptions and methods for missing data can lead to different results. Without a participant-flow account and analytic details, the impact of missingness cannot be assessed from the posted summaries.

The registry also does not report baseline-adjusted analyses, sensitivity analyses, subgroup analyses, interim analyses, or stopping rules. It is therefore not possible to assess robustness to alternative models or analysis populations, or to determine whether any additional analyses were planned. These are limits of the documented record, rather than proof that the trial lacked such procedures. The appropriate conclusion is that these statistical details are not reported in the registry record.

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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: ketoacidosis (5.0%), hypoglycemic coma (1.8%), foot surgery (1.7%), optic neuritis (1.7%), gastroenteritis (1.7%).

The registry lists serious adverse events affecting 6 of 60 participants at risk in the conventional insulin pump group and 2 of 55 at risk in the real-time system group. It lists other adverse events affecting 25 of 60 at risk in the conventional group and 16 of 55 at risk in the real-time system group. Deaths are recorded as 0 in each group. These counts are best read as registry-reported group summaries, not as evidence that the groups had identical exposure or complete safety follow-up.

The listed serious adverse event terms include Ketoacidosis at 5.0%, Hypoglycemic Coma at 1.8%, Foot Surgery at 1.7%, Optic Neuritis at 1.7%, Gastroenteritis at 1.7%, and Hyperglycemia at 1.7%. The registry’s term percentages do not, by themselves, explain the number of affected participants, whether events were related to treatment, or how event severity and timing were adjudicated.

As a general statistical point, safety counts are descriptive unless their definitions, ascertainment, follow-up, and comparative analysis are clear. The registry record does not report those details, nor does it provide a statistical comparison for adverse events. The counts should not be taken as proof of a safety difference or of no safety difference between the groups.

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

The posted primary result describes a mean decrease in HbA1C in both treatment groups over baseline to 6 months. The real-time system group had a more negative mean change than the conventional pump group, and the unadjusted mean difference was -0.24 percentage points. However, the 95% confidence interval includes zero and the unadjusted p-value was 0.208. The observed direction is therefore not enough to establish a clear difference between the groups.

This result does not mean that there was no effect. An interval that includes zero can reflect uncertainty around the estimate, including the possibility of differences in either direction. Nor does the point estimate prove that the real-time system produced a benefit. The posted result is a group-level estimate with uncertainty, not a definitive statement about an individual’s outcome.

The secondary results describe differences in mean glucose change from continuous monitoring and in total daily dose. Both unadjusted intervals exclude zero, but these outcomes are secondary and the registry does not report adjustment for multiple comparisons. Their results do not remove the uncertainty in the primary HbA1C comparison, and they do not establish that changes in these measures are clinically important. Thresholds for meaningful differences are not reported in the registry record.

The trial record supports a description of the randomized comparison, its posted group summaries, and the uncertainty around the unadjusted contrasts. It does not support conclusions about long-term outcomes, effects in subgroups, or how the results apply to populations not described in the registry. Further details about baseline characteristics, missing observations, treatment adherence, analysis populations, and the original statistical plan are not reported in the registry record.

As a general interpretation principle, statistical evidence and clinical importance are distinct. The p-value and confidence interval address uncertainty under statistical assumptions; neither decides whether an observed change matters to participants. The trial’s posted data should be interpreted within the six-month outcome timeframe and the limits of the registry’s reporting, without turning a group average into medical advice or an individual prediction.

17. Why This Trial Matters Statistically

This trial is statistically informative because its primary question is framed as a comparison of changes between randomized groups. That distinction matters: observing a change within either group does not by itself show that the assigned strategies differed. The relevant primary estimate is the difference between mean changes, and the posted interval makes the uncertainty in that contrast visible.

The result also illustrates why a point estimate and its precision should be read together. The estimated primary contrast favors a more negative average change in the real-time system group, but the confidence interval includes zero. Reporting direction alone would overstate what the data establish; reporting only a p-value would omit the range of contrasts compatible with the estimate.

The secondary measures illustrate another common issue in clinical-trial interpretation: outcomes can point in a similar direction yet differ in statistical certainty and in meaning. Blood glucose from continuous monitoring and daily dose are not the same endpoint as HbA1C. Since multiplicity handling is not reported, the nominal secondary findings deserve more caution than the primary question.

The record also shows the value and limits of registry reporting. It includes group-level means, standard deviations, confidence intervals for comparisons, and adverse-event counts, which support a transparent descriptive reading. At the same time, details needed to audit the original analysis, including missing-data methods and the analysis population, are not reported. Statistical interpretation depends both on the numerical result and on an understanding of how that result was obtained.

Finally, the planning illustrations make clear that sample-size calculations depend on the effect size chosen for detection. Smaller target effects require larger planned groups under the stated assumptions. These planning figures are not evidence about the trial’s original design rationale and do not change the uncertainty in the observed result.

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 gives a concise account rather than a full trial report. It does not provide baseline participant characteristics, detailed eligibility criteria, the randomization procedure, allocation concealment, or a participant-flow description. The recorded group sizes therefore cannot answer questions about baseline balance or the completeness of endpoint follow-up.

The trial was recorded as open-label, with masking set to none. The registry does not describe how outcomes were collected or whether outcome assessors were masked. HbA1C is a laboratory measure, but no further information about measurement procedures or quality control is reported in the registry record. The record also does not detail adherence, treatment changes, co-interventions, or departures from assigned treatment.

The outcome summaries are group-level means and standard deviations. No participant-level data, adjusted estimates, subgroup findings, or sensitivity analyses are reported. The reported comparisons are unadjusted, and the registry lists no reported analyses. It is not possible to evaluate how different modeling choices or missing-data assumptions might affect the results.

Only the primary endpoint and two secondary outcomes are described with posted results. The registry does not report a multiplicity plan or distinguish confirmatory from exploratory secondary analyses. This limits the strength of inferences drawn from the secondary p-values. The record also does not report a threshold for a clinically meaningful difference, so statistical uncertainty cannot be translated into a judgment of practical importance from these registry entries alone.

The stated endpoint timeframe is baseline and 6 months. Results beyond that period are not reported in the registry record. Safety information is presented as counts and selected event terms, without details on event relatedness, ascertainment, duration of follow-up, or comparative statistical analysis. These limitations should bound interpretation of both the efficacy outcomes and the adverse-event summaries.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Obtain a Good Blood Glucose Control With the Paradigm Real Time System — NCT00441129.
• Registry record last updated 2018-12-05; status last verified 2018-12.
• Results first posted 2018-12-05.
• 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

NCT00441129 is recorded as a completed, randomized, parallel-group trial with no masking and enrollment of 115. It compared conventional insulin pump therapy with the MiniMed Paradigm Real-Time System in people with type 1 diabetes. The primary endpoint was mean change in HbA1C from baseline to 6 months.

The posted primary mean changes were -0.57 percentage points for conventional pump therapy and -0.81 percentage points for the real-time system. The unadjusted mean difference was -0.24 percentage points, with a 95% confidence interval that includes zero and an unadjusted p-value of 0.208. The registry also posts two secondary outcomes and adverse-event counts.

The record does not report the original sample-size justification, the statistical analysis plan, missing-data methods, or analysis-population definition. Interpretation is therefore limited to the posted group summaries and their stated uncertainty.