Associated Factors in Perioperative Hypoglycemia in Patients With Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Associated Factors in Perioperative Hypoglycemia in Patients With Diabetes (NCT00826007), a registered phase not stated study. The primary outcome is Hypoglycemia Incidence.

2. Clinical Question

3. Trial Design

The study is listed as completed and has the title “Associated Factors in Perioperative Hypoglycemia in Patients With Diabetes.” Its stated purpose is to review mild, moderate, and severe hypoglycemia in preoperative care units, operating rooms, and postanesthesia care units, then analyze associated conditions and treatment. The registry record lists 587 enrolled participants. That enrollment figure is not itself an analysis denominator: the number contributing data to the primary endpoint, and the handling of participants without usable glucose measurements, are not reported in the registry record.

The listed study start is 2009-01, and primary completion is 2011-07. Corewell Health East is listed as the sponsor. The registry record does not describe a randomized assignment. Allocation is not stated, and any arms are not a like-for-like control comparison. The intervention, if any, and the criteria used to define comparison groups are not reported. Accordingly, the record does not establish a trial design in which assigned groups can be treated as equivalent apart from an intervention.

There is one listed outcome measure and one listed analysis. The primary outcome is a participant count for hypoglycemia defined by blood glucose values below 70 mg/dl during the perioperative period. The registry record does not describe the statistical test or model used for the analysis, adjustment for other variables, or whether the endpoint was assessed over a standardized observation window for each participant. Details such as eligibility criteria, recruitment methods, measurement schedules, and definitions for mild, moderate, and severe hypoglycemia are not reported in the registry record.

The record includes sample-size planning illustrations based on the observed effect, with a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Those assumptions describe a planning illustration, not evidence about the original design or the actual analysis. The record does not report a protocol-based sample-size justification or the planning effect used for the study.

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: Retrospective

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 Hypoglycemia Incidence, measured over perioperative period.

The primary endpoint is labeled Hypoglycemia Incidence and is measured as a number of participants. Its definition is blood glucose values below 70 mg/dl during the perioperative period. It is therefore a binary participant-level outcome in which a participant either meets the threshold-based event definition or does not, assuming the necessary glucose information is available. The registry record does not report the number who met the definition or the number assessed.

Counting participants with an event is useful for describing how often a defined outcome occurred in a study population. To interpret an incidence proportion, readers need both the number meeting the event definition and the relevant denominator. The posted record does not supply those results, so it is not possible to state the observed incidence or its precision. It also does not explain whether multiple low glucose measurements in one participant were counted once or handled in another way.

The outcome is distinct from a count of episodes: the stated unit is participants, not events per participant. The study purpose mentions mild, moderate, and severe hypoglycemia, but the primary endpoint description specifies only the threshold below 70 mg/dl. Definitions for severity categories and any separate category-specific results are not reported in the registry record. In general, a clear endpoint definition helps readers understand what the analysis counts, while a clear observation window and denominator are needed to interpret how representative that count is.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

What does a binary endpoint represent?

In general, a binary endpoint classifies each participant into one of two states for a defined outcome: the event meets the stated definition, or it does not. The registry record describes the primary endpoint as a number of participants with blood glucose values below 70 mg/dl during the perioperative period. This is a participant count rather than a count of every low-glucose measurement. The record does not explain how repeated measurements within a participant were handled or how missing measurements affected classification.

For a binary endpoint, a count alone does not describe frequency unless the relevant denominator is also known. An incidence proportion is interpreted as the participants meeting the definition relative to the participants assessed under the specified observation rules. Here, neither the endpoint count nor the analyzed denominator is reported. Enrollment of 587 describes the study’s recorded enrollment, but does not establish that all enrolled participants had endpoint data or were included in the analysis.

What would uncertainty measures add?

In general, a point estimate gives a single summary of the observed data, while a confidence interval gives a range of values compatible with the data and the method used to calculate it. The interval helps readers judge precision; it does not remove possible bias from selection, measurement, or confounding. The registry record does not report a point estimate or confidence interval for the primary endpoint, so its observed frequency and statistical precision cannot be assessed from the posted results.

A p-value, when used, describes how compatible the observed data are with a specified null hypothesis under the assumptions of a statistical procedure. It does not measure the size or practical importance of an association, and it does not establish causation. The statistical test and any p-value for this analysis are not reported in the registry record. No test should be inferred from the endpoint’s binary form alone.

Why do the design details matter?

General statistical interpretation depends on how participants entered the study, how groups were formed, what was measured, and which variables were included in the analysis. The record does not describe a randomized comparison; allocation is not stated, and any arms are not a like-for-like control comparison. Thus, group contrasts, if any, cannot be presumed to isolate a treatment effect. In general, differences in patient characteristics or clinical circumstances can influence both treatment and outcome, and an association may reflect those differences rather than a causal relationship. Whether the analysis adjusted for such factors is not reported in the registry record.

The stated study purpose refers to associated conditions and treatment, but the record does not identify the specific factors or how they were measured. It also does not report whether the analysis used unadjusted comparisons, a regression model, or another method. Without that information, readers cannot assess model assumptions, variable selection, or the extent to which potential confounding was considered. The listed count of one analysis does not specify the analytical method or its covariates.

What do the planning assumptions describe?

The record includes sample-size planning illustrations described as based on the observed effect, with a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. These are assumptions for planning illustrations, not necessarily the study’s own design assumptions. A normal approximation is a general way to estimate the behavior of a test statistic under specified conditions; the accuracy of such an approximation depends on the data and design. The record does not report the original sample-size rationale, the effect targeted in the study’s design, or the basis for selecting the listed planning assumptions.

In general, a planning calculation asks how much information might be needed to detect a specified effect under stated assumptions. It should not be confused with observed power, which is not a useful substitute for reporting the estimate and its uncertainty after data have been collected. The planning illustrations are not outcome findings and cannot indicate whether the study observed hypoglycemia or how strong any association was. No numerical sample-size illustration values or event results are described in the registry record narrative.

What is needed to interpret the endpoint?

General interpretation of a perioperative event count benefits from knowing the observation period, the frequency and timing of measurements, the rules for classifying an event, and the handling of incomplete records. The endpoint names the perioperative period and gives a glucose threshold, but the registry record does not provide further operational details. It does not say whether a participant needed one qualifying measurement, how measurement opportunities differed across care settings, or whether severity categories were analyzed separately.

These omissions do not change the stated endpoint definition, but they limit assessment of reproducibility and comparability. A standardized measurement schedule and transparent rules can help distinguish true differences in event frequency from differences in opportunities to detect events. Whether those procedures were standardized is not reported in the registry record. The endpoint result, its denominator, the statistical method, and uncertainty estimates would be needed for a quantitative interpretation.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Low Normal Group", "Hyperglycemia-treated Group")
n      <- c(308, 279)
events <- c(53, 10)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Low Normal Group  308  53  17.2  13.2  21.9  13.4  21.8  13.4  21.8
ARM  Hyperglycemia-treated Group  279  10  3.6  1.7  6.5  2.0  6.5  2.0  6.5

11. Multiplicity, Missing Data and Analysis Populations

The registry record lists one outcome measure and one analysis. It does not report whether these were the only outcomes and analyses specified in a protocol, whether other outcomes were assessed but not posted, or whether the primary endpoint and analysis were chosen before examining the data. The count of listed measures alone is not enough to establish a complete analysis plan.

Multiplicity arises in general when several outcomes, comparisons, subgroups, or analytical approaches are examined. Repeated testing can increase the chance of a nominally notable result arising by chance. Whether this study involved multiple comparisons beyond the listed analysis, or used any adjustment for multiplicity, is not reported in the registry record. The study purpose mentions mild, moderate, and severe hypoglycemia, but the registry record does not provide separate definitions, analyses, or results for those categories.

Missing-data methods are also not described. The record does not report how many participants had glucose data available, whether data were missing, why they were missing, or how any missing endpoint values were handled. It likewise does not identify the analysis population, such as whether the endpoint analysis included all enrolled participants or a subset with evaluable records. Enrollment of 587 should therefore not be interpreted as the analysis denominator.

In general, missingness can affect estimates when participants with observed data differ systematically from those without observed data. The extent and direction of any such effect cannot be assessed without information about completeness and handling. The registry record does not report sensitivity analyses or other checks for missing data. These gaps limit evaluation of the endpoint estimate as well as any analysis of associated conditions or treatment.

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

The study’s stated focus is perioperative hypoglycemia among patients with diabetes, and its primary endpoint uses blood glucose values below 70 mg/dl during the perioperative period. The registry record establishes the outcome definition and gives an enrollment of 587. It does not report the number meeting the endpoint definition, the number assessed, or a numerical estimate with uncertainty. As a result, the posted information does not quantify the frequency of this outcome in the study population.

The study purpose also refers to associated conditions and treatment, but no factor-specific results are reported in the registry record. No direction, magnitude, or precision of an association can be described. Nor can the record support a claim that a treatment caused a difference in hypoglycemia. It does not describe a randomized comparison, allocation is not stated, and any arms are not like-for-like control groups.

In general, an association means that two measured characteristics vary together in the analyzed data; by itself, it does not show that one caused the other. Causal interpretation requires a design and analysis that address alternative explanations, and those details are not reported in the registry record. The absence of reported results should also not be interpreted as evidence that the event did not occur or that no associations were found. It means the registry record does not provide those results.

The endpoint is a participant count, not necessarily a count of every qualifying glucose measurement. Definitions for mild, moderate, and severe categories, measurement schedules, and handling of repeated observations are not reported. Therefore, the endpoint definition should not be expanded beyond the stated threshold or treated as a complete account of episode burden.

The record can be used to identify the study’s topic, stated outcome, and important gaps in reporting. It cannot establish a perioperative event rate, identify associated factors, compare treatments, or support clinical recommendations. Those conclusions require outcome data and methodological details that are not reported in the registry record.

13. Why This Trial Matters Statistically

Perioperative glucose measurements can be collected across several care settings, and the study’s stated scope includes preoperative care units, operating rooms, and postanesthesia care units. Statistically, this makes clear outcome definitions and transparent measurement procedures important: differences in the opportunities to measure glucose could affect how often a threshold-defined event is detected. The registry record identifies the threshold for the primary endpoint but does not report the measurement schedule or event-classification procedures in detail.

The study is also framed around associated conditions and treatment, which raises an important distinction between describing associations and estimating causal effects. The registry record does not describe a randomized comparison, allocation is not stated, and any arms are not a like-for-like control comparison. These details matter when interpreting group differences, because general statistical adjustment cannot by itself guarantee that groups are comparable or that all relevant confounding has been addressed.

The record illustrates why outcome counts need accompanying denominators and uncertainty estimates. Enrollment is listed as 587, but the number assessed for the primary endpoint is not reported. Without that denominator and the event count, readers cannot estimate the frequency or precision of the endpoint. The same reporting principle applies to associated-factor analyses: estimates, definitions, and methods are needed to judge their meaning.

Finally, a completed study record may still leave important analytical questions unresolved. One outcome measure and one analysis are listed, but the full analysis plan, missing-data handling, and statistical methods are not reported. The planning assumptions describe sample-size illustrations, not observed power or proof that the original design was adequate. These distinctions help keep the interpretation aligned with what the registry record actually documents.

14. Limitations

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

The main limitation for interpretation is that the registry record does not report the primary endpoint result. Neither the number of participants meeting the glucose threshold nor the number included in the analysis is stated. Although enrollment is listed as 587, that figure cannot establish how complete the endpoint data were or what denominator was used. No estimate of incidence or its precision can therefore be recovered from the record.

Measurement and classification details are limited. The endpoint specifies blood glucose values below 70 mg/dl during the perioperative period, but the registry record does not explain the schedule of glucose measurement, how repeated low values were counted, or how participants with incomplete measurements were classified. The study purpose mentions mild, moderate, and severe hypoglycemia, but the definitions and category-specific results are not reported.

The analysis of associated conditions and treatment is not described in enough detail to assess its statistical approach. The factors examined, their operational definitions, the method used, covariate adjustment, and uncertainty estimates are not reported in the registry record. The record does not describe a randomized comparison; allocation is not stated, and any arms are not like-for-like control groups. Consequently, the posted information does not support causal interpretation of potential group differences.

Further limitations include the absence of reported missing-data methods and analysis-population definitions. It is not possible to determine whether participants without endpoint data were excluded, how many were affected, or whether sensitivity analyses were performed. The record lists one outcome measure and one analysis, but does not establish whether this reflects a complete prespecified analysis plan. These reporting gaps restrict assessment of precision, bias, and reproducibility.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: Associated Factors in Perioperative Hypoglycemia in Patients With Diabetes — NCT00826007.
• Registry record last updated 2013-05-27; status last verified 2013-03.
• Results first posted 2013-05-27.
• 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.

18. Record Summary

NCT00826007 is a completed study titled “Associated Factors in Perioperative Hypoglycemia in Patients With Diabetes,” sponsored by Corewell Health East. The registry record lists enrollment of 587, a study start of 2009-01, and primary completion of 2011-07. Its stated purpose is to review mild, moderate, and severe hypoglycemia in preoperative care units, operating rooms, and postanesthesia care units, and analyze associated conditions and treatment.

The listed primary outcome, Hypoglycemia Incidence, counts participants with blood glucose values below 70 mg/dl during the perioperative period. The endpoint result, analysis denominator, associated-factor estimates, and statistical methods are not reported in the registry record. The record does not describe a randomized comparison; allocation is not stated, and any arms are not like-for-like control groups. It lists sample-size planning illustrations based on the observed effect, but these do not establish the study’s original design rationale or observed power. Adverse events are identified as not collected, so the absence of reported adverse-event counts should not be interpreted as evidence that none occurred.