The Role of Umbilical Cord Thickness in Prediction of Fetal Macrosomia in Patients With Gestational Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Role of Umbilical Cord Thickness in Prediction of Fetal Macrosomia in Patients With Gestational Diabetes Mellitus (NCT02643225), a registered phase not stated study. The primary outcome is The Number of Participants Who Were Diagnosed With Fetal Macrosomia (Birth Weight).

2. Clinical Question

3. Trial Design

The registry record identifies the study as completed and lists Ain Shams University as the sponsor. It records a total enrollment of 80 and gives the study start as 2015-04 and primary completion as 2015-10. The population description divides pregnant women into a gestational-diabetes case group and a non-diabetic control group, with 40 participants in each group.

The record does not state how group membership was determined or how participants were allocated. It does not identify a randomization method, concealment procedure, blinding approach, or a specific design label. The group names should therefore be read as descriptions in the registry, not as evidence that the groups were randomized or matched. The record also does not explain whether recruitment, follow-up, or outcome assessment differed between groups.

The stated aim is prediction of fetal macrosomia using HbA1C, umbilical cord thickness and interventricular septum thickness. Umbilical cord cross-sectional area is listed as a secondary outcome, along with prediction of fetal macrosomia by measuring HbA1C and interventricular septum thickness. The registry lists four outcome measures overall. It does not specify the full measurement schedule, the way marker values would be combined, or a model for evaluating prediction.

The population description says participants would be divided into the two groups after approval by the local hospital ethics and research committee. Whether approval was obtained, and any further ethics details, are not reported in the registry record. No primary-outcome analysis or statistical analysis is listed. Thus the record establishes the intended groups and study question, but leaves important aspects of conduct and analysis unspecified.

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

Analysis population for the primary outcome, as defined in the registry: The patients will be divided into two groups, 40 pregnant women as case group with gestational diabetes mellitus and 40 non diabetic pregnant women as control group after being approved by the local hospital ethics and research committee.

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.

Population: The patients will be divided into two groups, 40 pregnant women as case group with gestational diabetes mellitus and 40 non diabetic pregnant women as control group after being approved by the local hospital ethics and research committee

6. Primary Endpoint

The registry lists the primary outcome as The Number of Participants Who Were Diagnosed With Fetal Macrosomia (Birth Weight), measured over at birth.

The primary endpoint is the number of participants diagnosed with fetal macrosomia on the basis of birth weight. The outcome is assessed at birth: the registry defines fetal macrosomia as fetal weight of 4 kg or more, and says neonates will be weighed. The endpoint is recorded as a participant count, making it a binary outcome for each participant: the neonate either meets the stated threshold or does not.

As a general statistical point, a binary endpoint translates a measurement into an event classification. This can make the outcome directly interpretable as the occurrence or non-occurrence of a prespecified event. For a prediction study, the endpoint supplies the target that proposed predictors are intended to forecast. Here, that target is the registry's birth-weight definition, rather than a broader measure of newborn health or a continuous analysis of birth weight.

The registry record does not report how many participants met the definition, provide birth-weight summaries, or give estimates of the relationship between the endpoint and the proposed markers. It also does not report details such as who performed weighing or whether assessment was blinded. Those omissions limit interpretation of the endpoint results because no outcome results or assessment details are available in the record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record lists a count endpoint: participants whose neonates are diagnosed with fetal macrosomia at birth. The threshold is 4 kg or more. Each participant's outcome can therefore be represented as an event or a non-event. The registry record does not report the observed counts or an analysis of those counts.

What does a binary outcome represent?

As a general statistical explanation, a binary outcome records whether a defined event occurred for each participant. Researchers may describe such data with event counts and the number of participants assessed. A comparison between groups can use these counts to estimate how often the event occurred in each group and how those frequencies relate. The appropriate analysis depends on the study design, the data available, and the analysis plan. None of those results or a specific analysis plan is reported in the registry record.

The birth-weight definition creates a threshold-based outcome. General statistical consideration: converting a continuous measurement such as weight into a binary category makes the endpoint easier to express as event occurrence, but it does not retain all the information in the original measurement. The registry names the threshold and says neonates will be weighed, but does not report continuous birth-weight results or details about measurement procedures.

How should the prediction aim be evaluated?

As a general statistical explanation, evaluating a predictor involves more than identifying whether its value differs between groups. A prediction model should be assessed for how well its predictions distinguish participants who do and do not experience the endpoint, and for whether predicted risks correspond to observed outcomes. Sensitivity and specificity describe classification at a chosen threshold; discrimination describes separation of outcome groups; calibration concerns agreement between predicted and observed risk. These measures answer different questions and are not interchangeable.

The record names HbA1C, umbilical cord thickness and interventricular septum thickness as candidate measures, and lists umbilical cord cross-sectional area as a secondary outcome. It does not report a prediction model, coefficients, thresholds, performance estimates, validation method, or uncertainty intervals. It is therefore not possible to assess any marker's predictive accuracy or determine whether a combination of markers was evaluated.

What can group comparisons establish?

The registry describes a case group of pregnant women with gestational diabetes and a control group of non-diabetic pregnant women, with 40 participants in each. Allocation is not stated, and the record does not identify a randomized comparison. General statistical consideration: group comparisons can be affected by differences in participant characteristics, measurement, or care, particularly when group assignment is not randomized. Adjustment can sometimes address measured differences, but cannot necessarily remove unmeasured confounding. The record does not state whether adjustment was planned or performed.

The group counts describe the registry's intended population, not the number of participants with complete outcome data. In general, a complete-case analysis uses participants with the variables needed for a particular analysis, while other approaches may address missing values differently. The registry record does not report missingness, exclusions, or analysis populations, so it is not possible to know how many participants contributed to an analysis.

What do uncertainty and significance mean?

As a general explanation, an estimate describes the effect or association calculated from observed data, while a confidence interval communicates its statistical uncertainty. A p-value, when used, describes how incompatible the data are with a specified null model under its assumptions; it does not quantify clinical importance or the probability that a hypothesis is true. The registry record reports no effect estimates, confidence intervals, or p-values, so these concepts cannot be applied to a trial result in this case.

The record's sample-size assumptions describe planning illustrations, not the trial's own design rationale. The illustrations use a two-sided significance level of 0.05, equal allocation between groups, a normal approximation, and an effect defined as a stated share of the observed effect. General statistical explanation: a planning calculation depends on its assumptions, including the target effect and variability. Changing those assumptions can change the implied sample size. A planning calculation based on an observed effect is not observed power, and it does not establish that the study had adequate precision. The registry record does not report its own sample-size justification or the numerical sample-size outputs.

General statistical consideration: over-dispersion matters when data vary more than the assumed statistical model allows. If a model assumes less variability than is actually present, uncertainty can be understated and inferential conclusions can be too confident. The primary endpoint is a participant count, but no model or dispersion estimate is reported; there is no basis to say that over-dispersion was assessed or relevant in the analysis.

Finally, a statistical method cannot be reconstructed from the study aim alone. The record lists no analyses, and does not report model specification, covariate selection, handling of repeated or correlated measurements, diagnostics, or validation. The absence of these details means that the intended analyses and their assumptions are not reported in the registry record, rather than establishing that any particular method was or was not used outside the record.

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("Pregnant Women With Gestational Diabetes", "Non Diabetic Pregnant Women")
n      <- c(40, 40)
events <- c(17, 0)
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  Pregnant Women With Gestational Diabetes  40  17  42.5  27.0  59.1  28.5  57.8  28.5  57.9
ARM  Non Diabetic Pregnant Women  40  0  0.0  0.0  8.8  0.0  8.8  0.1  8.6

11. Multiplicity, Missing Data and Analysis Populations

The study names several candidate measures and outcome topics: HbA1C, umbilical cord thickness, interventricular septum thickness, umbilical cord cross-sectional area, and fetal macrosomia prediction. Considering multiple markers or outcomes can create multiplicity: if many statistical tests are conducted, the chance of at least one apparently notable finding can increase. As a general statistical matter, investigators may specify a hierarchy of outcomes, adjust for multiple comparisons, or emphasize estimation and uncertainty. The registry record does not report a multiplicity strategy, a testing hierarchy, or an analysis plan. It is therefore not possible to determine how multiple analyses, if any, were handled.

The registry record lists no analyses and no primary-outcome results. It does not report the number of participants with missing marker measurements or birth-weight outcomes, reasons for missingness, exclusions, or how missing observations were handled. It also does not define analysis populations, such as whether analyses were intended to include all enrolled participants or only those with complete measurements. Without these details, the number of participants contributing to any analysis cannot be established from the record.

General statistical explanation: missingness can affect an estimate when the availability of measurements is related to participant characteristics or outcomes. The consequences depend on the pattern and reasons for missing data, as well as the analysis approach. No such pattern or approach is documented in the registry record, so the direction or size of any potential effect cannot be assessed.

The record's enrollment count and planned group descriptions should not be interpreted as proof that all participants had complete data for every outcome. Whether exclusions, protocol deviations, or different analysis populations were used is not reported in the registry record.

12. Safety Results

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

Other (non-serious) adverse events

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

The registry record lists 40 pregnant women with gestational diabetes and 40 non-diabetic pregnant women at risk for serious adverse events, with 0 affected in each group. It also lists 40 at risk for other adverse events in each group, with 0 affected in each group. No serious adverse event terms are listed.

These figures are reported counts for the categories shown. They should be read as zero affected participants recorded in those categories, not as proof that no events occurred or that all possible events were fully captured. The record does not describe the event-collection procedures, the period of safety follow-up, or the criteria used to classify events. The deaths field is not reported in the registry record; it should not be read as a reported count of zero deaths.

As a general statistical point, adverse-event counts depend on the definitions and observation process used. A zero count does not by itself establish that an event is impossible or that the data exclude risk. The registry record does not provide further safety analysis, comparative estimates, or uncertainty measures.

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

The registry record documents a study intended to examine whether measurements of HbA1C, umbilical cord thickness and interventricular septum thickness could predict fetal macrosomia in pregnancies with gestational diabetes, with a non-diabetic group also described. It defines the primary endpoint by birth weight at or above 4 kg and reports an enrollment of 80. These details identify the research question and intended outcome, but do not answer the prediction question.

No primary outcome counts, marker results, estimates, or statistical analyses are reported in the registry record. Accordingly, the record does not show whether the proposed markers were associated with the endpoint, whether they could distinguish participants by outcome, or how precise any estimated relationship might be. The absence of those results cannot be interpreted as evidence for or against predictive ability.

Even if a marker were associated with the endpoint, association alone would not establish accurate prediction. As a general statistical point, a useful prediction assessment also considers performance, uncertainty, and whether predictions remain reliable in participants beyond the data used to develop them. The registry record does not report validation or any such performance assessment. It also does not give enough detail to establish how measurement quality, group comparability, or missing observations were handled.

The named groups are not described as randomized, and allocation is not stated. Thus the record cannot support a causal interpretation of differences between groups. Its stated scope is prediction, and no results are available to evaluate even that aim. The safety counts are limited to the adverse-event categories recorded, with event definitions and collection methods not described. Overall, the record is a description of the study's intended comparison and endpoint, not a report of evidence that a marker succeeds or fails.

14. Why This Trial Matters Statistically

This study is statistically relevant because it poses a prediction question using measurable candidate markers and a clearly stated binary endpoint. Defining fetal macrosomia by a birth-weight threshold makes the target event explicit. The intended comparison between participants with gestational diabetes and non-diabetic participants also makes group definition central to interpretation.

Prediction studies require careful separation of distinct claims. A marker may differ between groups without accurately classifying individual outcomes; an apparent relationship may also be imprecise or fail to generalize. As a general statistical point, evaluation should therefore consider estimation, uncertainty, predictive performance, and validation, rather than treating a group difference alone as proof of useful prediction. The registry record does not report these analyses, which makes the distinction especially important when reading the study aim.

The study also illustrates why design information matters. The registry describes case and control groups but does not state allocation or identify randomization. Without that information, readers cannot determine how the groups were formed or how differences between them were addressed. A sample-size illustration based on an observed effect is also different from a prospective design justification; it cannot establish the precision of an unreported result or be treated as observed power.

Finally, transparent reporting of outcomes, missing data, analysis populations, and statistical methods is necessary to evaluate a prediction study. Those details are not reported in the registry record. The record's value is therefore in clarifying the intended question and the limits of what can be concluded from the recorded information, rather than providing evidence about marker performance.

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.

Several limitations specific to interpretation of this study arise from what the registry record does not report. Most importantly, it includes no primary endpoint results and no analyses. There are no event counts by group, marker estimates, measures of prediction performance, or confidence intervals. This prevents assessment of the stated prediction aim, as well as assessment of statistical precision.

The group descriptions do not establish how participants entered either group. Allocation is not stated, and randomization is not reported. The record provides no details about matching, baseline characteristics, or adjustment for differences between groups. Any potential influence of group composition therefore cannot be assessed from the registry record.

The record identifies the candidate measures but does not report measurement timing, procedures, assessor training, blinding, or reproducibility. It also does not describe how the prediction analysis would be specified or validated. Without those details, readers cannot evaluate whether the marker measurements were collected consistently or whether an apparent prediction model would be expected to perform beyond the participants used to develop it.

Information on missing data, exclusions, protocol deviations, and analysis populations is also not reported. The enrollment count does not establish how many participants had complete measurements and birth-weight outcomes. The registry record does not give the study's sample-size justification, a full statistical plan, or a multiplicity approach. Finally, safety-event collection and the deaths field are not fully described. These are limitations of the information available in the registry record; they do not establish what procedures may have occurred outside it.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: The Role of Umbilical Cord Thickness in Prediction of Fetal Macrosomia in Patients With Gestational Diabetes Mellitus — NCT02643225.
• Registry record last updated 2016-08-18; status last verified 2016-07.
• Results first posted 2016-08-18.
• 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

The registry record describes a completed study sponsored by Ain Shams University, with enrollment of 80 and study dates recorded as 2015-04 to 2015-10. The population description specifies pregnant women with gestational diabetes and non-diabetic pregnant women, with 40 participants in each group. Allocation is not stated.

The primary endpoint is the number of participants whose neonates meet the fetal-macrosomia definition of birth weight at or above 4 kg, assessed at birth. The stated prediction measures include HbA1C, umbilical cord thickness and interventricular septum thickness; umbilical cord cross-sectional area is also listed as a secondary outcome.

No analyses or primary-outcome results are reported in the registry record. Missing-data methods, analysis populations, multiplicity procedures, and a statistical plan are not reported. The record therefore describes the intended question and endpoint but does not provide results with which to assess prediction or uncertainty.