STorz Against Glidescope Effectiveness: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for STorz Against Glidescope Effectiveness (NCT01632683), a randomized na study. The primary outcome is Intubation Success Rate.

2. Clinical Question

The central statistical question is whether the observed proportion meeting this defined success criterion differed between randomized groups, and how precisely the comparison estimates that difference. The registry reports 548.0 participants in the C-MAC arm and 552.0 in the Glidescope arm. These are group results for the registered outcome; they do not, on their own, describe how results may vary across patient or provider characteristics. Those characteristics and any subgroup questions are not reported in the registry record.

3. Trial Design

This was a randomized, double-masked, parallel-group trial with an enrollment of 1100. The registry lists the phase as NA and the status as COMPLETED. The study compared two video laryngoscope devices in patients with a predicted difficult airway: C-MAC with a D-blade and Glidescope with a #4 blade. Providers used the allocated device to facilitate intubation.

The listed start was 2013-05, and primary completion was 2014-06. Oregon Health and Science University is the recorded sponsor. Random allocation supports a planned comparison between groups, while the parallel design means the groups received different devices rather than each participant being assigned to both. The record describes masking as double, but it does not identify which participants, providers, assessors, or other personnel were masked, nor does it describe how masking was implemented.

The primary outcome was the number of participants with successful intubation under the registry definition. The outcome timeframe was 1 week. The registry also lists secondary outcomes concerning intubation time, graded laryngeal view, adjunct use, and observed complications. The available numerical comparisons cover adjunct use and observed complications; separate results for intubation time and graded laryngeal view are not reported in the registry record.

The randomization procedure, allocation concealment, site structure, participant flow, eligibility details, and the trial's original sample-size justification are not reported in the registry record. The record also does not describe the protocol's planned statistical model or analysis population. Consequently, the design can be characterized from the registered allocation, masking, parallel structure, enrollment, interventions, and outcome definitions, but not from details absent from the registry.

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 Intubation Success Rate, measured over 1 week.

The primary endpoint counts participants who achieved successful tracheal tube placement after a single blade insertion, with success confirmed by return of end-tidal carbon dioxide. The registry gives a timeframe of 1 week. This definition makes the endpoint a binary participant-level outcome: each participant either meets the stated success criterion or does not. The posted arm values are therefore counts of participants meeting the criterion, alongside the number of participants in each arm.

A defined success endpoint makes it possible to compare the devices on a clinically interpretable procedural outcome rather than on an intermediate device characteristic alone. Requiring one blade insertion sets a specific threshold for what counts as success, and confirmation by end-tidal carbon dioxide provides the registry's stated confirmation criterion. The result should be interpreted according to this definition; it does not summarize every aspect of intubation, such as time, view quality, adjunct use, or complications.

The endpoint is useful for a between-group comparison because the registered outcome can be expressed as the proportion of participants meeting the criterion in each arm and as a difference between those proportions. It does not establish how the trial handled missing outcome observations or whether every randomized participant was included in the analysis. Those details are not reported in the registry record.

7. Results Posted in the Registry

• Glidescope: 96.2% (531/552) versus 93.4% (512/548) on control; risk difference 2.8 percentage points (95% CI 0.1 to 5.4), risk ratio 1.03 (1.00–1.06); unadjusted two-proportion z-test p = 0.039.

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.

Number of Particpants Requiring Adjuncts to Assist Intubation

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Glidescope: 23.2% (128/552) versus 21.4% (117/548) on control; risk difference 1.8 percentage points (95% CI -3.1 to 6.8), risk ratio 1.09 (0.87–1.35); unadjusted two-proportion z-test p = 0.464.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Glidescope and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Observed Complications

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Glidescope: 15.4% (85/552) versus 17.7% (97/548) on control; risk difference -2.3 percentage points (95% CI -6.7 to 2.1), risk ratio 0.87 (0.67–1.14); unadjusted two-proportion z-test p = 0.304.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Glidescope and the control. The interval gives the range of effects that remain compatible with the data.

The registry names secondary outcomes involving intubation time, graded laryngeal view, adjunct use, and observed complications. The available numerical comparisons cover adjunct use and observed complications. Separate results for intubation time and graded laryngeal view are not reported in the registry record.

Across the two secondary outcomes with numerical comparisons, the point estimates do not align in a single direction: adjunct use and complications have estimates pointing in opposite directions for the Glidescope-versus-C-MAC contrast. Their uncertainty intervals include no difference. In contrast, the primary success comparison has an interval on the positive side of zero. This makes the primary result more distinct in its direction than the secondary pattern, but the secondary outcomes do not supply a consistent independent signal that strengthens or overturns it.

Secondary outcomes may capture different aspects of the procedure, and their findings need not mirror a primary endpoint. They also warrant caution because the registry does not report a multiplicity plan, confirmatory analysis strategy, or detailed statistical analysis plan. When several outcomes are examined, the chance of finding an apparently notable result by chance can increase unless the analysis accounts for the set of comparisons. Without a reported approach to multiplicity, unadjusted secondary results carry less weight as confirmatory evidence.

The registry reports no analyses, and the available secondary comparisons should therefore be read as posted numerical results rather than as a documented hierarchy of prespecified tests. No conclusion about unreported secondary results can be drawn from the outcomes that do have numerical comparisons.

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

• Intubation Time
• Graded Score of Laryngeal View Achieved
• Number of Particpants Requiring Adjuncts to Assist Intubation
• Number of Participants With Observed Complications

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: the defined success criterion is either met or not met. The posted analysis reports arm counts and compares the proportions meeting that criterion. This is a natural way to summarize a binary outcome, because it retains the group denominators and makes the frequency of the event visible. The primary comparison is expressed as a risk difference, with relative measures also reported.

What does the risk difference describe?

The risk difference subtracts one group's event proportion from the other's. In the posted primary comparison, the direction is Glidescope relative to C-MAC. A positive estimate therefore indicates a higher observed success proportion in the Glidescope group; a negative estimate would indicate a lower observed proportion. The reported estimate is 0.028. The arm proportions are 0.934 for C-MAC and 0.962 for Glidescope. The risk difference describes the absolute contrast on the proportion scale, which is often easier to interpret directly than a relative measure.

The point estimate is not a guarantee that the underlying difference equals exactly 0.028. It is an estimate from the trial data. Its reported interval, from 0.002 to 0.054, communicates sampling uncertainty under the interval method used. The registry does not identify the confidence level or method, so those features should not be inferred from the displayed endpoints.

How do the relative measures differ?

A risk ratio divides one group's event proportion by the other's. The posted primary risk ratio is 1.03, with interval endpoints 1.001 and 1.059. A ratio of 1 corresponds to equal event proportions. An odds ratio compares the odds of the outcome rather than the proportions themselves; the posted primary odds ratio is 1.778, with interval endpoints 1.024 and 3.087. When an outcome is common, odds and proportions can be quite different quantities. For that reason, the odds ratio should not be read as though it were a risk ratio, and neither relative measure replaces the absolute risk difference.

These estimates are different summaries of the same comparison. They do not constitute multiple independent replications. The risk difference emphasizes the absolute separation between event proportions, while the risk ratio and odds ratio describe relative contrasts. Considering more than one scale can clarify what the result means, but the measures should be interpreted in their own units.

What does the p-value contribute?

The posted primary p-value is unadjusted and equals 0.039. In general, a p-value is calculated under a null model and describes the probability of data at least as extreme as the observed data under that model and its assumptions. It is not the probability that the null is true, the probability that a finding will replicate, or a measure of clinical importance. Its interpretation depends on how the comparison was specified and on the analysis assumptions.

The record does not report the trial's original statistical analysis plan, the test used, covariate adjustments, or a prespecified threshold for interpreting the p-value. It is therefore not possible from the registry record to determine whether this unadjusted value matches the trial's intended primary analysis or whether any other planned analysis would have been emphasized. The registry also lists zero reported analyses. The numerical comparison is available, but a full account of investigator-reported analysis methods is not.

Why do interval estimates matter?

An interval estimate expresses uncertainty around a point estimate. In general, the interval reflects both the observed data and the statistical procedure used to calculate it; it is not a range containing every plausible value with certainty. A narrower interval indicates greater precision under that procedure, while a wider interval indicates less precision. Interpretation also depends on the interval's confidence level and construction method, neither of which is specified in the registry record. The interval endpoints should therefore be read as reported, without assigning an unreported confidence level.

For a difference measure, zero represents no difference between groups. For a ratio measure, one represents no relative difference. The primary risk-difference interval lies above zero, while the relative-measure intervals lie above one. These features describe the posted estimates and intervals; they do not account for unreported multiplicity procedures or other departures from the intended analysis.

What are the limits of the posted analysis?

The registry gives no description of missing-data handling, analysis populations, model choice, or adjustments. It does not state whether the primary comparison was intention-to-treat, per-protocol, or based on another population. It also does not report how success was assessed, whether assessors were masked, or how protocol deviations were treated. These omissions limit assessment of whether the posted arm counts include all randomized participants and whether the analysis followed a prespecified plan.

General statistical interpretation should distinguish the observed group contrast from the process that generated it. Randomization is the assigned design, but evaluating its implementation and the analysis requires details that are not reported in the registry record. The numerical estimates describe the recorded results; they cannot fill in missing information about randomization procedures, analysis decisions, or data completeness.

11. Confidence Intervals and Precision

The primary risk difference is 0.028, and its reported interval extends from 0.002 to 0.054. The interval is entirely on the positive side of zero, the value corresponding to no difference on the risk-difference scale. This conveys the direction and statistical precision of the posted estimate under the interval method used. The registry does not report the confidence level or calculation method, so the interval should not be assigned an unreported label.

Precision is not the same as importance. An estimate can be precise without establishing whether a difference matters in practice, and an interval does not determine the value of the outcome to patients or clinicians. The point estimate and its interval should be considered together: the point estimate is the central summary, while the interval shows a range of values compatible with the data and method. The relative estimates also have reported intervals: 1.001 to 1.059 for the risk ratio and 1.024 to 3.087 for the odds ratio. These intervals use different scales and should not be compared as though their widths had the same meaning.

For the primary difference, the lower endpoint is close to zero, while the upper endpoint allows a larger positive contrast. Thus, even though the interval does not include zero, it does not imply that the true difference is known exactly. The group sizes and event counts contribute to the information available, but precision also depends on the outcome frequencies and analysis method. Details needed to independently evaluate the interval construction are not reported in the registry record.

The unadjusted p-value of 0.039 addresses a different question from interval width. A p-value summarizes compatibility with a null model; an interval presents uncertainty on the effect scale. Neither alone establishes clinical importance, and neither accounts for any unreported multiplicity strategy. The primary estimate is most clearly read as a positive observed contrast with uncertainty represented by the posted interval, not as an exact or definitive measure of the underlying difference.

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 sample-size entries are planning illustrations expressed as participants per arm, not total events. They use the observed effect as a reference and show planning for 100%, 75%, and 50% of that observed effect. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect.

The 80% power column gives the planned number of participants per arm under those assumptions for a design with 80% power to detect the specified effect. The 90% power column gives the corresponding number per arm for 90% power. In general, power is the probability that a statistical test will reject the null hypothesis when a specified alternative effect is true, under the planning assumptions. It is not a guarantee that a trial of that size will produce a particular result.

The planning curve represents the relationship between the effect targeted and the participant requirement under the stated assumptions. As the target effect becomes smaller, it is harder to distinguish from no difference, so more participants are needed. That is why the illustrations require more participants when planning for 75% or 50% of the observed effect than when using 100% of it. The displayed values should be interpreted as hypothetical design guidance based on the observed result, not as the original design calculation: the trial's own sample-size assumptions and justification are not reported in the registry record. These figures are not observed power.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.934; treatment proportion p₁ = 0.962; average p̄ = 0.948.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3136 = 0.6147.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3130 = 0.2634.
4. n = (0.6147 + 0.2634)² / (0.0276)² = 1,008.6, rounded up to 1,009 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
p0 <- 0.934306569343066                          # control proportion
p1 <- 0.96195652173913                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1632683)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,009 (80% power), 1,350 (90% power)
 75% of observed effect: n per arm = 1,907 (80% power), 2,552 (90% power)
 50% of observed effect: n per arm = 4,543 (80% power), 6,082 (90% power)
power.prop.test: 1008.6 
Simulated power at n = 1,009 per arm: 0.809 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 record does not report a statistical analysis plan describing how the primary and secondary outcomes were to be analyzed or prioritized. It also does not report a multiplicity strategy, such as adjustment of significance levels or a testing hierarchy. This matters because the record lists a primary outcome and multiple secondary outcomes. When multiple hypotheses are tested, interpreting each unadjusted p-value as though it were the only planned test can overstate the strength of evidence. The registry does not establish whether any such adjustment was planned or used.

The primary comparison has an unadjusted p-value of 0.039. That value should not be treated as a multiplicity-adjusted result because no adjustment is reported. Likewise, the secondary comparisons should not be treated as confirmatory evidence without a reported plan specifying their role. The record gives no reported analyses, so it does not clarify how investigators addressed the family of outcomes or whether the posted comparisons correspond to the prespecified analysis.

Missing-data procedures and analysis populations are also not reported in the registry record. It is unknown whether all randomized participants were included in each analysis, how any unavailable outcome observations were handled, or whether exclusions occurred. The record does not identify an intention-to-treat, per-protocol, or other analysis population. These are important details because the analysis population and missing-data assumptions can affect estimates and their uncertainty.

The outcome timeframe is listed as 1 week, but the record does not describe completeness of follow-up, timing of outcome ascertainment, or procedures for resolving uncertain outcomes. The effect of any missing data therefore cannot be evaluated from the registry record. These gaps do not change the arithmetic of the posted comparisons, but they limit assessment of whether those comparisons represent the original analysis plan and all randomized participants.

15. 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.

Most frequent non-serious adverse event terms

The serious adverse event figures report 0 affected participants among 548 at risk in the C-MAC group and 0 among 552 at risk in the Glidescope group. The registry lists no serious adverse event terms. These figures describe the serious adverse event counts recorded during the reported safety assessment; they do not establish that serious events are impossible or that the devices have identical safety profiles. An absence of recorded events in a trial of this size leaves uncertainty about events that are uncommon or not captured.

The registry also records other adverse events affecting 4 participants in the C-MAC group and 7 in the Glidescope group. These are listed separately from serious adverse events and should not be combined with the serious-event counts. Deaths are not reported in the registry record. The timeframe for the adverse event data and the specific criteria used to classify events are not described in the posted safety details, so the figures should be interpreted within those limits.

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

The posted primary results show that the observed success proportion was higher in the Glidescope group than in the C-MAC group under the registry's definition: successful tube placement after a single blade insertion, confirmed by return of end-tidal carbon dioxide. The estimated risk difference is positive, and its reported interval lies above zero. This describes the recorded comparison and its statistical uncertainty; it is not, by itself, a complete account of the devices' performance in every setting or patient group.

The result does not establish that one device is better for every patient, provider, airway situation, or clinical environment. The registry describes the population as having a predicted difficult airway but does not report detailed eligibility criteria, participant characteristics, provider experience, or setting. The outcome also focuses on a specific success definition and timeframe. It does not capture all dimensions of the procedure, and the available numerical comparisons do not report every listed secondary outcome.

The positive estimate and unadjusted p-value should be interpreted alongside the missing analysis details. The registry does not report the trial's original statistical plan, the analysis population, missing-data procedures, the confidence level for the interval, or a multiplicity approach. Those omissions make it difficult to assess whether the posted analysis reflects the intended confirmatory analysis and how results across outcomes were handled.

Randomization is a strength of the registered design because it assigns participants to comparison groups by chance, but the record does not describe the allocation procedure or its implementation. The double-masked designation is recorded, but who was masked and how masking was maintained are not specified. The posted data can therefore support a careful description of the observed randomized comparison, while leaving questions about implementation and analysis unresolved. No treatment recommendation follows from these registry results alone.

17. Why This Trial Matters Statistically

This trial illustrates how a binary procedural endpoint can be presented using both absolute and relative comparisons. The risk difference describes the absolute separation in success proportions, while the risk ratio and odds ratio express relative contrasts. Keeping the measures distinct prevents an odds ratio from being mistaken for a percentage-point difference and helps readers understand that one dataset can be summarized on several scales.

It also demonstrates why estimates and uncertainty should be read together. The primary point estimate indicates the direction of the observed contrast, while the reported interval describes uncertainty around that estimate. A p-value adds a measure of compatibility with a null model, but it does not replace the effect estimate, interval, or clinical judgment about importance. The registry does not report the interval's confidence level or the trial's analysis plan, making transparent limits part of the statistical interpretation.

The presence of secondary outcomes raises a further issue: multiplicity. Results across several outcomes may be useful for understanding different dimensions of a procedure, but unadjusted comparisons do not automatically provide confirmatory evidence. Without a reported testing strategy, the primary and secondary findings should not be treated as though they had the same evidential role.

Finally, the planning illustrations show the difference between trial design assumptions and a calculation based on an observed effect. They can help readers understand how targeted effect size influences required sample size, but they do not recover the trial's original design rationale. Separating observed results, precision, planning scenarios, and unreported protocol details is essential for a statistically disciplined reading of a completed randomized trial.

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.

Several trial-specific details needed to judge generalizability and implementation are not reported in the registry record. The population is described as having a predicted difficult airway, but the eligibility criteria, participant characteristics, clinical setting, and provider experience are not given. The registry also does not report how the prediction of a difficult airway was established. These omissions prevent assessment of how closely the enrolled participants and procedural context resemble other settings.

Although allocation is listed as randomized and masking as double, the method of randomization, allocation concealment, and identities of masked groups are not reported. The record does not describe whether the outcome assessor was masked or how success was adjudicated. Since the primary endpoint depends on a defined procedural event and its confirmation, details about assessment and documentation would help readers evaluate potential measurement differences between groups.

The registry lists a 1 week timeframe for the primary and posted secondary outcomes, but does not provide participant flow, follow-up completeness, or missing-data handling. The analysis population and treatment of protocol deviations are not reported. Nor are the original sample-size justification, model specifications, confidence-interval method, or multiplicity plan reported. The planning illustrations are based on the observed effect and should not be mistaken for the trial's original design assumptions.

The numerical secondary results available in the record do not cover every listed secondary outcome. Results for intubation time and graded laryngeal view are not reported in the registry record. Deaths are not reported in the registry record either. Together, these limitations mean the registered results offer a bounded view of the comparison rather than a complete report of trial conduct and analysis.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: STorz Against Glidescope Effectiveness — NCT01632683.
• Registry record last updated 2017-11-30; status last verified 2017-10.
• Results first posted 2014-10-07.
• 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

NCT01632683, titled STorz Against Glidescope Effectiveness, is a completed randomized, double-masked, parallel-group comparison sponsored by Oregon Health and Science University. The official title describes a comparison of the C-MAC D-blade with the Glidescope videolaryngoscope in a predicted difficult airway. Enrollment was 1100; the registry lists a start of 2013-05 and primary completion of 2014-06.

The primary outcome was intubation success, defined as successful tracheal tube placement after a single blade insertion confirmed by return of end-tidal carbon dioxide, with a 1 week timeframe. Posted results include a positive risk-difference estimate for Glidescope relative to C-MAC, accompanied by a reported interval and an unadjusted p-value. Secondary numerical comparisons cover adjunct use and observed complications. The registry does not report analyses, the original statistical plan, missing-data procedures, analysis populations, or a multiplicity strategy.