Efficacy and Safety of Increasing Doses of Inhaled Albuterol in Children With Acute Wheezing Episodes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of Increasing Doses of Inhaled Albuterol in Children With Acute Wheezing Episodes (NCT01323010), a randomized na study. The primary outcome is Hospital Admission.

2. Clinical Question

The study also planned to examine clinical response, respiratory measures, safety, and possible influences of respiratory viruses and ADRβ2 receptor genetics. The registry describes those as study aims; results for viral testing and receptor genetics are not reported in the registry record. The primary comparison is therefore the admission outcome, while the available secondary results offer additional but incomplete context about response and safety.

3. Trial Design

The registry describes a randomized, parallel-group trial with quadruple masking. It lists the study as completed and reports enrollment of 119. The sponsor was the University of Sao Paulo. The recorded study start was 2011-09 and primary completion was 2013-12. Phase is listed as NA. Details such as the randomization procedure, allocation concealment, the identities of the masked parties, and the conduct of masking are not reported in the registry record.

Both groups received albuterol using metered dose inhalers. The experimental regimen used dose bands based on weight during the first hour: 900 mcg up to 15 kg, 1200 mcg for more than 15 to 20 kg, 1500 mcg for more than 20 to 25 kg, and 1800 mcg for more than 25 kg. The control regimen used 600 mcg up to 25 kg or 1200 mcg for more than 25 kg. The record does not provide further information about the number or timing of inhalations, co-interventions, or treatment after the first hour.

The primary outcome was hospital admission starting at 4 hours post-treatment. Admission was operationalized as remaining in the emergency room for more than 4 hours because the participant did not meet the stated discharge criteria: a PRAM score at most 3 and pulse oximetry at least 92%. The registry lists 22 outcome measures and 18 analyses, and identifies 21 secondary outcomes as posted. The available numerical secondary results include changes in forced expiratory volume in the first second, glucose, and respiratory rate. Numerical results for the other listed outcomes are not reported in the registry record. The original design assumptions, including the planned sample-size rationale and any interim analysis plan, are not reported in the registry record.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Hospital Admission, measured over Starting at 4 hours post-treatment.

The primary endpoint is hospital admission, recorded as the number of participants who needed to remain in the emergency room for more than 4 hours because they had not met discharge criteria. The registry sets the assessment starting at 4 hours post-treatment. Its discharge criteria were a PRAM score at most 3 and pulse oximetry at least 92%.

This endpoint turns a clinical disposition decision into a binary outcome: each participant either met the admission definition or did not. Such outcomes can be compared between randomized groups by examining the event counts or the difference in event risks. In this trial, the higher-dose group had 11 participants with the event among 60, and the lower-dose group had 8 among 59. The risk-difference estimate is 0.048 for higher dose minus lower dose.

The endpoint is relevant to the study's stated question because it captures whether the initial treatment course was followed by a need for extended emergency-room care under the registry's definition. It is not a direct measurement of every aspect of symptom relief, lung function, or later health. Its interpretation depends on the stated threshold and on how consistently discharge decisions were assessed. Additional details about adjudication, outcome assessment procedures, or handling of borderline cases are not reported in the registry record.

7. Results Posted in the Registry

• Albuterol - Higher Dose (Experimental): 18.3% (11/60) versus 13.6% (8/59) on control; risk difference 4.8 percentage points (95% CI -8.3 to 17.9), risk ratio 1.35 (0.59–3.12); unadjusted two-proportion z-test p = 0.477.

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.

Forced Expiratory Volume in the First Second

• 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:
  • Albuterol - Higher Dose (Experimental): mean 14.67 versus 11.30 on control; difference 3.37 (95% CI -8.34 to 15.08), standardized effect d = 0.21; z-test p = 0.573.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Albuterol - Higher Dose (Experimental) and the control. The interval gives the range of effects that remain compatible with the data.

Changes in Glucose Serum Levels

• 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 errors.
• Result:
  • Albuterol - Higher Dose (Experimental): mean 34.73 versus 22.90 on control; difference 11.83 (95% CI -2.45 to 26.11), standardized effect d = 0.31; z-test p = 0.104.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Albuterol - Higher Dose (Experimental) and the control. The interval gives the range of effects that remain compatible with the data.

Changes in Respiratory Rate After One Hour

• 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 errors.
• Result:
  • Albuterol - Higher Dose (Experimental): mean -2.08 versus -4.31 on control; difference 2.23 (95% CI -0.57 to 5.03), standardized effect d = 0.29; z-test p = 0.119.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Albuterol - Higher Dose (Experimental) and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists a broad set of secondary aims, including lung function, clinical scores, respiratory rate, glucose, plasma albuterol, electrocardiogram findings, need for additional therapies, and clinical status at discharge or admission. Numerical comparisons are posted for three continuous measures: forced expiratory volume in the first second, glucose change, and respiratory-rate change. Numerical results for the other listed measures are not reported in the registry record.

The three available comparisons do not provide a single consistent, precise signal that can be treated as a second primary result. Their outcome scales and assessment times differ, and their analysis subsets differ. Each re-calculated confidence interval includes zero. These findings can add context about measured responses, but they do not resolve the uncertainty in the primary hospital-admission comparison. Nor do they establish that the groups are the same on secondary outcomes.

Secondary results usually carry less evidential weight when many outcomes are examined. Each separate test creates another opportunity for an apparently notable result to arise by chance. The record identifies 22 outcome measures, 18 analyses, and 21 posted secondary outcomes, but a multiplicity adjustment or a prespecified hierarchy for secondary analyses is not reported in the registry record. Without such information, individual secondary p-values should be interpreted cautiously and should not be treated as independent confirmatory evidence.

Some planned secondary outcomes address biological mechanisms or safety, while others measure clinical course. Their absence from the numerical results means that the overall pattern across every planned secondary endpoint cannot be assessed from the registry record. The available results therefore support a limited description of the reported measures, not a comprehensive conclusion about all secondary aims.

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

• Forced Expiratory Volume in the First Second
• Change in PRAM Score After One Hour
• Albuterol Determination in the Plasma
• Changes in Glucose Serum Levels
• Electrocardiogram at Baseline
• Changes in Respiratory Rate After One Hour
• Need for Additional Therapies
• Changes in PRAM Score at Discharge or Hospital Admission

9. Statistical Interpretation

10. Statistical Methods Explained

What does the risk difference describe?

The primary comparison is expressed as a risk difference: the event risk in the higher-dose group minus the event risk in the lower-dose group. A value of zero would indicate equal observed risks. A positive value points toward a higher observed risk in the first group, and a negative value points toward a lower observed risk. The re-calculated estimate is 0.048. This is an absolute difference on the risk scale, not a relative change. It is based on the posted event counts of 11 among 60 and 8 among 59.

The confidence interval for the risk difference runs from -0.084 to 0.179. It describes a range of values compatible with the data under the calculation's assumptions. Because it includes zero, the result does not distinguish a difference from no difference at conventional levels using that interval alone. The broad span also signals limited precision: effects in either direction remain plausible. The interval should be read alongside the observed counts and the outcome definition, not as a prediction of an individual participant's outcome.

What does the p-value add?

A p-value measures how unusual a result at least as discrepant as the observed result would be under a specified null model and its assumptions. It is not the probability that the null hypothesis is true, nor the probability that chance alone caused the observed result. The registry reports a Chi-squared p-value of 0.689 for the primary comparison. The simple unadjusted re-calculation gives p = 0.477. Their difference reflects that the reported analysis and the re-calculation do not use precisely the same calculation. The registry record does not report enough detail to reconstruct every aspect of its analysis.

A p-value does not give the magnitude of an effect, and a relatively large value does not establish equivalence. For this reason, the estimate and confidence interval are important: they show the direction and range of effect sizes consistent with the data. Interpretation should not reduce the result to whether a p-value crosses a threshold.

How should the continuous outcomes be read?

For a continuous measure, the mean difference compares the group means on that outcome's scale. The posted re-calculations compare the higher-dose and lower-dose groups. For forced expiratory volume in the first second, the measure is the change one hour post-treatment in comparison with baseline, expressed as percentage of predicted. The reported group means are 14.67 and 11.3, and the estimated mean difference is 3.37, with a confidence interval from -8.337 to 15.08. The analysis subset sizes are 18 and 12.

For glucose, the outcome is the change from baseline at discharge or admission, up to 4 hours post-treatment, with a minimum of 1 hour and a maximum of 4 hours. The group means are 34.73 and 22.9 mg/dL, and the estimated difference is 11.83 mg/dL, with a confidence interval from -2.448 to 26.11. The reported dispersion is standard error. For respiratory rate, the change from baseline at one hour is -2.08 and -4.31 breaths per minute; the estimated difference is 2.23, with a confidence interval from -0.570 to 5.03. The reported dispersion is also standard error.

Each continuous-outcome interval includes zero. This means the posted data do not pin down a nonzero mean difference with high precision. The measures are on different scales and reflect different aspects of response, so the numerical estimates should not be compared as if they were interchangeable. The registry also lists outcomes such as additional therapies and changes in PRAM score, but numerical results for them are not reported in the registry record.

Why does dispersion matter?

Dispersion describes how much individual observations vary around a group summary. A mean by itself cannot convey that variation. For forced expiratory volume, the listed dispersion is standard deviation, which describes variation among observations. For glucose and respiratory rate, it is standard error, which describes uncertainty in the estimated mean rather than the spread of individual values. These quantities answer different questions and should not be read as the same kind of variability.

When data vary substantially, the mean difference is estimated less precisely unless the amount of information is sufficient to offset that variability. In the forced expiratory volume comparison, the posted standard deviations are 16.62 and 15.62, alongside analysis subsets of 18 and 12. The confidence interval is correspondingly broad. The sample-size calculations are planning illustrations based on observed effects and stated assumptions; they are not evidence about the original trial's planning process or a substitute for the observed uncertainty.

What is the role of randomized design?

Random allocation is intended to support a fair comparison by reducing systematic differences in groups at the point of assignment. It does not guarantee that all characteristics are balanced, especially in a trial of this size, and it does not remove uncertainty from sampling or measurement. The registry identifies the design as randomized, parallel, and quadruple-masked, but procedural details and the analysis population are not reported in the registry record. Those omissions limit assessment of how closely the analysis followed the randomized comparison.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data locate the effect, not whether the point estimate is positive or negative. For the primary risk difference, the estimate is 0.048 and the confidence interval ranges from -0.084 to 0.179. The interval includes zero and values on either side, so the result does not precisely determine whether the higher-dose group had a lower or higher admission risk. The breadth of the interval is important: the observed counts do not rule out effects of meaningful size in either direction under the calculation's assumptions.

A confidence interval is not a guarantee that the true effect lies within its endpoints, and it is not a range containing a fixed proportion of individual outcomes. In repeated use of the same method under its assumptions, intervals constructed in this way would cover the target parameter at the stated confidence level. The registry comparison does not report its own confidence interval for the primary analysis; the interval is an unadjusted re-calculation.

Precision also varies across the secondary measures. The forced expiratory volume estimate has a confidence interval from -8.337 to 15.08; glucose has an interval from -2.448 to 26.11; and respiratory rate has an interval from -0.570 to 5.03. Each includes zero, and each is expressed on its own outcome scale. The differing analysis subsets and dispersion measures mean that the intervals should be interpreted outcome by outcome, rather than ranked as if they were directly comparable.

These intervals quantify sampling uncertainty under the analysis assumptions. They do not account for every possible source of uncertainty, such as measurement procedures or missing outcome data. Details about missing-data handling are 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 describe hypothetical future studies under explicit assumptions; they do not report how many participants were enrolled to achieve a particular power in this trial. For the binary primary outcome and the continuous secondary outcomes, the figures are participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The original trial's own sample-size assumptions are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm that would yield 80% probability of detecting the specified effect under the stated planning assumptions, if that effect and those assumptions held. The 90% power column gives the corresponding planning number for 90% probability. These are design probabilities under a model, not guarantees that a future study will reach a particular result. They do not indicate the probability that the treatment effect is real.

For hospital admission, planning for 100% of the observed effect gives 923 participants per arm for 80% power and 1,234 participants per arm for 90% power. Planning for 75% of the observed effect gives 1,590 and 2,128 participants per arm, respectively; planning for 50% gives 3,464 and 4,637. The calculations for the continuous outcomes are likewise expressed per arm. Smaller effects are harder to distinguish from random variation, so detecting a smaller effect generally requires more participants under the same planning assumptions.

These calculations use the observed effect as their starting point, which is uncertain, particularly when the observed estimate is based on limited data. They are planning illustrations, not observed power. The registry does not report the assumptions used in the original trial design, and these illustrations should not be read as evidence of the trial's planned or achieved 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 = 0.136; treatment proportion p₁ = 0.183; average p̄ = 0.159.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5178 = 1.0148.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5167 = 0.4348.
4. n = (1.0148 + 0.4348)² / (0.0477)² = 922.0, rounded up to 923 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 <- 0.135593220338983                          # control proportion
p1 <- 0.183333333333333                          # 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(1323010)
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 = 923 (80% power), 1,234 (90% power)
 75% of observed effect: n per arm = 1,590 (80% power), 2,128 (90% power)
 50% of observed effect: n per arm = 3,464 (80% power), 4,637 (90% power)
power.prop.test: 922 
Simulated power at n = 923 per arm: 0.794 (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. Analyses Reported by the Sponsor

The registry reports the sponsor's primary comparison as a Chi-squared analysis with p = 0.689. The simple unadjusted re-calculation from the posted counts gives a risk difference of 0.048, a confidence interval from -0.084 to 0.179, and p = 0.477. The re-calculation is a straightforward comparison of the posted summary counts; it is not a replacement for the registry's own analysis.

The two p-values differ because a re-calculation based on summary data need not reproduce the sponsor's exact method or conventions. The registry identifies the reported test as Chi-squared but does not report further details needed to match every aspect of that calculation. The record does not flag a discrepancy between the posted analysis and the re-calculation. The sponsor's reported result should therefore be retained as the trial's own analysis, while the re-calculated estimate and interval provide a transparent, unadjusted view of the contrast and its precision.

Neither p-value states the size of the group difference, and neither establishes equivalence. The event counts, effect estimate, interval, endpoint definition, and reported test contribute different pieces of information. The primary estimate's interval spans effects in both directions, so the uncertainty remains material regardless of which p-value is emphasized.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study examines more than one outcome, timepoint, subgroup, or statistical comparison. The more analyses considered, the greater the chance that at least one result may appear unusual even when there is no corresponding underlying effect. This matters for a trial with a primary outcome alongside many secondary measures. The registry lists 22 outcome measures and 18 analyses, and identifies 21 secondary outcomes as posted.

The record does not report whether the investigators adjusted for multiple comparisons, designated a hierarchy among secondary outcomes, or treated some analyses as exploratory. It also does not report a complete statistical analysis plan. Without those details, the secondary p-values should not be interpreted as if each came from a single, isolated confirmatory test. The primary outcome remains the clearest focus for interpretation, while the other findings are supporting or exploratory information unless a prespecified strategy is documented.

Information about missing data and analysis populations is also limited. The primary event counts use 60 participants in the higher-dose group and 59 in the lower-dose group. The available secondary comparisons have different analysis subsets: forced expiratory volume includes 18 and 12 participants, while glucose includes 57 and 55, and respiratory rate includes 60 and 59. These different denominators show that the analyzed samples vary by outcome, but the reasons are not reported in the registry record. The record does not explain whether measurements were unavailable, not collected, excluded, or handled through another procedure.

There is no reported description of an intention-to-treat analysis, per-protocol analysis, imputation method, sensitivity analysis for missing outcomes, or adjustment for baseline covariates. These details affect how confidently the estimates can be connected to the randomized comparison. Their absence does not prove that a particular method was not used; it means the method is not reported in the registry record. The estimates should therefore be read as comparisons based on the posted outcome data, with caution about the unreported analysis choices and missing-data handling.

16. 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 registry reports zero serious adverse events in the higher-dose group among 60 participants at risk and zero in the control group among 59 participants at risk. These are event counts, not proof that serious harms are impossible. In a trial of this size and duration, an event that was not observed could still occur in other participants or settings.

For other adverse events, the record reports 36 affected participants among 60 at risk in the experimental group and 37 among 59 at risk in the control group. The record does not provide serious adverse-event terms, and deaths are not reported as counts. The study description says safety assessment included clinical side effects and serum albuterol levels, but results for every planned safety measure are not reported in the registry record.

These figures describe recorded events over the study's observation period; they do not establish equivalence in safety or capture every possible adverse effect. The registry record does not report additional detail about event definitions, severity grading, timing, attribution, or follow-up duration. Safety interpretation should therefore remain limited to the reported counts and the information available about the observation process.

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

The primary result is an observed comparison of hospital admission under two first-hour albuterol dose regimens in children with acute wheezing episodes. Admission, as defined in the registry, occurred in 11 participants in the higher-dose group and 8 in the lower-dose group. The re-calculated risk difference is 0.048, with a confidence interval from -0.084 to 0.179. The point estimate is in the direction of more admissions in the higher-dose group, but the interval includes zero and values on either side.

This pattern does not establish a clear difference between the regimens for the registry-defined endpoint. It also does not establish that the regimens are equivalent or that any difference is absent. A failure to demonstrate a difference can reflect uncertainty, and the interval shows that the estimate is not tightly bounded. Equivalence or non-inferiority would require a prespecified margin and suitable design and analysis; such details are not reported in the registry record.

The secondary measurements add limited context. The posted continuous comparisons have intervals that include zero, and numerical results for many listed secondary outcomes are not reported in the registry record. The available results cannot demonstrate a broad pattern across all clinical, biological, and safety aims. Similarly, the reported absence of serious adverse events in the groups is an observation, not a guarantee of safety.

The conclusions apply to the posted data and the trial's stated outcome definitions. They do not establish how the regimens would compare in other populations, care settings, or treatment conditions. The registry record does not report enough information to assess all eligibility criteria, missing-data procedures, or the full analysis plan. These limits matter when extending the findings beyond this randomized comparison.

18. Why This Trial Matters Statistically

This trial illustrates several statistical issues that are common in clinical research. First, a randomized comparison can produce a point estimate that favors one group numerically while still leaving substantial uncertainty about the direction and size of the underlying effect. The admission estimate is positive for higher dose minus lower dose, but its confidence interval extends below and above zero. Reading the estimate together with its interval is more informative than treating the observed counts as a definitive answer.

Second, an outcome definition is part of the statistical result. Hospital admission was not simply any admission under any local practice; the registry operationalized it as remaining in the emergency room for more than 4 hours because discharge criteria were not met. Such a definition makes the endpoint interpretable, but its meaning depends on consistent assessment of the criteria and decisions. The record does not provide further assessment details.

Third, secondary outcomes can deepen understanding but create multiplicity and interpretation challenges. Lung function, glucose, respiratory rate, clinical scores, additional therapies, and safety measures do not all represent the same construct. A collection of individually analyzed endpoints cannot be treated as one coherent confirmatory result without a prespecified approach. The registry record does not report a multiplicity strategy.

Finally, planning calculations should not be confused with evidence about the trial's design or with post hoc power. Illustrative participant requirements depend on assumed effects and other planning conditions. Because the observed effect itself is uncertain, planning from it should be treated as a scenario rather than a definitive recommendation. The record's incomplete reporting of original design assumptions underscores the value of transparent sample-size and analysis plans.

19. 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 leaves important aspects of trial conduct and analysis unclear. It identifies randomized allocation, quadruple masking, and a parallel design, but does not describe the randomization method, concealment, who was masked, or whether masking was maintained. Further eligibility criteria and baseline characteristics are not reported in the registry record, limiting assessment of the population represented by the comparison.

The primary result is based on a relatively small set of posted event counts, and its confidence interval is broad. The record does not report an adjusted estimate, detailed statistical analysis plan, or the original sample-size rationale. It also does not report whether an interim analysis was conducted. These omissions make it difficult to evaluate the planning and analytic decisions beyond the methods named for the reported test.

Available secondary outcomes have different analyzed sample sizes, particularly the forced expiratory volume measure, for which the groups include 18 and 12 participants. The reasons for these smaller analysis subsets, the extent and handling of missing observations, and any sensitivity analyses are not reported in the registry record. Results are also not numerically posted for many listed outcomes, including viral testing, receptor genetics, plasma albuterol, electrocardiogram, and additional therapies.

The safety results report event counts but do not provide detailed definitions, severity, attribution, or follow-up information. The trial's admission definition depends on emergency-room duration and discharge criteria, while further details about endpoint assessment are unavailable. Together, these reporting gaps constrain evaluation of generalizability, analysis robustness, and the completeness of the outcome picture.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of Increasing Doses of Inhaled Albuterol in Children With Acute Wheezing Episodes — NCT01323010.
• Registry record last updated 2016-03-14; status last verified 2016-02.
• Results first posted 2016-03-14.
• 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.

23. Record Summary

The registry describes a completed randomized, parallel-group, quadruple-masked comparison of higher- versus lower-dose albuterol delivered by metered dose inhaler to children with acute wheezing episodes. Enrollment was 119, and the primary outcome was hospital admission, defined by remaining in the emergency room for more than 4 hours because discharge criteria were not met.

The primary counts were 11 of 60 in the higher-dose group and 8 of 59 in the lower-dose group. The unadjusted risk-difference estimate was 0.048, with a confidence interval from -0.084 to 0.179; the registry reports a Chi-squared p-value of 0.689. The interval includes zero and spans effects in either direction, leaving substantial uncertainty about the comparison.

Numerical secondary results are posted for forced expiratory volume, glucose change, and respiratory-rate change. Many other listed outcomes do not have numerical results reported in the registry record. Serious adverse events were reported in neither group, while other adverse events affected 36 participants in the experimental group and 37 in the control group. Multiplicity, missing-data handling, and original design assumptions are not reported in the registry record.