Effect of Ibuprofen on Postoperative Opiate Medication Use and Shoulder Functional Outcomes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Ibuprofen on Postoperative Opiate Medication Use and Shoulder Functional Outcomes (NCT02588027), a randomized na study. The primary outcome is Opiate Consumption in Patients Prescribed Ibuprofen Versus Placebo.

2. Clinical Question

3. Trial Design

The registry describes a randomized trial of postoperative ibuprofen versus placebo following arthroscopic rotator cuff repair. Masking is listed as triple. The registry classifies the model as single group, although the interventions, arm descriptions, and posted primary outcome identify Ibuprofen and Placebo arms. This classification does not align clearly with the two-arm randomized comparison reported for the primary outcome, and the registry record does not explain the discrepancy.

The study’s stated purpose was to assess whether postoperative ibuprofen affected postoperative opiate medication use, Visual Analog Scale pain scores, shoulder range of motion, and repair integrity. The posted primary endpoint is opiate consumption at 1 week post operative. Secondary outcomes listed include ASES, DASH, and SF-12 functional scores; Visual Analog Scale pain; and range-of-motion measures for forward flexion, abduction, and external rotation at the side and at 90 Degrees Abduction. The record lists 9 outcome measures, while 8 secondary outcomes are posted.

Enrollment is listed as 110, and status as completed. The record gives a start of 2015-10 and primary completion of 2022-09. It names the University of California, San Francisco as sponsor. The registry record does not report the trial’s original sample-size justification, detailed randomization procedure, or the operational details of masking. The listed phase is NA.

The primary outcome includes 51 participants in the Ibuprofen arm and 50 in the Placebo arm. Safety figures use risk denominators of 56 and 54, respectively. The registry does not explain why these outcome counts differ from one another or from the enrollment figure. These distinctions matter: enrollment, outcome-specific observations, and participants included in safety summaries are not necessarily interchangeable.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

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

Population: 110 patients were originally enrolled in the studied however 9 were dropped or elected to withdrawal and did not complete the study medication. Their baseline characteristics were excluded from the analysis because of violation of the protocol or because the patient requested to not have their information as part of the study.

6. Primary Endpoint

The registry lists the primary outcome as Opiate Consumption in Patients Prescribed Ibuprofen Versus Placebo, measured over 1 week post operative.

The primary endpoint is opiate consumption, expressed in morphine milligram equivalents, at 1 week post operative. Morphine milligram equivalents put different opioid amounts on a common scale, allowing the amount consumed to be summarized across participants. The registry describes the endpoint as a measure of pain control, and reports it as a continuous outcome using a mean and standard deviation.

In the posted results, the mean is 168.3 for the Ibuprofen arm and 210.9 for the Placebo arm. The standard deviations are 96.0 and 104.0, respectively. The outcome comparison is reported as a mean difference, with Ibuprofen minus Placebo indicated by the comparison values. The registry’s arm descriptions state that both groups also received the standard opiate medication for postoperative pain control, making the endpoint a measure of consumption under the described regimens rather than a comparison of opioid availability.

Consumption is a direct measure of medication use over the stated period, whereas pain scores and shoulder-function outcomes measure other aspects of participants’ experience and function. The registry lists those as secondary outcomes. The record does not provide further detail on how consumption was captured, whether the measure covers a defined set of days within the first week, or how missing consumption observations were handled. Those details would help interpret exactly what each recorded value represents.

7. Results Posted in the Registry

• Ibuprofen: mean 168.30 versus 210.90 on control; difference -42.60 (95% CI -81.65 to -3.55), standardized effect d = -0.43; z-test p = 0.033.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary endpoint is a continuous measure, and the registry summarizes each arm with a mean and standard deviation. A mean gives the arithmetic average of participants’ recorded morphine milligram equivalents. A standard deviation describes how dispersed observations are around that arm’s mean. It is not the standard error of the mean and is not an uncertainty interval for the arm average.

What does the mean difference express?

The reported comparison is a mean difference of -42.6, with Ibuprofen as the first arm and Placebo as the reference in the comparison. A mean difference expresses the contrast between the two arm averages in the endpoint’s original units. Here, those units are morphine milligram equivalents. The negative sign indicates that the observed average in the Ibuprofen arm is lower than the observed average in the Placebo arm. It does not imply that every participant in one arm had lower consumption than every participant in the other.

The registry also reports an unadjusted p-value of 0.033. In general, a p-value describes how compatible the observed data are with a specified statistical null model, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of an effect. The record does not give the full test specification, so the exact modeling and inferential details cannot be established from the registry entry alone.

Why report an interval with the estimate?

In general, a confidence interval conveys a range of values reasonably compatible with the data and the assumptions used to construct it. The reported interval for the mean difference runs from -81.65 to -3.547. The confidence level and full calculation method are not reported in the registry record. Intervals are useful because they show precision and a range of plausible effect values, rather than reducing the result to a single estimate or a p-value. Their interpretation depends on the method and assumptions behind them.

What do the standard deviations and standard errors tell readers?

The arm standard deviations are 96.0 for Ibuprofen and 104.0 for Placebo. The comparison information also reports standard errors of 13.44 and 14.71 for the arm means. In general, a standard error describes the sampling uncertainty of an estimate, while a standard deviation describes variation among individual observations. These quantities answer different questions. The registry does not provide additional distributional summaries, so the shape of the consumption data cannot be assessed from the reported means and standard deviations alone.

In general, continuous outcomes with a long tail or a small number of unusually high values can have means that are sensitive to those observations. The record does not report a distributional assessment or a transformation. It also does not state whether the comparison adjusted for baseline characteristics or used another model. It is therefore appropriate to describe the reported result as the posted mean comparison rather than attributing an unreported analysis strategy to the investigators.

Why can over-dispersion matter?

In general, over-dispersion means that the observed variability is greater than a model assumes. When a model underestimates variability, its standard errors can be too small and its intervals too narrow. That concern is especially relevant when a model’s variance assumptions do not fit the outcome. The posted endpoint is summarized as a continuous measure with substantial within-arm standard deviations, but the record does not report a formal over-dispersion assessment or a model that would permit one. It should not be assumed that over-dispersion was present or absent.

The reported confidence interval and p-value summarize inferential uncertainty under the analysis used, but the record does not fully describe that analysis. The registry also does not report whether the primary comparison was adjusted for any covariates, how missing observations were treated, or whether an analysis population was defined in advance. Those omissions limit independent evaluation of the assumptions behind the reported inference.

What does randomization contribute?

In general, random assignment is intended to make treatment groups comparable in expectation, reducing systematic differences in measured and unmeasured characteristics. The registry lists allocation as randomized and masking as triple. It does not report the random sequence method, allocation concealment details, or which roles were masked. The model is listed as single group despite the two posted arms, so the classification is not fully consistent with the reported comparison. These gaps do not establish that randomization or masking failed; they mean that their implementation cannot be assessed from the registry record.

The posted outcome counts are 51 and 50, while the enrollment is 110 and the safety denominators are 56 and 54. In general, differences among these counts can arise from outcome availability or analysis-population definitions, but the specific reason is not reported in the registry record. Without further information, these counts should be described separately rather than treated as evidence of a particular exclusion or missing-data process.

10. Confidence Intervals and Precision

The mean difference is -42.6 morphine milligram equivalents, with an interval from -81.65 to -3.547. The interval is the main reported indication of precision for the contrast: it shows that the estimate is not exact and gives a range of values compatible with the analysis. The registry record does not report the confidence level or all details of the interval’s construction, so those should not be inferred.

The interval’s endpoints are both negative, matching the direction of the observed means: 168.3 in the Ibuprofen arm and 210.9 in the Placebo arm. The interval extends from a more negative contrast to one closer to zero. Its width reflects uncertainty in the estimated difference, while the standard deviations of 96.0 and 104.0 show participant-level variability in the two groups. These quantities are related to precision but are not interchangeable: standard deviations describe spread among participants, whereas an interval describes uncertainty in an estimated contrast under a statistical method.

The unadjusted p-value is 0.033. A p-value does not substitute for an interval, since it does not directly show the range of effect sizes compatible with the analysis. Nor does the interval establish clinical importance: the registry record does not provide a threshold for interpreting the size of a difference in morphine milligram equivalents. Interpretation is also limited by the absence of a reported confidence level, full analysis specification, missing-data approach, and multiplicity plan.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total events. They are illustrations based on the observed mean difference, not the trial’s original design calculation. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect defined as a stated fraction of the observed effect. The registry record does not report the trial’s original sample-size assumptions or justification.

For planning based on 100% of the observed effect, the illustration gives 87 participants per arm for 80% power and 116 participants per arm for 90% power. For planning at 75% of the observed effect, it gives 154 participants per arm for 80% power and 207 participants per arm for 90% power. For planning at 50% of the observed effect, it gives 347 participants per arm for 80% power and 464 participants per arm for 90% power.

In plain terms, the 80% power column represents the illustrated number of participants per arm under the stated assumptions when aiming for an 80% chance of detecting the specified effect. The 90% column gives the corresponding planning count for a 90% chance. The curve can be read as the same relationship across effect sizes: planning to detect a smaller effect requires more participants under these assumptions. These are planning illustrations, not observed power; they do not describe the probability that this completed trial’s result is correct.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -42.600; pooled standard deviation σ = 100.040.
2. n = 2 × (1.96 + 0.842)² × 100.040² / -42.600² = 86.6, rounded up to 87 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -42.6                      # observed difference in means
sigma <- 100.039588123498                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2588027)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 87 (80% power), 116 (90% power)
 75% of observed effect: n per arm = 154 (80% power), 207 (90% power)
 50% of observed effect: n per arm = 347 (80% power), 464 (90% power)
power.t.test: 87.5 
Simulated power at n = 87 per arm: 0.801 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists a range of outcomes beyond the primary measure of opiate consumption. These include ASES, DASH, SF-12, postoperative Visual Analog Scale pain, and several shoulder range-of-motion measures. The study summary also mentions repair integrity. The record lists 9 outcome measures and 8 posted secondary outcomes. This difference is not explained in the registry record.

When a study assesses multiple outcomes or performs multiple comparisons, the chance of obtaining at least one apparently notable result can increase. In general, multiplicity methods can control or otherwise address that issue, but the registry record does not report a multiplicity adjustment, a hierarchy among secondary outcomes, or a complete analysis plan. The reported primary comparison is explicitly unadjusted. It is therefore not possible to determine from the registry entry whether multiplicity was considered elsewhere or how it should affect interpretation of the posted p-value.

The record does not describe missing-data handling, imputation, or sensitivity analyses. It also does not define an intention-to-treat, per-protocol, or other analysis population for the primary outcome. The primary outcome counts are 51 and 50; the safety risk denominators are 56 and 54; enrollment is 110. The record does not explain the differences among these counts or state whether observations were unavailable, excluded, or analyzed under different rules.

These omissions do not show that data were missing or that an analysis was inappropriate. They limit what can be concluded from the registry record about completeness, selection, and the robustness of the primary comparison. Details of prespecified outcomes, analysis populations, and missing-data procedures are not reported in the registry record.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

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

The safety summary lists 56 participants at risk for serious adverse events in the Ibuprofen group and 54 in the Placebo group. Serious adverse events affected 0 participants in each group. The record also lists 0 other adverse events in each group and 0 deaths in each group. No top serious-event terms are listed.

These figures are counts within the stated risk denominators, not estimates of comparative risk over a specified follow-up period. The registry record does not report the safety follow-up duration, event definitions, ascertainment procedures, or whether the denominators include everyone enrolled. The safety counts also differ from the primary outcome counts, and the record does not explain why.

Zero reported events means none are recorded in these safety fields; it does not establish that no events occurred outside the registry’s reporting and observation processes. With no serious events listed in either group, the record does not provide an observed serious-event contrast to estimate. These data should be read as registry-reported counts, not as a comprehensive safety assessment.

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

The result describes lower mean opiate consumption in the Ibuprofen arm than in the Placebo arm at 1 week post operative: 168.3 versus 210.9 morphine milligram equivalents. The reported mean difference is -42.6, with an interval from -81.65 to -3.547 and an unadjusted p-value of 0.033. These values summarize the posted outcome comparison; they do not by themselves establish the practical importance of the difference or explain how individual participants’ consumption varied.

The registry describes a randomized comparison, but the model classification says single group despite the two reported arms. The arm descriptions also label the ibuprofen regimen “Control,” whereas the outcome uses Ibuprofen and Placebo. Such inconsistencies make it important to follow the labels attached to the specific outcome and not assume that every registry field uses a consistent naming convention. The record does not explain these mismatches.

The registry’s study summary identifies pain, shoulder function, range of motion, and repair integrity as areas of interest, but the primary posted result addressed concerns opioid consumption. The listed secondary outcomes are not a substitute for that endpoint and should not be treated as results. The registry record does not report the full set of secondary outcome findings or provide details about the analysis plan.

The reported comparison cannot establish how well the result would generalize beyond the participants and setting represented in the record. The registry does not give detailed participant characteristics, the analysis population definition, missing-data procedures, or full methods for the primary comparison. The sample-size illustrations are based on the observed effect and are not evidence about the trial’s achieved power. The registry data therefore support a careful description of the posted means and uncertainty, while leaving important questions about analysis, completeness, and broader interpretation unresolved.

16. Why This Trial Matters Statistically

This trial illustrates why clinical outcome reporting benefits from separating the estimated effect, its precision, and the assumptions behind the analysis. The mean difference of -42.6 is interpretable in the endpoint’s original units, while the interval from -81.65 to -3.547 communicates uncertainty around that estimate. The unadjusted p-value of 0.033 adds a different piece of information and should not be treated as a measure of effect size or clinical importance.

The endpoint is medication consumption, a continuous measure with standard deviations of 96.0 and 104.0. Reporting both group means and variability gives more context than a single comparison statistic. At the same time, the registry record does not explain the distribution of individual values, the model used, or how missing observations were handled. Readers can see the summarized result but cannot fully evaluate the analysis choices from this record alone.

Trial registries also make reporting consistency visible. Here, a single-group model classification appears alongside randomized allocation and two outcome arms, and the control-arm description does not match the outcome’s arm naming. Enrollment, primary-outcome counts, and safety denominators are also distinct, without an explanation of the differences. These are reasons to interpret fields in context rather than assume that every registry entry is fully aligned.

Finally, planning calculations based on observed effects can illustrate how required sample size changes when the target effect is smaller or the desired power is higher. They are not a replacement for an original, prospectively justified sample-size plan. The record’s missing details about the original design assumptions, multiplicity, and analysis populations underscore the statistical value of transparent planning and reporting.

17. 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 several trial-specific limitations unresolved. It reports allocation as randomized and masking as triple, but does not describe the randomization method, allocation concealment, or which participants and study roles were masked. The model is classified as single group even though the posted primary outcome compares Ibuprofen with Placebo. The arm descriptions also label the ibuprofen arm “Control.” The record does not explain these inconsistencies.

The registry enrollment is 110, while the primary outcome includes 51 participants in the Ibuprofen arm and 50 in the Placebo arm. The serious and other adverse-event risk denominators are 56 and 54. The record does not explain these different counts or define the primary analysis population. It does not report missing-data methods, participant flow, or sensitivity analyses.

The primary endpoint is limited to opiate consumption at 1 week post operative. The registry does not provide further detail about how consumption was recorded or the exact observation window. It reports the outcome as a mean with standard deviation but does not state the full statistical model or the confidence level used for the reported interval. It also does not report the original sample-size justification, interim analyses, or a multiplicity plan.

The study summary mentions repair integrity, but the listed secondary outcomes and posted outcome counts do not explain whether or how that measure was assessed. The registry record does not provide detailed participant characteristics or a complete set of secondary results. These are limitations of what can be interpreted from this record, not proof that the trial itself lacked procedures or data beyond what is reported.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Effect of Ibuprofen on Postoperative Opiate Medication Use and Shoulder Functional Outcomes — NCT02588027.
• Registry record last updated 2024-12-06; status last verified 2024-12.
• Results first posted 2024-12-06.
• 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.

21. Record Summary

The registry record identifies NCT02588027 as a completed randomized trial sponsored by the University of California, San Francisco. It concerns postoperative ibuprofen versus placebo after arthroscopic rotator cuff repair and lists triple masking. Enrollment is 110; the recorded start is 2015-10 and primary completion is 2022-09.

The primary posted outcome is mean opiate consumption in morphine milligram equivalents at 1 week post operative. The reported means are 168.3 for Ibuprofen and 210.9 for Placebo, with a mean difference of -42.6, an interval from -81.65 to -3.547, and an unadjusted p-value of 0.033. The record also lists pain, shoulder function, and range-of-motion outcomes, but does not provide the full analysis plan, missing-data approach, or original sample-size justification.