Quadratus Lumborum Block Versus Control for Total Hip Arthroplasty: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Quadratus Lumborum Block Versus Control for Total Hip Arthroplasty (NCT03408483), a randomized phase 2, phase 3 study. The primary outcome is Pain Scores Using Visual Analog Scale (VAS) Scores.

2. Clinical Question

The trial asks whether postoperative pain scores differ between patients undergoing total hip arthroplasty who receive a quadratus lumborum block (QLB) and patients who receive standard care without a peripheral nerve block. The registry describes pain as assessed from immediately after surgery through 12 hours postoperatively. The comparison is between group means, so the reported estimate represents the difference in average pain scores, not the experience of every individual participant.

The study summary also names opioid consumption, physical therapy scores, and patient and surgeon satisfaction as outcomes of interest. The posted primary result is specifically a pain-score comparison. The clinical question is therefore narrower than the full set of aims described in the study summary: the primary result does not by itself address every intended measure of recovery or experience.

3. Trial Design

The registry identifies NCT03408483 as a completed randomized, double-masked, parallel-group trial. Its listed phases are Phase 2 and Phase 3. The sponsor is the University of Alabama at Birmingham. Enrollment is recorded as 80, with a study start date of 2018-04-01 and a primary completion date of 2019-05-10. The condition is total hip arthroplasty.

Participants were assigned to one of two groups: quadratus lumborum block (QLB) or standard of care. A parallel-group design compares participants assigned to one arm with those assigned to another, rather than comparing each participant with their own outcome under a different treatment. Random allocation is intended, in general, to reduce systematic differences between groups at assignment. The registry record does not report the sequence-generation method, allocation concealment procedures, or the details of masking. It labels the trial double-masked but does not identify which roles were masked or how masking was maintained.

The planned enrollment was 80, while the posted primary-outcome counts are 36 for QLB and 35 for standard of care. The primary outcome description says that three patients in each group were excluded for failed spinal anesthesia and that three patients in the QLB group were excluded because of missing data following early discharge. These details indicate that the outcome-specific population differs from the overall enrollment, but the registry record does not report a complete participant-flow account or a named analysis population such as intention-to-treat.

The registry lists 11 outcome measures and four posted secondary outcome entries, including a repeated entry for distance ambulated. It reports no named analyses for the primary or secondary outcomes. The original statistical analysis plan, original sample-size justification, and details of any interim analyses are not reported in the registry record. The posted comparisons can be described, but they do not establish what methods were prespecified for the trial.

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:

Analysis population for the primary outcome, as defined in the registry: Three patients in each group were excluded for failed spinal anesthesia. Three patients were excluded in the QLB group for missing data due to early discharge.

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: Three patients in each group were excluded for failed spinal anesthesia. Three patients were excluded in the Quadratus Lumborum Block group for missing data due to early discharge.

6. Primary Endpoint

The registry lists the primary outcome as Pain Scores Using Visual Analog Scale (VAS) Scores, measured over Assessed between immediately postoperatively to 12 hours postoperatively.

The primary endpoint is titled “Pain Scores Using Visual Analog Scale (VAS) Scores.” It is described as a mean on a scale and assessed between immediately postoperatively and 12 hours postoperatively. Pain is a subjective experience that cannot be measured directly in the same way as a physical quantity; a rating scale provides a structured way for participants to report it. A group mean condenses the ratings into an average, which supports a direct comparison between the assigned groups.

The registry description explains that the Visual Analogue Scale is a psychometric response scale for subjective characteristics. It also describes the Numeric Rating Scale (NRS-11) as an 11-point patient self-report measure, ranging from 0, no pain, to 10, severe pain, with categories for mild and moderate pain. The record does not fully clarify whether the posted primary values use a visual analogue format, the numeric rating format, or how observations across the stated postoperative interval were combined into the mean.

Using a pain scale is relevant to the study question because the study summary frames postoperative analgesia as a concern in total hip arthroplasty. However, the mean alone does not show the range of individual scores, the distribution of pain over time, or how many participants experienced particular pain levels. The registry record does not report a clinically important difference threshold for interpreting the scale.

7. Results Posted in the Registry

• Quadratus Lumborum Block (QLB): mean 2.34 versus 3.33 on control; difference -0.99 (95% CI -2.41 to 0.43), standardized effect d = -0.33; z-test p = 0.172.

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.

Patient Satisfaction

• 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:
  • Quadratus Lumborum Block (QLB): mean 9.14 versus 7.46 on control; difference 1.68 (95% CI 0.71 to 2.65), standardized effect d = 0.80; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Quadratus Lumborum Block (QLB) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Hours to Hospital Discharge

• 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:
  • Quadratus Lumborum Block (QLB): mean 53.17 versus 55.97 on control; difference -2.80 (95% CI -15.07 to 9.47), standardized effect d = -0.11; z-test p = 0.655.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Quadratus Lumborum Block (QLB) and the control. The interval gives the range of effects that remain compatible with the data.

Distance Ambulated

• 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:
  • Quadratus Lumborum Block (QLB): mean 127.75 versus 106.69 on control; difference 21.06 (95% CI -35.96 to 78.08), standardized effect d = 0.17; z-test p = 0.469.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Quadratus Lumborum Block (QLB) and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes span patient satisfaction, time to hospital discharge, and distance ambulated. Their estimates do not form a single consistent pattern across all domains. Patient satisfaction has a positive mean difference for QLB, with an unadjusted p-value of <0.001, while the comparisons for discharge time and distance ambulated have intervals that include zero and unadjusted p-values of 0.655 and 0.469. This mix of estimates means that the secondary findings cannot be condensed into a general claim that every aspect of recovery differed in the same way.

These outcomes are related to the broad study aims, which include patient experience and postoperative recovery, but they do not answer the primary pain question directly. A satisfaction score is not interchangeable with a pain rating, and discharge timing or walking distance captures different aspects of the postoperative course. The primary pain comparison remains the prespecified headline outcome as labeled in the registry, while secondary measures add context about other outcomes.

Unadjusted secondary results carry less weight when many outcomes may be examined. In general, the more comparisons considered, the greater the chance that at least one appears statistically notable by chance alone. A multiplicity strategy can control that risk, but whether one was specified or applied is not reported in the registry record. The registry lists no reported analyses for the secondary outcomes, so the posted comparisons do not establish how they were prioritized or whether any adjustment was planned.

The repeated entry for distance ambulated in the list of secondary outcomes is not accompanied by a second distinct posted result. The record also does not describe a hierarchy among secondary outcomes or identify one as confirmatory. It is therefore useful to treat the findings as exploratory signals rather than as a coordinated set of definitive tests. The reported estimates can inform questions for further study, but the secondary pattern does not remove the uncertainty around the primary endpoint.

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

• Patient Satisfaction
• Hours to Hospital Discharge
• Distance Ambulated
• Distance Ambulated

9. Statistical Interpretation

10. Statistical Methods Explained

In general, the mean is the arithmetic average of a set of observations. It is a natural summary when an outcome is measured on a numerical scale and the research question concerns average scores. In this trial, the primary outcome is a pain rating, reported as a mean for each randomized group. Comparing means gives a compact estimate of the average group separation, but it does not show the full distribution of scores. Two groups can have similar means while differing in variability, concentration of scores, or the number of participants at particular score levels.

What does the mean difference represent?

The posted estimate is a mean difference, defined by the comparison of the QLB group with the standard-of-care group. For the primary outcome, the estimate is -0.99. A negative sign indicates that the QLB group’s reported mean was lower, given this ordering. The estimate is expressed in the outcome’s scale units. It is not a percentage change or an individual-level treatment effect. It also does not tell whether the difference is clinically important, because the registry record does not report a threshold for importance.

In general, a standard error describes the sampling uncertainty of an estimated mean. It is not the same as the standard deviation, which describes variability among individual observations. The primary means are reported with standard errors of 0.46 for QLB and 0.56 for standard of care. The registry does not provide the raw observations or standard deviations for the primary outcome. The comparison also reports a pooled standard deviation, but the posting does not describe a trial-specific model or full analysis procedure from which to judge that summary’s role.

How should a p-value be read?

In general, a p-value measures how unusual data at least as incompatible with a specified null hypothesis would be, if that null hypothesis and the statistical model were true. It is not the probability that the null hypothesis is true, and it does not measure the probability that a result will replicate. The primary unadjusted p-value is 0.172. This value does not cross the commonly used 0.05 threshold, but the threshold alone does not establish whether a difference is absent or whether the study was sufficiently precise to rule out meaningful values.

The posted secondary satisfaction comparison has an unadjusted p-value of <0.001; the corresponding unadjusted p-values for hours to hospital discharge and distance ambulated are 0.655 and 0.469. These p-values are attached to different outcomes and should not be treated as interchangeable evidence. No adjusted p-values or reported secondary analyses are listed. Whether the comparisons were planned in advance and whether any correction for multiple testing was intended are not reported in the registry record.

Why do confidence intervals matter?

In general, a confidence interval expresses the uncertainty around an estimate using a procedure with a stated long-run coverage property, when its assumptions hold. It is more informative than a p-value alone because it shows a range of effect values consistent with the observed data and analysis method. For the primary comparison, the interval extends from -2.41 to just above zero. This range includes zero and also allows for a negative difference of more substantial size. Thus, the result is not a precise demonstration of either equality or a particular magnitude of benefit. The confidence interval is an estimate-based range, not a guarantee that the true value lies inside it.

The posted standard errors and confidence intervals are numerical summaries; the registry does not report a complete statistical methods description for the trial’s own analysis. Details such as model specification, assumptions about repeated pain assessments, handling of baseline measures, and any adjustment variables are not reported in the registry record. The methods used to produce the sponsor’s original analysis, if any, are also not described. For that reason, the posted unadjusted comparisons should be interpreted as summaries rather than as a full reconstruction of the original statistical plan.

Why can over-dispersion matter?

General explanation: over-dispersion occurs when the observed variability is greater than a statistical model assumes. If a model underestimates variability, standard errors can be too small and confidence intervals too narrow, making results appear more precise than they are. If variability is greater than expected, a suitable model may need to account for it. The posted primary outcome is continuous and has standard errors, but the registry record does not report an over-dispersion assessment or indicate that over-dispersion was relevant to the analysis. This general concept should not be taken as a claim that the trial’s data had over-dispersion.

The posted primary comparison is described as unadjusted. In general, an unadjusted comparison estimates the group contrast without accounting for additional covariates in a regression model. Randomization can support a fair comparison in expectation, but adjustment choices and the actual analysis population still matter for precision and interpretation. The registry does not report whether the primary comparison was the trial’s prespecified analysis, how missing outcomes were handled beyond the stated exclusions, or whether there were sensitivity analyses. Those omissions limit assessment of robustness.

11. Confidence Intervals and Precision

The primary mean difference is -0.99, with a confidence interval extending from -2.41 to slightly above zero. The interval includes zero, so the posted data are compatible with no average difference under the interval method. They are also compatible with a range of negative values, meaning the estimate does not identify one precise magnitude. The interval’s upper endpoint is close to zero but on its positive side. Taken together, the estimate and interval show uncertainty in both the presence and size of an average difference.

In general, a confidence interval is a measure of statistical precision under the analysis assumptions, not a measure of clinical importance. A narrow interval indicates that the estimate is relatively precise; a wide interval leaves more possible values compatible with the data. Whether any value in an interval matters depends on a clinical threshold and context. The registry record does not report a minimum clinically important difference for the pain scale, so no threshold-based conclusion can be drawn from the interval alone.

The primary outcome counts are 36 for QLB and 35 for standard of care. These are smaller than the enrollment of 80, and the registry describes exclusions for failed spinal anesthesia and missing data after early discharge. The modest outcome counts are relevant to the amount of information available, but they do not alone determine precision: outcome variability and the analysis method also contribute. The posted standard errors are 0.46 and 0.56, respectively, and the confidence interval captures uncertainty in the group contrast as calculated for the posted comparison.

For context, secondary confidence intervals have different patterns: the patient-satisfaction interval lies above zero, whereas the intervals for hours to hospital discharge and distance ambulated include zero. These interval patterns describe uncertainty for their own outcomes, not for pain. Because the registry does not report a multiplicity plan or complete analysis methods, the apparent precision of secondary estimates should be considered alongside the uncertainty about how those comparisons were selected and interpreted.

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 are participants per arm, not total participants, for these continuous outcomes. They are illustrations based on the observed effect rather than the trial’s original design. The listed assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

The 80% power column represents the number of participants per arm that the illustration estimates would be needed for an 80% chance of detecting the specified effect under the planning assumptions, if that effect and those assumptions held. The 90% power column uses a higher target chance of detection and therefore generally requires more participants per arm. These are design-planning quantities, not descriptions of what happened in the trial. This is not observed power.

The rows labeled as planning for 100%, 75%, and 50% of the observed effect explore different assumed effects. For example, the primary-outcome illustration lists 149 participants per arm for 80% power when planning for 100% of the observed effect, and 265 participants per arm when planning for 75% of the observed effect. Smaller effects are harder to distinguish from random variation, so they require more participants under the same assumptions. This explains why the entries increase as the assumed effect becomes smaller.

These calculations should not be read as a retrospective judgment about whether the completed trial was adequate. They are hypothetical planning illustrations based on the observed estimate, which itself is uncertain. A different assumed effect, variability, analysis method, or design could lead to different planning requirements. The registry record does not state whether the original trial used these assumptions or figures.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.990; pooled standard deviation σ = 3.045.
2. n = 2 × (1.96 + 0.842)² × 3.045² / -0.990² = 148.5, rounded up to 149 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 <- -0.99                      # observed difference in means
sigma <- 3.04507204645735                     # 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(3408483)
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 = 149 (80% power), 199 (90% power)
 75% of observed effect: n per arm = 265 (80% power), 354 (90% power)
 50% of observed effect: n per arm = 595 (80% power), 796 (90% power)
power.t.test: 149.5 
Simulated power at n = 149 per arm: 0.796 (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.

14. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, time points, subgroups, or statistical tests are examined. In general, every additional test can raise the chance of at least one small p-value even when there is no underlying effect for the tested outcomes. Researchers can address multiplicity through a prespecified hierarchy, adjusted significance thresholds, or other methods. The registry record does not report a multiplicity strategy, and it does not report whether the secondary outcomes were intended as confirmatory or exploratory.

The primary outcome is clearly titled as pain scores using VAS scores, but the record does not provide a full statistical analysis plan. It does not state whether repeated pain measurements were collected and combined, whether a particular time point was primary, or whether the reported mean represents an average over the full assessment interval. It also does not report any interim analyses. Those details matter because analysis decisions can affect both the estimate and the uncertainty attached to it.

Missing data are described for the primary outcome: three patients in each group were excluded for failed spinal anesthesia, and three in the QLB group were excluded for missing data due to early discharge. The record does not state the missing-data mechanism, whether the excluded participants differed from those analyzed, or whether any imputation or sensitivity analysis was undertaken. In general, missingness can affect interpretation if the probability of having an observed outcome is related to the outcome itself or to group assignment. The registry does not provide enough detail to assess that possibility.

The registry does not name an intention-to-treat, per-protocol, or other analysis population, and does not explain how randomization was reflected in the analysis after exclusions. It also does not report a baseline-adjusted model, covariate selection, or diagnostic checks. These omissions should not be filled by assumption. They limit the ability to determine whether the posted comparisons fully match a prespecified plan and how robust the results are to alternative analysis choices.

The safety group denominators differ from the primary endpoint group counts: the event listing uses 35 at risk for QLB and 36 for standard of care, whereas the primary outcome lists 36 and 35, respectively. The record does not explain why those populations differ. This is an additional reason to interpret each outcome using its own reported denominator rather than assume that all outcomes use the same analysis set.

15. 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 registry’s adverse-event listing records zero serious adverse events for the QLB group among 35 at risk and zero for standard of care among 36 at risk. It also records zero other adverse events in each group’s listed risk set. Deaths are recorded as zero for both groups. These are counts as entered in the registry, not evidence that the risk of an event is zero.

Zero reported events in a trial of this size can coexist with uncertainty about uncommon events. In general, an event not observed in a study is not necessarily impossible, and the amount of information depends on how many participants were observed, the duration of observation, and the definitions and collection procedures used. The registry record does not provide detailed adverse-event definitions, event-collection methods, or a description of the safety observation window.

The event denominators do not match the primary-outcome counts, and the reason for that difference is not reported. Safety counts should therefore be read using the risk sets attached to the adverse-event listing, rather than inferred from the pain outcome population. The record lists no serious adverse-event terms, and does not provide additional narrative explaining the zero counts.

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

The posted primary result shows a lower mean pain score in the QLB group than in the standard-of-care group, with a mean difference of -0.99. Its confidence interval includes zero and extends to values on either side of zero, while the unadjusted p-value is 0.172. Taken together, the result does not establish a clear between-group difference in mean pain scores, and it also does not precisely rule out potentially meaningful differences. The registry does not report a threshold for clinical importance, so the practical importance of values within the interval cannot be determined from the record alone.

The result does not show that every participant had less pain with QLB, nor does it describe individual responses. A mean comparison is a group-level summary. It also does not establish how pain changed over time, because the record does not fully explain how the postoperative assessments were summarized. The scale description includes both VAS and NRS material, and the exact instrument or scoring details underlying the posted mean are not fully clarified.

The secondary results broaden the picture but do not settle the primary question. The posted satisfaction comparison differs from the findings for discharge time and ambulation, and the registry does not report whether multiplicity was addressed. Those outcomes should be interpreted as distinct measures, not combined into a single treatment conclusion.

Likewise, zero adverse events in the listed risk sets should not be understood as proof of no safety risk. The counts are limited to the registry’s recorded observations and lack detail on definitions and follow-up. The overall result is best read as a small randomized comparison with an uncertain primary estimate, alongside secondary and safety summaries that have reporting limitations. It is not a basis for individualized medical advice or a conclusion beyond the outcomes and populations recorded.

17. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates the difference between the direction of an estimate and the strength or precision of evidence. The QLB group’s primary mean is lower, and the mean difference is negative, but the confidence interval includes zero and the unadjusted p-value is 0.172. A point estimate alone can suggest a direction; uncertainty determines how confidently the magnitude and even the direction can be distinguished from plausible alternatives.

It also shows why sample size planning should be connected to a clinically meaningful effect rather than only to an observed estimate. The posted planning illustrations use fractions of the observed effect and show that smaller target effects require more participants per arm under the stated assumptions. Since the original sample-size justification is not reported, the illustrations cannot be treated as the trial’s own rationale or as evidence about the design process.

The registry includes outcomes beyond pain, including satisfaction and measures of recovery. That breadth can be valuable, but it makes clear why a prespecified analysis plan and multiplicity handling are important. Without those details, a statistically notable secondary result cannot be given the same interpretive weight as a clearly designated primary test within a fully reported plan.

Finally, the record highlights the importance of transparent outcome populations. Exclusions and differing denominators can affect both estimates and interpretation. Reporting participant flow, missing-data handling, analysis populations, and outcome definitions would make the statistical evidence easier to evaluate and reproduce.

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 limitations are specific to the registry information for this trial. The primary outcome description refers to VAS pain scores, but also explains the NRS-11 and its 0-to-10 anchors. The record does not clearly specify which exact instrument generated the posted group means or how scores across the interval from immediately postoperatively to 12 hours postoperatively were summarized. This ambiguity complicates interpretation of the scale units and the clinical meaning of the difference.

The primary population includes exclusions for failed spinal anesthesia and for missing data following early discharge. The registry does not report the characteristics or outcomes of excluded participants, a missing-data strategy, or sensitivity analyses. It also does not name the analysis population. The safety denominators are reversed relative to the primary outcome denominators, and the reason for that difference is not given.

The record does not report the original sample-size rationale, a full statistical analysis plan, or a multiplicity strategy. It does not detail the randomization procedure, which participants or study personnel were masked, or how the double masking was maintained. The registry lists no reported analyses despite posting descriptive comparisons. This limits evaluation of whether the statistical approach followed a prespecified plan.

The primary confidence interval is compatible with values on both sides of zero, and the record supplies no clinical importance threshold. Secondary outcomes are reported without a stated hierarchy, and their unadjusted results need cautious interpretation. Safety reporting lists zero events but lacks definitions, collection details, and a clear observation window. These are limitations of the registry record and should not be replaced by assumptions about what the full protocol may have specified.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Quadratus Lumborum Block Versus Control for Total Hip Arthroplasty — NCT03408483.
• Registry record last updated 2021-06-09; status last verified 2021-05.
• Results first posted 2020-09-04.
• 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

NCT03408483 is a completed randomized, double-masked, parallel-group trial of quadratus lumborum block versus standard of care for total hip arthroplasty. The registry lists Phase 2 and Phase 3, enrollment of 80, and sponsorship by the University of Alabama at Birmingham. The primary outcome is mean postoperative pain score assessed from immediately postoperatively to 12 hours postoperatively.

The primary mean difference is -0.99, with an unadjusted p-value of 0.172 and a confidence interval that includes zero. Secondary results vary by outcome, and the registry reports zero serious adverse events in the listed groups. Important details—including the original statistical plan, sample-size justification, multiplicity approach, and full missing-data handling—are not reported in the registry record.