Intravenous Lidocaine Randomized Comparative Effectiveness Trial: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Intravenous Lidocaine Randomized Comparative Effectiveness Trial (NCT03300674), a randomized phase 4 study. The primary outcome is Change in 0-10 Pain Scale Between Baseline and 90 Minutes.

2. Clinical Question

3. Trial Design

This was a completed, phase 4, randomized, parallel-group comparative-effectiveness trial sponsored by Montefiore Medical Center. The registry lists an enrollment of 154. The posted primary-outcome results give 77 participants for intravenous hydromorphone and 77 for intravenous lidocaine; the record does not explain whether these counts represent all randomized participants or the population included in each outcome analysis.

The trial compared two intravenous medication strategies for acute abdominal pain in an emergency department. The recorded hydromorphone dose was 1mg, and the recorded lidocaine dose was 120 mg. In either arm, a second dose could be administered at 30 minutes. Whether participants actually received repeat doses, and how dosing decisions were made, are not reported in the registry record.

Allocation is listed as randomized, masking as quadruple, and the model as parallel. The brief description calls the study double-blind. The record does not clarify the difference between that wording and the quadruple masking designation. It also does not describe who was masked or how masking was maintained.

The primary endpoint covers pain-scale change from baseline through 90 minutes. The brief description says participants were followed over their emergency department course and then by telephone 7 days later. Rescue medication is reported over 4 hours; adverse events are also listed as a secondary outcome. Detailed eligibility criteria, site procedures, allocation concealment, follow-up completeness, and analysis-population definitions are not reported in the registry record. Those omissions limit how fully the conduct of the trial can be reconstructed from the record alone.

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 Change in 0-10 Pain Scale Between Baseline and 90 Minutes, measured over up to 90 minutes.

The primary endpoint is titled “Change in 0-10 Pain Scale Between Baseline and 90 Minutes.” Participants described pain on a scale from 0 to 10, where 0 means no pain and 10 means the worst pain imaginable. The endpoint is a continuous measure, and the registry reports its mean and standard deviation for each arm. The time frame is up to 90 minutes.

A pain-scale measure gives a numerical way to compare reported pain between treatment groups at a defined assessment period. A change measure can account for the starting score when describing how scores differ over time. However, the registry does not give the formula or sign convention used to calculate the change. The posted means therefore need to be read as the recorded endpoint values: 5.0 for hydromorphone and 3.8 for lidocaine. The mean difference is -1.2 for lidocaine relative to hydromorphone.

The endpoint captures a short-term patient-reported outcome. It does not by itself describe pain beyond the stated assessment window, the need for additional treatment, or the overall course of an emergency department visit. Rescue medication is reported separately. The registry record does not state whether the primary endpoint was assessed by a particular instrument beyond the described 0–10 scale, or how measurements were handled when an assessment was unavailable.

7. Results Posted in the Registry

• Intravenous Lidocaine: mean 3.80 versus 5.00 on control; difference -1.20 (95% CI -2.00 to -0.40), standardized effect d = -0.48; z-test p = 0.003.

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.

Rescue Medication

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Intravenous Lidocaine: 50.6% (39/77) versus 26.0% (20/77) on control; risk difference 24.7 percentage points (95% CI 9.8 to 39.5), risk ratio 1.95 (1.26–3.02); unadjusted two-proportion z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Intravenous Lidocaine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes add information about events beyond the short-term mean pain-scale change: rescue medication during the stated 4-hour period and adverse events. In general, these outcomes can help describe subsequent care and reported safety events, while the primary endpoint addresses the specified pain-scale measure through 90 minutes. They answer related but different questions, so a pattern in a secondary outcome does not redefine the primary result.

Rescue medication is a participant-level binary outcome, whereas the primary endpoint is continuous. The adverse-event results are also presented as group counts. Differences across outcome types should not be compared as if they were on a common scale. The registry lists no formal reported analyses for the secondary outcomes, and the posted secondary comparisons are unadjusted.

Unadjusted secondary results carry less weight as confirmatory evidence when multiple outcomes are examined. In general, examining several outcomes creates more opportunities for apparently notable findings by chance. A prespecified hierarchy or multiplicity adjustment can address that concern, but neither is reported in the registry record. This does not make the secondary data irrelevant; it means their role is primarily descriptive and hypothesis-generating unless further analysis documentation is available.

The secondary results can be considered alongside the primary estimate, but they cannot establish that the primary finding is clinically important or explain its mechanism. Nor can a secondary outcome alone resolve uncertainty about the direction of the primary change score, because the registry does not report its sign convention. Interpretation should keep the outcome definitions, assessment periods, and analysis status distinct.

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

• Rescue Medication
• Adverse Events

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: it is reported as a mean with a standard deviation. The posted comparison is a mean difference between intravenous lidocaine and intravenous hydromorphone. The group means are 3.8 and 5.0, respectively, and the estimated difference is -1.2 units. This estimate gives the difference in group averages on the recorded pain-scale change measure; it is not a count of participants who experienced a particular outcome.

The comparison uses the hydromorphone arm as the reference and expresses the estimate for lidocaine relative to it. A negative mean difference means the posted lidocaine mean is numerically lower. Whether lower change scores indicate more or less improvement depends on the change-score convention, which is not reported in the registry record. This distinction matters because the underlying scale’s endpoints alone do not explain how a change was calculated.

The reported 95% confidence interval is -1.995 to -0.405. In general, a confidence interval describes the range of values reasonably compatible with the estimate under the statistical model and its assumptions. It conveys precision as well as direction: a narrower interval indicates greater precision, while a wider interval indicates more uncertainty. It is not a range containing a specified proportion of individual participants’ scores. The interval is for the group mean difference, not for the distribution of individual responses.

The registry reports an unadjusted p-value of 0.003 for the primary comparison. In general, a p-value measures how unusual data at least as incompatible with a null hypothesis would be if that hypothesis and the test assumptions held. It does not measure the size or importance of the difference, and it does not give the probability that the null hypothesis is true. “Unadjusted” indicates that the value is not reported as corrected for multiple comparisons. The registry record does not give a more detailed testing plan or describe any adjustment.

The group standard deviations are 2.8 for hydromorphone and 2.2 for lidocaine. In general, a standard deviation describes the spread of individual observations around a group mean. It is different from the standard error, which describes uncertainty in an estimated mean. The record lists standard errors of 0.319 and 0.251 for the two arms. These quantities help characterize the data and estimate precision, but the registry does not give a complete account of the method used to construct the confidence interval or test.

The primary comparison also reports a pooled standard deviation of 2.518 and a standardized effect estimate of -0.477. In general, a standardized effect expresses a mean contrast in units of a pooled measure of variability, making its scale independent of the original measurement units. It does not replace the difference in pain-scale units, and it can be harder to interpret clinically. No clinical threshold tied to this standardized estimate is reported in the registry record.

For binary outcomes, the statistical question differs: the comparison concerns whether an event was recorded for a participant, rather than the mean of a continuous score. The rescue-medication outcome reports participant counts and a risk difference. In general, a risk difference is the difference between the proportions with an event in two groups. The registry also reports relative-effect measures for this outcome. Such measures answer different questions and can look different in magnitude, especially when the underlying event frequency varies. These are unadjusted results, and no formal secondary analyses are listed.

Randomization is intended, in general, to balance measured and unmeasured prognostic factors across groups on average. It does not guarantee balance in every trial, and the registry record does not report baseline characteristics or a balance assessment. The record lists quadruple masking and also describes the trial as double-blind; it does not explain these labels or the procedures used. Parallel-group allocation means participants are assigned to one group rather than crossing between both treatments, but further operational details are not reported.

Over-dispersion is a general issue for count or binary data when observed variability exceeds that expected under a simple model. It can make standard errors too small if the model does not account for the extra variability. The registry does not report a model-based secondary analysis or an assessment of over-dispersion, so it is not possible to determine whether such methods were relevant to any formal analysis. The posted primary endpoint is continuous, and the record gives group standard deviations rather than a count model.

Finally, the registry does not report the primary analysis population, missing-data method, covariate adjustment, handling of protocol deviations, or a prespecified statistical analysis plan. These details affect how an estimate should be interpreted and reproduced. The numbers should therefore be read as the posted group summaries and comparison, without assuming an unreported model, adjustment, or analysis procedure.

11. Confidence Intervals and Precision

The primary mean difference is -1.2 units on the pain-scale change measure, with a 95% confidence interval from -1.995 to -0.405. The interval describes uncertainty around the estimated group contrast under the method used. Because the entire reported interval is below zero, the range of values compatible with the estimate under that calculation is on the negative side. The result still does not establish the clinical importance of the difference, and the registry does not report a threshold for clinical importance.

Precision is not the same as certainty about every aspect of the trial. The interval reflects sampling uncertainty under the analysis assumptions; it does not capture possible effects of missing data, measurement choices, deviations from the planned procedures, or selective outcome reporting. Those issues cannot be assessed fully because relevant details are not reported in the registry record.

The standard deviations of 2.8 and 2.2 describe variation among participant scores, while the reported standard errors of 0.319 and 0.251 describe uncertainty in the respective group means. The confidence interval for the difference is the most direct summary of precision for the group contrast. It should not be read as a prediction interval for an individual participant’s score or response.

The unadjusted p-value is 0.003. It provides a test-based summary, whereas the confidence interval emphasizes the range and scale of the estimated difference. Neither statistic describes how many participants benefit, and neither accounts for multiplicity unless an adjustment is explicitly used. No multiplicity adjustment is reported. In general, precision improves with more information and less variability, but the record does not provide enough analysis detail to evaluate alternative modeling choices.

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 events. They are illustrations based on the observed effect, not a report of the trial’s original design calculations. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses a specified fraction of the observed effect as the effect to detect. The trial’s original sample-size assumptions are not reported in the registry record.

For the primary continuous outcome, planning for 100% of the observed effect corresponds to 70 participants per arm for 80% power and 93 participants per arm for 90% power. Planning for 75% of the observed effect corresponds to 123 participants per arm for 80% power and 165 participants per arm for 90% power. Planning for 50% of the observed effect corresponds to 277 participants per arm for 80% power and 371 participants per arm for 90% power.

In plain terms, 80% power is the probability of detecting an effect of the specified size at the stated significance level if that effect is truly present and the planning assumptions hold. The 90% power column describes a higher probability of detecting the specified effect under those same assumptions, and therefore generally calls for more participants per arm. Smaller effects require more participants because they are harder to distinguish from random variation.

These are planning illustrations, not observed power. The registry’s own original design assumptions are not reported, so the illustrations should not be taken as evidence that the trial was planned around the observed result or that its design met a particular target.

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 = -1.200; pooled standard deviation σ = 2.518.
2. n = 2 × (1.96 + 0.842)² × 2.518² / -1.200² = 69.1, rounded up to 70 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 <- -1.2                      # observed difference in means
sigma <- 2.51793566240283                     # 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(3300674)
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 = 70 (80% power), 93 (90% power)
 75% of observed effect: n per arm = 123 (80% power), 165 (90% power)
 50% of observed effect: n per arm = 277 (80% power), 371 (90% power)
power.t.test: 70.1 
Simulated power at n = 70 per arm: 0.798 (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

The registry lists a primary outcome and secondary outcomes that include rescue medication and adverse events. It also reports three outcome measures, but does not provide a statistical analysis plan or a hierarchy of hypotheses. No multiplicity adjustment is reported. The primary p-value is described as unadjusted, and no formal reported analyses are listed for the secondary outcomes.

In general, testing several outcomes can increase the chance of at least one result appearing statistically notable even when no true effect exists across the outcomes. A prespecified testing sequence or adjustment can help control this issue. Without information about which outcomes were planned as confirmatory, how tests were ordered, or whether any adjustment was used, the posted p-values should be read as unadjusted comparisons rather than evidence that accounts for all outcomes examined.

Missing-data handling is not reported in the registry record. The record does not state how many primary-outcome observations were unavailable, how missing observations were handled, or whether participants were analyzed according to randomized assignment. It also does not define the primary analysis population or describe exclusions. The posted group counts alone do not establish whether all randomized participants contributed to the endpoint analysis.

The record does not report whether the primary analysis adjusted for baseline pain scores or other covariates, whether protocol deviations were handled in a particular way, or whether sensitivity analyses were conducted. These details matter because they can affect the estimate, its uncertainty, and how well the analysis aligns with the randomized comparison. They cannot be inferred from the group means and unadjusted comparison.

These reporting gaps do not invalidate the posted results, but they limit independent assessment of robustness and reproducibility. The registry record supports interpretation of the reported summaries and estimates; it does not supply enough analysis detail to reconstruct all decisions behind them.

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.

Most frequent non-serious adverse event terms

The registry reports serious adverse-event figures for 77 participants at risk in each arm. The serious-event count is 0 for intravenous hydromorphone and 0 for intravenous lidocaine. The record also lists 0 deaths in each arm. These are the figures recorded for the trial; they do not establish that a serious event is impossible or rule out uncommon harms.

Other adverse events are listed for 28 participants in the hydromorphone arm and 23 participants in the lidocaine arm. These counts are separate from the serious-event figures. The registry does not provide event descriptions in the posted summary, detail severity or timing, or explain how events were collected and attributed. It therefore supports a description of the recorded counts, but not a complete comparison of the nature or clinical importance of adverse events.

Safety counts should be interpreted in light of the trial’s size, follow-up, event definitions, and ascertainment procedures. Those details are not fully reported in the registry record. The absence of recorded serious events in these groups is not proof of no risk, and the event counts alone do not establish a causal effect of either medication.

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

The posted primary result estimates a difference in mean pain-scale change between two randomized medication groups in an emergency department setting. The mean values are 3.8 for intravenous lidocaine and 5.0 for intravenous hydromorphone; the reported mean difference for lidocaine relative to hydromorphone is -1.2, with a 95% confidence interval from -1.995 to -0.405. The unadjusted p-value is 0.003. These figures describe the recorded comparison and its statistical precision.

The result does not by itself establish that the difference is clinically important. The registry does not report a clinically important threshold or explain how the change score was signed. The negative estimate means the lidocaine value is numerically lower, but the sign convention is needed to state what that means in terms of improvement. The scale endpoints are described, but the calculation of change is not.

The result also does not describe what every participant experienced. A group mean can conceal variation among individuals, and the posted standard deviations indicate that scores vary within both groups. The mean contrast does not tell how many participants had a particular degree of change. Nor does it establish effects outside the stated short-term endpoint period.

Randomization supports a comparative interpretation, but the registry record does not report all details needed to assess the analysis fully, including missing-data handling, analysis populations, or covariate adjustment. The secondary outcomes are unadjusted and have no formal reported analyses; they should not be treated as definitive confirmation of the primary result. The adverse-event counts also do not rule out uncommon events or establish that either strategy has no risk.

Overall, the posted data give a short-term between-group estimate with an interval and an unadjusted test result. They do not answer every question about clinical meaning, individual response, longer-term outcomes, or safety beyond the reported observations.

17. Why This Trial Matters Statistically

This trial illustrates how a randomized comparison can be summarized using a continuous patient-reported endpoint. The mean difference expresses the contrast in the endpoint’s original scale units, while the confidence interval communicates uncertainty around that estimate. Reading both together is more informative than relying on a p-value alone: the interval conveys direction and plausible magnitude, and the p-value gives a test-based summary under its assumptions.

It also demonstrates why outcome definitions matter. The registry identifies a change between baseline and 90 minutes on a 0–10 pain scale, but does not state the sign convention. Even when the scale’s endpoints are clearly described, a reader needs to know how a change score is calculated before assigning a clinical direction to a positive or negative estimate.

The distinction between the primary and secondary outcomes is important. The primary endpoint is continuous, while rescue medication and adverse events are reported as counts. Those measures contribute different kinds of information and should not be collapsed into a single judgment. Unadjusted secondary findings are especially limited when the analysis plan and multiplicity handling are not reported.

Finally, registry summaries can offer useful estimates while leaving essential design and analysis details unavailable. Here, the posted results include group means, variability, an interval, and a p-value, but do not report missing-data methods, analysis populations, or the original sample-size assumptions. Statistical interpretation therefore depends not only on the numerical result but also on understanding what was measured, how it was analyzed, and which uncertainties remain undocumented.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several trial-specific details needed for a fuller interpretation are not reported in the registry record. The endpoint is described as change from baseline to 90 minutes, but the sign convention and precise calculation are not stated. This prevents a confident interpretation of whether the numerically lower mean corresponds to a greater or smaller reduction in pain.

The record does not report eligibility criteria beyond the condition and emergency department context, baseline characteristics, or the detailed population included in the analyses. Although it lists an enrollment of 154 and outcome group counts of 77 in each arm, it does not explain how those counts relate to the randomized population or whether any observations were excluded.

Missing-data procedures, analysis-population definitions, covariate adjustment, protocol-deviation handling, and sensitivity analyses are not reported. Nor is the original design’s sample-size rationale stated. The posted planning illustrations are based on observed effects and should not be substituted for the original design information.

The registry calls the study quadruple-masked, while the brief description calls it double-blind; the masking procedures and the relationship between these descriptions are not explained. The record also does not specify how pain scores or adverse events were collected, whether repeat doses were administered, or how rescue-medication decisions were made.

Finally, the secondary analyses are not formally reported and no multiplicity approach is described. The adverse-event summary lacks event-level detail and does not establish the completeness or duration of safety ascertainment. These limitations constrain independent assessment of robustness, clinical relevance, and generalizability.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Intravenous Lidocaine Randomized Comparative Effectiveness Trial — NCT03300674.
• Registry record last updated 2020-08-10; status last verified 2020-07.
• Results first posted 2019-11-26.
• 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

The registry record describes a completed, randomized, phase 4, parallel-group comparative-effectiveness trial sponsored by Montefiore Medical Center. It compares intravenous lidocaine with intravenous hydromorphone for acute abdominal pain in the emergency department. The registry lists quadruple masking, while the brief description uses the term double-blind.

The primary outcome is change in a 0–10 pain scale between baseline and 90 minutes. The posted means are 3.8 for lidocaine and 5.0 for hydromorphone, with a mean difference of -1.2, a 95% confidence interval from -1.995 to -0.405, and an unadjusted p-value of 0.003. The change-score sign convention is not reported.

Rescue medication and adverse events are also listed. Formal secondary analyses, missing-data methods, analysis populations, multiplicity handling, and the original sample-size assumptions are not reported in the registry record. Interpretation is therefore limited to the posted summaries and the details documented in the record.