Modified Reporting From Indwelling Catheters: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Modified Reporting From Indwelling Catheters (NCT03488355), a randomized na study. The primary outcome is Number of Participants With Appropriate Treatment.

2. Clinical Question

3. Trial Design

NCT03488355, titled “Modified Reporting From Indwelling Catheters,” is recorded as a randomized, parallel-group trial comparing modified with standard laboratory reporting. Its official title describes it as a randomized controlled trial of modified reporting of positive urine cultures collected from indwelling catheters. The registry lists Memorial University of Newfoundland as the sponsor and urinary tract infections as the condition.

The study population in the registry summary is inpatients with positive urine cultures collected from indwelling catheters. The intervention was a modified laboratory report; the comparator was a standard laboratory report. The registry records single masking, but the identity of the masked group or groups and the masking procedures are not reported in the registry record. Details of sequence generation, allocation concealment, and implementation of randomization are also not reported in the registry record.

The registry lists enrollment as 100 and the study status as completed. The recorded start date is 2018-11-05, and the primary completion date is 2019-07-31. The trial’s primary outcome was the number of participants with appropriate treatment, assessed 7 days after a positive urine culture. The registry also lists death and adverse events as secondary outcomes.

The original sample-size justification, the intended analysis population, and the trial’s full statistical analysis plan are not reported in the registry record. The posted planning illustrations are based on the observed effect and should not be read as the trial’s original design assumptions. The record does not describe whether there were interim analyses or how missing outcome data were handled.

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 Number of Participants With Appropriate Treatment, measured over 7 days after positive urine culture.

The primary endpoint is the number of participants classified as receiving appropriate treatment 7 days after a positive urine culture. The registry defines the numerator as untreated catheter-associated asymptomatic bacteriurias plus treated catheter-associated urinary tract infections, divided by total patients. In other words, appropriateness depends on whether treatment was given in keeping with the distinction between asymptomatic bacteriuria and a urinary tract infection, as specified in the registry description.

This endpoint addresses the trial’s clinical decision-making question: whether changing the laboratory report is associated with different antibiotic treatment decisions. It is not a direct measure of the report itself, nor does the posted primary endpoint count specify treatment duration, antibiotic choice, or the appropriateness criteria beyond the registry definition. Those details are not reported in the registry record.

The posted result is expressed as a count of participants meeting the endpoint in each group. The comparison can also be expressed using a risk difference, which describes the difference between the proportions meeting the endpoint, or a risk ratio, which compares those proportions as a ratio. These measures describe the same binary outcome from different perspectives. The registry’s wording refers to a percentage, while the primary outcome measure is recorded as a participant count.

7. Results Posted in the Registry

• Modified Reporting: 57.4% (31/54) versus 50.0% (23/46) on control; risk difference 7.4 percentage points (95% CI -12.2 to 27.0), risk ratio 1.15 (0.79–1.66); unadjusted two-proportion z-test p = 0.459.

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.

Death

• 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:
  • Modified Reporting: 7.4% (4/54) versus 6.5% (3/46) on control; risk difference 0.9 percentage points (95% CI -9.1 to 10.9), risk ratio 1.14 (0.27–4.81); unadjusted two-proportion z-test p = 0.863.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Modified Reporting and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists death and adverse events as secondary outcomes. These outcomes provide safety context, while the primary endpoint focuses on appropriate treatment decisions. They therefore address related but distinct questions: a treatment-appropriateness count does not by itself summarize all potential harms, and secondary safety outcomes do not replace the primary comparison.

The posted secondary outcomes do not supply a separate reported inferential analysis. In particular, the registry record contains no reported analysis for the death outcome. The secondary information should consequently be read as descriptive rather than as a set of confirmatory tests. Sparse event counts tend to yield imprecise estimates, so a lack of strong statistical evidence in an unadjusted comparison would not establish equal safety outcomes.

Unadjusted secondary findings carry less weight than a prespecified primary analysis when several outcomes are examined. In general, the more outcome comparisons considered, the greater the chance that at least one may appear noteworthy through random variation alone. Adjustment for multiplicity, a prespecified hierarchy, or another strategy can address that concern, but such a plan is not reported in the registry record. The secondary findings are best treated as contextual signals that may inform interpretation and future questions, rather than independent proof for or against the primary result.

The record does not report a separate result for pyelonephritis or sepsis, despite mentioning those outcomes in the trial hypothesis. They should not be inferred from the broader secondary-outcome listings.

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

• Death
• Adverse Events

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports a two-sided t-test and gives the risk ratio as the analysis parameter. It reports a risk ratio of 1.15 and a p-value of 0.45. The record does not provide a confidence interval for that analysis or further details about how the reported test was implemented. The recalculated comparisons are simple, unadjusted calculations from the posted group summaries, rather than a reconstruction of an adjusted trial analysis.

What does a risk difference describe?

A risk difference compares the proportion meeting a binary outcome in one group with the proportion in the other. A value of zero corresponds to equal proportions. A positive value in the direction used for the posted comparison indicates a higher proportion in the modified-reporting group; a negative value indicates a lower proportion. The primary recalculated risk difference is 0.074. Its confidence interval extends from -0.122 to 0.270, which includes zero. This interval therefore does not rule out differences in either direction.

How is a risk ratio different?

A risk ratio divides one group’s outcome proportion by the other group’s proportion. A ratio of 1 corresponds to equal proportions, values above 1 indicate a higher proportion in the numerator group, and values below 1 indicate a lower proportion. The recalculated primary risk ratio is 1.148, with a confidence interval from 0.794 to 1.661. Because the interval includes 1, the data do not narrowly distinguish the observed ratio from equal proportions. A risk ratio is relative, while a risk difference expresses the contrast in absolute terms; both can help describe a binary outcome.

What does the odds ratio add?

The odds ratio compares the odds of meeting the outcome rather than the proportions themselves. Its reference value for no group contrast is also 1. The recalculated primary odds ratio is 1.348, with a confidence interval from 0.611 to 2.971. Odds ratios and risk ratios are not interchangeable, especially when outcomes are common. The odds ratio is included as a separate description of the posted binary data, not as a substitute for the risk difference or risk ratio.

What does the p-value test?

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 test’s assumptions held. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The recalculated unadjusted primary p-value is 0.459; the registry’s reported p-value is 0.45. Neither should be interpreted as proof of no difference. The direction and range of plausible effects are better considered alongside the confidence interval.

Why use a confidence interval?

In general, a confidence interval conveys sampling uncertainty around an estimate under the method used to construct it. A wide interval signals limited precision: the observed data are consistent with a broad range of underlying effects. For a risk difference, zero is the value corresponding to no difference; for a risk ratio or odds ratio, that reference value is 1. An interval that includes its no-difference reference value does not prove equivalence. Establishing equivalence or non-inferiority requires a prespecified margin and an appropriate design and analysis, which are not reported in the registry record.

What is meant by unadjusted recalculation?

The recalculated comparisons use the posted counts and group sizes without adjustment for other variables. They describe a direct contrast of the recorded group summaries. They do not account for any covariates, stratification, clustering, or other modeling choices. Whether such methods were part of a fuller analysis is not reported in the registry record. The registry’s own analysis is reported separately and should not be conflated with these calculations.

All of these methods concern statistical description of the posted outcome. They do not resolve limitations in outcome definition, missingness, masking, or generalizability. Those features require trial-record details that are not reported in the registry record.

11. Confidence Intervals and Precision

The primary estimate is imprecise. The recalculated risk-difference interval runs from -0.122 to 0.270, spanning zero and allowing for a lower or higher proportion meeting the endpoint under modified reporting. The corresponding risk-ratio interval, from 0.794 to 1.661, spans values below and above the no-difference reference of 1. The odds-ratio interval, from 0.611 to 2.971, is also broad. Taken together, these intervals indicate that the posted summary data do not locate the underlying group contrast precisely.

Confidence intervals are not guarantees that a particular range contains the true effect, and their interpretation depends on the statistical method and its assumptions. In general, they express uncertainty from sampling variability in a way that complements the point estimate. Here, the primary interval includes the no-difference value, but that alone is not evidence that the groups are equivalent. Equivalence requires a clinically justified margin and a design and analysis intended to evaluate that margin; these are not reported in the registry record.

The registry’s own analysis reports a risk ratio of 1.15 and p-value of 0.45 without a confidence interval. The recalculated interval gives an indication of precision based on the posted group summaries, but it is not a replacement for any sponsor-reported interval or a full analysis using participant-level data. The registry record does not report the number of missing primary outcomes or the method used to handle missing data, which also limits assessment of how completely the interval reflects uncertainty in the trial result.

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 illustrations based on the observed primary effect, not the trial’s original design assumptions. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses a stated fraction of the observed effect as the effect to detect. The original sample-size assumptions are not reported in the registry record. These figures are participants per arm, not total participants or total events.

For planning around 100% of the observed effect, the illustration gives 711 participants per arm for 80% power and 951 participants per arm for 90% power. For planning around 75% of the observed effect, it gives 1,267 participants per arm for 80% power and 1,695 participants per arm for 90% power. For planning around 50% of the observed effect, it gives 2,856 participants per arm for 80% power and 3,823 participants per arm for 90% power.

In general, power is the probability that a planned study will reject a specified null hypothesis if a particular effect is present and the design assumptions hold. The 80% and 90% columns therefore describe alternative planning targets: the latter targets a higher chance of detecting the chosen effect, under the stated assumptions. Smaller effects require more participants because they are harder to distinguish from sampling variation. The effect fractions are planning choices, not separate observed results. These figures are not observed power and do not describe what the completed trial was guaranteed to detect.

13. How the Sample Size Is Derived

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

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.500; treatment proportion p₁ = 0.574; average p̄ = 0.537.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7052 = 1.3821.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7032 = 0.5918.
4. n = (1.3821 + 0.5918)² / (0.0741)² = 710.1, rounded up to 711 participants per arm for 80% power.

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

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.5                          # control proportion
p1 <- 0.574074074074074                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(3488355)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 711 (80% power), 951 (90% power)
 75% of observed effect: n per arm = 1,267 (80% power), 1,695 (90% power)
 50% of observed effect: n per arm = 2,856 (80% power), 3,823 (90% power)
power.prop.test: 710.1 
Simulated power at n = 711 per arm: 0.805 (20000 replicates)

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

14. Analyses Reported by the Sponsor

The registry’s reported analysis gives a risk ratio of 1.15 with a two-sided p-value of 0.45. The unadjusted recalculation from the posted summaries gives a risk ratio of 1.148 and a p-value of 0.459. The point estimates and p-values are close, and both analyses describe a result that does not provide strong statistical evidence of a difference. The registry’s reported analysis does not include a confidence interval.

The record identifies the reported method as a two-sided t-test and the analysis parameter as a risk ratio. It does not provide further detail about the test implementation, adjustments, or analysis population. The recalculated result is a direct, unadjusted comparison of the posted counts and group sizes; it is not a reproduction of any analysis using participant-level data. It should therefore be read as a complementary check on the summary data, not as a replacement for the registry’s reported analysis.

The difference in displayed precision between 1.15 and 1.148 reflects how the two estimates are reported. The registry result is rounded to two decimal places, while the recalculated summary gives more digits. Neither point estimate removes the uncertainty indicated by the recalculated confidence interval.

15. Multiplicity, Missing Data and Analysis Populations

The primary outcome is clearly identified as the number of participants with appropriate treatment, assessed 7 days after a positive urine culture. The registry also lists death and adverse events as secondary outcomes. However, the analysis plan for handling multiple outcomes or repeated statistical tests is not reported in the registry record. It is therefore not possible to determine whether the secondary outcomes were intended as confirmatory tests, exploratory measures, or part of a formal testing sequence.

In general, multiplicity matters because evaluating several outcomes can increase the chance of obtaining at least one apparently notable result by chance. A prespecified hierarchy or a suitable adjustment can help control that risk. Without a reported multiplicity strategy, secondary p-values, if calculated elsewhere, would need cautious interpretation. The posted secondary information does not include a reported death analysis, and an adjustment method is not reported in the registry record.

The registry record does not state whether all randomized participants were included in the primary analysis, whether an intention-to-treat population was used, or whether any alternative analysis population was defined. The count outcome is described in terms of participants and total patients, but the handling of missing primary outcomes, withdrawals, or exclusions is not reported in the registry record. Nor are procedures for imputing missing values or sensitivity analyses described.

These omissions matter because analysis populations and missing-data methods can affect the interpretation of a randomized comparison. Randomization supports a fair group comparison when analyzed appropriately, but it does not by itself resolve missing outcome data or deviations from assigned reporting. The available summary results permit a direct unadjusted comparison; they do not establish which participant-level analysis choices were used beyond the registry’s reported test description.

16. 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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: bacteremia (5.6%).

For serious adverse events, the registry records 3 affected participants in the modified-reporting group and 0 in the standard-reporting group. The corresponding groups at risk are recorded as 54 and 46. The registry lists bacteremia at 5.6% among the top serious terms. The denominator and method used for that term percentage are not reported in the registry record.

Other adverse events are recorded for 13 participants in the modified-reporting group and 19 in the standard-reporting group. Deaths within 7 days are recorded for 4 and 3 participants, respectively. These are descriptive counts; the registry provides no reported inferential analysis for these secondary outcomes. In particular, the small serious-event counts do not support precise comparisons, and a zero count in a group does not establish that the underlying risk is zero.

Serious adverse events, other adverse events, and deaths are distinct recorded categories and should not be combined or treated as interchangeable. The record does not provide further details on event definitions, attribution, or the timing of adverse events beyond the stated death timeframe. These data describe what the registry posts; they do not by themselves establish that either reporting approach caused or prevented an event.

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

The primary result is a comparison of appropriate-treatment counts under modified and standard laboratory reporting. The modified-reporting group had 31 participants classified as receiving appropriate treatment, compared with 23 in the standard-reporting group. The recalculated risk difference is 0.074, but its confidence interval extends from -0.122 to 0.270. The data therefore leave substantial uncertainty about the direction and size of the underlying difference.

The registry’s own analysis reports a risk ratio of 1.15 and a two-sided p-value of 0.45. This does not provide strong statistical evidence of a difference, but it does not prove that the approaches are equivalent or that there is no effect. A result that is not statistically persuasive can still be compatible with effects that matter; the confidence interval shows the range of contrasts consistent with the posted summary under the calculation’s assumptions.

The trial’s stated hypothesis also concerned avoiding an increase in pyelonephritis or sepsis. Separate results for those outcomes are not reported in the registry record, so the primary endpoint cannot answer that part of the hypothesis. Death and adverse events are listed as secondary outcomes, but their posted information is descriptive and does not provide a full confirmatory safety comparison.

These findings should be interpreted as evidence from the posted randomized comparison, with limitations in precision and in the details available about outcome handling and analysis. They do not establish that modified reporting improves treatment decisions, nor do they establish that it worsens them. They also do not justify a conclusion about effects in settings or populations not described in the registry record. The central statistical message is uncertainty: the observed estimate favors a higher appropriate-treatment proportion under modified reporting, but the interval remains compatible with differences in either direction.

18. Why This Trial Matters Statistically

This trial asks a useful statistical question about an intervention in the information pathway rather than a direct clinical treatment: whether changing how a laboratory reports a positive culture is associated with different physician antibiotic decisions. The randomized comparison is intended to separate the effect of reporting approach from other influences on those decisions. The registry’s parallel-group design provides a straightforward framework for comparing the recorded binary outcome between the groups.

The endpoint also illustrates why outcome definitions matter. “Appropriate treatment” combines two classifications: leaving catheter-associated asymptomatic bacteriuria untreated and treating catheter-associated urinary tract infections. A single count can summarize whether decisions fit that definition, but it does not show which component contributed to the result. Nor does it describe the particular antibiotic decisions or the clinical course in detail. Those distinctions are important when interpreting a composite decision-based endpoint.

The trial is also a useful example of the difference between an observed point estimate and precision. The primary risk-difference estimate is positive, while its confidence interval includes zero and spans a broad range. Reporting the estimate alone could overstate certainty; reporting the interval makes the uncertainty more apparent. The sponsor’s reported risk ratio and p-value and the unadjusted recalculation tell a broadly similar statistical story, but neither resolves the uncertainty.

Finally, the stated hypothesis includes safety considerations beyond the primary outcome. This reinforces the need to interpret efficacy-oriented and safety-oriented outcomes together while respecting the limits of sparse secondary information and unreported analysis details. A clinically relevant question can be important even when a registry summary does not permit a definitive statistical conclusion.

19. Limitations

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

The primary result is based on a modest amount of posted outcome information, and the confidence intervals are broad. This limits how precisely the difference in appropriate treatment can be estimated. The registry lists enrollment as 100, but the record does not report a sample-size justification or the original assumptions used to plan the trial. The planning illustrations based on the observed effect cannot fill that gap.

The endpoint depends on classifying catheter-associated bacteriuria and urinary tract infection and judging whether treatment was appropriate. The registry provides a brief definition but does not report further adjudication procedures, criteria, or whether outcome assessors were masked. Although the trial is recorded as single masked, the identity of the masked party and the practical masking procedures are not reported in the registry record. The modified and standard reporting approaches themselves may be distinguishable to those receiving or acting on the reports; the record does not explain how that was handled.

The registry does not report the randomization sequence method, allocation concealment, participant flow, missing primary outcomes, or analysis population. These details are relevant to assessing whether the posted comparison represents all randomized participants and how missingness may have affected the estimate. The reported analysis also lacks a confidence interval, while the recalculated interval is based only on summary counts and is unadjusted.

Safety interpretation is limited by sparse serious-event information and the absence of a reported inferential analysis for the secondary outcomes. Separate results for pyelonephritis and sepsis are not reported in the registry record, although the trial hypothesis mentions them. The registry summary describes inpatients with positive cultures from indwelling catheters but does not report further setting or eligibility details, limiting assessment of how broadly the findings may apply.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Modified Reporting From Indwelling Catheters — NCT03488355.
• Registry record last updated 2023-01-25; status last verified 2022-04.
• Results first posted 2023-01-25.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT03488355 is a completed randomized, parallel-group trial of modified versus standard reporting for positive urine cultures collected from indwelling catheters in inpatients. The registry lists Memorial University of Newfoundland as sponsor, enrollment as 100, a start date of 2018-11-05, and a primary completion date of 2019-07-31. The record describes single masking but does not identify who was masked.

The primary outcome was the number of participants with appropriate treatment 7 days after a positive culture. The posted counts were 31 with modified reporting and 23 with standard reporting. The registry’s reported risk ratio is 1.15 with a two-sided p-value of 0.45; the unadjusted recalculation has a risk-difference confidence interval from -0.122 to 0.270. These results are uncertain and do not establish equivalence or a treatment effect.

Death and adverse events are listed as secondary outcomes. The original sample-size assumptions, missing-data methods, analysis population, and multiplicity strategy are not reported in the registry record.