Minimal Flow Anesthesia and Infection Risk: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Minimal Flow Anesthesia and Infection Risk (NCT07092046), a randomized na study. The primary outcome is Microbial Contamination of the Inspiratory Limb.

2. Clinical Question

3. Trial Design

The registry record describes a randomized, triple-masked, parallel-group trial, marked completed, with enrollment of 140. Participants were allocated to minimal-flow anesthesia at 0.5 L/min or standard-flow anesthesia at 2 L/min. The primary outcome was recorded at the end of anesthesia, immediately after disconnection of the breathing circuit. The record lists the start date and primary completion date as 2025-08-01. It does not report additional information about the sequence-generation method, concealment of allocation, or the roles covered by triple masking.

For the primary outcome, the posted results show 70 participants in each group. Microbial contamination was recorded for 6 participants in the minimal-flow group and 4 in the standard-flow group. Four secondary outcomes are listed: heart rate, peripheral oxygen saturation, end-tidal carbon dioxide, and mean arterial pressure at defined perioperative time points. Results for those outcomes are not reported in the registry record.

The listed interventions include several anesthetic and other drug names, but the registry record does not explain their assignment by group or their relationship to the primary comparison. The protocol’s original sample-size justification, planned statistical analysis, detailed masking procedures, and any interim analyses are not reported in the registry record. The trial’s enrollment and the later planning illustrations should therefore be read separately: the illustrations are calculations based on the observed effect, not a description of the original design.

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.

Before assignment: A total of 140 eligible adult patients (ASA I-II, aged 18-65 years) scheduled for elective surgical procedures were enrolled after providing written informed consent. All participants met the inclusion criteria and none were excluded prior to randomization. Participants were randomized in a 1:1 ratio to receive either minimal-flow anesthesia (0.5 L/min) or high-flow anesthesia (2 L/min).

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.

Population: All randomized participants were included in the baseline analysis. A total of 140 adult patients (ASA physical status I-II, aged 18-65 years) undergoing elective surgical procedures were randomized to either minimal-flow anesthesia (n=70) or high-flow anesthesia (n=70).

6. Primary Endpoint

The registry lists the primary outcome as Microbial Contamination of the Inspiratory Limb, measured over At the end of anesthesia (immediately after disconnection of the breathing circuit).

The primary endpoint is the count of participants with microbial contamination in a sample collected from the inspiratory limb of the anesthesia breathing circuit. A sample was considered contaminated when microbiological growth was identified by culture and MALDI-TOF MS analysis. The measurement time was at the end of anesthesia, immediately after the breathing circuit was disconnected.

This endpoint directly addresses the study’s stated concern about microbial growth within anesthesia equipment during minimal-flow anesthesia. It records whether contamination was detected in a participant’s sample, rather than the amount of microbial growth or a clinical infection in the participant. The distinction matters: a positive equipment sample is the measured outcome, while infection in a participant is not the primary outcome described in the registry record.

The reported group results are counts: 6 of 70 participants in the minimal-flow group and 4 of 70 in the standard-flow group had contamination recorded. The record does not report further details about sample collection beyond the inspiratory limb and timing, laboratory procedures beyond culture and MALDI-TOF MS, or how indeterminate or missing samples were handled. These omissions limit assessment of the endpoint’s implementation and completeness.

7. Results Posted in the Registry

• Minimal Flow Anesthesia (0.5 L/Min): 8.6% (6/70) versus 5.7% (4/70) on control; risk difference 2.9 percentage points (95% CI -5.7 to 11.4), risk ratio 1.50 (0.44–5.09); unadjusted two-proportion z-test p = 0.512.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant either had microbial contamination recorded or did not. The posted counts are 6 of 70 in the minimal-flow group and 4 of 70 in the standard-flow group. For a binary outcome, a group risk is the number of participants with the event divided by the number assessed in that group. The registry reports these risks as 0.086 and 0.057. The record does not report a more detailed analysis population or how missing outcome measurements were treated.

What does the risk difference describe?

The risk difference subtracts the comparator group’s risk from the intervention group’s risk. The reported estimate is 0.029. A value of 0 represents equal risks, a positive value means the observed risk is higher in the minimal-flow group, and a negative value means it is lower. This measure retains the absolute scale of the outcome and is often straightforward to relate to the observed event proportions. General interpretation: the estimate is a sample-based quantity, and its precision depends on the data and analysis method; it should not be read as a guaranteed difference in other participants.

How do relative measures differ?

The risk ratio compares the two group risks as a ratio, while the odds ratio compares their odds. The posted risk ratio is 1.5 and the odds ratio is 1.547. A ratio of 1 represents no relative difference; values above or below 1 indicate the direction of the comparison. Risk ratios and odds ratios use different scales and are not interchangeable. With a binary endpoint, the odds ratio can differ from the risk ratio, so both should be interpreted according to their definitions. The registry reports confidence intervals for each measure, and both include 1.

What does the confidence interval contribute?

A confidence interval expresses uncertainty around an estimate under the statistical procedure used. In general, it gives a range of values that are compatible with the observed data and that procedure, rather than a set of values known to contain the true effect. The reported risk-difference interval is -0.057 to 0.114; the risk-ratio interval is 0.442 to 5.086; and the odds-ratio interval is 0.417 to 5.739. The confidence level and interval-construction method are not reported in the registry record. As a result, the numerical limits can be quoted, but the record does not permit a complete reconstruction of how they were obtained.

How should the p-value be read?

The reported unadjusted p-value is 0.512. In general, a p-value is calculated under a specified null model and describes how often results at least as incompatible with that model would arise if its assumptions held. It is not the chance that the null model is true, and it does not quantify the probability that the finding will replicate. The registry record does not identify the test used for this p-value, whether it was prespecified, or whether any adjustment was planned. It should therefore be described as the posted unadjusted value, not as evidence about every possible analysis.

Why can sparse counts produce uncertainty?

General statistical explanation: when an outcome occurs in relatively few participants, each event can have a noticeable influence on the estimated risks and their comparison. The observed counts are 6 and 4. Sparse events can lead to broad uncertainty in relative measures, especially when estimates depend on ratios. The wide reported intervals are consistent with limited precision, but the record does not supply enough methodological detail to attribute their exact width to a particular interval method.

Over-dispersion is a general concern for some count outcomes when variability exceeds what a simple model assumes. It is not the main modeling issue for this participant-level binary endpoint, and the registry record does not report an over-dispersion assessment. The record also does not describe covariate adjustment, stratification, missing-data methods, or a detailed statistical analysis plan. General concepts can clarify what the posted measures mean, but they do not fill in those unreported choices.

10. Confidence Intervals and Precision

The uncertainty around the estimated risk difference is important to the interpretation. The reported estimate is 0.029, with confidence limits of -0.057 and 0.114. Because this interval crosses 0, the posted result is compatible with no risk difference as well as with differences in either direction under the procedure used. The interval does not support a narrow estimate of the size of the effect.

The relative estimates are also imprecise. The risk ratio is 1.5, with limits from 0.442 to 5.086, and the odds ratio is 1.547, with limits from 0.417 to 5.739. Each interval includes 1. Their ranges cover substantially different possible relative effects, so the point estimates should not be treated as settled values. The small number of recorded events—6 and 4—helps explain why the result should be read cautiously, though the registry record does not identify the interval method or give a formal precision analysis.

In general, a confidence interval’s interpretation depends on its construction and stated confidence level. The confidence level and calculation method are not reported in the registry record. Thus, the numerical limits are the available description of precision, but their nominal coverage cannot be verified from the record. Precision is distinct from whether an analysis crosses a significance threshold: a result can be uncertain even when its point estimate suggests a direction, and an interval containing a no-effect value does not prove equivalence.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total events. They are illustrations calculated from the observed effect, rather than the trial’s original sample-size plan. The listed 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 stated fraction of the observed effect. The trial’s original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the planned number of participants per arm under the stated assumptions for a design with an 80% chance of detecting the effect used in that scenario, if that effect and the assumptions were correct. The 90% power column gives the corresponding number per arm for a 90% chance. These are planning probabilities for a hypothetical study before data are collected; they do not describe the probability that the observed result is correct.

The rows use 100%, 75%, and 50% of the observed effect. Smaller effects require more participants to distinguish them from chance variation at the same significance level and power target. The figures therefore grow as the assumed effect becomes smaller. They are not observed power: observed power is not a useful substitute for interpreting the posted estimate and its uncertainty after the trial. The curve should be read as a visual representation of this planning relationship, not as additional trial outcomes or evidence that any particular effect is expected.

12. How the Sample Size Is Derived

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

Formula

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

Worked calculation for this trial

1. Control proportion p₀ = 0.057; treatment proportion p₁ = 0.086; average p̄ = 0.071.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3642 = 0.7138.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3637 = 0.3061.
4. n = (0.7138 + 0.3061)² / (0.0286)² = 1,274.3, rounded up to 1,275 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 <- 0.0571428571428571                          # control proportion
p1 <- 0.0857142857142857                          # 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(7092046)
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 = 1,275 (80% power), 1,706 (90% power)
 75% of observed effect: n per arm = 2,162 (80% power), 2,893 (90% power)
 50% of observed effect: n per arm = 4,626 (80% power), 6,193 (90% power)
power.prop.test: 1274.3 
Simulated power at n = 1,275 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.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists four secondary outcomes: heart rate, peripheral oxygen saturation, end-tidal carbon dioxide, and mean arterial pressure at defined perioperative time points. Their results are not reported in the registry record. The number of analyses is listed as 0, while the registry also lists outcome measures. This does not establish which analyses were conducted or whether secondary outcomes were assessed but not posted.

When a study evaluates multiple outcomes, time points, or alternative analyses, the chance of at least one apparently unusual result can increase. General statistical explanation: multiplicity methods can control or otherwise address that issue, but they require a defined family of tests and a stated approach. The registry record does not report whether multiplicity was considered, whether any adjustment was planned, or which outcome comparisons were designated in advance. The posted p-value is explicitly unadjusted and should not be assumed to account for other possible analyses.

The record does not report missing-data counts, the number of participants with an evaluable primary sample, or how incomplete or unusable samples were handled. Although the posted arm sizes are 70 each, those figures alone do not establish that every enrolled participant contributed a valid primary-outcome measurement. The record also does not describe an intention-to-treat, per-protocol, or other analysis population. These details matter because exclusions or missing measurements can change the population represented by an estimate.

The registry record does not report a detailed statistical analysis plan, prespecified handling of protocol deviations, covariate adjustments, or sensitivity analyses. It also does not report interim analyses or stopping rules. These absences do not show that such procedures were or were not used; they mean that they cannot be evaluated from the registry record. Accordingly, interpretation should stay close to the posted primary counts and unadjusted comparison rather than assume unreported methods.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

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

The serious adverse-event figures list 70 participants at risk in each group and 0 participants affected in each group. Deaths are listed as 0 in both groups. Other adverse events are also listed as 0 affected among 70 at risk in each group. No serious adverse-event terms are listed.

These are the posted counts for the registry record’s adverse-event categories. They should not be expanded into a conclusion that no adverse events of any kind occurred beyond what was recorded. The record does not provide event descriptions, collection procedures, severity definitions, follow-up duration, or additional detail about ascertainment. The listed counts are also distinct from the primary endpoint, which concerns microbial contamination of an equipment sample rather than an adverse event in a participant.

In general, zero recorded events in a group do not prove that an event is impossible or that a broader safety question has been resolved. These counts describe what was posted for the trial and should be read with the trial’s size and the unreported safety-collection details in mind.

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

The posted primary results show microbial contamination in 6 of 70 participants assigned to minimal-flow anesthesia and 4 of 70 assigned to standard-flow anesthesia. The estimated risk difference is 0.029, with a confidence interval from -0.057 to 0.114, and the unadjusted p-value is 0.512. The result therefore gives a point estimate in one direction but does not determine the direction or size of the underlying difference with precision. The relative-effect intervals are also broad and include their no-difference values.

The endpoint measures culture-identified microbial growth in the inspiratory limb at the end of anesthesia. It is not a direct measurement of infection in participants, and the registry record does not report clinical infection outcomes. Thus, the result cannot by itself establish whether either anesthesia flow strategy changes participants’ infection risk. Nor does the observed difference prove that heat or moisture caused the detected growth; the record does not provide a causal analysis of that proposed mechanism.

The event counts are limited, and the registry record does not report the confidence-interval method, detailed statistical analysis plan, missing-data handling, or multiplicity approach. These limitations affect how completely the comparison can be assessed. The reported zero serious and other adverse-event counts describe the posted categories but do not settle broader safety questions.

In general, a result that does not provide precise evidence of a difference is not the same as evidence of equivalence. An equivalence or non-inferiority claim would require a prespecified margin and an appropriate analysis, neither of which is reported in the registry record. The most restrained conclusion is that the trial recorded few contamination events and that the posted estimates leave substantial uncertainty about comparative contamination. They do not establish a clinical benefit, harm, or absence of effect.

16. Why This Trial Matters Statistically

This trial raises a statistical distinction between an intermediate equipment measure and a clinical outcome. Its primary endpoint is microbial contamination of the inspiratory limb, not infection in participants. That distinction determines what the results can answer: the counts describe detected growth in equipment samples at a specific time, rather than the downstream clinical consequences of such growth.

The comparison also illustrates why event counts, effect estimates, and uncertainty need to be considered together. The group counts are 6 and 4, and the estimated risk difference is 0.029. The confidence interval spans 0, while the reported relative-effect intervals include 1. A reader who focuses only on the point estimate could overstate the evidence; a reader who treats the p-value alone as proof of no effect could also overstate it. The intervals show that the estimate is not precise.

Randomization is an important design feature for comparing groups, but it does not eliminate uncertainty, missing-data concerns, measurement questions, or the need for transparent analysis methods. The registry record identifies the randomized, triple-masked, parallel design, yet does not report details such as allocation procedures, analysis populations, or a statistical analysis plan. Such reporting helps readers assess whether the result answers the intended question and how robust it may be.

The record’s planning illustrations also emphasize the difference between design calculations and post-trial interpretation. They show how required sample size depends on the effect a future study aims to detect and the chosen power target; they do not retroactively validate or invalidate this trial’s result. Together, these features make the study a useful example of interpreting a binary endpoint with relatively few observed events and separating statistical evidence about contamination from broader clinical claims.

17. Limitations

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

The primary endpoint is equipment contamination, so its interpretation does not directly extend to participant infection. The registry record does not report clinical infection as an outcome. It also provides limited detail about specimen collection and laboratory handling beyond the inspiratory-limb sampling location, end-of-anesthesia timing, culture, and MALDI-TOF MS analysis. The record does not describe how a sample without a usable result would be classified.

The posted primary counts are 6 and 4, with 70 participants in each group. The resulting effect estimates have broad confidence intervals, and the confidence-interval level and calculation method are not reported. The limited event counts make the estimates uncertain, while the absence of methodological detail restricts independent assessment of the analysis.

Other limitations specific to the record include missing descriptions of participant eligibility, allocation procedures, the practical implementation of triple masking, and the primary analysis population. The registry does not report how missing data or protocol deviations were handled, whether covariates were used, or how multiplicity across outcomes and time points was addressed. Although four secondary outcomes are listed, their results are not reported in the registry record.

The record lists drug interventions but does not explain their distribution across arms or their role in the primary comparison. It also does not provide a protocol-level sample-size justification or explain whether the listed enrollment was based on a particular target difference. Finally, adverse-event counts are posted without detail on definitions, ascertainment, or follow-up. These gaps do not establish that the trial was conducted inadequately; they limit what readers can verify from the registry record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Minimal Flow Anesthesia and Infection Risk — NCT07092046.
• Registry record last updated 2026-10-05; status last verified 2026-07.
• Results first posted 2026-10-05.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

The registry record describes a completed randomized, triple-masked, parallel-group trial with 140 participants enrolled. It compares minimal-flow anesthesia at 0.5 L/min with standard-flow anesthesia at 2 L/min. The primary endpoint is microbial contamination of the inspiratory limb at the end of anesthesia.

Contamination was recorded for 6 of 70 participants in the minimal-flow group and 4 of 70 in the standard-flow group. The risk-difference estimate is 0.029, with a confidence interval from -0.057 to 0.114; the unadjusted p-value is 0.512. The confidence interval includes no difference, and the estimate is imprecise.

The registry lists four secondary outcomes, but their results are not reported in the registry record. Serious adverse events, other adverse events, and deaths are each listed as 0 affected in both groups. Details of the original sample-size justification, analysis plan, missing-data methods, and interval calculation are not reported in the registry record.