Connecting Alaska Native People to Quit Smoking: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Connecting Alaska Native People to Quit Smoking (NCT03645941), a randomized na study. The primary outcome is Smoking Cessation Program Completion.

2. Clinical Question

The clinical question is about participation and program completion, not only whether participants stopped smoking. The trial also recorded self-reported smoking abstinence, use of evidence-based cessation treatments, and quit attempts at 6 months. Those outcomes provide related but distinct information: completing a program, reporting abstinence, using treatment, and attempting to quit are not interchangeable measures.

The comparison concerns the Facebook group added to referral materials and treatment information, versus referral materials and treatment information alone. It therefore does not isolate the effect of Facebook from the other elements of the intervention package. The registry record does not report a separate comparison of the Facebook group against no support or no referral.

3. Trial Design

The registry describes a randomized, parallel-group trial with no masking. A total of 61 participants were enrolled. One group was assigned to Quitline/Treatment Referral and the other to Facebook+Quitline/Treatment Referral. The registry record lists the trial status as completed, with a start date of 2019-12-13 and primary completion on 2021-03-26.

The Facebook intervention was intended to offer culturally relevant support through a private group moderated by an Alaska Native tobacco research counselor. The description specifies a 3-month group, daily moderator postings for 30 days repeated each month, and additional daily check-ins or responses to participant-generated content. The referral group received printed materials by postal mail and information by email about treatment services and how to access them. The intervention group also received the referral component, so the randomized contrast is the Facebook-supported package against referral alone.

The primary outcome was assessed at the 6 month follow-up assessment and counted participants who completed the smoking-cessation program and all activities per protocol. The posted primary outcome denominators were 30 participants in the referral group and 31 in the Facebook-plus-referral group. The registry also reports three secondary outcomes at 6 months; their denominators differ by outcome and are smaller than the enrollment counts.

The registry record does not report the randomization method, allocation concealment, eligibility details, participant flow, or the trial's original statistical analysis plan. It also does not report whether outcome assessors were masked. These omissions limit what can be said about the conduct of the trial beyond the design features explicitly recorded. No phase designation beyond NA is listed.

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 Smoking Cessation Program Completion, measured over 6 month follow-up assessment.

The primary endpoint is the number of participants who completed the smoking-cessation program and all activities per protocol, assessed at the 6-month follow-up. It is a count outcome: the posted results report 16 of 30 participants in the Quitline/Treatment Referral group and 19 of 31 in the Facebook+Quitline/Treatment Referral group as completing the program.

This endpoint captures engagement with the program as defined by its completion requirements. It can be useful in a pilot because participation and completion indicate whether people carried through the planned activities, which is relevant when evaluating a service-delivery approach. Completion is not itself a measure of smoking abstinence, treatment use, or quit attempts. Those behaviors were recorded separately as secondary outcomes.

The endpoint description refers to completion of all activities per protocol, but the registry record does not specify the full criteria used to classify a participant as having completed the program. It does not report a separate definition for partial completion or how participants with incomplete follow-up were classified. Accordingly, the posted count can be interpreted using the stated endpoint description, while details of its operational definition and missing-outcome handling remain unreported.

7. Results Posted in the Registry

• Facebook+Quitline/Treatment Referral: 61.3% (19/31) versus 53.3% (16/30) on control; risk difference 8.0 percentage points (95% CI -16.8 to 32.7), risk ratio 1.15 (0.74–1.78); unadjusted two-proportion z-test p = 0.530.

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.

Self-reported 7-day Point Prevalence Smoking Abstinence

• 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:
  • Facebook+Quitline/Treatment Referral: 17.6% (3/17) versus 38.9% (7/18) on control; risk difference -21.2 percentage points (95% CI -50.1 to 7.7), risk ratio 0.45 (0.14–1.48); unadjusted two-proportion z-test p = 0.164.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Facebook+Quitline/Treatment Referral and the control. The interval gives the range of effects that remain compatible with the data.

Self-reported Use of Evidence-based Cessation Treatments

• 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:
  • Facebook+Quitline/Treatment Referral: 47.1% (8/17) versus 22.2% (4/18) on control; risk difference 24.8 percentage points (95% CI -5.7 to 55.4), risk ratio 2.12 (0.78–5.76); unadjusted two-proportion z-test p = 0.122.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Facebook+Quitline/Treatment Referral and the control. The interval gives the range of effects that remain compatible with the data.

Quit Attempts

• 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:
  • Facebook+Quitline/Treatment Referral: 92.9% (13/14) versus 100.0% (11/11) on control; risk difference -7.1 percentage points (95% CI -20.6 to 6.3), risk ratio 0.93 (0.80–1.07); unadjusted two-proportion z-test p = 0.366.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Facebook+Quitline/Treatment Referral and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover different aspects of smoking-related behavior: self-reported abstinence, use of evidence-based cessation treatments, and quit attempts. Together, they broaden the description beyond whether participants completed the program. Their point estimates do not all align in direction with the primary completion estimate, so there is no single consistent pattern across completion and the reported behaviors.

These endpoints are related conceptually but measure different events. A participant may complete program activities without reporting abstinence, and treatment use or a quit attempt is not the same outcome as either completion or abstinence. The secondary results therefore should not be combined into a single judgment about the primary endpoint. The outcomes also have different recorded denominators, and the registry record does not explain that variation.

The secondary estimates are accompanied by unadjusted p-values, and no reported analyses are listed. In general, when multiple outcomes are examined, the chance of finding an apparently notable result somewhere among them can increase. Unless a testing strategy or multiplicity adjustment is specified, isolated secondary p-values carry less weight than a prespecified primary comparison. The registry record does not report a hierarchy, confirmatory status, or adjustment strategy for these outcomes.

These secondary results are useful as descriptive signals for future study planning, but their uncertainty and analysis context matter. They do not establish that the intervention package affected each behavior, and they do not resolve the uncertainty around the primary completion comparison. Their appropriate role is to provide context about the kinds of outcomes recorded, with cautious interpretation rather than a separate confirmatory claim.

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

• Self-reported 7-day Point Prevalence Smoking Abstinence
• Self-reported Use of Evidence-based Cessation Treatments
• Quit Attempts

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is recorded as a count of participants meeting the program-completion definition. For a binary outcome such as completion, each participant is classified as having or not having the event. The comparison can then be expressed as the difference between the groups' event proportions. The posted risk difference is 0.080, defined for the Facebook+Quitline/Treatment Referral group relative to Quitline/Treatment Referral. A positive value points toward a higher observed event proportion in the Facebook-plus-referral group; it is not, by itself, a statement about causation or precision.

What a risk difference describes

In general, a risk difference describes the absolute separation between two event proportions. It uses the same scale as the underlying proportions and can be read as a difference in the chance of an event, rather than as a relative multiple. The direction depends on which group is subtracted from which, so it is important to preserve the comparison's stated ordering. Here the Facebook-plus-referral group is compared with the referral group.

The risk difference is accompanied by an interval from -0.168 to 0.327. In general, an uncertainty interval describes a range of values compatible with the observed data under the method used to construct it. Its width communicates precision: a wider interval leaves more uncertainty about the underlying difference. Because this interval spans negative and positive values, the observed data do not pin down the direction of the underlying difference. The registry record does not state the confidence level or interval-construction method, so those details are not inferred.

How to read the p-value

The posted primary comparison includes an unadjusted p-value of 0.53. In general, a p-value measures how unusual data at least as incompatible with a specified null model would be if that model were true and the analysis assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. An unadjusted p-value also does not account for testing multiple outcomes or comparisons. The registry record does not report a multiplicity adjustment.

The interval and p-value answer related but different questions. The interval emphasizes the range of effect estimates compatible with the data under its method; the p-value summarizes evidence against a null value under its test. Neither is a substitute for examining the counts, the endpoint definition, and the precision. The registry does not provide the test specification, so no claim is made about which exact test generated the p-value.

Randomization and the comparison

In general, random assignment is used to make groups comparable on average at the point of assignment, including factors that may not have been measured. It does not guarantee identical groups in a small trial, and it does not resolve problems from missing outcomes or departures from the assigned intervention. The record identifies the study as randomized but does not describe the sequence-generation or concealment procedures. It also identifies no masking. The result is a comparison of the assigned intervention packages, not a separately randomized test of each component within the package.

The posted counts use group-specific denominators. The primary outcome has denominators of 30 and 31, while the secondary outcomes have different denominators. A denominator is essential context for an event count: the same count can mean something different depending on how many participants were included in the outcome calculation. The registry record does not explain why denominators vary or whether they reflect available responses, prespecified outcome populations, or another rule.

What the secondary comparisons add

The secondary outcomes are also reported as participant counts at 6 months. For each, the registry presents a group comparison and an unadjusted p-value, but the reported analyses list is empty. In general, secondary outcomes can help describe whether the intervention package is associated with related behaviors, but they do not replace the primary endpoint. They also create multiple opportunities to observe a seemingly notable result by chance, particularly when there is no prespecified hierarchy or adjustment. The record does not state whether these outcomes were confirmatory or exploratory.

These are binary event-count comparisons, not time-to-event analyses or continuous-outcome models. The registry record does not report covariate-adjusted estimates, subgroup analyses, interim analyses, or a model beyond the listed comparison measure. Such methods should not be assumed. The posted summaries support a straightforward descriptive reading of the counts and comparisons, while the missing analytic details constrain stronger conclusions.

11. Confidence Intervals and Precision

Precision concerns how narrowly the available data identify a comparison estimate. The primary risk-difference estimate is 0.080, and its interval extends from -0.168 to 0.327. This range includes differences in both directions. The point estimate alone suggests a positive difference for Facebook+Quitline/Treatment Referral relative to Quitline/Treatment Referral, but the interval indicates substantial uncertainty about the magnitude and direction.

In general, a confidence interval is a method-based range intended to express uncertainty in an estimate. Its interpretation depends on the interval method and confidence level. The registry record does not report those details, so the interval can be described by its endpoints and breadth without assigning an unreported confidence level. The fact that the interval crosses zero means the data are compatible with no difference under the interval's scale, as well as with differences in either direction.

The secondary comparisons also have broad intervals. Their precision is limited, and the denominators vary across outcomes. That variation matters because each comparison is based on a different set of recorded outcome counts. The registry record does not explain the denominator differences or report missing-data analyses, so it is not possible to determine how those factors affect the estimates.

Precision should not be confused with whether an estimate is important. A wide interval does not prove the absence of an effect; it indicates that the available data do not identify the effect narrowly. Similarly, a point estimate does not become reliable simply because it has a particular direction. The primary comparison is best understood as an uncertain estimate from a small pilot, rather than a precise forecast for a larger population.

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 and not total events. The planning illustration uses the observed effect as a reference, then considers detecting the full observed effect, 75% of the observed effect, or 50% of the observed effect. For the primary endpoint, the full-observed-effect illustration lists 606 participants per arm for 80% power and 810 participants per arm for 90% power. The other rows provide corresponding figures for smaller fractions of the observed effect.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The original design assumptions for the trial itself are not reported in the registry record. These planning figures are illustrations based on the posted observed effect, not evidence that the trial was designed with these assumptions.

In general, 80% power describes a design that would have an 80% chance of detecting the specified effect at the stated significance level if that effect and the planning assumptions were true. The 90% column describes the corresponding design with a higher planned chance of detection. Neither column is a probability that the treatment works, nor is it a description of what happened in this trial. This is not observed power.

Smaller effects require more participants to detect under the same planning assumptions. Thus, the rows for 75% and 50% of the observed effect call for larger per-arm samples than planning around the full observed effect. The curve should be read as a visual counterpart to those planning comparisons: it relates assumed effect size to the planned sample requirement, not to an observed trial outcome.

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 = 0.533; treatment proportion p₁ = 0.613; average p̄ = 0.573.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6995 = 1.3710.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6972 = 0.5868.
4. n = (1.3710 + 0.5868)² / (0.0796)² = 605.4, rounded up to 606 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 <- 0.533333333333333                          # control proportion
p1 <- 0.612903225806452                          # 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(3645941)
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 = 606 (80% power), 810 (90% power)
 75% of observed effect: n per arm = 1,084 (80% power), 1,450 (90% power)
 50% of observed effect: n per arm = 2,451 (80% power), 3,280 (90% power)
power.prop.test: 605.4 
Simulated power at n = 606 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. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary endpoint and three secondary endpoints. It does not report whether the secondary outcomes were prespecified as confirmatory, whether they were arranged in a testing hierarchy, or whether any multiplicity adjustment was planned or applied. The reported secondary comparisons include unadjusted p-values, and the reported-analyses fields are empty. As a result, the posted p-values should not be interpreted as if they were adjusted for examining several outcomes.

In general, testing multiple outcomes increases the opportunity for chance findings when each is assessed separately. A prespecified analysis plan can state which outcome is primary, how secondary tests are handled, and whether adjustments are used. Without those details, the primary endpoint remains the clearest basis for the main comparison, while secondary findings are more appropriately treated as exploratory or descriptive. The registry record does not state whether interim analyses were planned or performed.

Missing-data handling is also not reported. The primary denominators are 30 and 31, while the secondary denominators differ across outcomes. Those counts establish the participants included in each posted calculation, but they do not reveal why the denominators differ, whether all randomized participants were assessed, or how unavailable responses were handled. No imputation method, sensitivity analysis, or missingness assumption is listed.

The analysis population is not reported. The registry record does not say whether the primary comparison follows an intention-to-treat principle, includes only participants with available outcome data, or uses another population definition. It also does not report exclusions after randomization or protocol-deviation handling. The endpoint's phrase “per protocol” describes what counts as completion; it does not establish that the statistical analysis itself used a per-protocol population.

These omissions do not change the posted counts, but they limit how fully the estimates can be audited or generalized. They also prevent a clear assessment of whether secondary comparisons and outcome denominators followed the original plan. Interpretation should therefore distinguish the recorded results from analytic details that are not reported in the registry record.

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 record lists serious adverse events and other adverse events separately for the two groups. For serious adverse events, the recorded number affected is 0 among 30 participants at risk in the Quitline/Treatment Referral group and 0 among 31 at risk in the Facebook+Quitline/Treatment Referral group. The other-adverse-event counts are also recorded as 0 in both groups. The record lists 0 deaths in each group.

These entries mean that no events in those categories were recorded in the posted safety results for the participants counted as at risk. They do not establish that the risk of an event is zero, especially in a trial with a small number of participants. In general, observing no events in a study cannot rule out events that are uncommon or that were not captured or reported.

The registry record does not include serious adverse event terms, and it does not provide further detail about event definitions, collection procedures, timing, or attribution. The safety counts should therefore be read as a description of what was recorded, not as a comprehensive assessment of safety or a comparison capable of detecting uncommon events.

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

The posted results show that 16 of 30 participants in the referral group and 19 of 31 in the Facebook-plus-referral group met the primary program-completion definition at the 6-month follow-up assessment. The estimated risk difference is 0.080, with an interval from -0.168 to 0.327. The estimate points toward more completion in the Facebook-plus-referral group, but the interval is broad and includes values in both directions. The result is not precise enough to establish a clear difference between groups.

This comparison concerns the complete intervention packages. Because both groups received referral information and treatment options, the comparison does not measure Facebook support against no referral. Nor can it separate the contribution of the Facebook group from the other intervention elements. The trial records program completion as its primary endpoint; completion should not be treated as equivalent to smoking abstinence or another behavioral outcome.

The three secondary outcomes add descriptive information about self-reported abstinence, evidence-based treatment use, and quit attempts. Their estimates are uncertain, their denominators vary, and no multiplicity strategy is reported. They do not provide a definitive answer to the primary question, and they should not be used to claim a consistent overall effect across outcomes.

The record also does not report the original statistical plan, the analysis population, or missing-data methods. These gaps mean that important context for interpreting the comparisons is unavailable. The posted results are best understood as the outcome counts and estimates recorded for a small randomized pilot, with uncertainty that should remain central to interpretation.

These findings do not prove that the Facebook-plus-referral package increases completion, and they do not prove that it has no effect. They do not establish an effect on smoking behavior or predict results in a larger trial. They describe the observed outcomes and the precision of the available comparisons, while leaving substantial uncertainty about the underlying group differences.

17. Why This Trial Matters Statistically

This trial is statistically informative because it distinguishes the feasibility-related outcome of program completion from behavioral outcomes such as abstinence, treatment use, and quit attempts. Those measures address different questions. Treating them as interchangeable would obscure what the primary endpoint actually captures and could make an uncertain pilot result seem more conclusive than it is.

The randomized parallel-group design gives a direct comparison between the Facebook-plus-referral package and referral alone. At the same time, the enrolled sample is small, and the primary interval is broad. This illustrates why a point estimate should be read together with its uncertainty: the direction of the point estimate is not enough to support a firm conclusion when plausible values span both sides of no difference.

The study also illustrates the statistical importance of denominators and outcome definitions. The primary outcome is a count of participants meeting a stated completion criterion, while secondary outcomes have distinct definitions and different denominators. The registry record does not explain the denominator variation or the missing-data approach. These details matter because an event count is interpretable only in relation to the participants included in that outcome calculation.

Finally, the planning figures show how assumptions about the effect size influence prospective sample requirements. Planning for smaller effects calls for more participants per arm under the stated assumptions. Those figures are illustrations based on the observed effect, not proof of what the original trial needed or what a future study should use. The trial therefore offers a useful case for separating observed results, uncertainty, and design planning.

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.

The enrolled sample of 61 participants limits the precision of the group comparisons. The primary interval is broad, and the secondary outcome denominators are smaller and vary across outcomes. The registry record does not explain those denominator differences, so their causes and implications cannot be determined from the posted results alone.

The study had no masking, according to the registry record. For participant-reported outcomes, awareness of group assignment can be relevant to how responses are given or collected; the record does not state whether outcome assessors were masked. The registry also does not report the randomization method or allocation concealment, which limits assessment of how assignment was implemented.

The intervention comparison includes more than a Facebook group: the Facebook group was added to treatment referral. The results therefore cannot isolate the Facebook component from the referral package, nor do they compare the package with no support. The primary endpoint is completion rather than abstinence, and the completion criteria are not described in detail beyond completing the program and all activities per protocol.

The original analysis plan, analysis population, missing-data methods, and multiplicity strategy are not reported. The registry lists no reported analyses for the secondary outcomes. These omissions constrain evaluation of whether the posted calculations followed a prespecified plan and how missing outcomes were handled. The results are consequently best interpreted as limited pilot evidence with incomplete analytic detail, not as a definitive estimate of the intervention's effects.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Connecting Alaska Native People to Quit Smoking — NCT03645941.
• Registry record last updated 2022-06-08; status last verified 2022-06.
• Results first posted 2022-06-08.
• 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, parallel-group, unmasked pilot trial enrolling 61 participants. It compares Quitline/Treatment Referral with Facebook+Quitline/Treatment Referral among Alaska Native smokers.

The primary endpoint is completion of the smoking-cessation program and all activities per protocol at the 6-month follow-up assessment. The posted counts are 16 of 30 in the referral group and 19 of 31 in the Facebook-plus-referral group. The risk-difference estimate is 0.080, with an interval from -0.168 to 0.327 and an unadjusted p-value of 0.53.

Three self-reported secondary outcomes are recorded at 6 months. Their denominators vary, and the registry record does not report a multiplicity strategy, missing-data methods, or the analysis population. No serious adverse events, other adverse events, or deaths are recorded in either group. The findings are descriptive and imprecise; the registry record does not provide enough analytic detail to support a definitive conclusion about group differences.