Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (NCT02769338), a non-randomized na study. The primary outcome is Effectiveness: Without-fail Care Rate.

2. Clinical Question

This is an implementation and effectiveness evaluation rather than a randomized comparison. Its central question concerns delivery of care processes, not a direct comparison of a drug or procedure. The program aimed to support teams in improving care for Veterans with transient ischemic attack or minor stroke, while electronic data were used to monitor care at intervention sites.

The registry names recurrent vascular events, the Group Organization score, quality improvement activities completed, and program satisfaction as secondary outcomes. These outcomes concern different aspects of the program and its context. The record does not report their numerical results or specify the precise scales or event definitions for all of them. The primary outcome is described as an eligible-patient measure derived from electronic medical record data; the actual number meeting the without-fail criteria is not reported in the registry record. Consequently, the registry description establishes the question and intended measurement, but does not by itself answer whether care-process performance differed between sites.

3. Trial Design

PREVENT is a completed, non-randomized, sequential study of a quality improvement program. The registry lists an enrollment of 2292 and identifies transient ischemic attack and stroke as the conditions. The recorded study dates run from 2016-06-01 to primary completion on 2020-06-01. The registry labels the phase as not applicable and masking as none.

The intervention was a quality improvement program. The arm descriptions distinguish sites receiving the program with external facilitation from non-intervention VA medical centers. External facilitation was intended to support implementation. The brief summary describes a program at 6 Veteran Health Administration Hospitals and says that investigators would evaluate implementation and effectiveness. For the primary measure, the record describes intervention sites and control sites during the active implementation period. It does not give the number of control sites in that description.

Because allocation was non-randomized, the groups were not formed by random assignment. The registry explicitly cautions that the arms are not a like-for-like control comparison. Differences between groups may therefore reflect differences in sites or patients as well as any contribution from the quality improvement program. The sequential model is recorded, but the registry record does not explain the sequence of implementation or provide enough detail to characterize its analytic implications.

The main endpoint was based on electronic medical record data and counted eligible Veterans who received all applicable guideline-concordant processes. The stated primary timeframe was over the course of one year of active implementation. The record gives patient and eligibility counts for the primary measure, but does not report the number who met the measure, an estimated rate, a between-group effect, or an uncertainty interval. It also lists five outcome measures and no analyses. Details of the statistical analysis plan, including adjustment for site-level structure or baseline differences, are not reported in the registry record.

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.

Baseline Period

Active Implementation Period

Analysis population for the primary outcome, as defined in the registry: During the active implementation period, there were N=189 patients at the intervention sites, 176 of whom were eligible for the without-fail measure; and there were N=968 patients at the control sites, 869 of whom were eligible for the without-fail measure.

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: There were 6 intervention sites and 36 control sites and two time periods (baseline and active implementation). Different patients were cared for at the sites during the two time periods. During baseline, there were N=162 PREVENT intervention patients and N=973 patients at control sites. During the active implementation period, there were N=189 patients at PREVENT intervention sites and N=968 at control sites.

6. Primary Endpoint

The registry lists the primary outcome as Effectiveness: Without-fail Care Rate, measured over Over the course of One Year active implementation.

The primary endpoint is the without-fail care rate: the proportion of eligible Veterans who received every guideline-concordant process of care applicable to them. It is based on electronic medical record data and is described for the active implementation period. The denominator is restricted to patients eligible for the measure, rather than all patients identified at the sites. The registry lists 176 eligible patients at intervention sites and 869 eligible patients at control sites.

A measure requiring all applicable processes can summarize whether a care pathway was completed consistently across its relevant components. In general, this kind of all-or-none outcome is straightforward to interpret as a patient-level indicator, but it does not show which individual care processes were or were not delivered. The registry does not provide component-level results or the number of eligible patients who achieved the all-process criterion.

The endpoint is relevant to a quality improvement program because it focuses on delivery of guideline-concordant care rather than only on downstream clinical events. However, the registry record does not provide the observed without-fail counts or rates, nor an effect estimate comparing the arms. The measure's intended use is clear; its observed performance and precision cannot be assessed from the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

What does the without-fail measure represent?

The primary endpoint is a binary patient-level measure: an eligible patient either received all applicable guideline-concordant processes or did not. The registry describes the reported quantity as a proportion, with patients eligible for the measure forming its denominator. This distinction matters because the denominator is not the full group of patients described at each set of sites. The record gives 176 eligible patients among 189 at intervention sites and 869 eligible patients among 968 at control sites. It does not give the corresponding counts who met the measure, so the rates cannot be recovered from the registry description.

In general, a binary endpoint reduces a set of observations to categories such as meeting or not meeting a defined criterion. That can make a care-process outcome easier to communicate, but an all-process criterion can conceal which elements drove a result. The registry does not report component-specific delivery or clarify how an inapplicable or undocumented process was handled. Those details would be needed to fully evaluate how the measure was operationalized.

How should an effect estimate be read?

In general, a comparison of proportions can be expressed as a difference in rates or as another contrast. The estimate gives the size and direction of the observed group contrast, while a confidence interval describes the range of values reasonably compatible with the data under the chosen model. A narrower interval indicates greater precision; a wider interval indicates more uncertainty. Neither an estimate nor its interval establishes that a difference was caused by the intervention, especially when groups were not randomized.

No primary effect estimate, confidence interval, or analysis result is reported in the registry record. Therefore, there is no numerical contrast to interpret for this trial from the registry information. The published primary description is about the endpoint and eligibility counts, not the observed outcome counts.

Why does non-randomized allocation matter?

In general, random assignment can balance measured and unmeasured characteristics across groups on average. Here, allocation is recorded as non-randomized, and the registry cautions that the arms are not a like-for-like control comparison. A difference in care-process rates, if reported, could reflect the program, pre-existing differences among medical centers, changes over time, or other influences. Adjustment can address measured differences under suitable assumptions, but it cannot automatically remove unmeasured confounding.

The registry identifies a sequential model, but does not describe the sequence or the model's specification. It does not report whether comparisons accounted for clustering of patients within sites, site-level characteristics, baseline outcomes, or implementation timing. Since the intervention is delivered through sites and teams, the way site structure is reflected in an analysis could be important. The statistical plan and any such adjustment are not reported in the registry record.

What do precision and planning calculations mean?

In general, a confidence interval is an estimate of statistical uncertainty around an effect, conditional on the data and method used. It is not a guarantee that the true effect lies within its endpoints, and it does not address design bias or measurement error. No interval for the primary outcome is reported in the registry record, so the precision of the outcome comparison cannot be assessed.

The stated sample-size illustration uses a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. It considers effects expressed as a fraction of the observed effect. For time-to-event outcomes, the illustration is described as a total number of events; for other outcomes, it is described as participants per arm. These are planning assumptions, not a report of the study's design rationale or actual statistical power. Sample-size requirements based on an observed effect are not observed power. The registry record does not report the trial's own sample-size justification, and the observed primary effect needed to interpret such an illustration is not reported.

In general, over-dispersion means that outcome variability is greater than assumed by a simple model. It can make standard errors too small if ignored, producing intervals that are too narrow and tests that are too optimistic. The primary outcome is identified as binary, but no dispersion estimate or modeling details are reported. It would not be appropriate to infer that over-dispersion was present or how it was handled.

What can secondary outcomes add?

The listed secondary outcomes address clinical events, organizational context, implementation activity, and satisfaction. In general, multiple outcomes can provide a broader account of an intervention, but testing many outcomes raises questions about multiplicity: the chance of at least one apparently notable result can increase when many comparisons are examined. Prespecified outcome hierarchy or multiplicity adjustment can help define how such results should be interpreted. Neither the analysis results nor any multiplicity strategy is reported in the registry record.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("QI With External Facilitation", "Control")
n      <- c(176, 869)
events <- c(95, 363)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  QI With External Facilitation  176  95  54.0  46.3  61.5  46.6  61.2  46.6  61.2
ARM  Control  869  363  41.8  38.5  45.1  38.5  45.1  38.5  45.1

11. Multiplicity, Missing Data and Analysis Populations

The registry lists five outcome measures, including the without-fail care rate and four secondary outcomes. It reports no analyses. The record does not identify which secondary outcomes were analyzed, provide their results, state whether comparisons were prespecified, or describe any adjustment for multiple testing. Consequently, the degree to which multiplicity was considered is not reported in the registry record.

In general, examining multiple outcomes creates more opportunities for chance findings. This does not make multiple-outcome research invalid, but interpretation benefits from knowing which outcomes were primary, which were secondary, whether analyses were prespecified, and how the family of comparisons was handled. The registry identifies a primary measure, but does not give the analysis plan needed to assess those issues.

Missing-data procedures are also not reported in the registry record. The primary endpoint was to be determined from electronic medical record data, but the record does not describe how missing documentation, incomplete records, or unavailable eligibility information were handled. It does not report the amount of missing outcome data or whether patients were excluded from analyses for any reason.

The analysis populations are not fully described. The registry gives the number of patients and eligible patients for the primary measure at intervention and control sites, but does not state whether these numbers represent all patients assessed, an analytic subset, or a particular inclusion rule beyond eligibility for the measure. It also does not provide analysis-specific denominators or results. These omissions prevent assessment of missingness, exclusions, and the exact population contributing to any effect estimate.

12. 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 adverse-event record lists the QI With External Facilitation group with 6 at risk for serious adverse events and 0 affected, and 6 at risk for other adverse events and 0 affected. For the Control group, it lists 36 at risk for serious adverse events and 0 affected, and 36 at risk for other adverse events and 0 affected. Deaths are listed as 0 in both groups. The registry provides no serious adverse-event terms.

These are the adverse-event figures recorded in the registry; they should not be treated as evidence that no adverse events occurred outside the recorded fields or observation captured by this entry. The at-risk values in the adverse-event record differ from the primary-outcome patient counts. The record does not explain the populations or reporting period behind these safety fields, or how they relate to the full study enrollment.

In general, a zero count means that no events are recorded in the specified category and reporting population. It does not establish that the underlying risk is zero, and it does not describe the precision of an event-rate estimate without fuller information about ascertainment and follow-up. The registry does not provide additional safety analyses, event definitions, or comparative estimates. These figures should therefore be read narrowly as the event counts posted in the record, not as a comprehensive safety conclusion.

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

The registry record establishes that PREVENT evaluated a quality improvement program intended to improve care for Veterans with transient ischemic attack or minor stroke. It defines the primary outcome as the proportion of eligible patients receiving all applicable guideline-concordant processes and reports the sizes of the eligible populations at intervention and control sites. It also lists secondary outcomes and adverse-event counts.

The record does not report the primary outcome counts, rates, an effect estimate, confidence interval, or analysis result. It therefore does not establish whether the without-fail rate differed between intervention and control sites, how large any difference was, or how precise an estimate might be. Absence of a posted result is not evidence of no difference. The secondary outcome results are likewise not reported in the registry record.

Even with outcome estimates, the non-randomized design would call for caution about causal interpretation. The registry explicitly states that the arms are not a like-for-like control comparison. The program may be associated with changes in care, but separating program effects from site differences, timing, and other factors depends on design and analysis details that are not reported in the registry record.

The primary measure is a care-process outcome, not a direct measure of every aspect of patient health. It can describe whether specified processes were delivered to eligible patients, but it cannot on its own show which components changed or explain why. The record also does not report the precise operational details needed to assess documentation and missing-data handling.

Accordingly, the registry supports a description of the study's purpose, design labels, outcome definition, and certain population and safety counts. It does not support a numerical conclusion about effectiveness or a broad clinical conclusion. The interpretation of posted data should remain limited to the outcomes and populations actually reported.

14. Why This Trial Matters Statistically

This study is statistically notable because it evaluates a site-based quality improvement program in routine health-care settings, rather than describing a randomized treatment comparison. Such evaluations address a practical question: whether an implementation effort is associated with changes in care processes across participating services. They also make design and analysis especially important, because sites and patients may differ before implementation.

The without-fail outcome combines multiple applicable care processes into a patient-level measure. That approach can provide a clear summary of complete process delivery, while also motivating attention to the denominator, eligibility rules, and underlying components. The registry reports eligible-patient counts but not the number meeting the all-process criterion, so the principal quantity of interest is not available for statistical interpretation.

The registry's explicit warning about non-like-for-like groups is important. It points readers toward the distinction between observing a group difference and attributing that difference to an intervention. The sequential design label and the implementation setting raise questions about timing and site structure, but the registry does not give the analytic details needed to resolve them.

Finally, the gap between a clear endpoint definition and absent analysis results illustrates why registration records serve multiple purposes. They can identify intended outcomes, populations, and design features, but a record without posted outcome estimates cannot establish the size or precision of an effect. A disciplined reading separates the study's rationale and measurement plan from evidence about its observed outcomes.

15. 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 principal limitation for interpreting the posted record is that it does not include the observed primary outcome counts or rates, a comparative effect estimate, a confidence interval, or a reported analysis. The primary endpoint is defined, and eligibility counts are stated, but the outcome itself cannot be evaluated. Numerical results for the listed secondary outcomes are also not reported in the registry record.

The non-randomized allocation limits the strength of causal conclusions. The registry itself warns that the intervention and control arms are not a like-for-like comparison. It does not report baseline characteristics, baseline care-process rates, or adjusted estimates that would help readers assess group comparability. The sequential model is named, but details of sequence and timing are not reported.

Additional interpretive details are absent: the statistical analysis plan, handling of site clustering, adjustment for confounding, missing-data procedures, analysis populations, and multiplicity strategy are not reported in the registry record. The endpoint is derived from electronic medical record data, but documentation rules and component-level results are not given. These omissions make it difficult to assess measurement completeness or the assumptions behind a potential comparison.

The relationship between the overall enrollment of 2292 and the smaller patient populations described for the primary measure is not explained in the record. The adverse-event at-risk counts also differ from the primary-outcome population counts, without a stated explanation of the reporting populations. These figures should be read in their separate contexts rather than reconciled through assumptions.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms — NCT02769338.
• Registry record last updated 2023-12-13; status last verified 2023-03.
• Results first posted 2023-12-13.
• 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.

19. Record Summary

PREVENT is a completed, non-randomized, sequential evaluation of a quality improvement program for Veterans with transient ischemic attack or minor stroke. The registry lists an enrollment of 2292, dates from 2016-06-01 to 2020-06-01 for study start and primary completion, and no masking. The intervention combined a quality improvement program with external facilitation at intervention sites; control sites were described as non-intervention VA medical centers.

The primary outcome was the without-fail care rate, defined as the proportion of eligible patients receiving all applicable guideline-concordant processes, based on electronic medical record data. The record reports 176 eligible patients at intervention sites and 869 at control sites. It does not report outcome counts, rates, effect estimates, or analyses. Four secondary outcomes are listed without numerical results. The registry cautions that the groups are not a like-for-like control comparison.