DEFINE AFib (Atrial Fibrillation): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for DEFINE AFib (Atrial Fibrillation) (NCT04926857), a registered phase not stated study. The primary outcome is Healthcare Utilization Where AF Was a Reason or a Suspected Reason for the Healthcare Interaction..

2. Clinical Question

The registry describes confirmed healthcare visits in inpatient or outpatient hospitals, clinics or offices, emergency departments, and other care locations, including remote visits. The prediction setup uses measurements from the first 30 days of rolling 60 day blocks to predict whether confirmed healthcare utilization occurred in the trailing 30 days. This is a question about forecasting healthcare use from recorded device measurements; it is not a question about whether a treatment changes outcomes.

3. Trial Design

DEFINE AFib is described as a prospective, observational, post-market clinical study administered through the Medtronic Discovery app platform. Its listed intervention type is non-interventional. The registry record does not describe random assignment, treatment arms, or a like-for-like control group. Consequently, the study design is centered on collecting device measurements and participant-reported information, then assessing a predictive model.

The study summary describes screening through the app, app-based informed consent for eligible participants, and health-focused and quality-of-life surveys delivered at variable timepoints. Healthcare interactions are identified using administered surveys. Participants also receive a summary of their implantable cardiac monitor data through the app. The summary describes follow-up up to 5 years or until the end of the device's service life. The primary outcome timeframe separately states through study completion, with 2 years of enrollment and up to 2.6 years of follow-up. These descriptions are not interchangeable, and the registry record does not explain their relationship.

The record lists enrollment of 973 and gives a study start date of 2021-06-21 and primary completion date of 2024-01-25. Its status is TERMINATED. The study summary describes an intended enrollment of approximately 5,000, so the listed enrollment and the approximate enrollment described in the summary differ. The registry record does not explain that difference or give a reason for termination.

For model development, the description says 70% of patients with adequate data were used for training and the remaining 30% for validation. The record does not report how many patients met the adequate-data criterion or how many were included in each set. It also does not report the detailed model specification or the procedures used to select measurements.

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

Reasons for not completing this period:

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: Due to eligibility survey responses permanently missing for 3 subjects, 970 of the 973 subject enrollments are included in all analysis.

6. Primary Endpoint

The registry lists the primary outcome as Healthcare Utilization Where AF Was a Reason or a Suspected Reason for the Healthcare Interaction., measured over Through study completion (2 years of enrollment, up to 2.6 years of follow-up).

The primary outcome is intended to capture how well measurements from an implantable cardiac monitor predict AF-related healthcare utilization. The described utilization outcome is a confirmed healthcare interaction in which atrial fibrillation was a reason or suspected reason for the visit. It includes inpatient and outpatient hospital care, clinic or office visits, emergency department care, and other locations, including remote visits.

The registry description says that measurements in the first 30 days of rolling 60 day blocks predict whether confirmed healthcare utilization occurred in the trailing 30 days. This makes the endpoint a predictive-performance question: do earlier device measurements distinguish periods followed by an AF-related healthcare interaction from periods without one? The description says performance was to be assessed using sensitivity, specificity, and other confusion-matrix measures, balancing sensitivity and specificity, as well as AUROC.

There is an ambiguity in how the endpoint is registered. Its title refers to healthcare utilization, its unit is listed as “Proportion,” and its parameter is “NUMBER,” while the description states that the outcome measure entered is AUROC. The record does not clarify which measure is the primary reported endpoint. No endpoint result or analysis is reported in the registry record, so predictive performance cannot be characterized from the posted information.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The statistical aim is prediction rather than estimation of a treatment effect. A predictive model uses observed characteristics—in this case, summary and episodic measurements from an implantable cardiac monitor—to estimate whether a future outcome will occur. The target outcome is confirmed healthcare utilization for which atrial fibrillation was a reason or suspected reason. Because no treatment is assigned and no randomized comparator is described, the principal question is how well measurements classify future healthcare-use periods, not whether one intervention outperforms another.

Training and validation

The registry describes training the model with 70% of patients who had adequate data and assessing it in the remaining 30%. Training is the process of fitting a model to data. Validation assesses its performance on data set aside from that fitting process. This separation can give a more informative assessment than evaluating a model only on the data used to build it, because performance on training data may be optimistic. The description does not state how the split was carried out, whether it was stratified, how patients with incomplete data were handled, or whether any additional validation was performed. Those details are not reported in the registry record.

The described prediction windows are rolling 60 day blocks. Within each block, measurements from the first 30 days are used to predict whether confirmed healthcare utilization occurs in the trailing 30 days. In general, a rolling-window approach repeatedly aligns a predictor period with a later outcome period. It can make use of measurements over time, but interpretation depends on how overlapping windows and repeated observations from the same participant are handled. The registry record does not report those details, so the independence of the evaluated observations cannot be assessed from the description alone.

Discrimination and classification

The description names sensitivity and specificity, which summarize different aspects of classification. Sensitivity describes how often a model identifies outcome-positive periods among periods when the outcome occurs. Specificity describes how often it identifies outcome-negative periods among periods when the outcome does not occur. A model can make a different trade-off between these quantities depending on the threshold used to classify a prediction. The registry says performance was assessed while balancing sensitivity and specificity, but the threshold-selection procedure and the resulting estimates are not reported.

AUROC, or area under the receiver operating characteristic curve, summarizes discrimination across classification thresholds. In general, discrimination concerns how well a model separates observations with the outcome from observations without it. AUROC does not by itself show whether predicted probabilities are well calibrated, whether a particular threshold is useful, or whether use of the model improves decisions. Those questions require additional information and analyses. No AUROC result is reported in the registry record.

Endpoint definition and precision

A confidence interval describes uncertainty around an estimate under the assumptions of the analysis. A narrower interval generally indicates greater statistical precision, while a wider interval indicates more uncertainty. The primary outcome lists a 95% Confidence Interval as its dispersion measure, but no estimate or interval is reported. It is therefore not possible to assess the precision of the intended outcome. In addition, the outcome description uses AUROC while the registered unit is “Proportion” and the parameter is “NUMBER.” This mismatch leaves uncertainty about the exact endpoint and its scale.

The description refers to confirmed interactions identified through surveys. The registry does not report a detailed outcome-adjudication process, rules for assigning a visit to a particular window, or how uncertain reports were classified. Such choices can affect whether an interaction is counted as AF-related. The record also does not report how repeated interactions or multiple qualifying visits within a prediction window were treated.

Planning calculations

Sample-size illustrations are planning exercises, not observed power. The stated illustration assumptions use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; the effect to detect is described as a fraction of the observed effect. These assumptions do not describe the observational study's design: the registry does not describe two assigned arms or equal allocation. A planning calculation based on those assumptions should therefore not be read as evidence that this study had a particular probability of detecting a result. The registry record does not report the study's own sample-size justification.

For a predictive-model study, sample size and precision depend on the amount and distribution of usable data, outcome frequency, the number and structure of predictors, and the validation approach. These are general considerations, not details reported for DEFINE AFib. The record gives enrollment of 973 but does not report the number with adequate data, the number of outcome events, or performance estimates with confidence intervals. Without those results, neither predictive accuracy nor its precision can be evaluated.

10. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a statistical analysis plan addressing multiplicity, missing data, or analysis populations. It describes one primary outcome measure and names several performance measures, including sensitivity, specificity, and AUROC, but does not state which were designated as primary or how multiple evaluations would be interpreted. In general, multiplicity arises when several outcomes, models, subgroups, or analytic choices are examined; without a prespecified approach, the chance of highlighting an apparently favorable result can increase. The record does not say whether any adjustment or prioritization was planned.

The model was to be trained using patients with adequate data, but “adequate data” is not defined in the registry description. The number excluded for incomplete or insufficient information, the reasons for missingness, and the handling of missing monitor measurements or survey responses are not reported in the registry record. In general, missingness can affect both which participants contribute to an analysis and how representative the analyzed group is. The record does not state whether imputation, complete-case analysis, or another method was used.

The training and validation sets are described as portions of patients with adequate data, but the sizes and characteristics of those populations are not reported. No analysis population is specified for the primary outcome, and no subgroup or sensitivity-analysis plan is reported. The registry record also does not explain whether repeated windows from a participant were analyzed together or separately. These omissions limit assessment of the analysis population, the potential for selection effects, and the robustness of any predictive-performance estimate.

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

What the registry record establishes is that DEFINE AFib was designed as a prospective observational study to examine whether implantable cardiac monitor measurements could predict AF-related healthcare interactions. It describes an app-based process for collecting survey information, a training and validation split, and rolling prediction windows. It also lists enrollment of 973 and a TERMINATED status. These registry entries describe the study's design and registry status; they are not results showing that the model achieved a particular level of performance.

No analysis results are reported. Consequently, the record does not establish the model's sensitivity, specificity, AUROC, calibration, or ability to predict healthcare utilization. It also does not establish whether the model was completed or validated as intended. The endpoint wording is ambiguous about whether the primary measure is a proportion or AUROC, further limiting interpretation in the absence of results.

The study is observational, so its purpose differs from comparing assigned treatments. Predictions from device data would not by themselves show that acting on a prediction improves health outcomes or changes healthcare use. General predictive-model concepts also matter: discrimination describes separation of outcome-positive and outcome-negative observations, while calibration concerns agreement between predicted and observed risks. One cannot be substituted for the other, and neither is reported in the registry record.

The adverse-event record lists 9 deaths among enrolled patients, alongside zero counts in the serious and other event categories and zero at-risk counts for those categories. The record does not state the causes, circumstances, or relationship of the deaths to the study. These entries should not be interpreted as a causal safety assessment, nor as evidence about model performance.

The registry status and enrollment are not enough to explain why the study was terminated or whether all planned work was completed. The reason is not reported in the registry record. The posted information therefore supports a description of the intended predictive study and its recorded status, but does not support conclusions about predictive success, clinical usefulness, or treatment benefit.

12. Why This Trial Matters Statistically

This study is statistically notable because it frames device measurements as predictors of later healthcare interactions rather than as outcomes of an assigned treatment. That distinction changes the central analytic task: the relevant evidence would be validated prediction performance, not a treatment-versus-control contrast. The registry describes a patient-level training and validation split and rolling windows that align earlier measurements with subsequent healthcare use.

Prediction studies require careful attention to the definition of the outcome and to how performance is evaluated. Here, the outcome concerns confirmed interactions for which AF was a reason or suspected reason, as identified through surveys. The record also describes multiple classification measures and AUROC. Yet the registered title, unit, and parameter do not align clearly with the description's statement that the outcome measure is AUROC. This uncertainty illustrates why endpoint definitions and reporting labels need to be coherent for readers to assess what an estimate means.

Validation is important because a model's apparent performance on the data used to construct it may not reflect its performance on separate data. The stated split acknowledges that issue, although the record does not report the actual validation results or enough detail to assess the split and handling of repeated windows. Without those results, the statistical objective cannot be judged as achieved or not achieved.

Finally, the record highlights the difference between study registration and study results. It provides a design description, enrollment, dates, outcome intent, and termination status, but no analyses. That distinction is essential when reading predictive-model registrations: a planned method is not a performance estimate, and a study status is not an explanation of its findings.

13. 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 this trial is that no analysis results are reported in the registry record. The model's predictive performance, uncertainty, and validation findings are therefore unavailable. The reason for the TERMINATED status is also not reported, so it cannot be determined from the record whether termination affected recruitment, follow-up, model development, or analysis.

The enrollment listed is 973, while the study summary describes an intended enrollment of approximately 5,000. The record does not explain this difference. It also does not report how many enrolled participants had adequate data for model training, how many were included in validation, or how many contributed outcome information. The listed enrollment alone cannot show the size or completeness of the analytic data set.

The primary outcome has a labeling inconsistency: the title concerns healthcare utilization and the unit is “Proportion,” while the description identifies AUROC as the outcome measure. No clarification is reported. The record also does not provide the detailed model specification, feature-selection process, threshold choice, missing-data method, or treatment of repeated prediction windows. These details would be needed to assess reproducibility and the risk of optimistic performance estimates.

Healthcare interactions were to be identified using administered surveys, but the registry does not describe the validation or adjudication of survey reports. It does not report how AF-related attribution was determined or how multiple interactions were handled. The study summary and outcome timeframe also describe follow-up differently: up to 5 years or the end of device service life in the summary, versus through study completion with 2 years of enrollment and up to 2.6 years of follow-up for the outcome. The record does not explain how these timeframes relate.

14. Related Tutorials

15. Related Statistical Calculators

16. Sources

• ClinicalTrials.gov: DEFINE AFib (Atrial Fibrillation) — NCT04926857.
• Registry record last updated 2025-08-01; status last verified 2025-07.
• Results first posted 2025-08-01.
• 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.

17. Record Summary

DEFINE AFib (NCT04926857) is listed as a prospective, observational, post-market study sponsored by Medtronic Cardiac Rhythm and Heart Failure. It concerns atrial fibrillation and measurements from Reveal LINQ, LINQ II, or eligible future LINQ implantable cardiac monitors. Enrollment is listed as 973. The study started on 2021-06-21, has a primary completion date of 2024-01-25, and is marked TERMINATED.

The primary objective was to evaluate whether monitor measurements could predict confirmed healthcare interactions for which AF was a reason or suspected reason. The description names a training and validation split, rolling 60 day blocks, sensitivity, specificity, and AUROC. The registered outcome labeling is not fully consistent with the description, and no analyses are reported. The reason for termination is not reported in the registry record.

The adverse-event record lists 9 deaths among Enrolled Patients; causes and relationship to the study are not reported. Overall, the registry describes the intended design and objective but does not report the model's performance or the reason the study ended.