Home-based Kidney Care in Native Americans of New Mexico (HBKC) - Enhancement: COVID-19 Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Home-based Kidney Care in Native Americans of New Mexico (HBKC) - Enhancement: COVID-19 Study (NCT04520191), a registered phase not stated study. The primary outcome is Number of Participants With Problems in Their Health Care Due to COVID-19 Related Isolation.

2. Clinical Question

The question is descriptive: it concerns whether participants experienced specified health-care problems during the period, rather than whether one assigned intervention performed better than another. The study summary also identifies symptoms of COVID-19 and changes in medication adherence, physical activity, diet, smoking, and alcohol use as additional domains of interest. These domains give context to the intended tracking activity, but the registry record does not report results for them.

The registry lists enrollment of 309 and a single primary outcome measure. Enrollment describes the study record; it does not establish how many participants contributed data to the primary outcome or how many had a reported problem. The primary outcome population is not described in the record. Accordingly, the central question can be stated, but its observed answer cannot be determined from the registry record.

3. Trial Design

The registry describes a completed, single-group survey associated with the Home-based Kidney Care study. Its title identifies Native Americans of New Mexico, and its summary says the activity aimed to track the impact of the COVID-19 epidemic on participants with diabetes and chronic kidney disease. The sponsor is the University of New Mexico. The registry lists enrollment of 309, a start date of 2021-01-04, primary completion on 2024-08-01, and status as completed.

The COVID-19-related activity modified the original study protocol by expanding the data collected. The planned domains included symptoms of COVID-19 disease, access to health care, and health-related behaviors, including medication adherence, physical activity, dietary behaviors, smoking, and alcohol use. The primary outcome concerns participants with problems in their health care due to COVID-19-related isolation, with a six-month timeframe. Its description names disruptions to normal health-care check-ups, transportation, economic status, and access to food and water.

This is not described as a randomized comparison. The registry gives no separate control group, and allocation is not stated. That design matters for interpretation: a count from a single group can describe reported experiences, but it cannot by itself estimate a contrast between assigned groups. The record lists one outcome measure and no analyses. It does not report the number assessed for the primary outcome, the outcome count, or a statistical analysis plan.

The listed enrollment should not be read as the number with complete endpoint data. Nor does the completed status establish that every intended measurement was obtained or analyzed. The registry record does not report further detail about recruitment, survey administration, participant follow-up, or how the COVID-19-related addition was integrated with the original study beyond the protocol modification described in its summary.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Problems in Their Health Care Due to COVID-19 Related Isolation, measured over six months.

The primary endpoint is the number of participants with problems in their health care due to COVID-19-related isolation. It is recorded as a count of participants and has a six-month timeframe. The endpoint description identifies several kinds of disruption: normal health-care check-ups, transportation, economic status, and access to food and water. The registry record does not report a more detailed operational definition of which answers qualify as a problem or how responses across these areas are combined.

Using a participant count can make the outcome directly interpretable as the number of people identified as having a problem. It can be useful for describing the frequency of reported disruptions in the study group. However, a count alone does not show the proportion affected unless the relevant denominator is also known. The record does not report the number assessed for this endpoint, the endpoint count, or a percentage. Enrollment is not a substitute for an endpoint denominator because the registry does not state how many enrolled participants contributed outcome data.

The outcome is intended to document health-care disruption during the specified timeframe, not to measure a treatment effect. The registry record contains no reported primary-outcome result, so it does not establish how many participants experienced these problems or how precisely that count was estimated.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the primary measure as a participant count and lists its outcome type as binary. In this context, the underlying participant-level classification can be understood generally as whether a person did or did not meet the outcome definition. The reported aggregate measure would count participants classified as having a problem. The record does not give the operational rules used to turn survey responses into that classification, and it does not provide the resulting count.

What does a participant count describe?

General statistical explanation: a count describes the number of observations meeting a stated criterion. To judge how common the criterion is in a study group, readers also need an appropriate denominator and, often, a proportion. Counts and proportions answer related but different questions: a count gives the number identified, while a proportion places that number in relation to the population assessed. Neither can be reconstructed when the underlying result and denominator are absent. Enrollment alone does not establish how many participants posted usable data for this endpoint.

The outcome's six-month timeframe indicates the period to which the measure refers. The registry record does not explain whether the survey asked participants to recall the entire period, whether information was collected at one or multiple occasions, or how the timing of responses was handled. Those details can affect how an outcome is interpreted, but they should not be inferred from the stated timeframe.

What would uncertainty measures add?

General statistical explanation: a confidence interval describes a range of values compatible with the observed data under a specified statistical procedure and its assumptions. Its width reflects precision; a wider interval generally indicates greater uncertainty. A point estimate without an uncertainty measure can be hard to distinguish from a noisy estimate, especially when the number of observations contributing to it is unclear. No primary-outcome estimate or confidence interval is reported in the registry record, so neither the size nor the precision of an observed result can be evaluated.

For a binary participant-level outcome, analyses may describe a count or proportion, or use a model suited to the study question. The appropriate method depends on the data structure, outcome definition, and intended estimand. This record reports no analyses and does not report a statistical analysis plan. It is therefore not possible to say which method, if any, was used for the primary outcome. The general possibilities should not be mistaken for methods documented in this study.

Why does the single-group design matter?

General statistical explanation: a comparison requires clearly defined groups and a contrast that matches the question. Random assignment can support causal comparisons when the design and analysis are appropriate, but this registry record does not describe randomized allocation or a separate comparator. The primary question is framed as documenting the number of participants with disruptions, not estimating a difference between study arms. A descriptive result from one group would not by itself show that isolation caused a disruption or quantify how outcomes would differ under another condition.

Similarly, a count does not explain why a disruption occurred. The outcome description names check-ups, transportation, economic status, and access to food and water, while the study summary lists additional domains such as medication adherence and physical activity. The record does not report whether these were combined, analyzed separately, or related to one another. No associations or explanatory model should be inferred.

How should planning calculations be read?

The registry's stated sample-size assumptions describe a planning illustration based on an observed effect: two-sided significance level 0.05, equal allocation between two arms, normal approximation, and a target effect expressed as a fraction of the observed effect. The assumptions also distinguish participants per arm for non-time-to-event outcomes from a total event count for time-to-event calculations. These are planning assumptions, not evidence that this single-group survey used equal allocation or a two-arm design. The record does not report a study-specific design justification, and the listed planning illustration is not observed power. Since no primary-outcome result is reported, the observed effect on which such an illustration is based cannot be assessed from the registry record.

General statistical explanation: power is a design-stage probability defined in relation to an assumed effect, variability, sample size, and statistical procedure. A retrospective calculation using an observed effect is not a substitute for a prespecified design justification and should not be presented as the probability that a finding is true. Planning sample sizes are illustrations of assumptions, not observed outcomes. Here, the registry record does not provide an endpoint analysis with which to evaluate an effect estimate or its uncertainty.

Over-dispersion is a general concern in count data when variation exceeds what a chosen count model assumes. It can make model-based standard errors too small if ignored. This endpoint, however, is defined as a count of participants with a binary outcome, and the registry record reports no count model or dispersion estimate. Over-dispersion should therefore be understood as a general modeling issue, not as a documented feature of this study's analysis.

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("COVID Survey")
n      <- c(309)
events <- c(155)
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  COVID Survey  309  155  50.2  44.4  55.9  44.6  55.7  44.6  55.7

11. Multiplicity, Missing Data and Analysis Populations

The registry lists one outcome measure and no analyses. It does not report a multiplicity procedure, such as a strategy for controlling false-positive findings across multiple statistical tests. The study summary describes several additional areas of data collection, including symptoms, access to health care, and health-related behaviors, but it does not say whether these domains were analyzed as outcomes or how any testing across them was handled. Without reported analyses, the impact of multiplicity cannot be evaluated.

Missing-data methods are also not reported in the registry record. It does not state how many participants had complete responses for the primary endpoint, whether any responses were missing, how missing answers were handled, or whether sensitivity analyses were conducted. These details matter because an endpoint count based only on available responses may not describe everyone enrolled, particularly if data availability differs among participants. No such pattern can be assessed from the record.

The primary outcome population is not specified, and the record does not report an analysis population. Enrollment of 309 does not establish the number included in the endpoint analysis. The registry also gives no information about exclusions, survey completion, or the handling of participants with incomplete follow-up. As a result, the relationship between enrollment, outcome availability, and any analyzed population is not reported in the registry record.

General statistical explanation: multiplicity concerns arise when several hypotheses or outcomes are examined, while missing-data concerns arise when some measurements are unavailable. Both can affect the interpretation of estimates and tests, but their consequences depend on the analysis and the missingness process. Neither can be resolved by assuming a method that the registry does not document.

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 5% reporting threshold.

The registry's adverse-event summary is for a single-group survey. It lists 309 participants at risk in the serious-event field and 309 at risk in the other-event field; it reports zero affected in each field and zero deaths. These are the figures recorded for the adverse-event summary, not results for the primary health-care-disruption outcome. The two at-risk entries are separate fields and should not be added together.

The record lists no serious adverse-event terms. A zero in the reported affected count means that the registry summary records zero in that field; it does not describe how adverse events were solicited, defined, monitored, or verified. The record does not report an adverse-event follow-up timeframe or additional detail about ascertainment. It also does not establish whether all enrolled participants contributed to adverse-event reporting.

General statistical explanation: safety counts are most informative when the observation period, event definitions, and population at risk are clear. A reported zero is not proof that an event is impossible or that every event would necessarily have been detected. Here, the posted adverse-event figures should be read narrowly as registry-reported counts, not as evidence about the primary outcome or a comparison of safety between groups.

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

The registry record identifies a survey intended to document COVID-19-related disruption in health care among participants with diabetes and chronic kidney disease. Its primary question concerns the number of participants with problems during a six-month timeframe. The record also states that data collection was expanded to cover symptoms, access to health care, and health-related behaviors. These statements describe the study's purpose and scope.

They do not provide the study's primary result. The outcome count, denominator, proportion, and uncertainty are not reported in the registry record, and no analyses are listed. Therefore, the record does not establish how many participants experienced a problem, how frequent such problems were among those assessed, or how precisely any estimate was measured. The completed status and enrollment figure do not fill in these missing results.

The single-group survey should not be interpreted as a randomized comparison. The record does not report a separate comparator, and allocation is not stated. A descriptive survey could characterize reported experiences among respondents, but it would not alone show that COVID-19-related isolation caused those experiences or that one approach to care was better than another. No such causal or comparative conclusion is supported by the information reported.

The safety summary separately records zero affected in its serious-event and other-event fields, and zero deaths. Those figures do not answer the primary question about health-care disruption. They also do not provide information about how the survey's primary outcome was measured or how complete the outcome data were.

General statistical explanation: an estimate is most useful when readers can identify the population it represents, the measurement period, the denominator, and the uncertainty around it. The registry gives a timeframe for the primary measure but does not report the other information needed to interpret its magnitude. The appropriate conclusion is therefore limited: the registry documents the study aim and design features, but the reported record does not supply an analyzable primary-outcome result.

14. Why This Trial Matters Statistically

This study addresses a practical measurement question: whether participants in a kidney-care study experienced disruptions in health care during a period associated with the COVID-19 epidemic. The outcome description reaches beyond clinical appointments to include transportation, economic status, and access to food and water. That breadth reflects the study summary's interest in health-care access and health-related behavior, while also making precise outcome definitions important for interpretation.

Statistically, the record illustrates why a stated research question and a reported result are different things. It identifies a participant-count endpoint and a six-month timeframe, but it does not report the count, denominator, or analysis. Without those elements, readers cannot judge the observed burden or the precision of an estimate. Enrollment alone cannot supply the missing denominator.

The single-group design is also central to the statistical reading. A descriptive survey can address how many participants reported a specified problem, but a comparison or causal question requires a suitable contrast and corresponding design and analysis. The registry does not report a comparator or randomized allocation. Keeping those questions separate prevents a descriptive aim from being interpreted as an estimate of treatment effect or causation.

Finally, the record's planning assumptions show why planning calculations must be distinguished from observed evidence. The stated assumptions refer to equal allocation between two arms, whereas the study is described as a single-group survey. Such calculations are planning illustrations, not evidence of the design actually used or of observed power. Clear reporting of the endpoint definition, analyzed population, missingness, and results would be needed to connect the research question to an interpretable estimate. The absence of these details limits what can be learned statistically from the registry record.

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 interpretation is that the registry record does not report the primary-outcome result or any analyses. Although it lists one outcome measure, it does not provide the count of participants with problems, the number assessed, a percentage, or an uncertainty estimate. The primary outcome population is not specified. Enrollment of 309 cannot be assumed to equal the number contributing data.

The outcome description identifies several types of disruption but does not report detailed criteria for classifying a participant as having a problem. The record gives a six-month timeframe without describing survey timing, recall procedures, or whether data were collected once or repeatedly. These omissions make it difficult to determine exactly what the endpoint represents in practice.

The single-group design is not a like-for-like control comparison. Allocation is not stated, and no separate comparator is reported. The study can be understood as a survey intended to document experiences, but the registry does not support comparative or causal interpretation. The summary identifies Native Americans of New Mexico in the study title and participants with diabetes and CKD, but the endpoint's analysis population and the extent of outcome availability are not reported.

Missing-data procedures, analysis populations, and multiplicity handling are not described. The record also does not report whether or how the additional data-collection domains were analyzed. These are limits on what can be assessed from the registry record; they do not establish that a particular problem occurred. More detailed outcome reporting would be needed to evaluate completeness, representativeness, and precision.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Home-based Kidney Care in Native Americans of New Mexico (HBKC) - Enhancement: COVID-19 Study — NCT04520191.
• Registry record last updated 2025-03-04; status last verified 2025-02.
• Results first posted 2025-03-04.
• 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

The registry record describes a completed COVID-19-related addition to the Home-based Kidney Care study, focused on tracking health and health-care disruption among participants with diabetes and chronic kidney disease. The study title identifies Native Americans of New Mexico. The sponsor is the University of New Mexico; enrollment is listed as 309, with a start date of 2021-01-04 and primary completion on 2024-08-01.

The primary measure is a count of participants with health-care problems due to COVID-19-related isolation during a six-month timeframe. Its description includes disruptions to check-ups, transportation, economic status, and access to food and water. The registry reports one outcome measure and no analyses; it does not report the primary result, denominator, or analysis population.

The design is described as a single-group survey, with no separate comparator and allocation not stated. The adverse-event summary records zero affected in its serious and other event fields and zero deaths. These safety counts do not supply the missing primary-outcome result.