Changes in the Risk Factors of Coronary Heart Disease Observed After Scaling and Root Planing: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Changes in the Risk Factors of Coronary Heart Disease Observed After Scaling and Root Planing (NCT02417376), a randomized na study. The primary outcome is Change From Baseline in C-Reactive Protein Level at 6 Months.

2. Clinical Question

The trial addresses a biomarker question rather than a direct comparison of coronary events or other clinical cardiovascular outcomes. C-reactive protein is one of the systemic risk markers considered in the record. The primary endpoint is the change in its level from baseline to 6 months, compared between participants assigned to periodontal treatment and participants assigned to no periodontal intervention.

The record also lists changes in C-reactive protein at earlier follow-up and changes in lipid and white blood cell profiles. These are secondary outcomes, not replacements for the designated primary endpoint. The trial was randomized, with an experimental group and a control group, and the listed enrollment was 70. Demographic characteristics, baseline distributions of other clinical factors, and details about how participants were recruited are not reported in the registry record.

3. Trial Design

The registry record describes a randomized, single-masked, parallel-group trial. Participants were assigned to either scaling and root planing or no periodontal intervention. The listed enrollment was 70, with 35 participants in each arm in the posted primary-outcome results. The record does not specify which individuals were masked or how masking was maintained. It also does not report the method used to generate the random sequence or how treatment assignments were concealed.

The experimental intervention used a piezoelectric ultrasonic scaler and Gracey curettes to remove supra- and subgingival calculus. The record describes two appointments, each lasting 45 to 60 min. The control arm was described as receiving no periodontal intervention in any form. Other co-interventions, restrictions on usual care, and adherence monitoring are not reported in the registry record.

The primary endpoint was change from baseline in high-sensitivity C-reactive protein at 6 months, assessed quantitatively by immunoturbidimetric analysis. The record lists secondary assessments of C-reactive protein, lipid profile, and white blood cell profile at earlier or additional follow-up times. The trial status is completed. The listed start was 2013-05 and the primary completion was 2014-10. The sponsor is Government College of Dentistry, Indore.

Further design details that would help assess implementation are not reported in the registry record. These include the original sample-size justification, the definition of the analysis population, the handling of participants who did not complete follow-up, and any interim-analysis plan. The record also does not give enough information to determine whether the statistical analysis followed a prespecified protocol. The posted results therefore support a reading of the reported group summaries and their unadjusted comparisons, but not a reconstruction of every design or analysis decision.

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

Analysis population for the primary outcome, as defined in the registry: All patients suffered from CHD and Periodontitis both.

5. Baseline Characteristics

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

Population: All are CHD patients - never smoker, without any other systemic disease

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in C-Reactive Protein Level at 6 Months, measured over Baseline and 6 months.

The primary endpoint is change from baseline in high-sensitivity C-reactive protein at 6 months. C-reactive protein is a continuous laboratory measure, and the record reports the outcome in mg/L. The measure was assessed quantitatively by immunoturbidimetric analysis. The posted arm results are means with standard deviations, which describe the average change and the spread of individual values around that average.

Using change from baseline focuses the endpoint on how the measured level differs from its starting value over follow-up, rather than reporting only a measurement at the final visit. Comparing mean changes between randomized groups can describe whether their average trajectories differed. This is a general statistical rationale for a change score; the registry record does not state why this endpoint or the 6-month time point was selected, or whether an analysis adjusting for baseline values was planned.

The endpoint is a systemic biomarker, not a direct measure of a coronary event or a patient-reported clinical outcome. The record does not specify a clinically important difference for C-reactive protein, nor does it explain how to interpret a positive versus negative change in relation to clinical benefit. Consequently, the posted mean difference describes the numerical contrast in change scores but does not, on its own, establish the clinical importance or direction of benefit.

7. Results Posted in the Registry

• Experimental: mean 6.30 versus 4.94 on control; difference 1.36 (95% CI -1.22 to 3.94), standardized effect d = 0.25; z-test p = 0.302.

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.

Change From Baseline in C-Reactive Protein Level at 1 Month

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental: mean 6.21 versus 4.31 on control; difference 1.90 (95% CI 0.87 to 2.93), standardized effect d = 0.87; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Experimental than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in C-Reactive Protein Level at 3 Month

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental: mean 6.22 versus 4.09 on control; difference 2.13 (95% CI 0.78 to 3.48), standardized effect d = 0.74; z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Experimental than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Lipid Profile at 1 Month

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Experimental: mean 35.67 versus 25.20 on control; difference 10.47 (95% CI 2.98 to 17.96), standardized effect d = 0.65; z-test p = 0.006.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Experimental than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry record lists secondary outcomes covering C-reactive protein, lipid profile, and white blood cell profile at several follow-up times. Numerical comparisons are posted for a subset of those secondary outcomes. Across that posted subset, the experimental-arm means and the experimental-minus-control estimates are numerically higher. Some of the unadjusted secondary confidence intervals exclude zero, while the primary 6-month C-reactive protein interval includes zero. The secondary pattern is therefore not identical to the primary result, but it does not supersede it.

These endpoints provide related biomarker information, not independent confirmation of a clinical cardiovascular outcome. The 1-month and 3-month C-reactive protein comparisons concern the same general measure as the primary endpoint but at different times. Lipid and white blood cell profiles assess other outcomes. Differences in follow-up time and outcome type mean that these results should be interpreted as complementary observations rather than as interchangeable tests of the primary question.

The registry record lists 19 secondary outcomes, and it does not report a multiplicity adjustment or a prespecified hierarchy for interpreting them. When many outcomes and time points are considered, some unadjusted results may look more compelling by chance. This is why secondary results generally carry less weight than a clearly specified primary endpoint, particularly when the analysis plan is unavailable. The record also contains no reported analyses, so it does not clarify which comparisons were prespecified or how the secondary findings were intended to influence conclusions.

The secondary results can motivate further questions about the timing and consistency of biomarker changes, but they do not establish that the primary result should be reinterpreted. Their appropriate role is descriptive and hypothesis-generating unless supported by a prespecified analysis strategy and suitable confirmation. Clinical meaning cannot be inferred from the statistical pattern alone, especially because the record does not state thresholds for important changes in these measures.

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

• Change From Baseline in C-Reactive Protein Level at 1 Month
• Change From Baseline in C-Reactive Protein Level at 3 Month
• Change From Baseline in Lipid Profile at 1 Month
• Change From Baseline in Lipid Profile at 3 Months
• Change From Baseline in Lipid Profile at 6 Months.
• Change From Baseline WBC Profile at 1 Month
• Change From Baseline WBC Profile at 3 Months
• Change From Baseline WBC Profile at 6 Months

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mean difference describe?

The primary outcome is continuous, so the registry record summarizes each arm with a mean and standard deviation. The mean describes the average change from baseline within an arm. The standard deviation describes how dispersed individual change values are around that average. These quantities answer different questions: the mean concerns the group average, while the standard deviation concerns variation among participants.

The mean difference compares the arm means. In the posted primary comparison, the experimental group is contrasted with the control group, and the result is expressed in mg/L. A positive or negative estimate identifies the numerical direction of the contrast under that ordering. It does not by itself indicate which direction is clinically desirable. That requires a defined interpretation of the change score and clinical context, neither of which is fully posted by the registry record.

How should the confidence interval be read?

A confidence interval describes uncertainty around an estimated group contrast under the statistical method used. A narrower interval indicates a more precise estimate; a wider interval indicates greater uncertainty. It is not a range containing a known proportion of individual participants' outcomes, and it does not show the full distribution of their measurements.

For the primary result, the confidence interval extends from -1.225 to 3.945 mg/L and includes zero. Zero represents no difference in mean change between the arms. The interval's inclusion of zero means that the posted estimate is compatible with no group difference under the interval's assumptions, while also allowing differences on either side of zero. The registry record does not report the exact procedure used to construct the interval, so the method should not be inferred from the interval alone.

What does the p value add?

The unadjusted p value for the primary comparison is 0.302. In general, a p value measures how incompatible the observed result, or a more extreme result, would be with a statistical model in which the null hypothesis of no difference is true. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect.

The p value is unadjusted, so it does not account for testing multiple outcomes or time points. The registry record does not report a multiplicity plan. A p value should therefore be considered alongside the estimate and confidence interval, not as a stand-alone decision rule. The confidence interval conveys the range of contrasts that are reasonably compatible with the data under its assumptions, whereas the p value provides a summary of evidence against a null value.

Why do standard deviations matter?

Standard deviations describe variability in outcome values within each arm. Greater variability generally makes a mean contrast less precise when other factors are unchanged. The primary arm standard deviations are 7.53 mg/L in the experimental group and 2.04 mg/L in the control group. Their difference indicates that the posted change values were more dispersed in the experimental arm. This matters because an average can conceal substantial variation among participants, and a mean contrast does not describe how many individuals had increases, decreases, or values near the average.

When variability differs between arms, the assumptions of a statistical comparison matter. General methods that assume equal variances may not behave as intended when the arm spreads differ substantially; methods that allow unequal variances are one possible alternative. The registry record does not state which variance assumption or test was used. The reported confidence interval and p value should therefore be treated as the posted unadjusted comparison, rather than as evidence of a particular variance model.

Why can over-dispersion matter?

Over-dispersion is a general issue in outcomes whose observed variability exceeds what a chosen statistical model expects. It can make standard errors too small and confidence intervals too narrow if the model does not allow for the extra variability. The primary endpoint is continuous and summarized with means and standard deviations; the record does not report an over-dispersion assessment or a model-based analysis. It would not be appropriate to claim that over-dispersion was present. The general point is that the model and the observed variability should be compatible for uncertainty estimates to be trustworthy.

What can the secondary comparisons establish?

Secondary outcomes can provide context about other measured biomarkers and follow-up times. Each comparison is still an estimate with uncertainty, but multiple tests increase the chance that some results appear statistically notable by chance. Adjustment procedures or a prespecified testing hierarchy can address this concern in different ways. Neither a multiplicity adjustment nor a hierarchy for the secondary outcomes is reported in the registry record. The posted secondary p values are explicitly unadjusted, so they should not be treated as equivalent in evidential weight to a single prespecified primary comparison.

In general, a nonsignificant result does not prove that two groups are identical, just as a small p value does not establish clinical importance. The estimate, confidence interval, measurement quality, analysis plan, and clinical meaning all matter. For the primary endpoint, the confidence interval is compatible with a range that includes no difference, and the record does not provide a threshold for clinical importance. The statistical result is therefore best described as an imprecise estimate that does not establish a clear group difference, rather than as proof of equivalence or proof of a particular clinical effect.

11. Confidence Intervals and Precision

The primary mean difference is 1.36 mg/L, and its 95% confidence interval ranges from -1.225 to 3.945 mg/L. This interval is broad enough to include zero as well as values on either side. It therefore does not pin down the direction or size of the underlying group contrast with high precision. The point estimate is the center of the reported comparison, but it should not be read without the uncertainty around it.

In general, a confidence interval is a way to represent sampling uncertainty around an estimate under a specified method and its assumptions. A 95% interval is not a guarantee that the true effect lies within the particular interval, nor does it describe the range of individual participants' responses. It is also not a measure of clinical relevance. Clinical interpretation would require a defined threshold or other context for judging whether a difference matters; such a threshold is not reported in the registry record.

The primary arm standard deviations are 7.53 mg/L for the experimental group and 2.04 mg/L for the control group. This spread, especially the greater variability in the experimental arm, helps explain why the mean difference should be interpreted with care. Group averages do not reveal the full shape of the outcome distributions or whether a small number of observations strongly influenced the mean. Distributional information and the methods used to address unequal variability are not reported in the registry record.

The confidence interval and p value describe the same primary comparison from different angles. The interval includes zero, and the unadjusted p value is 0.302. Together they do not establish a clear difference, but they also do not demonstrate that the groups are equivalent. The available precision leaves uncertainty about the size and direction of the contrast.

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 events. They are illustrative calculations based on the observed effect in the posted comparison, rather than a record of the original trial's design calculation. The registry record does not report the original sample-size justification or the assumptions used when the trial was planned.

The calculations use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario asks how many participants per arm would be needed to detect a stated fraction of the observed effect. The 80% power column expresses the planned sample size for a design with an 80% chance of detecting that assumed effect under the calculation's assumptions if the effect is present. The 90% power column expresses the corresponding target for a design with a 90% chance.

Read each planning scenario according to the assumed effect size: the full observed effect, 75% of the observed effect, or 50% of the observed effect. A smaller effect is harder to distinguish from random variation, so the planning calculation requires more participants per arm to achieve the same power target. The estimates are therefore sensitive to the assumed effect. If the effect in a future study differs from the observed estimate, its required sample size could differ as well.

This is not observed power. It is a planning illustration, not a retrospective measure of how likely the completed trial was to detect an effect, and it does not substitute for the unreported original design rationale. The displayed relationship between assumed effect and required sample size is a general feature of such planning calculations; it should not be read as evidence that the completed trial had any particular probability of detecting its result.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 1.360; pooled standard deviation σ = 5.516.
2. n = 2 × (1.96 + 0.842)² × 5.516² / 1.360² = 258.3, rounded up to 259 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
delta <- 1.36                      # observed difference in means
sigma <- 5.51645266452999                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2417376)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 259 (80% power), 346 (90% power)
 75% of observed effect: n per arm = 460 (80% power), 615 (90% power)
 50% of observed effect: n per arm = 1,034 (80% power), 1,384 (90% power)
power.t.test: 259.2 
Simulated power at n = 259 per arm: 0.799 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 multiple secondary outcomes and follow-up times, but it does not report how multiplicity was handled. No adjustment method, testing hierarchy, or rule for drawing conclusions across the outcomes is stated. The posted secondary p values are unadjusted. When multiple hypotheses are tested, the chance of observing at least one apparently unusual result can increase; this is a general statistical concern, not evidence that any particular result is spurious. Without a reported plan, the secondary p values should be interpreted cautiously and separately from the primary comparison.

Missing-data handling is not reported in the registry record. The record does not state whether all randomized participants had measurements at each follow-up, how incomplete observations were treated, or whether any imputation or sensitivity analysis was used. The arm summaries list 35 participants per group, but those entries alone do not establish that every participant contributed an outcome at every time point. The reasons for missing measurements, if any, are also not reported.

The analysis population is not described beyond the primary-outcome population being identified as patients with both coronary heart disease and periodontitis. The record does not say whether the comparisons were based on all randomized participants, participants with available measurements, or another defined population. It also does not describe adherence to the assigned intervention or whether participants were analyzed according to assignment. These details matter because different analysis populations can lead to different estimates and interpretations.

The record lists no reported analyses. It therefore does not document a prespecified statistical analysis plan, covariate adjustments, interim analyses, or methods for handling deviations from the assigned intervention. None of these features should be assumed to have occurred or not occurred solely because they are not described. The registry information is insufficient to evaluate how the analysis decisions were made or whether the posted comparisons followed an original plan.

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

The posted primary result describes the difference between the experimental and control groups in mean change in high-sensitivity C-reactive protein at 6 months. The experimental mean was 6.3 mg/L, the control mean was 4.94 mg/L, and the unadjusted mean difference was 1.36 mg/L. Its confidence interval includes zero, and the unadjusted p value is 0.302. The result does not establish a clear difference in the mean change between groups, while the interval also leaves uncertainty about the possible size and direction of the contrast.

This finding is not proof that the groups are equivalent. Demonstrating equivalence or non-inferiority requires a prespecified margin and an analysis designed for that purpose; neither is reported in the registry record. Nor does the result show that the intervention has no effect. The estimate is uncertain, and the available record does not provide the clinical threshold needed to judge whether any compatible difference would matter.

The outcome is a biomarker. The record does not report coronary events, cardiovascular mortality, or another direct clinical outcome as the primary endpoint. A change in a biomarker should not be presented as evidence of a change in clinical risk or patient health without supporting evidence and an appropriate clinical interpretation. The direction that would be desirable for the recorded change is also not specified in the registry record.

The posted secondary results involve other biomarkers and follow-up times. Because they are secondary and unadjusted, they are not a substitute for the primary result or a basis for a definitive overall conclusion. The multiplicity plan, missing-data procedures, and analysis populations are not reported, which limits assessment of how robustly the comparisons represent the randomized groups.

The adverse-event entries list zero participants at risk and zero affected for serious and other categories in both groups, with deaths recorded as null. These entries cannot establish that adverse events did not occur, because the record does not list participants at risk. The safety information is therefore insufficient for a complete account. Overall, the registry results support a cautious description of the observed biomarker summaries and their uncertainty, not a treatment recommendation or a broad clinical claim.

16. Why This Trial Matters Statistically

This trial is statistically instructive because it distinguishes a numerical difference from a precise or clinically interpretable result. The primary point estimate is positive, but its confidence interval includes zero and extends to values on both sides of zero. Reading the estimate, interval, and p value together is more informative than relying on one statistic alone. The result does not establish a clear difference, and it does not demonstrate equivalence.

The primary outcome is continuous, and its variability differs between the two posted arms. That makes it useful to consider not only the mean contrast but also the spread of observations and the assumptions behind the comparison. A mean can summarize a group while concealing substantial variation. The registry record does not document the variance assumptions or the analysis method, so the uncertainty estimates cannot be fully assessed from the record alone.

The record also illustrates the distinction between a primary endpoint and a set of secondary outcomes. Multiple unadjusted comparisons can produce a mixed statistical pattern, and results from other times or measures do not automatically overturn the primary finding. A clear prespecified multiplicity strategy helps define how such results should be interpreted, but one is not reported.

Finally, the sample-size illustrations are based on the observed effect and stated planning assumptions, whereas the original design justification is not reported. These are different purposes: a planning calculation can illustrate how assumptions about effect size affect required enrollment, but it cannot reveal what assumptions informed the completed trial. Together, these issues show why statistical interpretation depends on the design, endpoint definition, uncertainty, analysis plan, and completeness of reporting, not simply on whether a p value is small.

17. Limitations

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

The registry record gives limited information for evaluating recruitment and generalizability. It identifies the population as patients with coronary heart disease and periodontitis, but additional eligibility criteria, demographic characteristics, disease severity, and recruitment setting are not reported. The results therefore cannot be extended confidently to populations whose characteristics are not described.

Important details of randomization and masking are also absent. The record labels the trial randomized and single-masked, but does not identify who was masked, explain allocation concealment, or describe the random-sequence procedure. It does not report whether intervention delivery or outcome assessment was standardized beyond the stated procedure. These omissions make it difficult to assess risks of bias in assignment, measurement, or conduct.

The intervention description identifies the instruments and appointment schedule, while the control group received no periodontal intervention. The record does not describe other care, adherence, treatment fidelity, or whether participants in either arm received additional periodontal or cardiovascular care during follow-up. Such details would help clarify how the assigned groups differed in practice.

The primary result is a mean change with a broad confidence interval that includes zero. The arm standard deviations differ, while the analysis method and handling of unequal variability are not reported. The record does not state the clinically important difference for C-reactive protein, so statistical uncertainty cannot be translated into a threshold-based clinical judgment.

Analysis limitations include unreported missing-data procedures, analysis populations, multiplicity handling, and original sample-size justification. The record also provides limited adverse-event information: zero participants are recorded as at risk in the event categories. These reporting gaps do not establish that problems occurred, but they restrict how fully the results and safety information can be assessed.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Changes in the Risk Factors of Coronary Heart Disease Observed After Scaling and Root Planing — NCT02417376.
• Registry record last updated 2017-02-24; status last verified 2017-01.
• Results first posted 2017-02-24.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT02417376 is a completed randomized, single-masked, parallel-group trial sponsored by Government College of Dentistry, Indore. The registry record lists enrollment of 70 and compares scaling and root planing with no periodontal intervention among patients described as having both coronary heart disease and periodontitis. The primary endpoint is change from baseline in high-sensitivity C-reactive protein at 6 months.

The posted primary mean difference is 1.36 mg/L, with a 95% confidence interval from -1.225 to 3.945 mg/L and an unadjusted p value of 0.302. The interval includes zero, so the comparison does not establish a clear difference in mean change. The record does not report the original sample-size justification, analysis populations, missing-data procedures, or multiplicity plan. These omissions limit interpretation of the posted results and secondary comparisons.