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Resting Pulse Rate Analysis for an Individual Undergoing Different Types of Exercise: A case study in Methodology

Authors:
  • Hart Chiropractic
Resting Pulse Rate Analysis for an Individual
Undergoing Different Types of Exercise:
A case study in Methodology
D.O.I: https://doi.org/10.4127/jbe.2018.0132
JOHN HART, DC, MHSC
1-2
1
Hart Chiropractic, Greenville, South Carolina
2
Adjunct Faculty, Southern New Hampshire University, Manchester,
New Hampshire
ABSTRACT
Introduction: Resting pulse rate (RPR) is a user-friendly
method of assessing neurological fitness. RPR tends to be low
in athletes and healthy people. A novel method for monitoring
an individual’s RPR over time is presented, where the subject
experienced different levels of exercise rigor. The method may
be of interest to those who would also like to monitor their level
of neurological fitness using RPR.
Methods: An adult male, who is a chiropractor and author of
this paper, self-measured and analyzed his RPR over a 1.6 year
period (293 RPR measurements). Four phases of exercise that
differed in rigor were analyzed: Low rigor solo (Phase 1); high
rigor solo (Phase 2); high rigor solo + a structured running pro-
gram (Phase 3) 6 days total per week running; and alternating
run and bicycling (Phase 4). Consecutive phases were analyzed
using the two sample t test and effect size statistics.
Results: RPR decreased (improved) steadily from Phase 1
to Phase 3. The difference between consecutive phases was
statistically significant (P < 0.0001) with large effect sizes (of
> 0.5). There was no statistical difference between phases 3
and 4.
Key Words: Pulse rate, Self-assessment, Biostatistics, Exercise,
Running
VOLUME 14.1, 2018
76 JBE – VOL. 14.1, 2018
Conclusion: The method presented is feasible for personal use and may be of
interest to those seeking to self-monitor their level of neurological fitness during
their exercise program.
INTRODUCTION
Resting heart rate, also known as resting pulse rate (RPR) when obtained by
counting beats while palpating a peripheral artery (e.g. the radial artery at the
wrist), is considered a measure of neurological fitness since the nervous system
controls heart rate. [1-4] RPR is evidence-based from a clinical standpoint in that
people with lower RPR tend to be healthier (e.g., live longer) than their counter-
parts who have a higher RPR. [5-7] In addition, RPR has: a) good agreement with
resting heart rate derived from the electrocardiogram; [8] and b) good (inverse)
agreement with heart rate variability, where lower RPR (a healthy finding) corre-
lates with higher heart rate variability (also a healthy finding). [9]
The author, who is also a chiropractor, uses RPR in his neurologically-based
practice in a novel way – as an added tool to help him determine when his patients
need a chiropractic adjustment. The working theory in this approach is that stress
in the patient’s nervous system could be due to a misaligned vertebra that dis-
turbs spinal nerve function, resulting in elevated (worsened) RPR measurements.
The remedy for this condition would be a chiropractic adjustment to realign the
offending vertebra, to improve nervous system function evidenced by a subse-
quent reduction (improvement) in RPR. [10-12] Obviously there are a number of
other factors that can affect RPR such as exercise. Of course during exercise RPR
increases but over time, true resting heart rate tends to decrease in physically fit
persons. The author has noticed this in his own case and presents his data as a
case example on how one’s RPR can be analyzed.
Self-measured clinical tests, such as blood pressure and RPR, can provide
important information for clinicians and researchers. [13-14] Since RPR is user-
friendly, requiring no special equipment, individuals can readily measure their own
level of neurological fitness using RPR, as was done in the present study. Smart
watches that measure RPR are common these days and can be tested against the
gold standard of RPR (manual palpation at the radial artery [wrist]).
Statistical analysis is typically used at the group level rather than the individual
level. However, if assumptions, such as normal distribution for a t test are satisfied,
then statistical analysis is appropriate at the level of the individual. Typically a case
study does not have so many data points as the present study does. This author
has previously applied statistical analysis at the level of the individual, indicating
precedence for this approach. [15-16]
RESTING PULSE RATE ANALYSIS FOR AN INDIVIDUAL UNDERGOING DIFFERENT TYPES OF EXERCISE
77
Purpose
A novel method of RPR analysis is presented in this case study. The method
compares different phases of exercise activity. Research indicates that RPR tends
to improve (decrease) over time in those who exercise. [17] The self-measurement
method in this study may be of interest to those who wish to monitor their own level
of neurological fitness.
METHODS
A 60-year old male and author of this paper, self-measured and analyzed his
RPR over a 1.6 year period, from 5-10-16 to 12-11-17, for a total of 293 RPR meas-
urements. Measurements for RPR were taken: a) in the seated position, after at
least 5 minutes of seated rest, and b) using a digital timer, palpating and counting
beats at the radial artery for either 30 seconds, then multiplying by 2 to achieve a
beats per minute [BPM] value – the method used for readings obtained in 2016; or
for a full 60 seconds to obtain the BPM value – the method used for readings ob-
tained in 2017. Agreement between these two different time counts (30 x 2 versus
the full 60 second count) is good. [18] Reference RPR for this subject’s demo-
graphic group, based on other research of healthy individuals, is 71.0 BPM. [19]
The four phases of activity during the study period were as follows, one occur-
ring right after the other:
1. Phase 1: 5-10-16 to 8-3-16: low rigor solo, 5 minutes per time, 3 times per
week, consisting of bicycling and walking. This phase is referred to as the
low solo phase.
2. Phase 2: 8-4-16 to 2-23-17: High rigor solo, consisting of running 1-2 miles
(approximately the first half of his phase); elliptical workouts, stairs running,
and bicycling (the second half of this phase); 6 times per week, about 20
minutes per time. This phase is referred to as the high solo phase.
3. Phase 3: 2-24-17 to 7-19-17. This phase consisted of high rigor solo running
4 times per week along with a structured program that met two times per
week and ran with high rigor (total of 6 time per week running), approxi-
mately 30 minutes (3 miles) per time. The structured program is called No
Boundaries (NoBo) and is sponsored by Fleet Feet Sports of Greenville,
South Carolina. [20] Compared to solo running, the NoBo program has
some additional rigor such as sprints, including uphill sprints. This phase is
referred to as the NoBo phase.
4. Phase 4: 7-20-17 to 12-11-17. This phase consisted of medium-to-high rigor,
78 JBE – VOL. 14.1, 2018
alternating between running 30 minutes per time, 3 days per week; and bi-
cycling the other days per week, 30 minutes per time for a total of 6 exercise
times per week. The selection of 12-11-17 end date was based on the aver-
age number of days in phases 1-3 (n = 144 days from 7-20-17 to 12-11-17).
This phase is called run-bike (Table 1).
Analysis
Phases were compared in the statistical software program Stata (StataCorp,
College Station, TX). One way analysis of variance (ANOVA), with Bonferroni cor-
rection, was used to determine whether differences between consecutive phases
were statistically significant at the 0.05 alpha level. Since there were at least 30
observations (RPR measurements) in each phase, data normality is assumed. [21]
To assess the magnitude of differences between phases, an effect size statistic,
using a pooled standard deviation was also performed (in Excel 2016, Microsoft
Corp, Redmond, WA). Effect sizes greater than 0.5 were considered large. [22] All
reported p-values are two-tailed.
Outlier analyses were performed for the subject’s four race times [23-26] and
five heart rate variability during the study period. Both of these (race times and
heart rate variability) occurred only in phases 3 and 4, and thus are outcome
measures comparing these two phases. His previous races occurred about 45
years prior when he was in junior high track. Total seconds were used for analysis
in the races. The measure for heart rate variability was the standard deviation of
normal-to-normal beats (SDNN) using the Biocom Heart Rhythm Scanner, clinical
edition 1.0, a 5 minute seated test. A larger SDNN indicates a more adaptive, and
therefore a healthier nervous system. [27] The outlier analysis took the form of:
Quartile 1 – (1.5 * interquartile range) for lower fence
Quartile 3 + (1.5 * interquartile range) for upper fence
RESULTS
A scatter plot of all RPR measurements is provided in Figure 1. Average RPR
for all 293 RPR readings over the 1.6 year study period was 62.3 BPM, represented
by the horizontal line in Figure 1 placed at the exact point of this average. Vertical
lines in Figure 1 are placed at the exact point of the last RPR measurement in the
phase. Mean RPR by phase is provided in Figure 2.
RESTING PULSE RATE ANALYSIS FOR AN INDIVIDUAL UNDERGOING DIFFERENT TYPES OF EXERCISE
79
Phases: 1 2 3 4
Figure 1. Scatter plot for all RPR over the 1.6 year study period. Vertical lines are software-
constructed at exact data point for last observation in a phase and separate the phases. The
horizontal line, also software-constructed, is placed at exact location for mean RPR for all
293 RPR measurements (at 62.3 BPM). Phase 1 = low rigor solo, Phase 2 = high rigor solo,
Phase 3 = NoBo phase (high rigor solo + NoBo), Phase 4 = run-bike.
Figure 2. Mean RPR by phase. Phase 1 = low rigor solo, Phase 2 = high rigor solo, Phase 3
= NoBo phase (high rigor solo + NoBo), Phase 4 = run-bike. Differences between phases
were statistically significant with large effect sizes, with the exception of Phases 3 versus 4.
80 JBE – VOL. 14.1, 2018
Table 1
Summary statistics for RPR.
Phase Days Obs Mean SD Diff p ES
1 85 48 70.3 4.7
2 203 120 62.5 4.6 -7.8 < 0.0001 1.7
3 145 75 58.8 4.0 -3.7 < 0.0001 0.8
4 144 50 59.5 3.6 0.7 0.2 0.2
Phase 1 = low rigor solo, Phase 2 = high rigor solo, Phase 3 = NoBo phase (high rigor solo + NoBo),
Phase 4 = run-bike. Days = number of days in the phase. Obs = number of observations (RPR meas-
urements). Mean and SD (standard deviation) pertain to RPR in the phase. Diff is the mean RPR dif-
ference between consecutive phases. p = p value, and ES = effect side, both of which also pertain to
RPR difference between consecutive phases.
Statistically significant changes (p < 0.0001), even at the Bonferroni-corrected
alpha, with large effect sizes (of > 0.5) were observed between the first three con-
secutive phases. Phases 3 and 4 were essentially the same (p = 0.2, effect size =
0.2); (Figures 1-2, Table 1). In addition, similar to Phase 3, Phase 4’s lower RPR
compared to Phase 2 (solo high rigor) was also statistically significant (p < 0.001)
with a large effect size (of 0.7). Overall reduction, from Phase 1 to Phase 4 was
by 10.8 BPM, which was also statistically significant (p < 0.001) with a very large
effect size (of 2.6).
Race times (in total seconds) were as follows. Race 1, in Phase 3: 1717; Race 2,
in Phase 3: 1683; Race 3, 17 days into Phase 4: 1705; Race 4, five weeks into Phase
4: 1569. In this analysis, one outlier was detected for the race times – in the last race
that showed the fastest time, of 1569 seconds (26 minutes, 9 seconds; Table 2). No
outliers were detected for the heart rate variability test results. (Table 3)
RESTING PULSE RATE ANALYSIS FOR AN INDIVIDUAL UNDERGOING DIFFERENT TYPES OF EXERCISE
81
Table 2
Outlier analysis of race times in phases 3 and 4.
Race Total seconds
1 1717
2 1683
3 1705
4 1569
Quartile 1 1654.1
Quartile 3 1708.0
Interquartile range 53.5
Lower fence 1574.3
Upper fence 1788.3
Race 4 time is an outlier, where it is less than the lower fence time.
Table 3
Outlier analysis of heart rate variability (SDNN) in phases 3 & 4.
Date SDNN
2-28-17 25.9
4-7-17 38.2
9-22-17 29.7
9-25-17 38.2
11-13-17 42.1
Quartile 1 28.1
Quartile 3 38.2
Interquartile range 10.1
Lower fence 13.0
Upper fence 53.3
No outliers observed.
82 JBE – VOL. 14.1, 2018
DISCUSSION
The highest (worst) mean RPR was observed in the low solo (initial) phase,
where it was 70.3 BPM, when exercise exertion level was at its lowest. This RPR
mean was nonetheless better (lower), though only slightly, than the normative
mean for this individual, as previously mentioned, of 71.0 BPM, [19] This suggests
that improvement (decrease) in RPR is possible, at least for this individual, even
when the RPR is initially better than the norm for his demographic group.
Reductions (improvements) in mean RPR were 7.8 BPM from Phase 1 to Phase
2, and then 3.7 BPM from Phase 2 to Phase 3. The reductions were statistically
significant, meaning they probably did not happen by chance alone. Nonethe-
less, there may be a question of whether such changes are clinically significant. It
should be noted that a change in resting heart rate as small as 1 BPM is associated
with a change in mortality risk by 1%, at least at the group level for hypertensive
patients. [28]
There was no statistical difference between RPR in Phase 3 (6 days of running,
in NoBo) versus Phase 4 (running 3 days per week – biking 3 days per week). This
would appear to be a good thing since less running would seem to lessen the risk
of injury, particularly at this individual’s age, where he is no spring chicken. Also
similar to Phase 3, Phase 4’s lower RPR compared to Phase 2 (solo high rigor) was
also statistically significant with a large effect size. Overall reduction in mean RPR
was by almost 11 BPM over the study period of 1.6 years.
Two phases noticeably (in Figure 1) had most of their RPR below the mean line:
NoBo and run-bike (Figure 1). There may be a question of whether improvements
in the various phases were related to trends that began in the previous phases.
The scatter plot (Figure 1) would seem to answer this in that there were no notice-
able trends in prior phases that would indicate such a phenomenon.
The decreased rigor in Phase 4 did not adversely affect race time performance.
Race 3, which was the first of two races in this phase, was essentially the same
time as the previous two races. Race 3 however occurred after only 17 days into
Phase 4. Thus, any benefit that Phase 4 may have had, this amount of time (17
days) may not have been long enough to measure an effect in the way of race
times. The last race in the study, in Phase 4 did show a statistical difference, in the
way of an improved race time. Thus, for this subject, it could be that a medium-
high rigor 6 days per week approach may be ideal compared to high rigor 6 days
per week approach. The reason for the improvement may pertain to increased
recovery time between the high rigor running days. This in turn could result in a
stronger runner, paradoxically, amid a lower rigor.
The mechanism for long term improvement (reduction) in resting heart rate
following an exercise program is likely due to a prevailing effect of vagal (para-
RESTING PULSE RATE ANALYSIS FOR AN INDIVIDUAL UNDERGOING DIFFERENT TYPES OF EXERCISE
83
sympathetic) tone. [27] This tone, when it predominates (versus a predominating
sympathetic tone), has a slowing effect on RPR.
Resting pulse rate measurement is sufficiently user-friendly for personal use
(self-measurement). For those who might be experienced in basic statistical analy-
sis, common spreadsheets (such as Excel) allow for convenient numerical assess-
ment. Alternatively, the RPR can be simply written down, and progress, or lack
thereof can be ascertained by merely viewing the numbers in a list. As a side-note,
I have my patients who are interested, keep track of theirs.
Limitations to the study include those that typically pertain to a case study, e.g.
a convenience sample of only one individual. Similarly, the statistical results apply
only to this individual. Thus, results in this study may not apply to other individuals.
In addition, if the order of the phases was different, the results may have been dif-
ferent. For example, if Phase 1 (low rigor) became the last phase, where it followed
the more rigorous phases, it might have had the lowest RPR instead of the highest.
In either case it is reasonable to conclude that higher rigor exercise has a greater
effect on lowering RPR compared to lower rigor.
CONCLUSION
The method of self-measurement and analysis of resting pulse rates in this
study is feasible for personal use, to monitor one’s level of neurological fitness,
and is conducive to statistical analysis. Future application of the method in other
individuals is a reasonable next step.
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Address for correspondence:
John Hart, DC, MHSc
Email: jhartdc@yahoo.com
... The present study is like a previous study of mine where I compared resting heart rate (RHR) between different types of running That study showed significant improvement (decrease) in RHR when Fleet Feet group training (of Greenville, SC) was added to my routine (p < 0.05) [11]. In the present study, RHR was statistically the same across all three groups. ...
... In the present study, RHR was statistically the same across all three groups. In the earlier study [11], HRV was not assessed because I was not measuring it at that time. ...
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Abstract Introduction: Resting heart (pulse) rate (PR) is an autonomic marker that may be useful in subluxation-centered chiropractic practice. The present study investigated the change in PR following chiropractic adjustment of C1 subluxation. Methods: A convenience sample of 23 chiropractic students was examined on three visits; two pre-adjustment visits and one post-adjustment visit. The outcome variable was the PR difference between the second pre-intervention visit and the post-intervention visit using the paired t-test. Since PR changes may be different between genders, subgroup analysis by gender was also performed. Results: A decrease in post-intervention PR from pre-intervention PR was observed but was not statistically significant (mean reduction of 2.7 beats per minute [BPM]; p = 0.243). However, a statistically significant reduction in PR was observed, with a large effect size for males (n = 12; mean reduction = 8.0 BPM, p = 0.014, ES = 0.74). Proportion-wise, five of the 11 females (45.5%) showed a PR that either decreased (n = 4; 36.4%) or was unchanged (n = 1) following adjustment, compared to the remaining six (54.5%) whose PR increased following their adjustment. Eleven of the 12 males (91.7%) showed a PR that either decreased (n = 9; 75%) or stayed the same (n = 2) following adjustment compared to one (8.3%) whose PR increased following his adjustment. Discussion: It is not clear why a greater percent of males showed PR decreases following their adjustment compared to females. Still, it is noteworthy that more than a third of the females in this preliminary study showed success (a reduced PR) following their adjustment. Increases in PR on the post-adjustment visit, whether female or male, could be due to circumstances such as an incorrect subluxation listing (resulting in adjustment from the wrong side). Further research with different chiropractic procedures may reveal greater success in PR decreases following their chiropractic care. Conclusion: In this preliminary study, a statistically significant decrease in pulse rate was observed for males following adjustment of C1 subluxation. More than a third of females showed a decrease in pulse rate following their adjustment while three-fourths of males showed pulse rate decreases following their adjustment.
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One model for neurological assessment in chiropractic pertains to autonomic variability, tested commonly with heart rate variability (HRV). Since HRV may not be convenient to use on all patient visits, more user-friendly methods may help fill-in the gaps. Accordingly, this study tests the association between manual pulse rate and heart rate variability. The manual rates were also compared to the heart rate derived from HRV. Forty-eight chiropractic students were examined with heart rate variability (SDNN and mean heart rate) and two manual radial pulse rate measurements. Inclusion criteria consisted of participants being chiropractic students. Exclusion criteria for 46 of the participants consisted of a body mass index being greater than 30, age greater than 35, and history of: a) dizziness upon standing, b) treatment of psychiatric disorders, and c) diabetes. No exclusion criteria were applied to the remaining two participants who were also convenience sample volunteers. Linear associations between the manual pulse rate methods and the two heart rate variability measures (SDNN and mean heart) were tested with Pearson's correlation and simple linear regression. Moderate strength inverse (expected) correlations were observed between both manual pulse rate methods and SDNN (r = -0.640, 95% CI -0.781, -0.435; r = -0.632, 95% CI -0.776, -0.425). Strong direct (expected) relationships were observed between the manual pulse rate methods and heart rate derived from HRV technology (r = 0.934, 95% CI 0.885, 0.962; r = 0.941, 95% CI 0.897, 0.966). Manual pulse rates may be a useful option for assessing autonomic variability. Furthermore, this study showed a strong relationship between manual pulse rates and heart rate derived from HRV technology.
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This theoretical report gives an example for how coefficient of variation (CV) and quartile analysis (QA) to assess outliers might be able to be used to analyze numeric data in practice for an individual patient. A patient was examined for 8 visits using infrared instrumentation for measurement of mastoid fossa temperature differential (MFTD) readings. The CV and QA were applied to the readings. The participant also completed the Short Form-12 health perception survey on each visit, and these findings were correlated with CV to determine if CV had outcomes support (clinical significance). An outlier MFTD reading was observed on the eighth visit according to QA that coincided with the largest CV value for the MFTDs. Correlations between the Short Form-12 and CV were low to negligible, positive, and statistically nonsignificant. This case provides an example of how basic statistical analyses could possibly be applied to numerical data in chiropractic practice for an individual patient. This might add objectivity to analyzing an individual patient's data in practice, particularly if clinical significance of a clinical numerical finding is unknown.
Article
This report presents national reference data on resting pulse rate (RPR), for all ages of the U.S. population, from 1999-2008. During 1999-2008, 49,114 persons were examined. From this, a normative sample comprising 35,302 persons was identified as those who did not have a current medical condition or use a medication that would affect the RPR. RPR was obtained after the participant had been seated and had rested quietly for approximately 4 minutes. RPR is inversely associated with age. There is a mean RPR of 129 beats per minute (standard error, or SE, 0.9) at less than age 1 year, which decreases to a mean RPR of 96 beats/min (SE 0.5) by age 5, and further decreases to 78 beats/min (SE 0.3) in early adolescence. The mean RPR in adulthood plateaus at 72 beats/min (SE 0.2) (p < 0.05 for trend). In addition, there is a significant gender difference, with the male pulse rate plateauing in early adulthood, while the female resting pulse plateaus later when middle-aged. There are two exceptions, that is, infants under age 1 year and adults aged 80 and over, when the mean RPR is statistically and significantly higher in females than in males (females under age 20 have an RPR of 90 beats/min, SE 0.3, and males under age 20 have an RPR of 86 beats/min, SE 0.3, p <0.05; females aged 20 and over have an RPR of 74 beats/min, SE 0.2, and males aged 20 and over have an RPR of 71 beats/min, SE 0.3, p <0.05). After controlling for age effects, non-Hispanic black males have a significantly (p <0.001) lower mean RPR (74 beats/min) than non-Hispanic white males (77 beats/min) and Mexican-American males (76 beats/min). Among females, non-Hispanic black females (79 beats/min) and Mexican-American females (79 beats/min) had statistically and significantly (p < 0.01) lower mean RPRs compared with non-Hispanic white females (80 beats/min). Among males, the prevalence of clinically defined tachycardia (abnormally fast heart rate, RPR 100 beats/min) is 1.3% (95% CI = 1.1-1.7), and the prevalence of clinically defined bradycardia (abnormally slow heart rate, RPR < 60 beats/min) is 15.2% (95% CI = 14.1-16.4). For adult females, these prevalences are 1.9% (95% CI = 1.6-2.3) for clinical tachycardia and 6.9% (95% CI = 6.2-7.8) for clinical bradycardia. Controlling for age, males have higher odds (2.43, 95% CI = 2.09-2.83) of having bradycardia, and notably lower odds (0.71, 95% CI = 0.52-0.97) of having tachycardia than women. The data provides current, updated population-based percentiles of RPR, which is one of the key vital signs routinely measured in clinical practice.
Article
Elevated resting heart rate (RHR) is known to be associated with reduced survival but inconsistencies remain, including lack of significance in most studies of healthy women, lack of independence from systolic blood pressure (SBP) in some, and the suggestion that RHR is merely functioning as a marker of physical inactivity or other comorbidities. We aimed to clarify these inconsistencies. We analyzed the effect of RHR on end points in the National FINRISK Study; a representative, prospective study using Cox proportional hazards model. Ten-thousand five-hundred nineteen men and 11,334 women were included, excluding those with preexisting coronary heart disease, angina, heart failure, or on antihypertensive therapy. The hazard ratios for cardiovascular disease (CVD) mortality for each 15 beats/min increase in RHR were 1.24 (1.11-1.40) in men and 1.32 (1.08-1.60) in women, adjusted for age, gender, total cholesterol, physical activity (categorical), SBP, body mass index, and high-density lipoprotein cholesterol. This relationship remained significant after exclusion of those with comorbidities and events occurring within first 2 years of observation. Relationship with coronary mortality was stronger and with total mortality was slightly weaker. Inclusion of nonfatal end points weakened the relationship. A strong, graded, independent relationship between RHR and incident CVD was demonstrated. This was consistent in healthy men and women. We have clarified that the relationship is independent of SBP and that the temporal sequence would be compatible with a causal relationship. New findings include independence from both a validated measure of physical activity and comorbidities and the demonstration of a stronger effect for fatal than nonfatal events, supporting increased arrhythmogenicity of one of the mechanisms.
Article
There is a linear relationship between resting heart rate (HR) and mortality in normotensive and untreated hypertensive individuals. However, it is not clear whether HR is a marker of increased risk in hypertensive patients on treatment. We investigated the relationship between HR and mortality in patients with hypertension. We analyzed baseline HR, final HR, and HR change during follow-up in patients attending the Glasgow Blood Pressure Clinic. Using a threshold of 80 bpm, we classified patients into those who had a consistently high (high-high) or low (low-low) HR or patients whose HR increased (low-high) or decreased (high-low) over time. Survival analysis was carried out using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, rate-limiting therapy, systolic blood pressure, and serum cholesterol. For each beat of HR change there was a 1% change in mortality risk. The highest risk of an all-cause event was associated with patients who had increased their HR by >or=5 bpm at the end of follow-up (1.51 [95% CI: 1.03 to 2.20]; P=0.035). Compared with low-low patients, high-high patients had a 78% increase in the risk of all-cause mortality (HR: 1.78 [95% CI: 1.31 to 2.41]; P<0.001). Cardiovascular mortality showed a similar pattern of results. Rate-limiting therapy did not have an independent effect on outcomes in this analysis. Change in HR achieved during follow-up of hypertensive patients is a better predictor of risk than baseline or final HR. After correction for rate-limiting therapy, HR remained a significant independent risk factor.