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Confidential: For Review O
nly
Blood pressure variability and cardiovascular disease: A
systematic review and meta-analysis
Journal: BMJ
Manuscript ID BMJ.2015.029896
Article Type: Research
BMJ Journal: BMJ
Date Submitted by the Author: 14-Oct-2015
Complete List of Authors: Stevens, Sarah; University of Oxford, Primary Care Health Sciences
Wood, Sally; University of Oxford, Primary Care Health Sciences
Koshiaris, Constantinos; University of Oxford, Primary Care Health
Sciences
Law, Kathryn; University of Oxford, Primary Care Health Sciences
Glasziou, Paul; Bond University, CREBP
Stevens, Richard; University of Oxford, Nuffield Dept Primary Care Health
Sciences
McManus, Richard; University of Oxford, Dept of Primary Care Health
Sciences
Keywords: blood pressure, variability, cardiovascular, review, ambulatory, mortality
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Blood pressure variability and cardiovascular disease: A systematic review and 1
meta-analysis 2
3
Sarah L Stevens, Sally Wood, Constantinos Koshiaris, Kathryn Law, Paul Glasziou, Richard J Stevens, 4
Richard J McManus 5
Sarah L Stevens, Statistician, Nuffield Department of Primary Care Health Sciences, University of 6
Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom. Sally 7
Wood, General Practitioner, Nuffield Department of Primary Care Health Sciences, University of 8
Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom. 9
Constantinos Koshiaris, Statistician, Nuffield Department of Primary Care Health Sciences, University 10
of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom. 11
Kathryn Law, General Practitioner, Nuffield Department of Primary Care Health Sciences, University 12
of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom. Paul 13
Glasziou, Professor of Evidence-Based Medicine, Faculty of Health Sciences and Medicine, Bond 14
University, QLD 4229, Australia. Richard J Stevens, Associate Professor of Medical Statistics, Nuffield 15
Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, 16
Woodstock Road, Oxford, OX2 6GG, United Kingdom. Richard J McManus, Professor of Primary Care, 17
Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory 18
Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom 19
Correspondence to: Richard J Stevens. Email: [email protected]. Phone: 01865 289355. 20
21
Word count: 3755 22
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Abstract 24
Objective: Variability in blood pressure (BP) has been increasingly recognized as an independent risk 25
factor for cardiovascular disease (CVD) over and above mean BP. Results from previous studies have 26
been conflicting, reflecting heterogeneity of approach and failure to consider important 27
confounders. We aimed to review studies assessing the prognostic utility of long, short and very 28
short term BP variability (measured through clinic, home and ambulatory monitoring), independent 29
of mean BP, for CVD events and mortality. 30
Data Sources: Medline, Embase, Cinahl and Web of Science were searched to 27th February 2014 for 31
full text articles in English. 32
Eligibility criteria for selecting studies: Prospective cohort studies or clinical trials in adults with at 33
least 2500 person-years follow-up were included. Studies in haemodialysis patients, where the 34
inherent nature of the condition may have a direct impact on BP variability were excluded. 35
Standardized hazard ratios were extracted and, if there was no evidence of confounding, combined 36
using random effects meta-analysis in primary analyses. Outcomes included all-cause and CVD 37
mortality and CVD events. Measures of variability included standard deviation, coefficient of 38
variation, variation independent of mean and average real variability but not night dipping or day-39
night variation. 40
Results: Thirty-one papers representing seventeen observational cohort studies and twelve clinical 41
trial cohorts were identified. Ambulatory, home and clinic monitoring were studied in fifteen, four 42
and twenty-one papers respectively (eight studied both clinic and ambulatory monitoring). Increased 43
visit-to-visit variability in clinic systolic BP was significantly associated with risk of all-cause mortality 44
(HR=1.15, 95% CI [1.07 to 1.23]), coronary heart disease (HR=1.10, 95% CI [1.00 to 1.21]) and stroke 45
(HR=1.15, 95% CI [1.02 to 1.30]). Increased day-by-day variability in home systolic BP was 46
significantly associated with all-cause mortality (HR=1.15, 95% CI [1.06 to 1.26]), as was increased 47
variability in daytime ambulatory systolic BP (HR=1.10 95% CI [1.06 to 1.15]). 48
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Conclusions: Visit-to-visit clinic BP variability is associated with cardiovascular and mortality 49
outcomes, over and above the effect of mean BP. The observed effect is similar in size to that for 50
cholesterol. The extent to which systems providing information to clinicians about BP variability 51
could alter or enhance the management of cardiovascular risk needs further investigation. 52
Systematic review registration: PROSPERO ID: CRD42014015695. 53
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Introduction 54
Blood pressure is a leading risk factor for cardiovascular disease.1,2 Most studies have used mean 55
blood pressure (BP) as the indicator of risk, measured in clinic or “out of office” settings.3–5 56
However, BP is physiologically dynamic and shows marked oscillations over the short and long term.6 57
Historically, such variability has been viewed as inhibiting accurate measurement of mean BP and as 58
a phenomenon to be overcome by improved monitoring.7 BP variability has also been recognised as 59
a potential risk factor in its own right for at least two decades.8,9 In 2010 an analysis of three cohort 60
studies and two randomized trials found that BP variability was a predictor of stroke and coronary 61
events in high risk patients.10 A companion paper proposed that the disparity between the effects of 62
beta blockers and calcium channel blockers on stroke risk could be explained by BP variability.11 63
However, understanding BP variability has been hampered by statistical and clinical methodological 64
issues. Some studies of variability have not adequately adjusted for mean BP and therefore fail to 65
rule out the possibility that high variability is a surrogate for hypertension.12,13 Others, in using 24-66
hour mean to adjust for daytime variability, may have turned high daytime variability into a 67
surrogate marker for nocturnal or 24-hour BP.14 Further studies have defined variability on the basis 68
of measurements taken during follow-up, but analysed it as a baseline risk factor15–17 which may 69
introduce problems of informative censoring or immortal time bias.18 Informative censoring occurs 70
when individuals are lost to follow-up for reasons related to the study. This could occur if individuals 71
with extreme or erratic BP readings were withdrawn from studies due to concerns over safety, in 72
particular in secondary analysis of trial data. Immortal time bias can occur if individuals are required 73
to have a certain number of repeat BP measurements in order to be included in analysis for 74
mortality outcomes. The time up until their qualifying measurement becomes 'immortal time' since 75
by definition these individuals could not have died prior to having the prerequisite number of BP 76
readings. 77
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Other studies fail to use consistent BP monitoring equipment over time, to define a consistent 78
protocol for BP measurement or to account for medication change, leaving doubt as to the source of 79
any observed variability.15,19,20 Measurement at different times of the day21 or year,22 in different 80
arms,23 or using inconsistent cuff sizes24 can affect accurate measurement, thereby inducing 81
variability. We reviewed prospective studies that quantified the longitudinal associations of (i) long 82
term variability measured through clinic BP monitoring, (ii) short term variability measured through 83
home BP monitoring and (iii) very short term variability measured through ambulatory BP 84
monitoring with cardiovascular events and mortality, independent of mean BP, in adults. We 85
focused our primary analysis on studies meeting pre-specified methodological criteria, so that any 86
apparent effect of BP variability was likely to be a true independent effect. 87
Methods 88
The protocol for this review has been published (http://www.crd.york.ac.uk/PROSPERO/, PROSPERO 89
ID: CRD42014015695). 90
91
Study selection 92
Medline, Embase, Cinahl and Web of Science were searched to 27th February 2014 for full text 93
articles in English, describing trials and prospective cohort studies, which assessed the association of 94
(i) long term variability measured through clinic BP monitoring, (ii) short term variability measured 95
through home BP monitoring and (iii) very short term variability measured through ambulatory BP 96
monitoring with cardiovascular outcomes in adults (see Supplement, Table e1 for full search 97
strategy). Studies included in a recent systematic review,25 were also screened. Titles and abstracts 98
were scrutinised by two reviewers (SW and KL/SS) with adjudication by a third (RM). 99
100
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Inclusion and exclusion criteria 101
Studies were included if they considered the following outcomes: (i) all-cause mortality, (ii) 102
cardiovascular events (including stroke, myocardial infarction, coronary heart disease, and heart 103
failure), (iii) cardiovascular mortality (including sudden death) or (iv) a combination thereof. Studies 104
that only assessed intermediate outcomes (e.g. “arterial intima-media” thickness) or studies 105
concerning “nocturnal dipping” or “day-night variation” were excluded, since these metrics of 106
variability have been considered previously.26 107
Studies in disease specific populations (e.g. hypertensive or diabetes patients) were included, except 108
studies in haemodialysis patients. This is due to the nature of haemodialysis treatment; during which 109
changes in blood pressure (intradialysis hypo- and hypertension27,28) are common and have been 110
shown to be associated with hospitalization and mortality.29,30 111
We included studies with at least 2500 person-years of follow-up where BP variability was assessed 112
in the long, short or very short term in clinics, at home or through ambulatory BP monitoring (ABPM) 113
respectively. Studies of clinic monitoring had to measure visit-to-visit variability over at least five 114
clinic visits.10 For home monitoring, at least twelve measurements over at least three days was 115
required.31 For ABPM, at least fourteen daytime readings were required.31 116
117
Data extraction 118
Study and patient characteristics data were extracted independently by two reviewers (SS/SW and 119
KL/RM), as were statistical results (SS and KC/RS) using pre-specified forms (Table e2). For each 120
paper, hazard ratios (HRs) for every variability measure and outcome were extracted. For studies 121
reporting multiple analyses, the HR from the analysis with the greatest adjustment for confounders 122
but containing only a single variability measure was extracted. Where required data were not 123
available, this was requested by contacting the study authors by email. 124
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Data analysis and statistical methods 126
To allow pooling across the variety of variability measures, extracted HRs were converted to 127
standardized hazard ratios, using a general method for regression models (Table e3).32 Briefly, a 128
standardized log-HR was calculated as the log-HR per unit of standardized exposure (the exposure 129
divided by its sample standard deviation). These standardized hazard ratios were pooled using a 130
random-effects meta-analysis, stratified by outcome. Separate analyses were performed for: (i) long 131
term variability measured through clinic BP monitoring, (ii) short term variability measured through 132
home BP monitoring and (iii) very short term variability measured through ambulatory BP 133
monitoring. Heterogeneity was assessed using the Chi-squared test and the I-squared statistic. 134
Where studies reported results for multiple different variability measures, HRs were selected for 135
inclusion according to the following hierarchy (preferred to least preferred): standard deviation (SD), 136
coefficient of variation (CV), variation independent of mean (VIM), average real variability (ARV), 137
standardised residual (SR), root successive variance (RSV) and other. Where HRs were calculated 138
using data from the same primary study but reported in different papers, the most recently 139
published HR was included. Hazard ratios for study subgroups were combined before inclusion. 140
Risk of bias was assessed using the QUIPS tool33 by two independent reviewers (SS and RS), with 141
adjudication by a third (RM). Information about other potential confounders, specific to studies of 142
variability were also extracted (Table e2, indicated by *). Consistency of BP measurement with 143
respect to device, cuff size, personnel and measurement is important to prevent inducing variability. 144
For example, inter-arm differences in BP will increase apparent BP variability and are also associated 145
with CVD outcomes.34 The impact of other potential confounders may be adjusted for during 146
analyses. Adjustment for mean BP is required since patients with higher absolute BP (an established 147
CVD risk factor) also have higher absolute BP variability. Similarly, adjustment for antihypertensive 148
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medication use is important since less adherent patients will have poorer outcomes and increased 149
BP variability.35 150
We decided (a-priori) to include in the main analyses only those hazard ratios which were correctly 151
adjusted for the appropriate mean BP level (e.g. adjusted for mean daytime BP if variability assessed 152
over daytime ABPM readings), where outcome ascertainment took place after the BP measurement 153
period and, for studies involving antihypertensive treatment, if at least 80% of patients were 154
adherent to medication, did not change treatment during the measurement period or if patients 155
were censored at the point of treatment change. When these requirements were not met or it was 156
unclear, hazard ratios were only included as part of sensitivity analyses. 157
Results 158
Searches identified 4800 references. Removal of duplicates and screening by two reviewers yielded 159
twenty-nine full-text articles for inclusion (Figure 1). A further two full-text articles were included 160
from a relevant systematic review .25 These thirty-one papers represented seventeen observational 161
cohort studies and twelve clinical trial cohorts. Of these twenty-nine distinct studies, we were able 162
to extract sufficient data for meta-analysis from twenty-seven studies; the authors of two studies 163
failed to respond to requests for additional data. 164
Six papers studied ABPM,13,14,36–39 four papers studied home monitoring,40–43 thirteen studied clinic 165
monitoring15–17,19,20,44–51 and eight papers studied both clinic and ABPM.10,12,52–57 The number of 166
participants per study ranged from 45752 to 58,22851 and follow-up ranged from 2514 person-years52 167
to 101,011 person-years.36 Full details of included papers are given in Table 1. 168
Risk of bias 169
Using QUIPS, a majority of studies were rated at moderate risk of bias for study participation, often 170
due to inclusion criteria based on BP readings and a potential for regression to the mean effects 171
(Table e4). Many studies did not use consistent measurement devices for BP or used mercury 172
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sphygmomanometers and varying personnel. Information about cuff size, reading arm and 173
personnel was missing in the majority of studies. Whilst ABPM studies generally considered daytime 174
and night-time variability separately, most long term studies failed to consider seasonal variation. 175
Eleven studies were at high risk of bias because the measurement period for BP variability was 176
confounded with the follow-up period or because they failed to report non-significant results. These 177
were excluded from our main analysis as were results from studies in cohorts with changing 178
antihypertensive regimens or inappropriate adjustment for mean BP. Overall, results from sixteen 179
analyses were eligible for inclusion in our pre-specified main analysis (Table 2). 180
181
i) Long term variability measured through clinic BP monitoring 182
Twenty-one papers reported results from twenty-four studies that measured BP in clinic. Five 183
studies were primarily concerned with variability in ambulatory BP and only measured clinic BP at 184
baseline12,54–56 or had fewer than five clinic measurements,57 and two studies,46,53 one of which 185
examined both clinic and between ABPM variability,53 did not present results in sufficient detail for 186
extraction. 187
Of the seventeen studies with extractable data, eleven were excluded from the main analysis (Table 188
2). A majority of studies reported results for stroke events, for which systolic BP variability was a 189
significant predictor (Figure 2; standardized HR = 1.15, 95% CI [1.02 to 1.30]; I-squared = 85.6%, 190
p<0.001). Note that the standardized hazard ratio reflects the hazard ratio per one standard 191
deviation increase in BP variability. The HRs from the UK-TIA,58 ASCOT-BPLA,59 and Dutch TIA60 trials 192
(which were determined from analyses in subgroups of patients with previous transient ischaemic 193
attack or stroke) were significantly larger than the HRs reported by other studies. Removal of these 194
studies from the meta-analysis in a post-hoc sensitivity analyses reduced heterogeneity and resulted 195
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in smaller but non-significantly different pooled HRs (HR=1.09, 95% CI [1.04 to 1.14]; I-196
squared=0.0%, p=0.573). 197
Three studies examined long term systolic BP variability and all-cause mortality (Figure e1). 198
Increased variability in systolic BP was significantly associated with increased mortality (standardized 199
HR = 1.15, 95% CI [1.07 to 1.23]). Heterogeneity between studies (I-squared = 76.3%, p=0.015), was 200
reduced after removal of a study in patients with previous stroke or vascular disease45 and did not 201
significantly alter results (HR = 1.10, 95% CI [ 1.07 to 1.14]; I-squared=0.0%, p=0.805). 202
Only one study examined systolic BP variability and coronary heart disease events, showing a 203
marginally significant relationship (HR = 1.10, 95% CI [1.00 to 1.21]) which was unchanged in when 204
adding further studies in sensitivity analyses (Figure e2). 205
Results for CVD mortality, CVD events and myocardial infarction showed similar results (HR = 1.18, 206
95% CI [1.09 to 1.28], HR = 1.18, 95% CI [1.07 to 1.30] and HR = 1.22, 95% CI [1.08 to 1.37] 207
respectively, Figures e3 to e5). Results for diastolic BP variability are also given in the online 208
supplement (Figures e6 to e9) and showed similar sized hazard ratios. 209
210
ii) Short term variability measured through home BP monitoring 211
Four papers reported results from two studies that measured BP at home. Results from all four 212
papers could be included in the main analyses, but a lack of data from distinct study populations and 213
heterogeneity in terms of the outcome studied meant it was only possible to perform formal meta-214
analysis for the all-cause mortality outcome. Systolic BP variability was a significant predictor of 215
death regardless of whether BP was measured in the morning, evening, or in both the morning and 216
evening (Figure e10). 217
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Results for other outcomes are given in the online supplement (Table e5) along with the diastolic BP 218
results (Figure e11, Table e6). Morning systolic BP variability was predictive of all outcomes except 219
CHD death. Evening systolic BP variability was predictive of CVD death, stroke death and cerebral 220
infarction death. Variability in combined morning and evening measurements was predictive of 221
stroke mortality, non-CVD mortality and cerebral infarction mortality. 222
223
iii) Very short term variability measured through ambulatory BP monitoring 224
Fourteen papers examined variability in ambulatory BP in eleven distinct studies. Of these, one study 225
considered visit-to-visit variability in ambulatory BP, and has been considered above as part of the 226
long-term variability results.53 A further five studies were excluded from the main analysis due to 227
potential confounding (Table 2). 228
A single study examined daytime systolic BP variability and all-cause mortality, showing a significant 229
association between increased daytime variability and risk of death (Figure e12; standardized HR per 230
= 1.10, 95% CI [1.04 to 1.17]). When results from a further study were included in sensitivity 231
analyses, results did not change. Meta-analysis of two studies found no association between 232
daytime ABPM variability and coronary heart disease events in the main analysis (Figure e13; HR = 233
1.04, 95% CI [0.93 to 1.17]) although this became significant when adding data from a further study 234
in sensitivity analysis (HR= 1.05, 95% CI [1.01 to 1.10]). Daytime BP variability was significantly 235
associated with increased risk of stroke (Figure e14; HR = 1.11, 95% CI [1.01 to 1.21]). 236
The effects of daytime systolic variability on CVD mortality and CVD events were similar (HR = 1.11, 237
95% CI [1.01 to 1.22] and HR = 1.04, 95% CI [0.98 to 1.11] respectively, Figures e15 and e16). Results 238
for night-time and 24-hour systolic ABPM and diastolic ABPM are also detailed in the online 239
supplement (Figures e17 to e31). 240
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Discussion 241
This review, which has systematically assessed the literature for the association of visit-to-visit, day-242
by-day or hour-by-hour blood pressure variability with cardiovascular outcomes and mortality, found 243
that visit-to-visit variability in clinic BP measurements is significantly associated with all-cause and 244
CVD mortality, CVD events, stroke and myocardial infarction, independent of mean BP. Data for BP 245
variability across days and hours were more limited but broadly supported an association of shorter 246
term BP variability with cardiovascular outcomes. Across all analyses (clinic, home and ABPM), the 247
hazard ratios for coronary heart disease events were smaller than those for stroke, suggesting that 248
the effect observed for CVD events – as with mean blood pressure - may be driven primarily by 249
cerebrovascular events. 250
This review is, to the authors’ knowledge, the first review to evaluate the effect of BP variability on 251
outcomes across all three modalities of measurement, hence allowing comparison between each 252
modality. Despite heterogeneity of approach in defining variability, this is the first review where 253
reported hazard ratios have been standardized wherever possible to allow pooling across variability 254
measures, whereas previous studies used single measures of variability only,25,61, namely standard 255
deviation or coefficient of variation. This has allowed us to pool results from greater numbers of 256
studies; for example, our meta-analysis for long term variability and stroke events includes data 257
from eleven studies in which variability was measured by standard deviation, standardised residual, 258
coefficient of variation or root mean squared error, compared to previous work including data from 259
six25 and two61 studies measuring variability by standard deviation alone. This review is also the first 260
with sufficient data to enable meta-analysis of the effect of very short term BP variability on 261
outcomes, which was a limitation of a previous review of ambulatory BP variability,26 which 262
considered the effect of night-dipping and day-night variation on outcomes. 263
The results for variability in clinic blood pressure are in line with those reported in similar 264
reviews,25,61 which may seem unsurprising given some overlap in included studies. However, 265
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previous reviews included studies in haemodialysis patients, where treatment can directly impact BP 266
variability,62 studies with few repeat measurements63 and those with short follow-up. Furthermore, 267
previous reviews did not distinguish results from studies that may be confounded e.g. by measuring 268
BP variability during follow-up.17,52 Results from our main analyses, including only studies that avoid 269
these potential sources of confounding, are therefore robust to such confounding. Hence this 270
review is the first to confirm that the apparent prognostic value of BP variability is a true prospective 271
association and can be demonstrated even in studies that avoid potential sources of confounding. 272
Studies in patients with history of cerebrovascular events reported the largest HRs, suggesting that 273
BP variability may have additional benefit for predicting recurrent events in this population.10 274
However, since results did not change substantially after removal of these studies from analysis, the 275
findings remain applicable to broader populations free from cerebrovascular disease. Some studies 276
also explicitly recruited hypertensive patients,15,39,44 where blood pressure variability could be 277
confounded by entry criteria (leading to regression-to-the-mean effects) and treatment.64 However, 278
such effects would diminish rather than exaggerate hazard ratios for variability, so this issue does 279
not affect our overall conclusions. 280
A limitation of this review is that we were unable to perform formal meta-analyses for many 281
outcomes with respect to short term, day-by-day BP variability due to a lack of data from unique 282
cohorts. A previous review was also similarly limited by paucity of data,65 despite including studies 283
which assessed target organ damage (in addition to hard outcomes) and studies which would not 284
meet our strict criteria. Meta-analyses were possible for ambulatory (hour-by-hour) BP variability 285
results, but were dominated by one very large study which included eleven cohorts.36 This study 286
reported results for average real variability in BP, which may arguably be a better measure than 287
others, e.g. SD, for accurately reflecting gradual variation in daytime BP. However results for other 288
measures of variability from other studies were similar and our pooled results were similar to those 289
obtained from the single large study. It was also not possible to determine if the effect of variability 290
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varied with the timing or number of readings.10 Despite these caveats, results supported an effect of 291
shorter term variability on cardiovascular outcome, and pooled hazard ratios were similar to those 292
observed for long-term variability (overlapping point estimates and confidence intervals). 293
In several analyses, there was significant heterogeneity between studies. In some cases this may be 294
attributable to outlying studies in specific populations e.g. patients with previous vascular disease. 295
Hazard ratios in some papers had to be converted from a categorical (e.g. from deciles10 or tertiles49) 296
to a continuous scale and this is reliant on normal distribution assumptions which may hold only 297
approximately and hence inflate heterogeneity. Conversely, it is well established that categorising 298
continuous variables can result in biased estimates of effects and increase the chance of a spurious 299
false positive result.66–68 However, not all converted hazard ratios were outliers,14,55 and we verified 300
our conversion method in simulated data (not shown). In cases of significant heterogeneity, removal 301
of outlier studies did not significantly alter the results. 302
In some cases, few studies contributed to main analyses and the validity of these meta-analyses is 303
open to debate. The addition of results from potentially confounded studies in sensitivity analyses 304
greatly increased the amount of available data but did not materially change the findings. Some 305
papers failed to report results in enough detail to allow full extraction of data, but this was mitigated 306
by direct contact with authors requesting the relevant additional data. Only two46,53 otherwise 307
eligible studies failed to contribute any quantitative data. 308
In general, there was poor reporting of study factors that may confound the relationship between BP 309
variability and outcomes. Although studies were excluded from the main analysis based on three of 310
the most important factors (pre-specified) it was not possible to do this for a wider range of factors, 311
in particular those regarding BP measurement, without greatly reducing the available data. Further 312
adjustment for confounders might be possible using individual patient data and would also facilitate 313
comparison of the prognostic utility of different variability measures, but was beyond the scope of 314
this review. 315
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The mechanism linking blood pressure variability to cardiovascular events is not well understood. 316
Short term blood pressure variability is affected by a number of factors. Behavioural, emotional and 317
postural influences on cardiovascular physiology are important along with cardiac rhythm.69,70 318
Arterial stiffness contributes to both short71,72 and long term variability.70,73,74 Meanwhile poor 319
control of blood pressure resulting in changes to, and titration of, antihypertensive medications also 320
affects variability.69 Use of certain classes of antihypertensive medication has also been linked with 321
increased visit-to-visit variability11 and may not be entirely explained by variation in adherence.35 322
The estimated standardized hazard ratio for the effect of long term BP variability on CVD mortality 323
was 1.18. For comparison, the effect of mean BP on CVD mortality reported in a previous meta-324
analysis3 corresponds to a standardised hazard ratio of approximately 1.7 (assuming between-325
person standard deviation of 15 mmHg). Note that the latter standardized hazard ratio for mean BP 326
is not adjusted for BP variability, whereas the former (for BP variability) is adjusted for mean, and 327
hence the hazard ratios for BP mean and variability cannot be directly compared. However, BP 328
variability does add additional prognostic information over and above the mean. 329
How does BP variability compare with other risk factors for CVD? A recent review75 found that the 330
standardized hazard ratio for increases in total cholesterol on CVD death was 1.19, and so variability 331
in BP has similar prognostic value to cholesterol measures. However, BP variability, unlike other risk 332
factors, is less easily assessed currently. This may be overcome though: visit-to-visit variability could 333
be automatically calculated by electronic health records, assisting physicians to take into account 334
both BP mean and variability concurrently when assessing cardiovascular risk. This may be 335
particularly important for patients with highly variable, but comparatively low mean BP or for whom 336
the traditional cardiovascular risk estimate lies close to treatment thresholds. Further work is 337
needed to determine the feasibility of different methods and the clinical impact of such additional 338
information, on subsequent risk management. 339
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In summary visit-to-visit clinic BP variability in adults is associated with cardiovascular and mortality 340
outcomes, over and above the effect of mean BP. The current evidence of an association between 341
day-by day (home) or hour-by-hour (ABPM) BP variability and outcomes is unclear and requires 342
further investigation in novel cohorts. 343
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Contributors 344
SS, SW, RS, RM and PG helped to design the study. SS, SW, KL and RM carried out article screening. 345
SS, SW, KL, KC, RS and RM extracted data. SS, KC and RS carried out statistical analyses. SS drafted 346
the original manuscript and all authors revised the paper. SS is the guarantor. 347
Competing interest statement 348
All authors have completed the Unified Competing Interest form 349
atwww.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and 350
declare: i) SS is funded by the National Institute for Health Research School for Primary Care 351
Research (NIHR SPCR), ii) RM has received grants and personal fees from Omron and grants from 352
Lloyds Pharmacy, outside the submitted work; PG reports grants from National Heart Foundation, 353
Australia, outside the submitted work, iii) no other relationships or activities that could appear to 354
have influenced the submitted work. The views expressed are those of the author(s) and not 355
necessarily those of the NHS, the NIHR or the Department of Health. 356
Copyright 357
The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of 358
all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats 359
and media (whether known now or created in the future), to i) publish, reproduce, distribute, display 360
and store the Contribution, ii) translate the Contribution into other languages, create adaptations, 361
reprints, include within collections and create summaries, extracts and/or, abstracts of the 362
Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all 363
subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to 364
third party material where-ever it may be located; and, vi) licence any third party to do any or all of 365
the above. 366
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Figure 1: Study screening flowchart 587
588
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Table 1: Included study characteristics
Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
Asayama,
201240
Ohasama
(observational)
Home Men and women >35 years old, at
home during working hours, not
hospitalised, not incapacitated
2421 VIM, ARV, MMD (min-max
difference)
12 years (median) 27.1% Total mortality, CVD
mortality, stroke
events
Bjorklund,
200412
Uppsala
Longitudinal Study
of Adult Men
(observational)
ABPM and
clinic
(baseline)
70 year old men 872 SD 9.5 years (max,
mean 6.6 +/- 2.1
years)
30.0% CVD events
Carr,
201244
MRC Elderly trial Clinic Hypertensive patients with a mean
systolic BP at 160-209mmHg and
diastolic BP < 115mmHg at entry
4396 SR and RSV (Root successive
variance = SR divided by BP at
baseline)
5.8 years (mean) Yes (trial of
antihypertensive
medication)
Stroke events and
CHD events
Eguchi,
201252
Observational ABPM and
clinic
Asymptomatic patients aged 33-88
attending general internal medicine
clinics at three institutes in Japan, for
the evaluation and management of
hypertension
457 SD 66 months
(mean)
55.6% Hard CVD and all
CVD events
Gao,
201416
Observational Clinic US Primary care patients aged 60+ years
approached for a depression screening
study 1991-1993
2906 RMSE (root mean squared
error)
12.9 years
(median)
89.7% All-cause mortality,
CHD events or
stroke events
Gavish,
200913
Observational ABPM Non pregnant, greater than 16 years
old, good quality ABPM
3433 SD, CV and day/ night SD ratio 7.6 years (mean,
max 16 years)
59% All-cause mortality
Hansen,
201036
IDACO
(observational)
ABPM Multiple different populations in ABPM
database. Mean age 53 years.
8939 SD, ARV, mean of day and
night SD
11.3 years
(median)
19.6% All-cause mortality,
CVD mortality, CVD
events, cardiac,
coronary events and
stroke events
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Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
Hashimoto,
201241
Ohasama
(observational)
Home Japanese men. Mean age 58.6 years 902 SD, CV 13.1 years
(median)
26.1% All-cause mortality,
CVD mortality,
stroke mortality, MI
mortality, stroke
events
Hata,
201345
ADVANCE trial Clinic Patients aged 55+ years with type 2
diabetes and history of major macro- or
micro- vascular disease
8811 SD, CV 2.4 years
(median)
69% (at baseline but
trial of
antihypertensive
medication)
All-cause mortality,
CVD mortality
stroke, CVD events,
stroke events, MI
events
Hsieh,
201246
Observational Clinic Patients with type 2 diabetes visiting the
diabetic clinic in the Metabolism
Division at Changhua Christian hospital
Sept 2003-Apr 2005
2161 SD, CV 66.7 months
(mean)
80% All-cause and CVD
mortality
Johansson,
201242
Health 2000 study
(observational)
Home Finnish adults aged 45-74 years 1866 SD, CV, ARV and SD of day-
night difference and first-
second difference
7.8 years (mean) 30.6% All-cause mortality
and CVD events
Kawai,
201315
NOAH study
(observational)
Clinic Non-Invasive Atherosclerotic Evaluation
in Hypertension (NOAH) study.
Outpatients diagnosed with essential
hypertension sequentially recruited
between January 1998 and June 2004 at
Osaka University Medical Hospital
485 SD 7.59 years (mean) 47.3% CVD events
Kikuya,
200014
Ohasama
(observational)
ABPM Japanese general population > 40 years
(mean age 61.7 years, 40% men)
1542 SD 8.5 years (mean) 30.9% CVD mortality
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Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
Kikuya,
200843
Ohasama
(observational)
Home Japanese population 35-96 years (mean
age = 59.3 +/- 12.3 years). 60.5%
women.
2455 SD, CV 11.9 years
(median)
72.6% All-cause mortality,
CVD mortality, Non-
CVD mortality,
stoke mortality,
CHD mortality, MI
mortality
Kostis,
201447
SHEP (trial) Clinic Systolic hypertension in the elderly
program. Average age 72.
57% women and 15% black. USA.
4736 VIM, rSSR (sum of squared
deviations between average
and trend predicted BP),
VABS2 (variance of absolute
difference between
successive daily BP (VABS2)
17 years (max) 100% CVD mortality
Lau,
201417
Observational Clinic Ischaemic stroke patients without atrial
fibrillation, Hong Kong. Average age 71
years.
632 CV 76+/- 18 months
(mean)
80% All-cause mortality,
CVD mortality, non-
fatal stroke and
nonfatal acute
coronary syndrome
Mallamaci,
201348
Observational Clinic Italians aged 18-75 with CKD stages 3
and 4, recruited in renal clinics from Oct
2005 to Nov 2007
1618 SD, CV 37 months
(median)
94% CVD events
Mancia,
200737
PAMELA
(observational)
ABPM 2012 randomly selected individuals in
Milan aged 25-74 years
2012 SD 148 months (max) Not stated All-cause mortality
and CVD mortality
Mancia,
201253
ELSA trial ABPM and
clinic
European Lacidipine Study on
Atherosclerosis trial which randomized
antihypertensive treatment for 4 years
to mildly or moderately hypertensive
patients at relatively low cardiovascular
risk
1521 (clinic
analysis)
1264 (ABPM
analysis)
SD, CV 4 years (max) Yes (trial of
antihypertensive
medication)
CVD events
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Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
McMullan,
201349
AASK trial Clinic African American Study of Kidney
Disease trial. African Americans with
hypertensive nephropathy. Mean age 55
years, 62% men.
908 SD 75 months (max,
median 52
months).
Yes (trial of
antihypertensive
medication)
All-cause mortality,
CVD mortality, CVD
events
Mena,
201438
IDACO
(observational)
ABPM Discovery data: Copenhagen cohort
subjects equally distributed among sex
and age groups with complete ABPM
(41, 51, 61, and 71 years). Test data:
IDACO subjects 18+ years with at least
10 daytime
readings, 5 night-time readings, and 48
readings over 24 hours who were not
included in the discovery data.
1254 (discovery
data)
5353 (test data)
ARV 10.2 years
(median in test
data)
21.3% (test data) All-cause mortality,
CVD mortality, CHD
mortality, CVD
events, CHD events,
stroke events
Pierdomenico,
200556
Abruzzo, Italy
(observational)
ABPM and
clinic
(baseline)
Uncomplicated mild clinic hypertensive 1088 SD 4.74 years (mean) 87% at follow-up CVD events
Pierdomenico,
200654
Abruzzo, Italy
(observational)
ABPM and
clinic
(baseline)
Hypertensive patients undergoing ABPM
in Italy
1472 SD 4.88 years (mean) 100% CVD events
Pierdomenico,
200955
Abruzzo, Italy
(observational)
ABPM and
clinic
(baseline)
Hypertensive patients age 40+ years
who were referred for an outpatient
evaluation for hypertension in Italy
1280 SD, ARV 4.75 +/- 1.8 years
(mean, range 0.2-
7.5 years)
57.0% CVD events
Poortvliet,
201250
PROSPER trial Clinic Men and women aged 70–82 years from
Scotland, Ireland or Netherlands with
either pre-existing vascular disease
(coronary, cerebral, or peripheral) or at
high risk due to smoking, hypertension
or diabetes.
4819 (short-term
follow-up)
1808 (long-term
follow-up)
SD and CV 3 years (max,
mean 2.3 years)
or 9.3 years (max,
mean 7.1 years)
in Scottish sub-
group:
62.6% (short term
follow-up) 59.6% (long
term follow-up)
All-cause mortality,
CVD mortality,
stroke events, CHD
events
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Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
Pringle,
200357
Syst-Eur trial ABPM and
clinic
(placebo
run-in)
Elderly patients (60+ years) with
isolated systolic hypertension
744 SD 4.4 years
(median)
100% (384 on active
treatment in trial)
CVD mortality,
stroke events, CHD
events.
Rothwell,
201010
UK-TIA trial Clinic Patients with history of TIA, mean age
60.3 years.58
2006 SD, CV, VIM. 3.3 years
(median, max
6.67 years).
27%58 Stroke events
Rothwell,
201010
European Stroke
Prevention Study
(ESPS-1) (trial)
Clinic Patients with recent cerebrovascular
event76
2500 SD, CV, VIM. 2 years (max). Not stated Stroke events
Rothwell,
201010
Dutch TIA trial. Clinic Patients with recent TIA or stroke77 3150 SD, CV, VIM. 2.6 years (mean) 42%77 Stroke events
Rothwell,
201010
ASCOT BPLA trial
(subset of
stroke/TIA patients)
Clinic Patients with previous TIA or stroke 2011 SD, CV, VIM. 5 years (median) 100%59 Stroke, CVD and
CHD events
Rothwell,
201010
ASCOT BPLA trial
ABPM sub-study
(subset of stroke/
TIA patients)
ABPM Patients with previous TIA or stroke 1905 SD, CV, VIM. 5 years (median) 100%59 Stroke, CVD and
CHD events
Shimbo,
201251
Women’s Health
Initiative
(observational)
Clinic Post-menopausal women 58228 SD 5.4 years
(median)
Not stated Stroke events
Suchy-Dicey,
201319
Cardiovascular
Health Study
(observational)
Clinic Subjects not using antihypertensive
medication during a 5 year baseline
period or those using the same
antihypertensive regimen during that
period. Mean age 71 years. 95% white.
2548
(1570 no
antihypertensive
medication,
978 with
medication)
SR (standardised residual) 9.9 years (mean) 38.4% All-cause mortality,
MI events, stroke
events.
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Paper,
Year
Study Modality Population N Measure of Variability Follow-up Antihypertensive
medication
Outcome Measure
Verdecchia,
200739
PIUMA study
(observational)
ABPM Initially untreated subjects with
essential hypertension. Mean age = 51
years. 47% women.
2649 SD 6 years (mean,
max 16 years)
Untreated initially -
subsequent
antihypertensive use
recorded
CHD events
Wei,
201320
PROBE trial Clinic Hypertensive Chinese patients aged 70+
years
724 SD 4 years (mean) 100% CVD events
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Table 2: Study and analysis characteristics that may confound the relationship between blood pressure variability and outcomes
Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Asayama,
2012
Not
mentioned
Not
mentioned
Omron HEM
401C
Yes (home) Adjustment
for mean
BP
Not
mentioned but
inclusion not
based on BP
readings
Morning and
evening assessed
separately
Analysis
adjusted for
medication
use and
morning
measurements
taken before
medication
No
(observational,
followed
through
registries and
questionnaires)
Measurement
only over 4
weeks
First
reading in
morning/
evening
over 28
days
Yes
Bjorklund,
2004
Not
mentioned
Right arm
for office.
Non-
dominant
arm for
ABPM
Mercury for
office.
Accutracker 2
equipment for
ABPM
Yes (ABPM) No
adjustment
Not
mentioned but
inclusion not
based on BP
readings
Day and night
variability
assessed
separately
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
reading
every 20
mins.
No
adjustment
for mean BP
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Carr,
2012
Not
mentioned
Not
mentioned
Hawksley
Random Zero
Sphyg.
No -
physician
and nurse
Adjustment
for mean
BP
Trends for BP
modelled to
avoid
regression
dilution bias
No diurnal
variation given
as clinic BP only.
Seasonal pattern
present in the
raw data for
mean BP.
No. Nested
case-control
study but not
matched on
medication
adherence.
Adherence
low.
No (case-
control study
nested within
trial but
adherence and
cross-over not
considered)
Measure of
variability
based on
measures
preceding
event
Mean of
two
readings
fortnightly,
then
monthly,
then 3
monthly.
Treatment
adherence
low
Eguchi,
2012
Not
mentioned
Not
mentioned
Mercury sphyg
for office.
Yes for
ABPM.
Unclear for
clinic.
Adjusted
for clinic BP
only
Not
mentioned.
Inclusion
based on
referral due to
actual or
suspected
hypertension.
Not mentioned No No
(observational,
followed
through
registries and
interviews)
Unclear for
clinic, but yes
for ABPM
Clinic:
mean of
2nd and 3rd
reading
every
month.
ABPM:
every 30
mins.
Follow-up
and
measurement
confounded.
Adjusted
ABPM
analysis for
clinic mean
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Gao,
2014
Not
mentioned
Not
mentioned
Not mentioned
(routine data
source)
Unclear
(routine
data)
Yes (trend
adjusted)
BP not an
entry criteria
Not mentioned No (routine
data)
No
(observational.
Information
about
medications
collected but
not included in
time-
dependent
modelling)
No (routine
data)
Measure
in record
from
routine
visits
Follow-up
and
measurement
confounded.
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Gavish,
2009
Selected
according to
arm
circumference
.
Non
dominant
Pre 1999:
Accutracker 2.
Post 1999:
SpaceLabs 90207
Yes (ABPM) Analysis of
CV and
adjusted for
mean
arterial
pressure
Not
mentioned.
Patients
referred as
part of usual
care.
Only looked at
SD over 24 hours
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
reading
every 20
mins.
Incorrect
adjustment
for mean BP
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Hansen,
2010
Not
mentioned in
paper -
different
cohorts
Not
mentioned
in paper -
different
cohorts
Variable
depending on
cohort:
Accutracker 2 in
Uppsala, Space
Labs
90202/90207,
Nippon Colin,
ABPM-630 in
other cohorts
Yes (ABPM) Adjusted
for mean
BP
Not recruited
on basis of BP
Taken account of
via SDdn
measure
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
reading
every 30
mins.
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Hashimoto,
2012
Not
mentioned
Not
mentioned
Oscillometric
device: HEM
401C
Yes (home) Adjusted
for mean
BP
Not
mentioned but
inclusion not
based on BP.
No - all readings
within one hour
of waking.
No No
(observational,
followed
through
registries and
questionnaires)
Measurements
only over 4
weeks
Single
reading in
morning/
evening
over 28
days
Yes
Hata,
2013
Not
mentioned
Not
mentioned
Automated
sphyg (Omron
HEM 705CP)
Unclear Adjusted
for mean
BP
Not recruited
based on BP.
Measurements
at
randomization
not included in
assessment of
variability
Not mentioned No (50%
changed
regimen but
results similar
for those that
did/ did not
change)
No (trial, but
treatment
during follow-
up could be
modified)
Yes Mean of 2
readings at
3, 4, 6, 12,
18 and 24
months.
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Hsieh,
2012
Measurement
taken "after
cuff size was
corrected"
Not
specified
Standardized
automated
sphyg, Omron
HEM-1000
Not stated Adjusted
for mean
BP
Inclusion not
based on
baseline BP
measures
Not mentioned No No
(observational,
followed
through
registries)
Unclear Mean of
two
readings
every 2-6
months
No
extractable
data
Johansson,
2012
Not
mentioned
Not
mentioned
Omrom HEM
722C
Yes (home)
Adjusted
for mean
BP
Not recruited
based on BP.
SD of
morning/evening
difference
calculated
No No
(observational,
followed
through
registries)
Measurement
only over 7
days
2 readings
in morning
and
evening
for 7 days
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Kawai,
2013
Not
mentioned
Not
mentioned
Electronic sphyg
(HEM 705IT/
HEM-711)
Unclear Yes Not
mentioned but
recruited
based on
outpatient
diagnosis of BP
not values
Not mentioned Yes - 18
people
excluded if
treatment
altered in
measurement
period.
No
(observational,
followed
through
questionnaires)
Unclear Mean of 2
readings
every 1-2
months
Follow-up
and
measurement
confounded.
Kikuya,
2000
Not specified Not
specified
ABPM630
Nippon Colin
Yes (ABPM) Adjusted
for 24-hour
mean BP
Not
mentioned but
not recruited
based on BP.
Daytime and
night time
variability
analysed
separately
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
every 30
minutes
Incorrect
adjustment
for mean BP
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Kikuya,
2008
Not
mentioned
Not
mentioned
HEM 401C,
Omron
Healthcare
Yes (home) Analysis by
CV and
adjusted for
mean BP
Not
mentioned
explicitly
No - single home
reading taken in
the morning
No but
analysis
adjusted for
medication
use
No
(observational,
followed
through
registries)
Measurement
only over 4
weeks
One
reading
morning/
evening
for 28 days
Yes
Kostis,
2014
Not
mentioned
Not
mentioned
Random zero
sphyg
Unclear
(trained
personnel)
Adjusted
for mean
BP
Not
mentioned
Not mentioned No but
adherence
high and
analysis
results
restricted to
those patients
who did not
cross over
similar
No (trial, but
extended
observational
follow-up after
end of trial)
Yes 2 readings
at months
0, 1,2,3
and then 3
monthly
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Lau,
2014
Not
mentioned
Not
mentioned
Validated
automated BP
machine (GE,
DINAMAP,
PRO100,Fairfield,
CT)
Unclear Adjusted
for mean
BP
Not
mentioned but
not recruited
based on BP
Not mentioned No but
medication
adjusted for in
analysis
No
(observational,
followed
through
registries)
Unclear Mean of
2nd and 3rd
readings
every 3-4
months
Follow-up
and
measurement
confounded.
Mallamaci,
2013
Not
mentioned but
according to
ESH guidelines
Not
mentioned
but
according
to ESH
guidelines
Mercury sphyg No
nephrologist
OR nurse
Adjusted
for mean
BP
Not
mentioned but
recruited
based on eGFR
not BP
Not mentioned No No
(observational)
Unclear Mean of 3
readings
twice a
year for 3
years
Follow-up
and
measurement
confounded.
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Mancia,
2007
Not
mentioned
Not
mentioned
Spacelabs 90207 Yes (ABPM) Adjusted
for mean
24-hour BP
Not
mentioned but
not recruited
based on BP
SD for day and
night analysed
separately
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
reading
every 20
mins
Adjusted for
24-hour
mean in day
and night
analysis.
Mancia,
2012
Not
mentioned
Not
mentioned
Mercury sphyg Yes (ABPM)
but unclear
for clinic
(trained
physicians)
Mean BP
included in
models
Not
mentioned
Not mentioned Yes – only
clinic
measurements
after titration
period
included in
analysis
Yes (only
measurements
after titration
included,
measurement
and follow-up
period
coincides)
No Clinic:
mean of 3
readings
every 6
months.
ABPM:
mean of
24-hour
ABPM
yearly
No
extractable
data
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
McMullan,
2013
Not
mentioned
Not
mentioned
Random zero
sphyg
Not stated Adjusted
for mean
BP
Not
mentioned but
only post-
baseline
measures used
in the analysis
No - clinic BP Measurement
period after 3
month
titration
period but
adherence low
(71%)
No (only
compliance
during first 12
months
considered)
Yes Mean of
2nd and 3rd
readings at
4, 6, 8, 10
and 12
months
Adherence
low
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Mena,
2014
"Appropriate
cuff size"
Not
mentioned
Accutracker II in
Uppsala or
SpaceLabs 90202
and 90207,
Nippon Colin,
and ABPM 630
in the other
cohorts.
Yes (ABPM) Adjusted
for 24-hour
BP mean.
Not
mentioned but
not recruited
on BP
Only 24-hour
variability
considered
No but ABPM No
(observational,
followed
through
registries)
Yes (ABPM) Single
ABPM
reading
every 30
mins.
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Pierdomenico
,
2005
Not
mentioned
Not
mentioned
Clinic: mercury
sphyg, ABPM:
Spacelabs 90208
Yes (ABPM) Adjusted
for mean
BP
Not
mentioned but
recruited
based on
referral and
ABPM
occurred after
baseline
Not mentioned No but ABPM No
(observational,
follow-up
through family
doctors)
Yes (ABPM) Single
ABPM
reading
every 15
mins
No
extractable
data
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Pierdomenico
,
2006
"Appropriate
cuff size"
Not
mentioned
Clinic: mercury
sphyg, ABPM:
Spacelabs 90207
Yes (ABPM) Adjusted
for mean
BP
Not
mentioned but
recruited
based on
referral and
ABPM
occurred after
baseline
Analysis split by
day/ night.
No but ABPM No
(observational,
follow-up
through family
doctors)
Yes (ABPM) Single
ABPM
reading
every 15
mins
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Pierdomenico
,
2009
"Appropriate
cuff size"
Not
mentioned
Clinic: mercury
sphyg, ABPM:
Spacelabs 90207
Yes (ABPM) Adjusted
for mean
BP
Not
mentioned but
recruited
based on
referral and
ABPM
occurred after
baseline
Analysis split by
daytime and
night-time
ABPM.
No but ABPM No
(observational,
follow-up
through family
doctors)
Yes (ABPM) Single
ABPM
reading
every 15
mins
Yes
Poortvliet,
2012
Not
mentioned
Not
mentioned
Omron M4 Unclear
(trained
nurses)
Adjusted
for mean
BP
Not
mentioned but
not recruited
on BP
Not mentioned No but trial of
statins
No (long-term
follow-up
observational)
Yes, patients
with events
during
measurement
period
excluded
Once
every 3
months
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Pringle,
2003
"If arm
circumference
exceeded
31cm, larger
cuffs with
35x15 cm
bladder were
used"
Non-
dominant,
or arm
giving
highest
reading if
difference
of more
than
10mmHg
systolic
between
arms
Clinic: mercury
sphyg. ABPM:
Validated
monitors incl.
Spacelabs 90202
and 90207
Yes (ABPM) Adjusted
for mean
BP
Not
mentioned,
recruitment
based on clinic
BP not ABPM
Day-time and
night time
considered
separately and
combined
No but ABPM
and analysis
split by
treatment
group.
No (addition of
treatments
possible)
Yes (ABPM)
Single
ABPM
reading
every 30
minutes
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Rothwell,
2010: UK TIA
Not
mentioned
Not
mentioned
Mercury sphyg. Not
mentioned
Adjusted
for mean
BP
Not
mentioned but
inclusion
based on
previous
stroke history
Not mentioned RCT of aspirin
only.
No (RCT of
aspirin only
and follow-up
part of trial but
about a third
hypertensive
so could have
other
treatment)
Patients with
events in
measurement
period
excluded
Single
reading
every 4
months
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Rothwell,
2010: ESPS1
Not
mentioned
Both arms.
Mean of
left and
right
recorded.
Mercury sphyg. Not
mentioned
Adjusted
for mean
BP
Not
mentioned but
inclusion
based on stoke
history
Not mentioned Analysis of
placebo group
only due to
vasoactive
medication.
Yes, analysis of
placebo group
only and
follow-up part
of trial. Less
than 5% had
hypertension
and would be
eligible for
treatment)
Unclear Mean of 1
reading in
each arm
every 3
months
Follow-up
and
measurement
confounded.
Rothwell,
2010: Dutch
TIA
Not
mentioned
Not
mentioned
Mercury sphyg. Not
mentioned
Adjustment
for mean
BP
Not
mentioned but
inclusion
based on stoke
history
Not mentioned No. RCT of
aspirin with
atenolol
subgroup.
Analysis
excluding
subgroup
similar.
No, follow-up
part of trial
and subgroup
including
added atenolol
Unclear Single
reading
every 4
months
Follow-up
and
measurement
confounded.
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Rothwell,
2010: ASCOT
BPLA
Not
mentioned
Not
mentioned
Clinic: Omron
HEM-705CP
Unclear. Adjusted
for mean
BP
Not
mentioned
explicitly
Not mentioned No. RCT of
hypertensive
medication
with titration.
No, RCT with
titration.
Follow-up as
part of trial
Unclear Clinic:
mean of
2nd and 3rd
readings
every 6
months.
ABPM:
Every 30
mins.
Follow-up
and
measurement
confounded
for clinic
analysis.
Rothwell,
2010: ASCOT
BPLA ABPM
sub-study
Not
mentioned
Not
mentioned
ABPM:
SpaceLabs
90207.
Yes (ABPM), Unclear Not
mentioned
explicitly
Day and night
considered
separately
Yes (ABPM) No, RCT with
titration.
Follow-up as
part of trial
Yes (ABPM) Clinic:
mean of
2nd and 3rd
readings
every 6
months.
ABPM:
Every 30
mins.
Adjustment
for mean
unclear
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Shimbo,
2012
Appropriate
cuff size used
at each visit by
arm
measurement
Right Mercury sphyg Unclear
(certified
staff)
Adjusted
for mean
BP
Not recruited
based on BP
No - clinic BP No but
medication
included as
time
dependent
covariate in
models and
adjusted for
regression line
trend
Yes. Anti-
hypertensive
medication
was considered
as a
time
dependent
covariate.
Covariates
were updated
through follow
up (and post-
measurement)
whilst patient
remained at
risk.
Yes Mean of 2
readings
annually.
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Suchy-Dicey,
2013
Not
mentioned
Right arm Initial
measurement:
random zero
sphyg.
Remaining:
mercury sphyg
Not stated Adjusted
for mean
BP
Not
mentioned but
not recruited
on BP
Not mentioned Yes - users of
changing
medications
not included in
analysis
No (only
restricted
analysis to
users of
changing
medications
during
measurement
not follow-up)
Yes Mean of
2nd and 3rd
readings, 5
times
annually.
Yes
Verdecchia,
2007
Not
mentioned
Not
mentioned
ABPM:
SpaceLabs 5200,
90202, 90207
Yes (ABPM) Adjusted
for mean
BP
Not
mentioned.
Recruitment
based on
office BP not
ABPM.
Daytime and
night-time
variability
considered
separately
No but ABPM No
(observational
follow-up
through family
doctors)
Yes (ABPM) Single
ABPM
every 15
minutes
Yes
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Paper,
Year
Study design characteristics Potential confounders Main analysis
(yes or
reason for
exclusion)
Cuff Size Reading
Arm
Device used Same
person
taking
readings
Adjustment
for
appropriate
mean
Regression to
mean
considered
Diurnal or
Seasonal
variation
considered
Medication
change during
measurement
period limited
Medication
change during
follow-up
limited
Measurement
before follow-
up
Definition
of single
reading
Wei,
2013
Not
mentioned
Right arm Manual sphyg Unclear Adjusted
for mean
BP
Not
mentioned
explicitly, but
entry to trial
based on two
readings on
two days
Not mentioned No – after one
year many had
increase in
number of
medications
No (trial but
medication
change
possible)
Unclear Mean of 2
readings
every 6
months
Follow-up
and
measurement
confounded.
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Figure 2
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1
Online supplement
Table e1: Search strategy
CINAHL (EBSCOHost)
S24 S22 OR S23 Limiters - Clinical Queries: Prognosis - Specificity
S23 S20 OR S21 Limiters - Clinical Queries: Prognosis - High Sensitivity
S22 S20 OR S21
S21 TI ( ((blood pressure or bp or sbp or dbp) N5 (variabilit* or variation*)) ) OR AB ( ((blood pressure or bp or sbp or dbp) N5
(variabilit* or variation*)) )
S20 S3 AND S6 AND S19
S19 S7 OR S8 OR S9 OR S10 OR S11 OR S12 OR S13 OR S14 OR S15 OR S16 OR S17 OR S18
S18 TI within subject* OR AB within subject*
S17 TI ( (dipping or dipper* or nondipping or nondipper* or non-dipping or non-dipper*) ) OR AB ( (dipping or dipper* or nondipping or nondipper* or non-dipping or non-dipper*) )
S16 TI ( (((daytime or day-time or diurnal) N5 (blood pressure or bp or sbp or sbp)) and ((night-time or nocturnal) N5 (blood pressure or bp or sbp or sbp))) ) OR AB ( (((daytime or day-time or diurnal) N5 (blood pressure or bp or sbp or sbp)) and
((night-time or nocturnal) N5 (blood pressure or bp or sbp or sbp))) )
S15 TI ( ((daytime or day-time or diurnal) N5 (night-time or nocturnal)) ) OR AB ( ((daytime or day-time or diurnal) N5 (night-
time or nocturnal)) )
S14 TI repeat* measure* OR AB repeat* measure*
S13 TI "measure* to measure*" OR AB "measure* to measure*"
S12 TI ( ("day to day" or "day by day") ) OR AB ( ("day to day" or "day by day") )
S11 TI ( "between day" OR "within day" ) OR AB ( "between day" OR "within day" )
S10 TI "visit to visit" OR AB "visit to visit"
S9 TI ( ((between or within) N3 visit*) ) OR AB ( ((between or within) N3 visit*) )
S8 TI variation*
S7 TI ( variability or variabilities ) OR AB ( variability or variabilities )
S6 S4 OR S5
S5 TI ( blood pressure or bp or sbp or dbp ) OR AB ( blood pressure or bp or sbp or dbp )
S4 (MH "Blood Pressure") OR (MH "Blood Pressure Determination")
S3 S1 OR S2
S2 TI ( hypertensive* or hypertension* or antihypertens* or anti-hypertens* ) OR AB ( hypertensive* or hypertension* or antihypertens* or anti-hypertens* )
S1 (MH "Hypertension+")
Embase (OvidSP)
1 *hypertension/
2 (hypertensive* or hypertension* or antihypertens* or anti-hypertens*).ti,ab.
3 1 or 2
4 *Blood Pressure/
5 exp *blood pressure measurement/
6 (blood pressure or bp or sbp or dbp).ti,ab.
7 4 or 5 or 6
8 (variability or variabilities).ti,ab.
9 variation?.ti.
10 ((between or within) adj3 visit?).ti,ab.
11 "visit to visit".ti,ab.
12 ((between or within) adj day?).ti,ab.
13 ("day to day" or "day by day").ti,ab.
14 "measure* to measure*".ti,ab.
15 "reading? to reading?".ti,ab.
16 repeat* measure*.ti,ab.
17 ((daytime or day-time or diurnal) adj5 (night-time or nocturnal)).ti,ab.
18 (((daytime or day-time or diurnal) adj5 (blood pressure or bp or sbp or sbp)) and ((night-time or nocturnal) adj5 (blood pressure or bp
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or sbp or sbp))).ti,ab.
19 (dipping or dipper? or nondipping or nondipper? or non-dipping or non-dipper?).ti,ab.
20 within subject?.ti,ab.
21 8 or 9 or 10 or 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18 or 19 or 20
22 3 and 7 and 21
23 blood pressure variability/
24 3 and 23
25 ((blood pressure or bp or sbp or dbp) adj5 (variabilit* or variation?)).ti,ab.
26 22 or 24 or 25
27 ((exp animal/ or exp vertebrate/ or exp invertebrate/) not human/) or animal experiment/ or animal model/ or animal tissue/ or animal
cell/ or nonhuman/
28 26 not 27
29 follow up.mp. or ep.fs. or prognos*.tw.
30 28 and 29
31 (prognos* or survival).tw.
32 28 and 31
33 30 or 32
Medline (OvidSP)
1 exp Hypertension/
2 (hypertensive* or hypertension* or antihypertens* or anti-hypertens*).ti,ab.
3 1 or 2
4 *Blood Pressure/
5 *Blood Pressure Determination/
6 (blood pressure or bp or sbp or dbp).ti,ab.
7 4 or 5 or 6
8 (variability or variabilities).ti,ab.
9 variation?.ti.
10 ((between or within) adj3 visit?).ti,ab.
11 "visit to visit".ti,ab.
12 ((between or within) adj day?).ti,ab.
13 ("day to day" or "day by day").ti,ab.
14 "measure* to measure*".ti,ab.
15 "reading? to reading?".ti,ab.
16 repeat* measure*.ti,ab.
17 ((daytime or day-time or diurnal) adj5 (night-time or nocturnal)).ti,ab.
18 (((daytime or day-time or diurnal) adj5 (blood pressure or bp or sbp or sbp)) and ((night-time or nocturnal) adj5 (blood pressure or bp
or sbp or sbp))).ti,ab.
19 (dipping or dipper? or nondipping or nondipper? or non-dipping or non-dipper?).ti,ab.
20 within subject?.ti,ab.
21 8 or 9 or 10 or 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18 or 19 or 20
22 3 and 7 and 21
23 ((blood pressure or bp or sbp or dbp) adj5 (variabilit* or variation?)).ti,ab.
24 22 or 23
25 exp animal/ not human/
26 24 not 25
27 incidence.sh. or exp mortality/ or follow-up studies.sh. or prognos*.tw. or predict*.tw. or course*.tw.
28 26 and 27
29 (prognos* or first episode or cohort).tw.
30 26 and 29
31 28 or 30
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Web of Science:
# 17 #16 AND #15
# 16 Topic=(prognos* OR cohort* OR incidence OR mortality OR "follow-up" OR predict OR course)
# 15 #14 AND #13
# 14 Topic=(hypertens* OR antihypertens* OR anti-hypertens*)
# 13 #12 OR #2 OR #1
# 12 #11 AND #3
# 11 #10 OR #9 OR #8 OR #5 OR #4
# 10 Topic=("within subject*")
# 9 Topic=(dipping or dipper* or nondipping or nondipper* or non-dipping or non-dipper*)
# 8 #7 AND #6
# 7 Topic=(nightime NEAR/5 ("blood pressure" or bp or sbp or dbp)) OR Topic=(nocturnal NEAR/5 ("blood pressure" or bp or sbp
or dbp))
# 6 Topic=(daytime NEAR/5 ("blood pressure" or bp or sbp or dbp)) OR Topic=(day-time NEAR/5 ("blood pressure" or bp or sbp or
dbp)) OR Topic=(diurnal NEAR/5 ("blood pressure" or bp or sbp or dbp))
# 5 Topic=((daytime NEAR/5 (night-time or nocturnal))) OR Topic=((day-time NEAR/5 (night-time or nocturnal))) OR
Topic=((diurnal NEAR/5 (night-time or nocturnal)))
# 4 Topic=(between NEAR/3 visit*) OR Topic=(within NEAR/3 visit*) OR Topic=("between day*" OR "within day*") OR
Topic=("day to day" OR "day by day") OR Topic=("measure to measure") OR Topic=("measurement to measurement") OR
Topic=("repeat measur*" OR "repeated measur*") OR Topic=("visit to visit") OR Topic=("reading to reading" OR "readings to readings")
# 3 Topic=("blood pressure" OR bp OR sbp OR dbp)
# 2 Title=(variation* OR variability OR variabilities) AND Title=("blood pressure" OR bp OR sbp OR dbp)
# 1 Topic=("blood pressure" NEAR/5 (variability OR variabilities OR variation*)) OR Topic=(bp NEAR/5 (variability OR
variabilities OR variation*)) OR Topic=(dbp NEAR/5 (variability OR variabilities OR variation*)) OR Topic=(sbp NEAR/5
(variability OR variabilities OR variation*))
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Table e2: Extracted information
Patient characteristics
Number of participants Gender
Age Source population
Proportion on anti-hypertensive medication
Study characteristics
Type of monitoring Type of study (trial/ observational)
Measurement device used* Measurement arm*
Person taking readings* Cuff size used*
Length of monitoring period Outcomes studied
Length of follow-up Variability measures studied
Authors overall conclusion
Statistical analysis
Analysis strategy Definition of a single measurement*
Variability measure Outcome
Systolic or diastolic BP Units of reported hazard ratio
Reported hazard ratio/ 95% confidence interval Standard deviation of variability measure
Adjustment for equivalent mean BP* Diurnal/ Seasonal variation considered*
Regression to the mean considered*
Medication change during measurement period limited/ adjusted for*
Medication change during follow-up period limited/ adjusted for*
*considered as potential confounders of the effect of BP variability on outcomes.
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Table e3: Standardized hazard ratios explanation
A standardized beta coefficient is calculated as the beta coefficient per unit of the standardized exposure (the
exposure divided by its sample SD). For proportional hazards models, the beta-coefficient is the logarithm of the
hazard ratio. For example, for Eguchi et al. (2012) reported that the standard deviation of SBP is 20 mm Hg and
the HR per 10 mm Hg of mean SBP is 1.18; hence the beta coefficient is 0.166 per 10 mm Hg, the standardized
beta coefficient is 0.331 per SD and the standardized hazard ratio is 1.39 per SD. This has an interpretation as
“hazard ratio per one SD of SBP”. Because our exposure measurements include SD of SBP, and the phrase
“hazard ratio per one SD of SD” may not promote clarity, we use the term “standardized hazard ratio” rather
than “hazard ratio per one SD”.
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Table e4: Risk of bias assessment
Paper, year Study Study Participation Study Attrition Prognostic Factor Measurement Outcome Measurement Study Confounding Statistical Analysis and Reporting
Asayama, 2012
Ohasama (observational)
moderate low low low low low
Bjorklund,
2004
Uppsala Longitudinal
Study of Adult Men (observational)
low moderate low low moderate low
Carr,
2012
MRC Elderly trial moderate moderate moderate moderate low low
Eguchi,
2012
Observational moderate low low high moderate low
Gao, 2014
Observational low low moderate high high low
Gavish,
2009
Observational moderate low moderate low moderate low
Hansen,
2010
IDACO
(observational)
moderate low low low low low
Hashimoto, 2012
Ohasama (observational)
moderate low low low low low
Hata,
2013
ADVANCE trial low low low low low low
Hsieh,
2012
Observational low low low high low low
Johansson,
2012
Health 2000 study
(observational)
low low low low low low
Kawai, 2013
NOAH study (observational)
low moderate moderate moderate low low
Kikuya,
2000
Ohasama
(observational)
moderate low low low moderate low
Kikuya,
2008
Ohasama
(observational)
moderate moderate low low low low
Kostis, 2014
SHEP (trial)
moderate low moderate low low low
Lau,
2014
Observational low high low high low low
Mallamaci,
2013
Observational moderate low moderate high low low
Mancia,
2007
PAMELA
(observational)
moderate low low low moderate low
Mancia,
2012
ELSA trial moderate low low high low moderate
McMullan,
2013
AASK trial moderate low moderate moderate low low
Mena, 2014
IDACO (observational)
moderate low low low low low
Pierdomenico, Abruzzo, Italy moderate moderate low moderate low high
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Paper, year Study Study Participation Study Attrition Prognostic Factor Measurement Outcome Measurement Study Confounding Statistical Analysis and Reporting
2005 (observational)
Pierdomenico, 2006
Abruzzo, Italy (observational)
moderate moderate low moderate low low
Pierdomenico,
2009
Abruzzo, Italy
(observational)
moderate moderate low moderate low low
Poortvliet,
2012
PROSPER trial low low low low low low
Pringle, 2003
Syst-Eur trial moderate low moderate low low low
Rothwell,
2010
UK-TIA trial low low moderate low low low
Rothwell,
2010
European Stroke
Prevention Study
(ESPS-1) (trial)
low low moderate high low low
Rothwell,
2010
Dutch TIA trial. low low moderate high low low
Rothwell,
2010
ASCOT BPLA trial moderate low low high low low
Rothwell, 2010
ASCOT BPLA ABPM substudy
low low low low moderate low
Shimbo,
2012
Women’s Health
Initiative (observational)
low moderate moderate low low low
Suchy-Dicey,
2013
Cardiovascular Health
Study (observational)
moderate low moderate low low low
Verdecchia,
2007
PIUMA study
(observational)
moderate low low moderate low moderate
Wei,
2013
PROBE trial low moderate moderate high moderate low
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Figure e1
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Figure e2
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Figure e3
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Figure e4
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Figure e5
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Figure e6
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Figure e7
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Figure e8
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Figure e9
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Figure e10
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Table e5: Hazard ratios (HRs) for cardiovascular and mortality outcomes per standard deviation increase in home systolic blood pressure (BP) variability
Morning measurements Evening measurements Morning and evening measurements
Outcome Variability
measure
Paper [Study],
year
HR (95% CI) Variability
measure
Paper [Study],
year
HR (95% CI) Variability
measure
Paper [Study],
year
HR (95% CI)
CVD mortality VIM Asayama [Ohasama],
2012
1.26
(1.07, 1.49)
VIM Asayama [Ohasama],
2012
1.23
(1.05, 1.45)
SD Kikuya [Ohasama],
2008
1.16
(0.99, 1.36)
CHD mortality SD Hashimoto
[Ohasama], 2012
0.84
(0.59, 1.19)
SD Kikuya [Ohasama],
2008
0.99
(0.79, 1.25)
SD Kikuya [Ohasama],
2008
1.02
(0.81, 1.29)
Stroke mortality SD Hashimoto
[Ohasama], 2012
1.47
(1.11, 1.95)
SD Kikuya [Ohasama],
2008
1.38
(1.12, 1.70)
SD Kikuya [Ohasama],
2008
1.31
(1.05, 1.64)
Non-CVD
mortality
SD Kikuya [Ohasama],
2008
1.18
(1.04, 1.34)
SD Kikuya [Ohasama],
2008
1.07
(0.94, 1.22)
SD Kikuya [Ohasama],
2008
1.15
(1.01, 1.31)
Cerebral
infarction
mortality
SD Hashimoto
[Ohasama], 2012
1.88
(1.31, 2.69)
SD Kikuya [Ohasama],
2008
1.42
(1.08, 1.86)
SD Kikuya [Ohasama],
2008
1.47
(1.11, 1.95)
CVD events SD Johansson [Health
2000], 2012
1.17
(1.02, 1.34)
SD Johansson [Health
2000], 2012
1.08
(0.93, 1.26)
SD Johansson [Health
2000], 2012
1.06
(0.93, 1.22)
Stroke events VIM Asayama [Ohasama],
2012
1.14
(1.00, 1.30)
VIM Asayama [Ohasama],
2012
1.06
(0.93, 1.21)
- - -
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Figure e11
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Table e6: Hazard ratios (HRs) for cardiovascular and mortality outcomes per standard deviation increase in home diastolic blood pressure (BP) variability
Morning measurements Evening measurements Morning and evening measurements
Outcome Variability
measure
Paper [Study],
year
HR (95% CI) Variability
measure
Paper [Study],
year
HR (95% CI) Variability
measure
Paper [Study],
year
HR (95% CI)
CVD mortality SD Kikuya [Ohasama],
2008
1.14
(0.98, 1.32)
SD Kikuya [Ohasama],
2008
1.13
(0.96, 1.33)
- - -
CHD mortality SD Kikuya [Ohasama],
2008
1.02
(0.81, 1.28))
SD Kikuya [Ohasama],
2008
0.97
(0.76, 1.23)
- - -
Stroke mortality SD Kikuya [Ohasama],
2008
1.26
(1.03, 1.55)
SD Kikuya [Ohasama],
2008
1.27
(1.04, 1.56)
- - -
MI mortality SD Kikuya [Ohasama],
2008
0.76
(0.52, 1.12)
SD Kikuya [Ohasama],
2008
0.63
(0.41, 0.97)
- - -
Non-CVD mortality SD Kikuya [Ohasama],
2008
1.09
(0.97, 1.23)
SD Kikuya [Ohasama],
2008
1.09
(0.96, 1.24)
- - -
Cerebral infarction
mortality
SD Kikuya [Ohasama],
2008
1.30
(1.00, 1.68)
SD Kikuya [Ohasama],
2008
1.33
(1.03, 1.72)
- - -
CVD events SD Johansson [Health
2000], 2012
1.23
(1.09, 1.39)
SD Johansson [Health
2000], 2012
1.12
(0.97, 1.28)
SD Johansson [Health
2000], 2012
1.16
(1.01, 1.34)
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Figure e12
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Figure e13
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Figure e14
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Figure e15
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Figure e16
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Figure e17
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Figure e18
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Figure e19
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Figure e20
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Figure e21
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Figure e22
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Figure e23
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Figure e24
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Figure e25
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Figure e26
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Figure e28
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Figure e29
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Figure e30
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Figure e31
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