Abstract
Background
Hypertension is a leading cause of premature mortality and morbidity. Recent guidelines advocate for out-of-office blood pressure monitoring, including ambulatory and home BP monitoring, to better identify hypertension phenotypes like masked hypertension, white coat hypertension, and sustained hypertension. However, clinical inertia persists due to a lack of robust evidence on the effectiveness of screening these phenotypes and their association with cardiovascular and all-cause mortality. This systematic review and meta-analysis aims to evaluate the relationship between various hypertension phenotypes and future cardiovascular events and all-cause mortality to support the broader implementation of out-of-office BP monitoring.
Main body
Following PRISMA, Cochrane, and MOOSE guidelines, we conducted a comprehensive search in Pubmed, OvidSP, and Cochrane Central databases up to October 17, 2023. Eligible studies reported associations between hypertension phenotypes and cardiovascular or all-cause mortality, with normotension as the reference group. Hazard ratios with 95% confidence intervals (CIs) were pooled using random-effects models. Eight studies with 15,327 participants were included. Masked hypertension was associated with increased cardiovascular mortality (pooled HR 2.05, 95% CI 1.69–2.48). Sustained hypertension also showed a higher risk (pooled HR 2.42, 95% CI 2.12–2.76). WCH did not significantly increase cardiovascular mortality risk (pooled HR 1.18, 95% CI 0.98–1.42). For all-cause mortality, neither masked hypertension (pooled HR 2.10, 95% CI 0.91–4.88) nor white coat hypertension (pooled HR 1.96, 95% CI 0.71–5.42) showed significant increases.
Conclusion
Masked hypertension and sustained hypertension are linked to higher cardiovascular mortality compared to normotension, highlighting the importance of out-of-office BP monitoring to identify and manage high-risk phenotypes effectively. Further high-quality studies are needed to generalize these findings and support policy changes.
Supplementary Information
The online version contains supplementary material available at 10.1186/s43044-024-00597-w.
Keywords: White coat hypertension, Masked hypertension, Cardiovascular mortality, All-cause mortality
Background
Globally, hypertension is the primary preventable cause of premature mortality and morbidity [1]. The most common way to diagnose hypertension is through blood pressure measurements in the office. Conversely, recent guidelines for the diagnosis and management of hypertension firmly advocate for BP monitoring outside the office, including ambulatory BP monitoring (ABPM) and self-BP monitoring (SBPM) or home BP monitoring (HBPM) [2]. Several blood pressure phenotypes with varying prognostic implications for long-term cardiovascular risk have been identified as a result of the greater implementation of blood pressure monitoring out-of-office in recent years [3]. These blood pressure phenotypes are difficult to diagnose without the readings of both in the office and out-of-office measurements. They comprise sustained normotension, which is defined as normal in the office and outside the office blood pressure in people who are not taking antihypertensive medication; controlled hypertension, which is defined as normal in the office blood pressure and outside the office blood pressure in people taking antihypertensive medication; masked hypertension (MH), which is defined as normal in the office blood pressure but elevated outside the office; white coat hypertension (WCH); increased in the office but normal outside the office blood pressure, which is defined as WCH in individuals that are not on any antihypertensive medications, and as white coat effect (WCE) or white coat uncontrolled hypertension in people taking antihypertensive medication; and uncontrolled hypertension or sustained hypertension, which is elevated in the office and outside the office blood pressure readings [4].
There has been a clinical inertia for adopting this outside the office BP monitoring, despite guideline recommendations, which is most probably due to various patient, provider, and policy-related hurdles. A significant obstacle in obtaining outside the office blood pressure readings is the lack of evidence surrounding the effectiveness of screening for the various phenotypes of hypertension [5]. The studies done for quantifying the relationship between the various phenotypes of hypertension and associated cardiovascular and all-cause mortality have shown inconsistent results [4].
Our goal in conducting this systematic review and meta-analysis (SRMA) is to fully evaluate the relationship between future cardiovascular events and all-cause mortality in the various phenotypes of hypertension. These data may encourage BP monitoring outside of the office to be more broadly recognized and accepted as the standard of care and may help shape policy changes that increase funding and support BP monitoring outside of the office.
Methods
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were adhered to, and the Cochrane Handbook for Systematic Reviews of Interventions principles were followed in this meta-analysis [6]. The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed [7]. The study protocol is registered with PROSPERO under registration number CRD42023473231.
Study selection criteria
The following PICOS criteria were used to identify and select studies for this meta-analysis: population (P) of interest was people with white coat hypertension, masked hypertension, or sustained hypertension; intervention (I) was not applicable; controls (C) were normotensive people; and the outcomes (O) were cardiovascular mortality, all-cause mortality.
Only publications in the English language that (1) reported associations between different phenotypes of hypertension and cardiovascular mortality, or all-cause mortality, and (2) included a reference group of people with normotension or controlled hypertension, were eligible for inclusion. To ascertain eligibility, two investigators (JT and KAQ) independently screened abstracts and evaluated full texts. A third reviewer resolved any discrepancies (SR).
Search strategy
An electronic search was undertaken in Pubmed, OvidSP, and Cochrane Central databases from inception till 17 October 2023 using appropriate MeSH terms. The search strategy has been included in the supplementary file 1.
Data extraction
Using standardized forms, two investigators (JT and KAQ) separately extracted data from every eligible publication. Cohort name, year of publication, type, and duration of out-of-office blood pressure measurement, the total number of study participants, number of participants with a history of diabetes, number of current smokers and male sex, mean age, body mass index, length of follow-up, and type of outcome (cardiovascular mortality or all-cause mortality) were among the extracted data. All the included studies utilized the ACC/AHA criteria for classifying the subjects into various phenotypes of hypertension, i.e., the thresholds were 140/90 mmHg for office BP and 135/85 mmHg for home BP. Any discrepancies were resolved by a third reviewer (AR).
Risk of bias assessment
Three authors (JT, KAQ, and AT) independently assessed the risk of bias in the included study using the Risk Of Bias In Non-randomized Studies—of Exposures (ROBINS-E) tool [8]. The studies were judged under seven domains. The risk of bias (ROB) table and graph were generated using the Robvis tool [9].
Measures of treatment effect
Cardiovascular mortality and all-cause mortality were represented as Hazard ratios (HRs) with 95% confidence intervals (CIs). The data were pooled using pooled logarithm hazard ratios using random-effects inverse-variance models, with profile likelihood estimation [10]. The analysis was done on Revman 5.4 [11].
Heterogeneity assessment
The τ2 and I2 tests were also used to assess heterogeneity. Significant heterogeneity is present when the P-value is less than 0.5. The significance of I2 values depended on the strength of the evidence supporting heterogeneity and the direction and magnitude of treatment effects.
Data synthesis
A random-effects model was used to pool the data to analyze the outcomes, which were reported as 95% confidence intervals (95% CIs). Using Revman 5.4, forest plots were created. Statistical significance was attained when the P-value was less than 0.05. The hazard ratios were pooled using logarithm hazard ratios using inverse-variance models [10].
Results
Study selection and characteristics
Following our initial search (from inception till 17 October 2023), we found 643 articles (Pubmed-253; OvidSP-388; and Cochrane Central-2). After de-duplication (150 duplicates) and screening the articles based on title, abstract, and finally the main text, we finally included 8 studies in the quantitative analysis. The PRISMA study flowchart is shown in Fig. 1 [12]. The characteristics of the included studies and the demographic characteristics of the included participants are shown in Tables 1 and 2, respectively.
Fig. 1.
Study selection and inclusion flowchart
Table 1.
Characteristics of eligible studies
| Study | Year of study | Country | Cohort | Type of measurement | Study duration | Total number of participants |
|---|---|---|---|---|---|---|
| Bobrie et al., [13] | 2004 | France | SHEAF | Home BP | 3 Years | 4939 |
| Hänninen et al., [14] | 2012 | Finland | Finn-Home | Home BP | 7.5 Years | 2046 |
| Hermida et al. [15] | 2012 | Spain | MAPEC | 48-h ABPM | 5.6 Years | 3344 |
| Minutolo et al., [16] | 2014 | Italy | Italy-CKD | 24-h ABPM | 5.2 Years | 512 |
| Pereira et al. [17] | 2020 | Brazil | CKD Cohort | 24-h ABPM | 8 Years | 367 |
| Pierdomenico et al. [18] | 2017 | Italy | Chieti-Pescara | 24-h ABPM | 9.1 Years | 1191 |
| Satoh et al. [19] | 2015 | Japan | Ohasama | 24-h ABPM and Home BP | 17.1 Years | 1464 |
| Satoh et al., 2 [20] | 2018 | Japan | Ohasama | 24-h ABPM and Home BP | 17.1 Years | 1464 |
Table 2.
Baseline participant characteristics of included studies
| Study | Males (%) | Mean age | Diabetes (%) | Smokers (%) | Mean BMI, kg/m2 |
|---|---|---|---|---|---|
| Bobrie et al., [13] | 49 | 70 | 15 | 8 | NR |
| Hänninen, et al., [14] | 46 | 56 | 6 | 19 | 27.4 |
| Hermida et al. [15] | 51 | 53 | 20 | 15 | 29.8 |
| Minutolo et al., [16] | 57 | 64 | 34 | 22 | 28.9 |
| Pereira et al. [17] | 44 | 60 | NR | NR | NR |
| Pierdomenico et al. [18] | 42 | 68 | 12 | 12 | 27.9 |
| Satoh et al. [19] | 32 | 61 | 14 | 15 | 23.4 |
| Satoh et al., 2 [20] | 32 | 61 | 14 | 15 | 23.4 |
NR Not reported
Risk of bias assessment
The risk of bias assessment summary has been shown in the ROB table and ROB summary plot in Figs. 2 and 3, respectively.
Fig. 2.
Fig. 3.
Risk of bias summary plot
Cardiovascular mortality
Masked hypertension versus normotension
Eight studies were included in the analysis of cardiovascular mortality in people with masked hypertension versus normotension. The pooled HR was 2.05 with a 95% CI of 1.69–2.48. The overall effect was significant [Z = 7.36 (P < 0.00001)]. Insignificant heterogeneity was seen (P = 0.72). The forest plot is shown in Fig. 4.
Fig. 4.
Forest plot for cardiovascular mortality; comparing masked hypertension and normotension. Legend: References: [13–20]
White coat hypertension versus normotension
Eight studies were included in the analysis of cardiovascular mortality in people with white coat hypertension versus normotension. The pooled HR was 1.18 with a 95% CI of 0.98–1.42. The overall effect was insignificant [Z = 1.79 (P = 0.07)]. Insignificant heterogeneity was seen (P = 0.72). The forest plot is shown in Fig. 5.
Fig. 5.
Forest plot for cardiovascular mortality; comparing white coat hypertension and normotension. Legend: References: [13–20]
Sustained hypertension versus normotension
Seven studies were included in the analysis of cardiovascular mortality in people with sustained hypertension versus normotension. The pooled HR was 2.42 with a 95% CI of 2.12–2.76. The overall effect was significant [Z = 12.98 (P < 0.00001)]. Insignificant heterogeneity was seen (P = 0.76). The forest plot is shown in Fig. 6.
Fig. 6.
Forest plot for cardiovascular mortality; comparing sustained hypertension and normotension. Legend: References: [13–16, 18–20]
Masked hypertension versus white coat hypertension
Eight studies were included in the analysis of cardiovascular mortality in people with masked hypertension versus white coat hypertension. The pooled HR was 1.81 with a 95% CI of 1.81–2.07. The overall effect was significant [Z = 8.59 (P < 0.00001)]. Significant heterogeneity was seen (P = 0.01). The forest plot is shown in Fig. 7.
Fig. 7.
Forest plot for cardiovascular mortality; comparing masked hypertension and white coat hypertension. Legend: References: [13–20]
Sustained hypertension versus masked hypertension
Seven studies were included in the analysis of cardiovascular mortality in people with sustained hypertension versus masked hypertension. The pooled HR was 1.24 with a 95% CI of 1.11–1.39. The overall effect was significant [Z = 3.85 (P = 0.0001)]. Insignificant heterogeneity was seen (P = 0.008). The forest plot is shown in Fig. 8.
Fig. 8.
Forest plot for cardiovascular mortality; comparing sustained hypertension and masked hypertension. Legend: References: [13–16, 18–20]
Sustained hypertension versus white coat hypertension
Seven studies were included in the analysis of cardiovascular mortality in people with sustained hypertension versus white coat hypertension. The pooled HR was 2.09 with a 95% CI of 1.78–2.46. The overall effect was significant [Z = 8.94 (P = 0.0001)]. Insignificant heterogeneity was seen (P < 0.00001). The forest plot is shown in Fig. 9.
Fig. 9.
Forest plot for cardiovascular mortality; comparing sustained hypertension and white coat hypertension. Legend: References: [13–16, 18–20]
All-cause mortality
Masked hypertension versus normotension
Two studies were included in the analysis of all-cause mortality in people with masked hypertension versus normotension. The pooled HR was 2.10 with a 95% CI of 0.91–4.88. The overall effect was insignificant [Z = 1.73 (P = 0.08)]. Insignificant heterogeneity was seen (P = 0.08). The forest plot is shown in Fig. 10.
Fig. 10.
Forest plot for all-cause mortality; comparing masked hypertension and normotension. Legend: References: [16, 17]
White coat hypertension versus normotension
Two studies were included in the analysis of all-cause mortality in people with white coat hypertension versus normotension. The pooled HR was 1.96 with a 95% CI of 0.71–5.42. The overall effect was insignificant [Z = 1.30 (P = 0.19)]. Insignificant heterogeneity was seen (P = 0.17). The forest plot is shown in Fig. 11.
Fig. 11.
Forest plot for all-cause mortality; comparing white coat hypertension and normotension. Legend: References: [16, 17]
Discussion
The present SRMA includes eight studies with a total of 15,327 participants, who underwent in-office BP measurement and home BP and/or ambulatory BP measurement. In this meta-analysis, we found out that masked hypertension is associated with a significant rise in cardiovascular mortality when compared to normotensive people, with a pooled hazard ratio of 2.05 (95% CI: 1.69–2.48, P < 0.00001) and an insignificant heterogeneity (P = 0.72). Likewise, sustained hypertension also presents a significantly higher risk, with a pooled HR of 2.42 (95% CI: 2.12–2.76, P < 0.00001) and an insignificant heterogeneity (P = 0.76). On the other hand, White Coat Hypertension does not significantly increase cardiovascular mortality risk compared to normotension, with a pooled HR of 1.18 (95% CI: 0.98–1.42, P = 0.07) and insignificant heterogeneity (P = 0.72).
Upon comparing masked hypertension to white coat hypertension, the former shows a significantly higher cardiovascular mortality risk with a pooled HR of 1.81 (95% CI: 1.81–2.07, P < 0.00001) and significant heterogeneity (P = 0.01). We can hypothesize that this may be because masked hypertension often remains underdiagnosed compared to white coat hypertension. Consequently, timely measures to manage hypertension might not be implemented. Sustained hypertension shows an increased risk of cardiovascular mortality compared with masked hypertension and white coat hypertension, with results being significant with insignificant heterogeneity.
For all-cause mortality, masked hypertension does not show a statistically significant increase in risk compared to normotension, with a pooled HR of 2.10 (95% CI: 0.91–4.88, P = 0.08) and insignificant heterogeneity (P = 0.08). Similarly, white coat hypertension also does not show a significant increase in all-cause mortality risk compared to normotension, with a pooled HR of 1.96 (95% CI: 0.71–5.42, P = 0.19) and insignificant heterogeneity (P = 0.17).
We realize that many inconsistencies in findings among research may be explained by variations in study design characteristics. We notice that the older age-group had a greater risk of cardiovascular mortality as compared to the younger age-group. These findings align with the detailed subgroup analyses conducted by Franklin et al., [21]. This may be because such events in younger age-groups require a longer follow-up period. Additionally, shorter follow-up durations attenuated the risk of mortality, whereas longer follow-up studies showed a higher incidence of cardiovascular mortality. This could be due to two reasons: shorter follow-up periods do not account for events occurring later, and white coat or masked hypertension progresses to sustained hypertension in longer follow-up studies.
Upon literature review, we found SRMAs focused on individual phenotypes of hypertension, but few have compared different phenotypes. Our study provides the most updated SRMA comparing various hypertension phenotypes and their association with cardiovascular and all-cause mortality. Unlike most previous SRMAs that utilized fixed-effect models, we employed a random-effects model, which sufficiently accounts for the variations in study design and participant characteristics observed across studies [22, 23]. This SRMA is unique as it directly compares different phenotypes of hypertension. The study was conducted in a standardized manner with rigorous quality control measures. Additionally, the individual studies included in our SRMA are of high quality and have a relatively minimal risk of bias. Moreover, most of the results from our meta-analyses exhibit relatively low heterogeneity.
Our SRMA included only those studies that reported associations between different phenotypes of hypertension and cardiovascular mortality or all-cause mortality. Therefore, the number of studies focusing on individual phenotypes' associations with these outcomes is fewer compared to previous SRMAs. The present study includes only eight studies; a larger number of studies would have produced more robust results. The available studies have been conducted in limited geographical and demographic settings, and more studies would have made the results more generalizable. Therefore, there remains a need for high-quality studies like those included in this SRMA.
Conclusion
Overall, our analysis shows that masked hypertension and sustained hypertension are associated with significantly higher cardiovascular mortality compared to normotension, while white coat hypertension although associated with worse outcomes was inferior in comparison to both the former phenotypes. Additionally, sustained hypertension poses a higher risk than masked hypertension and white coat hypertension. For all-cause mortality, neither masked hypertension nor white coat hypertension shows a statistically significant increased risk compared to normotension.
Supplementary Information
Acknowledgements
None.
Abbreviations
- BP
Blood pressure
- ABPM
Ambulatory blood pressure monitoring
- HBPM
Home blood pressure monitoring
- MH
Masked hypertension
- WCH
White coat hypertension
- SRMA
Systematic review and meta-analysis
- HRs
Hazard ratios
- CIs
Confidence intervals
- SBPM
Self-blood pressure monitoring
- WCE
White coat effect
- PRISMA
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
- ROBINS- E
Risk Of Bias In Non-randomized Studies—of Exposures
- ROB
Risk of bias
Author contributions
JT, KAQ, SR, AT, VT, and AM were involved in the conception and design of the study. JT, KAQ, MS, and AR were involved in creating the search strategy and selection of articles to be included in the analysis. JT, KAQ, SR, MS, and AR were involved in data extraction and data analysis. All the authors were involved in writing the manuscript, and critical appraisal of the manuscript was done by AT, VT, and AM. All the authors have read and approved the final manuscript to be submitted for publication. All the authors agree to be responsible and accountable for the manuscript.
Funding
None.
Availability of data and materials
The data can be obtained from the corresponding author upon reasonable request by contacting them through their email ID.
Declarations
Ethics approval and consent to participate
This is a systematic review and meta-analysis; all the included studies obtained ethical approval and consent for participation in their respective studies. This is not applicable in this systematic review and meta-analysis.
Consent for publication
Not applicable.
Competing interests
None.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Supplementary Materials
Data Availability Statement
The data can be obtained from the corresponding author upon reasonable request by contacting them through their email ID.