Evidence map›Paper›PMID 35490246›Full record

ArticleClinical hypertension2022

Interventions in hypertension: systematic review and meta-analysis of natural and quasi-experiments.

Tong Xia, Fan Zhao, Roch A Nianogo

Open access · diamondAbstract read
In one paragraph

Article in Clinical hypertension, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Diverse Biological Activity of Pyrimidine Derivatives: A Review.Current drug discovery technologies · 2026
    Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tong XiaDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.ORCID https://orcid.org/0000-0001-7136-8361
Fan ZhaoDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.ORCID https://orcid.org/0000-0002-1261-5841
Roch A NianogoDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA. niaroch@ucla.edu.ORCID http://orcid.org/0000-0001-5932-6169
University of California, Los Angeles · US

Funding

The SMART-CV Study: Systems Modeling Approaches to Reducing Disparities in Cardiovascular DiseasesK01MD014163 · NIMHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NIANOGO, ROCH · 2020 to 2024
$671k
NIMHD NIH HHS K01 MD014163
6 · The paper itself

Abstract

backgroundHypertension is an urgent public health problem. Consistent summary from natural and quasi-experiments employed to evaluate interventions that aim at preventing or controlling hypertension is lacking in the current literature. This study aims to summarize the evidence from natural and quasi-experiments that evaluated interventions used to prevent or control hypertension.

methodsWe searched PubMed, Embase and Web of Science for natural and quasi-experiments evaluating interventions used to prevent hypertension, improve blood pressure control or reduce blood pressure levels from January 2008 to November 2018. Descriptions of studies and interventions were systematically summarized, and a meta-analysis was conducted.

resultsThirty studies were identified, and all used quasi-experimental designs including a difference-in-difference, a pre-post with a control group or a propensity score matching design. Education and counseling on lifestyle modifications such as promoting physical activity (PA), promoting a healthy diet and smoking cessation consultations could help prevent hypertension in healthy people. The use of computerized clinical practice guidelines by general practitioners, education and management of hypertension, the screening for cardiovascular disease (CVD) goals and referral could help improve hypertension control in patients with hypertension. The educating and counseling on PA and diet, the monitoring of patients' metabolic factors and chronic diseases, the combination of education on lifestyles with management of hypertension, the screening for economic risk factors, medical needs, and CVD risk factors and referral all could help reduce blood pressure. In the meta-analysis, the largest reduction in blood pressure was seen for interventions which combined education, counseling and management strategies: weighted mean difference in systolic blood pressure was - 5.34 mmHg (95% confidence interval [CI], - 7.35 to - 3.33) and in diastolic blood pressure was - 3.23 mmHg (95% CI, - 5.51 to - 0.96).

conclusionsInterventions that used education and counseling strategies; those that used management strategies; those that used combined education, counseling and management strategies and those that used screening and referral strategies were beneficial in preventing, controlling hypertension and reducing blood pressure levels. The combination of education, counseling and management strategies appeared to be the most beneficial intervention to reduce blood pressure levels.

Indexed as

Comparative effectiveness researchHypertensionNon-randomized controlled trials as topic

Identifiers

PMID35490246
PMCPMC9057066
OpenAlexW4225256557

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.