Evidence map›Paper›PMID 35586744›Full record

ReviewGlobal heart2022

Addressing Failures in Achieving Hypertension Control in Low- and Middle-Income Settings through Simplified Treatment Algorithms.

Jennifer Cohn, Helen Bygrave, Teri Roberts, Taskeen Khan, Dike Ojji, Pedro Ordunez

Abstract readReview
In one paragraph

Review in Global heart, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  19. HEARTS in the Americas: innovations for improving hypertension and cardiovascular disease risk management in primary care.Revista panamericana de salud publica = Pan American journal of public health · 2022
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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

6 authors.

Jennifer CohnResolve to Save Lives, New York, US.ORCID 0000-0002-3446-7982
Helen BygraveInternational AIDS Society, Geneva, CH.ORCID 0000-0001-8481-4447
Teri RobertsInternational AIDS Society, Geneva, CH.ORCID 0000-0002-1046-2490
Taskeen KhanDepartment of Public Health Medicine, University of Pretoria, Pretoria, ZA.ORCID 0000-0002-1676-4895
Dike OjjiDepartment of Internal Medicine, Faculty of Clinical Sciences, College of Health Sciences, University of Abuja, Abuja, NG.ORCID 0000-0002-2084-1988
Pedro OrdunezDepartment of Non-Communicable Diseases and Mental Health, Pan American Health Organization, Washington DC, US.ORCID 0000-0002-9871-6845

Funding

World Health Organization 001
6 · The paper itself

Abstract

Hypertension is the most important risk factor for cardiovascular diseases (CVDs), which are the leading global cause of death. Hypertension is under-diagnosed and under-treated in most low- and middle-income countries (LMICs). Current algorithms for hypertension treatment are complex for the healthcare worker, limit decentralization, complicate procurement and often translate to a large pill burden for the person with hypertension. We summarize evidence supporting implementation of simple, algorithmic, accessible, non-toxic and effective (SAANE) algorithms to provide a feasible way to access and maintain quality care for hypertension. Implementation of these algorithms will enable task shifting to less specialised health care workers and lay cadres, provision of fixed dose combinations, consolidation of the market while retaining generic competition, simplification of laboratory requirements, and lowering costs for health systems and people who incur out of pocket expenses.

Indexed as

Cardiovascular DiseasesHypertensionAlgorithmsDeveloping CountriesHumansIncomehealth policyhypertensiontreatment

Identifiers

PMID35586744
PMCPMC9009360

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.