Evidence map›Paper›PMID 33139827›Full record

ReviewJournal of human hypertension2021

Hypertension management in 2030: a kaleidoscopic view.

Spoorthy Kulkarni

Abstract readReview
In one paragraph

Review in Journal of human hypertension, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. 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

1 author.

Spoorthy KulkarniCambridge University Hospitals NHS Foundation Trust, Cambridge, UK. Spoorthyburli@gmail.com.ORCID http://orcid.org/0000-0003-0598-9834

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The last decade has witnessed the healthcare system going paperless with increased use of electronic healthcare records. Artificial intelligence tools including smartphones and smart watches have changed the landscape of day-to-day lives. Digitisation, decentralisation of healthcare and empowerment of allied healthcare providers and patients themselves have made shared clinical decision-making a reality. The year 2020 quickly turned into an unprecedented time in our lives with the entry of COVID-19. Amidst a pandemic, healthcare systems rapidly adapted and transformed, and changes that otherwise would have taken a decade, took a mere few weeks (Webster, Lancet 395:1180-1, 2020). This essay reviews evidence of transformation in the realm of hypertension management, namely diagnosis, lifestyle changes, therapeutics and prevention of hypertension at both individual and population levels, and presents an extrapolation of how this transformation might shape the next decade.

Indexed as

COVID-19HypertensionArtificial IntelligenceHumansPandemicsSARS-CoV-2

Identifiers

PMID33139827
PMCPMC7605343

What OpenQuestion holds

Textmetadata
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.