Evidence map›Paper›PMID 38867857›Full record

ArticleEuropean heart journal supplements : journal of the European Society of Cardiology2024

Is the response to antihypertensive drugs heterogeneous? Rationale for personalized approach.

Mario Muselli, Raffaella Bocale, Stefano Necozione, Giovambattista Desideri

Abstract read
In one paragraph

Article in European heart journal supplements : journal of the European Society of Cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

Mario MuselliDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila.
Raffaella BocaleUnit of Endocrinology, Agostino Gemelli University Hospital Foundation Scientific Institute for Research, Hospitalization and Healthcare (IRCCS), Catholic University of the Sacred Heart, Rome.
Stefano NecozioneDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila.
Giovambattista DesideriDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arterial hypertension represents the most important cardiovascular risk factor with a direct responsibility for a large share of cardiovascular mortality and morbidity in the world. Despite the wide availability of antihypertensive therapies with documented effectiveness, blood pressure control still remains largely unsatisfactory in large segments of the population. Guidelines for the management of arterial hypertension suggest the preferential use of five classes of drugs-angiotensin-converting enzyme inhibitors, angiotensin II type I receptor inhibitors, calcium channel blockers, thiazide/thiazide-like diuretics, and beta-blockers-recommending the use of combination therapy, preferably in pre-established combinations, for the majority of hypertensive patients. The evidence of a non-negligible heterogeneity in the response to different antihypertensive drugs in different patients suggests the opportunity for personalization of treatment. The notable phenotypic heterogeneity of the population of hypertensive patients in terms of genetic structure, behavioural aspects, exposure to environmental factors, and disease history imposes the need to consider all the potential determinants of the response to a specific pharmacological treatment. The progressive digitalization of healthcare systems is making enormous quantities of data available for machine learning systems which will allow the development of management algorithms for truly personalized antihypertensive therapy in the near future.

Indexed as

Artificial intelligenceHypertensionPersonalized therapy

Identifiers

PMID38867857
PMCPMC11167967

What Socratic holds

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Registered trials

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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 Socratic graph.