Evidence map›Paper›PMID 35011825›Full record

ArticleJournal of clinical medicine2021

Computational Simulator Models and Invasive Hemodynamic Monitoring as Tools for Precision Medicine in Pulmonary Arterial Hypertension.

Giovanna Manzi, Cristiano Miotti, Marco Valerio Mariani, Silvia Papa, Federico Luongo, Gianmarco Scoccia, Beatrice De Lazzari, Claudio De Lazzari, Raymond L Benza, Francesco Fedele and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical medicine, 2021. 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. Article
  2. 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

12 authors.

Giovanna ManziDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0003-0676-3132
Cristiano MiottiDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0001-6391-0309
Marco Valerio MarianiDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0002-9480-1209
Silvia PapaDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0001-8653-4035
Federico LuongoDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0001-6385-7931
Gianmarco ScocciaDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.ORCID 0000-0002-8761-0711
Beatrice De LazzariDepartment of Engineering, Roma Tre University, 00146 Rome, Italy.
Claudio De LazzariNational Research Council, Institute of Clinical Physiology (IFC-CNR), 00185 Rome, Italy.ORCID 0000-0001-5149-4109
Raymond L BenzaDivision of Cardiovascular Diseases, Ohio State University, Columbus, OH 43210, USA.
Francesco FedeleDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.
Carmine Dario VizzaDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.
Roberto BadagliaccaDepartment of Clinical, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Viale del Policlinico, 155, 00161 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine, providing the right therapeutic strategy for the right patient, could revolutionize management and prognosis of patients affected by cardiovascular diseases. Big data and artificial intelligence are pivotal for the realization of this ambitious design. In the setting of pulmonary arterial hypertension (PAH), the use of computational models and data derived from ambulatory implantable hemodynamic monitors could provide useful information for tailored treatment, as requested by precision medicine.

Indexed as

big datacomputational modelsimplantable hemodynamic monitorsprecision medicinepulmonary arterial hypertension

Identifiers

PMID35011825
PMCPMC8745441

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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 OpenQuestion graph.