Evidence map›Paper›PMID 20339474›Full record

ReviewJournal of biomedicine & biotechnology2010

Novel approaches to treat experimental pulmonary arterial hypertension: a review.

S Umar, P Steendijk, D L Ypey, D E Atsma, E E van der Wall, M J Schalij, A van der Laarse

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of biomedicine & biotechnology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 26 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

S UmarDepartment of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
P Steendijk
D L Ypey
D E Atsma
E E van der Wall
M J Schalij
A van der Laarse
Leiden University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPulmonary arterial hypertension (PAH) is a life-threatening disease characterized by an increase in pulmonary artery pressure leading to right ventricular (RV) hypertrophy, RV failure, and ultimately death. Current treatments can improve symptoms and reduce severity of the hemodynamic disorder but gradual deterioration in their condition often necessitates a lung transplant. METHODS AND

resultsIn experimental models of PAH, particularly the model of monocrotaline-induced pulmonary hypertension, efficacious treatment options tested so far include a spectrum of pharmacologic agents with actions such as anti-mitogenic, proendothelial function, proangiogenic, antiinflammatory and antioxidative. Emerging trends in PAH treatment are gene and cell therapy and their combination, like (progenitor) cells enriched with eNOS or VEGF gene. More animal data should be collected to investigate optimal cell type, in vitro cell transduction, route of administration, and number of cells to inject. Several recently discovered and experimentally tested interventions bear potential for therapeutic purposes in humans or have been shown already to be effective in PAH patients leading to improved life expectation and better quality of life.

conclusionSince many patients remain symptomatic despite therapy, we should encourage research in animal models of PAH and implement promising treatments in homogeneous groups of PAH patients.

Indexed as

Disease Models, AnimalAnimalsAntihypertensive AgentsCell- and Tissue-Based TherapyGenetic TherapyHypertension, PulmonaryMonocrotalineAntihypertensive AgentsMonocrotaline

Identifiers

PMID20339474
PMCPMC2843902
OpenAlexW2141182783

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.