Evidence map›Paper›PMID 24250954›Full record

ArticleJournal of cardiovascular and thoracic research2011

The Relationship between Serum NT- Pro-BNP Levels and Prognosis in Patients with Systolic Heart Failure.

Sepideh Sokhanvar, Mahdiye Shekhi, Saeedeh Mazlomzadeh, Zahra Golmohammadi

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Article in Journal of cardiovascular and thoracic research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sepideh SokhanvarDepartment of Cardiology, Zanjan University of Medical Sciences, Zanjan, Iran.
Mahdiye Shekhi
Saeedeh Mazlomzadeh
Zahra Golmohammadi
Zanjan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMost studies reported using N-terminal pro-brain natriuretic peptide (NT-proBNP) in diagnosis of heart failure but there is controversy about use of these tests in determining prognosis and classification of severity of heart failure. The objective of this study was to determine the value of plasma NT-proBNP levels assessment in evaluation of mortality and morbidity of patients with systolic left ventricular dysfunction.

methodsA cohort study was performed in 150 patients with heart failure since September 2009 until February 2010. The patients were followed for 6 months to assess their prognosis. Patients were divided into two good and bad prognosis groups according to severity of heart failure in New York Heart Association (NYHA) class and frequency of hospital admission and mortality due to cardiac causes. Patients with good prognosis had ≥1 admission or no mortality or NYHA class ≥2 and patients that had one of this criteria considered as bad prognosis groups. Pro-BNP levels were measured at baseline and left ventricular ejection fraction (LVEF) was estimated with echocardiography. Data was analyzed with using Chi-square, t-test, ANOVA, Kruskal-Wallis tests.

resultsIn patients with heart failure that enrolled in this clinical study, ten patients were lost during follow-up. The mean of NT-proBNP is significantly correlated with ejection fraction (p=0.003) and NYHA class (p<0.001). In our study among 140 patients who were follow-up for 6 months, 11(9.7%) of individuals died with mean NT-proBNP of 8994.8±8375 pg/ml, in survived patients mean NT-proBNP was 3756.8±5645.6 pg/ml that was statistically significant (P=0.02). Mean NT-proBNP in the group with good prognosis was 2723.8±4845.2 pg/ml and in the group with bad prognosis was 5420.3±6681 pg/ml, difference was statistically significant (P=0.0001).

conclusionOur study in consistent with other studies confirms that NT-proBNP is significantly correlated with mortality and morbidity. This could be predicting adverse out come and stratification in patients with heart failure. It is recommended that more research be performed in Iran.

Indexed as

Heart failureMorbidityMortalityPro-BNPPrognosis

Identifiers

PMID24250954
PMCPMC3825328
OpenAlexW1870890037

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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.