Evidence map›Paper›PMID 38327929›Full record

ReviewCureus2024

Unveiling the Role of Biomarkers in Cardiovascular Risk Assessment and Prognosis.

Sumit Bhatnagar, Mohit Jain

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Methods to assess atherosclerotic cardiovascular risk in chronic respiratory diseases: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2025
    Pooled it
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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

2 authors.

Sumit BhatnagarMedicine/Interventional Cardiology, Ram Krishna Dharmarth Foundation University (RKDF) Medical College Hospital & Research Centre, Bhopal, IND.
Mohit JainCardiology, Liaquat National Hospital and Medical College (LNMC), Bhopal, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality, necessitating innovative approaches for accurate risk assessment and prognosis. This review explores the evolving role of biomarkers in advancing cardiovascular risk evaluation and prognostication. Utilizing cardiac biomarkers that represent diverse pathophysiological pathways has the potential to enhance risk stratification for CVD. We delve into the intricate molecular signatures indicative of cardiovascular health, focusing on established biomarkers such as troponins, natriuretic peptides, and lipid profiles while also examining emerging candidates like microRNAs and inflammatory markers. This review provides a holistic perspective on the current landscape of cardiovascular biomarkers, offering insights into their applications in risk assessment and prognosis. In evaluating the risk and prognosis of heart failure (HF), the measurement of natriuretic peptides (B-type natriuretic peptide [BNP] or N-terminal pro-B-type natriuretic peptide [NT-proBNP]) or markers of myocardial injury (cardiac troponin I [TnI] or T [TnT]) has demonstrated utility. By elucidating the synergistic interplay between traditional markers and cutting-edge technologies, this work aims to guide future research endeavors and clinical practices, ultimately contributing to more effective strategies for risk assessment and prognosis of cardiovascular disease.

Indexed as

biomarkerscardiovascular riskmicrornas (mirnas)natriuretic peptidestroponins

Identifiers

PMID38327929
PMCPMC10849159

What OpenQuestion holds

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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.