Evidence map›Paper›PMID 36982164›Full record

ReviewInternational journal of molecular sciences2023

New Insight in Cardiorenal Syndrome: From Biomarkers to Therapy.

Giovanna Gallo, Oreste Lanza, Carmine Savoia

Open access · goldFull text readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 2 pooled it
11.6field-weighted citation impact, top 1% 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

42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 53 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

3 authors at 1 institution in 1 country.

Giovanna GalloClinical and Molecular Medicine Department, Faculty of Medicine and Psychology, Sant'Andrea Hospital, Sapienza University of Rome, 00189 Rome, Italy.ORCID 0000-0003-4845-117X
Oreste LanzaClinical and Molecular Medicine Department, Faculty of Medicine and Psychology, Sant'Andrea Hospital, Sapienza University of Rome, 00189 Rome, Italy.
Carmine SavoiaClinical and Molecular Medicine Department, Faculty of Medicine and Psychology, Sant'Andrea Hospital, Sapienza University of Rome, 00189 Rome, Italy.ORCID 0000-0002-2296-1959
Sapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiorenal syndrome consists in the coexistence of acute or chronic dysfunction of heart and kidneys resulting in a cascade of feedback mechanisms and causing damage to both organs associated with high morbidity and mortality. In the last few years, different biomarkers have been investigated with the aim to achieve an early and accurate diagnosis of cardiorenal syndrome, to provide a prognostic role and to guide the development of targeted pharmacological and non-pharmacological therapies. In such a context, sodium-glucose cotransporter 2 (SGLT2) inhibitors, recommended as the first-line choice in the management of heart failure, might represent a promising strategy in the management of cardiorenal syndrome due to their efficacy in reducing both cardiac and renal outcomes. In this review, we will discuss the current knowledge on the pathophysiology of cardiorenal syndrome in adults, as well as the utility of biomarkers in cardiac and kidney dysfunction and potential insights into novel therapeutics.

Indexed as

Cardio-Renal SyndromeHeart FailureBiomarkersHeartHumansKidneyBiomarkersheart failurerenal diseaseSGLT2 inhibitors

Identifiers

PMID36982164
PMCPMC10049666
OpenAlexW4323362196

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read15
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.