Evidence map›Paper›PMID 37367393›Full record

ArticleJournal of cardiovascular development and disease2023

The Importance of Mehran Score to Predict Acute Kidney Injury in Patients with TAVI: A Large Multicenter Cohort Study.

Salvatore Arrotti, Fabio Alfredo Sgura, Daniel Enrique Monopoli, Valerio Siena, Giulio Leo, Vernizia Morgante, Paolo Cataldo, Paolo Magnavacchi, Davide Gabbieri, Vincenzo Guiducci and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cardiovascular development and disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

14 authors at 4 institutions in 1 country.

Salvatore ArrottiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Fabio Alfredo SguraCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Daniel Enrique MonopoliCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Valerio SienaCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Giulio LeoCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Vernizia MorganteCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Paolo CataldoCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.
Paolo MagnavacchiCardiology Division, Baggiovara Hospital, 41100 Modena, Italy.
Davide GabbieriCardiac Surgery Division, Hesperia Hospital, 41125 Modena, Italy.
Vincenzo GuiducciDivision of Cardiology, AUSL-IRCCS Reggio Emilia, 42121 Reggio Emilia, Italy.ORCID 0000-0002-0833-2785
Giorgio BenattiCardiology Division, Parma University Hospital, 44129 Parma, Italy.
Luigi VignaliCardiology Division, Parma University Hospital, 44129 Parma, Italy.ORCID 0000-0003-1662-024X
Giuseppe BorianiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.ORCID 0000-0002-9820-4815
Rosario RossiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41124 Modena, Italy.ORCID 0000-0001-9065-1808
University of Modena and Reggio Emilia · ITUniversity of Parma · ITAzienda Sanitaria Unità Locale di Reggio Emilia · ITHesperia Hospital · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscatheter aortic valve implantation (TAVI) has developed as an alternative to surgery for symptomatic high-risk patients with aortic stenosis (AS). An important complication of TAVI is acute kidney injury. The purpose of the study was to investigate if the Mehran Score (MS) could be used to predict acute kidney injury (AKI) in TAVI patients.

methodsThis is a multicenter, retrospective, observational study including 1180 patients with severe AS. The MS comprised eight clinical and procedural variables: hypotension, congestive heart failure class, glomerular filtration rate, diabetes, age >75 years, anemia, need for intra-aortic balloon pump, and contrast agent volume use. We assessed the sensitivity and specificity of the MS in predicting AKI following TAVI, as well as the predictive value of MS with each AKI-related characteristic.

resultsPatients were categorized into four risk groups based on MS: low (≤5), moderate (6-10), high (11-15), and very high (≥16). Post-procedural AKI was observed in 139 patients (11.8%). MS classes had a higher risk of AKI in the multivariate analysis (HR 1.38, 95% CI, 1.43-1.63,

conclusionsMS was shown to be a predictor of AKI development in TAVI patients.

Indexed as

acute kidney injuryMehran Scoretranscatheter aortic valve implantation

Identifiers

PMID37367393
PMCPMC10298873
OpenAlexW4377987124

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.