Evidence map›Paper›PMID 30184037›Full record

ArticleBrazilian journal of cardiovascular surgery

Development and Application of a System Based on Artificial Intelligence for Transcatheter Aortic Prosthesis Selection.

Álvaro M Rösler, Jonathan Fraportti, Pedro Nectoux, Gabriel Constantin, Sílvio Cazella, Mauro Ricardo Pontes Nunes, Fernando A Lucchese

Open access · diamondAbstract read
In one paragraph

Article in Brazilian journal of cardiovascular surgery. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
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.

Álvaro M RöslerHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Jonathan FraporttiHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Pedro NectouxHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Gabriel ConstantinHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Sílvio CazellaUniversidade Federal de Ciências da Saúde de Porto Alegre - UFCSPA, Porto Alegre, RS, Brazil.
Mauro Ricardo Pontes NunesHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Fernando A LuccheseHospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Universidade Federal de Ciências da Saúde de Porto Alegre · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection.

methodsThe system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions.

resultsFor 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend.

conclusionThe utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.

Indexed as

Artificial IntelligenceAgedAged, 80 and overClinical Decision-MakingFemaleHeart Valve ProsthesisHumansMaleReference StandardsReproducibility of ResultsRetrospective StudiesSoftware DesignStatistics, NonparametricTranscatheter Aortic Valve Replacement

Identifiers

PMID30184037
PMCPMC6122758
OpenAlexW2888648021

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.