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Record W4386941774 · doi:10.5281/zenodo.3958567

Transcatheter aortic valve implantation. First experience of minimally invasive treatment in the Republic of Moldova

2020· article· en· W4386941774 on OpenAlexaboutno aff
Marcel Abraş, Artiom Surev, Mariuca Vasa‐Nicotera, Andrei Grib, Ion Popovici, Catalina Beiu

Bibliographic record

VenuePublication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyRadiology

Abstract

fetched live from OpenAlex

<strong>Background: </strong>Aortic stenosis (AS) is the most prevalent primary heart valve disease and the third most prevalent cardiovascular disease in the world, having a severe and slowly progressive evolution. The implementation of Transcatheter Aortic Valve Implantation (TAVI) is necessary because the population is constantly ageing, and most elderly people have various comorbidities, which places them among patients with high surgical risk. The aim was to report immediate and 9 months follow-up results of first TAVI implantations in the Republic of Moldova. <strong>Material and methods:</strong> Three patients with severe symptomatic AS and high surgical risk underwent TAVI implantation using Portico valves. <strong>Results: </strong>The mean age was 76.7 ± 1.2 years, 2 women and 1 man. The mean Logistic EuroSCORE II was 5.68 ± 0.67%. Procedural success was achieved in all (100%) patients. After the intervention, it was shown that the GP mean decreased by an average of 20.27±1.61 mmHg, the Vmax of the jet through AoV decreased on average by 2.05±0.19 m/s, and they were maintained all over the nine months follow-up period. Quality of life, using the TASQ (Toronto Aortic Stenosis Quality of Life) questionnaire, was improved by 62.3 ± 2.2 points. <strong>Conclusions: </strong>TAVI, as a new minimally invasive method of treatment for aortic valve stenosis appears to be safe, with a low rate of early and late complications in elderly patients at high surgical risk, with good clinical outcomes at 9 months. Its implementation in the Republic of Moldova is welcome in the conditions of continuously ageing population and the prevalence of associated comorbidities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.259
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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