Evidence map›Paper›PMID 42688520›Full record

ReviewKardiochirurgia i torakochirurgia polska = Polish journal of cardio-thoracic surgery2026

The evolution of cardiothoracic surgery training: from apprenticeship to AI-assisted simulation.

Vasileios Leivaditis, Francesk Mulita, Vasiliki Androutsopoulou, Andreas Antonios Maniatopoulos, Elias Liolis, Konstantinos Tasios, Konstantinos Nikolakopoulos, Chrysa Andrikopoulou, Paraskevi Katsakiori, Nikolaos G Baikoussis

Abstract readReview
In one paragraph

Review in Kardiochirurgia i torakochirurgia polska = Polish journal of cardio-thoracic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Vasileios LeivaditisDepartment of Cardiothoracic and Vascular Surgery, Westpfalz Klinikum, Kaiserslautern, Germany.
Francesk MulitaSecond Department of Surgery, Medical School, Democritus University of Thrace, Alexandroupolis, Greece.
Vasiliki AndroutsopoulouDepartment of Cardiothoracic Surgery, Faculty of Medicine, University of Thessaly, Biopolis, Larissa, Greece.
Andreas Antonios ManiatopoulosDepartment of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece.
Elias LiolisDepartment of Oncology, General University Hospital of Patras, Greece.
Konstantinos TasiosJohn Radcliffe Hospital Emergency Department, University Hospitals NHS Foundation Trust, Headley Way, Headington, Oxford OX3 9DU, UK.
Konstantinos NikolakopoulosDepartment of Vascular Surgery, General University Hospital of Patras, Greece.
Chrysa AndrikopoulouDepartment of Surgery, General Hospital of Eastern Achaia - Unit of Aigio, Greece.
Paraskevi KatsakioriDepartment of Surgery, General Hospital of Eastern Achaia - Unit of Aigio, Greece.
Nikolaos G BaikoussisDepartment of Cardiac Surgery, Ippokrateio General Hospital of Athens, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A highly structured, technologically advanced educational paradigm has replaced the unstructured apprenticeship approach in the training of cardiothoracic surgeons. Early surgical education, which was historically based on the "see one, do one, teach one" principle, mostly depended on one-on-one mentoring and varying operative exposure, with the shortcomings of conventional training becoming more obvious as cardiothoracic surgery developed into a unique, high-stakes specialty requiring extraordinary technical accuracy and judgment. This evolution led to the implemention of standardized curricula, competency-based assessments, and simulation-based learning to ensure consistent skill acquisition and patient safety. In an increasingly digitized and globalized world, personalized learning pathways, objective skill evaluation, and remote training access are all made possible by recent developments in virtual reality (VR), artificial intelligence (AI), and real-time data analytics, further changing surgical education and thereby shaping the future of surgical proficiency.

Indexed as

artificial intelligencecardiothoracic educationhistory of medicinesimulationsurgical training

Identifiers

PMID42688520
PMCPMC13535811

What OpenQuestion holds

Textmetadata
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.