94 th Annual Meeting of the American Association for Thoracic Surgery (AATS) seen through thoracic surgical glasses
Bibliographic record
Abstract
The 94th Annual Meeting of the American Association for Thoracic Surgery (AATS) was held from Saturday, April 26 till Wednesday, April 30 in Toronto, Ontario, Canada, home of a world renowned department of general thoracic surgery and lung transplantation where one of our junior colleagues is currently performing a fellowship to obtain more experience with complex thoracic surgical interventions. The AATS congress was very well organized, smoothly running and providing an outstanding scientific program addressing all major thoracic topics. My main interests for this congress were lung cancer, mesothelioma, quality improvement, transplantation and basic research. The general thoracic symposium was entitled ‘Becoming a master thoracic surgeon’. Timely subjects were chosen which were of major interest to our specialty. Regarding lung cancer the topics ranged from the smallest lesions to large cancers invading the spine, aorta or main carina. Scientific updates and technical aspects were thoroughly discussed. Alternative techniques to surgery were put into perspective as brachytherapy and stereotactic radiotherapy. There is clearly a need for more prospective randomized trials and the difficulties of performing such trials including financial and regulatory issues seem to be universal! Interesting debates were presented on pulmonary metastasectomy and stage IIIA lung cancer for which the role of surgery remains highly controversial. Multimodality treatment clearly presents the way to move forward and improve overall survival results. The non-oncological procedures, lung volume reduction surgery and endobronchial valves continue to be debatable interventions. Very interesting was the presentation on ex vivo lung perfusion allowing marginal donor lungs to recover and subsequently to be used for lung transplantation. The presidential address of Dr. D. Sugarbaker was centered around “focused attention” which is essential to obtain excellence in our specialty. Disturbing circumstances should be avoided as much as possible in order to stay focused especially in the operating room when performing technically challenging procedures. In the scientific sessions highly selected abstracts were presented and most of them were of high quality giving rise to vivid discussions. Also the pro-con debates e.g., on robotic surgery were animated and certainly, technology is advancing in a fast way. Concerning quality control and improvement, it is obvious that specific indicators are being developed and will be introduced in daily clinical practice to benchmark the results of different thoracic centers. A minimal surgeon and hospital volume is required to obtain the best postoperative results. There were also quite a lot of interesting posters often presented by junior staff and fellows. I particularly liked the poster discussions with the authors which enables them to interact with senior colleagues. Current guidelines which are of special interest to cardiothoracic surgeons were included in the program as e.g., on the prevention and management of atrial fibrillation in thoracic surgical procedures. Atrial fibrillation remains a major postoperative complication in general thoracic surgery. Treatment should be tailored to specific patients’ characteristics. Late-breaking clinical trials brought interesting and stimulating subjects to our attention as the analysis of exhaled carbonyl compounds to differentiate between benign and malignant pulmonary disease. Image-guided video-assisted thoracic surgery seems a promising technique to adequately remove pulmonary nodules with safe margins. Invited speakers were scheduled within scientific sessions and the ‘Evolution of staging in lung cancer’ presented by Dr. Peter Goldstraw brought a refreshing and enlighting historical overview of the different versions of the tumour-node-metastasis (TNM) classification of lung cancer. In general, the AATS annual meeting was extremely valuable in providing a summary and update of general thoracic surgery at the same time offering a lot of opportunities to interact and discuss not only with colleagues of North America but in fact of large parts of the world, making it a real international conference.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.119 | 0.070 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".