International survey on the perioperative management of pulmonary endarterectomy: the perfusion perspective
Bibliographic record
Abstract
INTRODUCTION: Pulmonary endarterectomy (PEA) is the most effective treatment available for chronic thromboembolic pulmonary hypertension (CTEPH). Patient selection, surgical technique and perioperative management have improved patient outcomes, which are traditionally linked to surgical and center experience. However, optimal perfusion care has not been well defined. The goal of the international survey was to better characterize the contemporary perfusion management of PEA and highlight similarities and controversies. METHOD: The combined caseload of 15 participating centers was 5,066 cases. Topics queried included materials and types of cardiopulmonary bypass (CPB) equipment, choice of prime, fluid management, deep hypothermia strategy, temperature management, treatment of acid-base abnormalities and intraoperative hematocrit as well as anticoagulation management for heparin-induced thrombocytopenia. CONCLUSION: Our assessment could provide a base for further advancement and may help design future studies to elucidate the impact of perfusion in this challenging field.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".