Role of extracorporeal life support after pulmonary endarterectomy: a single-centre experience
Bibliographic record
Abstract
OBJECTIVES: Extracorporeal life support (ECLS) for rescue after pulmonary endarterectomy (PEA) has become a viable option. This study aims to present a single-centre experience looking at the indications and outcome of ECLS after PEA. METHODS: Retrospective analysis of all patients undergoing PEA from January 2008 to January 2015 in our institution. RESULTS: Among 144 consecutive patients undergoing PEA for chronic thromboembolic pulmonary hypertension, 6 (4%) received ECLS postoperatively for right ventricular (RV) failure (n = 3), severe hypoxaemia (n = 2) and haemorrhagic pulmonary oedema (n = 1). ECLS configuration was central veno-arterial (cVA) in 3 patients, peripheral VA (pVA) in 1 and veno-venous (VV) in 2. One patient with cVA was switched to VV after 5 days. Overall ECLS duration ranged between 3 and 39 (median 5) days. ECLS patients had higher preoperative total pulmonary vascular resistance (TPR) compared with non-ECLS patients (1477 ± 671 vs 954 ± 462 Dynes.s.cm(-5), P = 0.009) and more frequently required hospital admission for RV failure before surgery (50 vs 9%, P = 0.02). The overall in-hospital mortality rate for all patients was 2% (3/144), including one ECLS patient on pVA. The remaining 5 ECLS patients (83%) were discharged from the hospital and are alive after a median follow-up of 11 (range 6-27) months. Two ECLS patients (40%) are on therapy for residual PH compared with 13 (10%) in the non-ECLS patients (P = 0.09). CONCLUSIONS: ECLS is a safe and important rescue option after PEA. The use of ECLS may expand eligibility for PEA by allowing sicker patients to undergo surgery.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".