Approach to Lung Transplantation in Pulmonary Arterial Hypertension: A Delphi Consensus on Behalf of the Transplant Task Force of the Pulmonary Vascular Research Institute
Bibliographic record
Abstract
Lung transplantation is indicated for selected patients with advanced pulmonary arterial hypertension (PAH). We used a modified Delphi process to develop recommendations on care of patients with PAH undergoing lung transplantation. This Delphi panel was recruited from the Pulmonary Vascular Research Institute's Innovative Drug Discovery Initiative - Lung Transplantation Workstream, consisting of clinical and research experts in PAH and lung transplantation. In this process, 29 panelists were given open-ended questions, querying topics related to lung transplantation in PAH. A steering group converted the responses into discrete statements. Panelists then rated agreement using a Likert scale in two further survey rounds: -5 (strongly disagree) to 5 (strongly agree). Consensus was defined as mean ≥ 2.5 or ≤ -2.5, with a standard deviation not crossing zero. Consensus was reached on 141 of 223 statements. Notable areas of consensus were for early discussions about transplantation, and agreement with previously published referral and listing criteria. There was agreement that lung transplantation could be offered in sick candidates, including those with concurrent renal or hepatic insufficiency. Bilateral lung transplantation was considered the procedure of choice for most patients, with rare indications for heart-lung transplantation. Consensus on bridging strategies included use of veno-arterial extracorporeal membrane oxygenation and preemptive awake cannulation in those with severe right ventricular dysfunction. Consensus was also achieved on intraoperative use of invasive hemodynamic monitoring, and prolonged postoperative circulatory support guided by hemodynamic response and echocardiography. Patients with PAH undergoing transplantation require specialized management, which differs somewhat from other candidates.
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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 | 0.160 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".