Bilateral lobar lung transplantation and size mismatch by pTLC-ratio
Bibliographic record
Abstract
We read with great interest the important investigation by Inci et al. [1] on bilateral lobar lung transplantation (LTx). As a rationale, the authors cite that significantly oversized allografts are associated with perioperative complications and worse outcomes. The citation provided refers to a dog model of lobar LTx that compared allografts oversized on average 3.1-fold vs allografts that were similarly 3.3-fold oversized, but subsequently downsized 10–19% via peripheral wedge resections. At 4 h after LTx, the control group had higher pulmonary vascular resistance (PVR) and lower PaO2 [2]. In a porcine model of lobar LTx, a 1.8-fold oversized allograft was compared with a size-matched allograft. That study reported a superior function with lower pulmonary artery pressures and lower PVR associated with the oversized allografts [3]. Neither animal model ideally reflects the clinical experience in humans. The human experience using significantly oversized lobar LTx with a 2.07-fold-oversized allograft was reported with good long-term outcomes [4]. Whereas there is evidence that (within surgically feasible limits) oversized allografts are not associated with worse clinical outcomes, there is evidence that significant undersizing could be problematic [5]. Donor-to-recipient lung-size mismatch is preferably assessed by the predicted total lung capacity (pTLC)-ratio (=donor pTLC/recipient pTLC) [5, 6]. In paediatric living lobar LTx, there is an association between undersizing (pTLC-ratio < 0.8) and worse survival [5]. Inci et al. focus on height difference between groups and the donor pTLC to recipient actual TLC difference. However, recipient actual TLC likely reflects the lung pathology more than the recipient's thorax size. Thus, it would be helpful, if Inci et al. could provide pTLC-ratio matching data for their cohorts. If, for example the pTLC-ratio of a conventional LTx is 1.25 (which should not be associated with worse clinical outcomes) and a lobar LTx leads to an actual pTLC-ratio of 0.75, one could expect that the very undersized situation created could lead to inferior clinical outcomes. Inci et al. report on a 39% occurrence of haemothorax. The association of undersizing (pTLC-ratio < 1.0) with return to OR for bleeding, primary graft dysfunction, longer length of stay and increased resource utilization was reported [6]. Thus, it would be helpful, if more details on post-transplant complications between groups could be provided. The survival data, which are limited to an unadjusted Kaplan–Meier survival analysis comparing conventional with lobar LTx, make it difficult to interpret the results in context. The lobar LTx group consisted predominantly of patients with cystic fibrosis, who in general have the most favourable long-term survival. It would be informative if the authors could show analysis within the same diagnostic groups (i.e. cystic fibrosis). Furthermore, providing a multivariate Cox proportional hazard model adjusted for important confounders would strengthen the assessment of clinical outcomes. We wish to conclude by thanking and congratulating Inci et al. on their important study on bilateral lobar LTx allowing life-saving transplants in ‘short’ recipients, who otherwise might not be able to receive an appropriately sized allograft in a timely way.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".