ArticleAmerican journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons2024
"Horses for courses" computed tomography or predicted total lung capacity for size matching in lung transplantation.
Article in American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 citations in OpenAlex.
- Development and Validation of a Computed Tomography-Based Convolutional Neural Network Model for Assisting Donor Lung Acquisition in Lung Transplantation.Journal of imaging informatics in medicine · 2026Article
- Maximizing Lung Transplant Donor Utilization: Developing a Lobar Donor Repository Guided by Chest Computed Tomography Visual Scoring.Interdisciplinary cardiovascular and thoracic surgery · 2026Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Size-matching donors to recipients in lung transplantation continues to be a clinical challenge. Predicted total lung capacity equations, or more simply, donor and recipient heights, while widely used, are imprecise and may not be representative of the pool of donors and recipients. These inherent limitations may result in size discrepancies. The advent of easily accessible software and the widespread availability of computed tomography (CT) imaging in donor assessments have made it possible to directly measure lung volumes in donors and recipients. As a result, there is a growing interest in adopting personalized CT volumetry as an alternative. This article explores both methods and underscores the potential benefits and precision offered by CT.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.