Navigating the clinical and research landscape of lung transplantation in Canada: Insights from a National Survey and JLA Priority-Setting Partnership
Bibliographic record
Abstract
Lung transplantation (LTx) is a complex and life-saving intervention for patients with end-stage lung disease. While advancements in surgical techniques, immunosuppression, and post-transplant care have significantly improved outcomes, considerable variability in clinical practices persists across transplant centers. This variability suggests a state of equipoise, uncertainty or lack of consensus about the most effective approaches, highlighting the need for new or higher quality evidence and evidence-based guidelines. Although much patient-centered research exists, there remains uncertainty about which aspects of care require further study to fill the knowledge gaps that exist in practice. This thesis aims to address these challenges by exploring two dimensions of uncertainty in LTx. First, it investigates the extent of variability in clinical practices among Canadian LTx centers, which may indicate gaps in evidence or consensus regarding optimal care. Second, it seeks to identify the most pressing areas for future research from the perspective of diverse stakeholders, including patients, caregivers, and healthcare professionals, using a structured, stakeholder-driven James Lind Alliance (JLA) approach. The overarching aim is to identify areas where clinical equipoise may exist and prioritize research topics that could guide future research and lead to more evidence-based LTx practices. Objective: The objectives of this thesis are: 1. to assess the average clinical practice in Canada as well as the variability both within and between centers 2. to identify research priorities in LTx according to patients, caregivers, and clinicians. Methods Project 1: A digital survey was conducted targeting all physicians and surgeons involved in LTx at Canadian transplant centers. The survey included both surgical centers (performing LTx and managing pre- and post-operative care) and non-surgical centers (providing pre- and post-transplant care without performing the surgeries). Survey responses captured clinical practices related to key areas such as infection prophylaxis, immunosuppression, surgical care, perioperative management, and candidate selection. Variability was analyzed both across and within centers using Fishers exact test or Pearson chi-square tests for categorical data and Mann Whitney U test or Kruskal-Wallis test, and interquartile ranges for continuous variables. Project 2: The James Lind Alliance (JLA) methodology was employed to identify priorities for future LTx research. An initial survey engaged a broad range of stakeholders: patients, caregivers, and clinicians to generate potential research questions, addressing uncertainties in the LTx process. These responses were consolidated into "indicative" questions. A second, interim prioritization survey asked stakeholders to rank the importance of these questions using a Likert scale. A systematic literature search ensured that the top-ranked questions had not been adequately addressed by existing research. Finally, a virtual, two-half day workshop using a modified nominal group technique facilitated a consensus-driven prioritization of the Top 10 research questions. Conclusion i. Significant variability exists in various areas of LTx clinical practices across Canada. ii. Key research priorities were identified to address gaps in LTx literature. These findings will guide future research funding and efforts, aiming to enhance LTx research and improve outcomes for all stakeholders.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".