Invited Response to “Potential Disadvantages of Over Centralization of Organ Recovery Centers: Response to Marsolais et al.”
Bibliographic record
Abstract
To the Editor: We thank the authors for their very attentive reading of our article and the opportunity to clarify a few points (1Marsolais P Durand P Charbonney E et al.The first 2 years of activity of a specialized organ procurement center: Report of an innovative approach to improve organ donation.Am J Transplant. 2017; 186: 95Google Scholar,2Weis MJ Healey A Dhanani S Lizé JF Potential disadvantages of over centralization of organ recovery centers: Response to Marsolais et al..Am J Transplant. 2017; (https://doi.org/10.1111/ajt.14357. [Epub ahead of print].)Abstract Full Text Full Text PDF Scopus (1) Google Scholar). Regarding the indicator of transplant per million population (tpm), we would like to reemphasize its worldwide use to report the organ donation process efficiency. This indicator encompasses all potential obstacles to the donation process such as identification of potential donors, conversion rate, support to donor’s families, quality of donor support, and organizational efficiency. The tpm is used by international organizations such as “Le Comité européen sur la transplantation d’organes” as their main measure since 2003 (3International figures on organ donation and transplantation.Newsletter Transplant. 2003; 8 (Available from: http://www.ont.es/publicaciones/Documents/Newsletter%20Transplant%202003.pdf.): 1-48Google Scholar). Our comparative data using tpm from 107 countries are extracted from the Global Observatory on Donation and Transplantation database (under the signed agreement between the World Health Organization and the Spanish Ministry of Health) (4International figures on donation and transplantation 2015. Newsletter Transplant. 2016; 21.Google Scholar). Interestingly, the authors refer in their argument to a publication on organ donation in Canada specifically reporting results in tpm (5Canadian Blood Services. Organ donation and transplantation in Canada—System Progress Report 2006–2015. 2016; 1–98.Google Scholar). Our colleagues point out two discrepancies regarding reported tpm in other jurisdictions. They were unfortunately misled by the fact that the numbers they are referring to include living donors who were excluded from our study. Furthermore, the Canadian reference cited by the authors was not published at the time of manuscript submission. We agree that transfer of potentially unstable patients may carry some risk. In the current model of care in the province of Quebec, these patients identified in smaller centers are already transferred to other academic centers. During the 2-year period, we did not experience any adverse events during donor transfers. Doyle et al previously published their experience using a model similar to the Organ Procurement Center (OPC) (6Doyle MB Vachharajani N Wellen JR et al.A novel organ donor facility: A decade of experience with liver donors.Am J Transplant. 2014; 14: 615-620Crossref PubMed Scopus (29) Google Scholar). They reported that out of 850 patients, 90% were transferred. Donors were found to be too unstable in only 1% (9 cases) and family refused the transfer in 3.9% of the cases. The discussion of expertise centralization and associated risks or benefits is an important one. Most referring centers identify between 0 and 3 patients a year and do not have access to advanced investigation techniques essential in the care of such patients (echocardiography, coronarography, bronchoscopy, organ biopsies, etc). The organ donation process could also be quite stressful for less exposed physicians, especially since most of these smaller hospitals have staff who are family physicians and internists with infrequent encounter with the organ donation process. Rapid transfer to a specialized unit relieves both the system and the physician from the challenging task of supporting and optimizing the organ donation process. This centralization of expertise is already well supported for a variety of other complex medical situations (trauma, lung transplantation, cardiac surgery, etc.) where it has also been associated with improved outcomes. The OPC is an adapted replication of these models of reference centers in areas where the total number of cases by center is relatively low. The results of our experience strongly support centralization of expertise for organ donation as well (Figure 1). Finally, we certainly support a scientific approach to better understand the advantages and disadvantages of different organizational models in organ donation and would invite the authors to appraise their proposed model of care. The authors have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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 | 0.008 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.030 | 0.041 |
| Insufficient payload (model declined to judge) | 0.014 | 0.012 |
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".