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Enregistrement W2754445609 · doi:10.1097/tp.0000000000001901

Kim Solez, Edmonton, Alberta, Canada Banff

2017· article· en· W2754445609 sur OpenAlexaffabout
Kim Solez

Notice bibliographique

RevueTransplantation · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueOrgan Donation and Transplantation
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésWifeTransplantationMedicineGeneral surgeryFamily medicineHistorySurgeryLawPolitical science

Résumé

récupéré en direct d'OpenAlex

Transplantation: You were trained in pathology at Johns Hopkins. What sparked you to go to Medical School and to continue a career in pathology?FigureKS: My father, uncle, and grandfather were all physicians, so from an early age, I was interested in a career in medicine. My faculty mentor in medical school at the University of Rochester, Dr. G.W. Richter, was a pathologist. When I said I wanted to do research in medical school, he suggested I “gum up the kidneys” so that is where my first 2 papers on Sephadex microembolization came from. Dr. Richter had high regard for Dr. Robert Heptinstall, my eventual mentor in renal pathology at Johns Hopkins, so it seemed natural to work with him when I went to Hopkins for residency training. Transplantation: You cofounded the Banff Classification and Consensus Process and chair the Banff Foundation for Allograft Pathology. What events led to the first Banff meeting in 1991? KS: December 1990 Paul Keown wrote to me about the just published international heart and lung classification and suggested we do the same thing for the kidney. On Easter day 1991, I visited the Banff Centre for Conferences with my wife, who had attended a conference there, and decided to hold the initial classification meeting at that facility. I asked Lorraine Racusen to join me in the effort, and she said it was the most interesting thing I ever asked her to do. We have been partners in the endeavor ever since. The first Banff meeting occurred 4 months later August 2 to 4, 1991. In the end, what we were doing proved to be entirely different from the heart and lung effort in that we included all stakeholders, whereas their effort included pathologists only. Transplantation: The Banff classification has since then covered all organs commonly transplanted. What has the Banff classification achieved and what are its limitations? KS: The Banff Classification and Consensus Process created a common language for transplant pathology worldwide with a robust consensus process for updating and expanding the classification. It has become the main diagnostic modality determining treatment, able to diagnose all conditions, the main measure of success of anti-rejection treatments, and the principle endpoint for international clinical trials of antirejection agents. There are many standards in medicine, but most have competing standards. The Banff classification is one of the very few truly worldwide medical standards that has no competition. The number of Banff related publications each year continues to rise (Figure 1).FIGURE 1: The number of Banff publications has increased steadily since the initiation of the conference.The associated Banff consensus process is also remarkable. The NIH gave up their Consensus Development Conferences permanently in 2013 because of numerous problems. They now refer individuals inquiring about such conferences to “the Banff people.” There are inherent sampling error limitations in any biopsy-based standard with semiquantitative readout. Eventually, we will have completely quantitative soluble biomarkers that will sum rejection and other disease process activity in the entire transplanted organ, eliminating sampling error. Transplantation: Although the Banff classification has contributed tremendously, we are still facing challenges of reproducibility in readouts. Will we be able to address this issue? KS: Many centers lack trained renal pathologists. Central reading of biopsies is one solution. Various training initiatives have been discussed at the Banff meeting to train pathologists in the use of the system. This has already been undertaken in the context of clinical trials. We should probably consider doing this sort of practical training at the Banff meetings, perhaps with a digital slide set, for those that are interested. Transplantation: What do you see as the next big challenge that the Banff classification aims to tackle? KS: The next big challenge is the incorporation of tissue engineering pathology and full embrace of regenerative medicine transplantation that could completely eliminate the organ shortage. Transplantation: Before establishing the Banff classification, you have started the Disaster Relief Task Force of the International Society of Nephrology. This task force has worked closely with Medicins sans frontiers. Is this initiative still active? KS: It might interest readers to know how it is that I, a “nonclinician” laboratory physician ended up creating and running a worldwide disaster relief task force for many years. While clinicians at the time could see the need for this disaster relief task force, they felt they would receive no academic credit from leading such an entity, in fact it was an activity they would be criticized for. I on the other hand was Chair of Pathology at the University of Alberta reporting directly to the Dean of Medicine, Doug Wilson, a nephrologist who shared my interest in acute renal failure. Doug, fortunately, was strongly supportive of the things I was doing. When an earthquake would occur, I would drop everything else I was doing for a time. Leading up to the International Congress of Nephrology in Jerusalem in 1993, I had proposed a plenary talk on renal disaster relief. The criticism this proposal received made me realize that it was not good enough on my part to sit in my office in Edmonton, Canada, sending other task force members out into harm's way. Instead, I began doing dangerous but necessary things to establish my credibility as a task force leader, going to Kosovo and Nigeria. Much was accomplished during those trips, and it was the start of my interest in mass poisonings that led to my appearance on 60 Minutes in 1997. Eventually, Norbert Lameire emerged as a clinician with the wisdom and political skills to be the task force leader, and I began to focus more on informatics and communications. The task force has remained active up until the present day and engaged in specific activities relating to the 2015 earthquake in Nepal and 2016 to 2017 dialysis disruption in the European refugee crisis.1 Of note, the Banff classification also grew out of the ISN Commission on ARF. In fact, at the first Banff meeting in August 1991, half of the meeting was about disaster relief, with 2 separate sets of participants, and me as the only person taking part in both meetings. The social events were joint and very pleasurable owing to the great diversity of the participants! Transplantation: You have also worked on solving the Haitian diethylene glycol poisoning during which a contaminated cough syrup led to the acute kidney failure in more than 100 children. How did you help solve this disaster? KS: My involvement came from my leadership of the NEPHROL nephrology Email discussion group which coordinated response to this disaster in 1996.2 I started the NEPHROL Email discussion group in 1994, and it is the oldest medical Email discussion group still under the same leadership. Transplantation: You have led the University of Alberta’s initiative of a medical school in Nepal. Can you share that experience? KS: We helped create a new medical school in Nepal, the Patan Academy of Health Science devoted to rural health where graduates are strongly motivated to stay in the country. At the peak of the activity, more than 16 University of Alberta faculty were involved in this project under my leadership. I have been involved in humanitarian projects in Nepal since 1998. Transplantation: You share your office (“cyberNephrology”) with a rotating cadre of young people between 17 and 30 years of age). What is your concept of mentoring? KS: Age is just a number. People are people, worthy of mutual respect, and worth listening to. I surround myself with young people all day every weekday, and most of my interactions are with them rather than with people my own age. It keeps me young like you would not believe! A great deal of learning occurs in both directions. I have known young people who became very influential later in life, so I always assume that might be the case with the young people I am dealing with now. That assumption hurts no one. In over 44 years of mentoring I have never had a serious discipline problem, never had a major conflict with a trainee. I won a major mentoring award last year. Transplantation: Your interests go far beyond medicine and pathology. Can you share some of your hobbies with us? KS: When you look around my shared office and see all the art and artifacts contributed by the students and me, you would realize that the usual definition of a hobby—an interest outside of work—does not apply to me. All my interests in art, poetry, and music are integrated with my work and have been for over a decade. With 23-year-old singer Mallory Chipman,3 I have initiated a project called “The Future and All That Jazz” that uses poetry, music, and the sound bytes of modern life to communicate important messages about artificial intelligence and regenerative medicine that audiences are unlikely to sit still for a lecture on. The communication works and is enjoyable besides! Does any of this art stuff enhance the rest of what I am doing? My poetry is mainly about technology and medicine, work-related subjects. I coedit the http://www.breathinpoetry.com website and Facebook page, and the person coediting it with me is the current poet laureate of the city of Edmonton, Ahmed Knowmadic Ali. This week he addressed the Premiers' leadership conference for the leaders of all the provinces in Canada. You can’t get much higher impact than that!

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,406
Score d'incertitude au seuil0,807

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0030,001
Communication savante0,0040,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,6310,202

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,010
Tête enseignante GPT0,252
Écart entre enseignants0,242 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2017
Routes d'admission2
Résumé présentoui

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