476. A Global Survey of Countermeasures Against the COVID-19 Pandemic Among Solid Organ Transplant Centers
Notice bibliographique
Résumé
Abstract Background Solid organ transplantation (SOT) profoundly impacts vulnerable recipients with chronic end organ diseases. The COVID-19 pandemic disrupted healthcare systems, including organ transplants. We aimed to evaluate the responses of SOT centers to COVID-19 at the beginning of the pandemic around the world. Methods We conducted a web-based survey amongst transplant centers, sent to members of The American Society of Transplantation Infectious Diseases Community of Practice Group, between April and May 2020. The survey included basic information of each transplant center (number and types of transplants in 2019), the countermeasures employed against COVID-19 such as timing of postponing of transplantation, and management of outpatient clinics including implementation of telemedicine and screening for in-person visits. Results A total of 65 centers from 19 countries responded (Table 1). Regarding the percentage of hospitalized patients with COVID-19 at the time of the survey, 39 (60%) centers reported < 10%, two centers reported > 80%. All centers reduced their services to some extent as shown in Table 2. Centers reported postponing living donor kidney transplant (50/58, 86%), deceased donor kidney transplant (20/57, 35%), living donor liver transplant (32/42, 80%), deceased donor liver transplant (17/41, 41%), lung transplant (20/31, 65%), heart transplant for LVAD (18/33, 55%) and non-LVAD patients (18/33, 55%). In March and April 2020, cancellation of pre- and post- transplant clinics were reported by 36/64 (56%) and 17/65 (26%) centers. Postponing clinic appointments were reported by 56/65 (86%) centers. Most institutions (54/64, 85%) used telemedicine. Screening for COVID-19 for clinic visits was done by telephone, in-person questionnaires and/or temperature checks. Conclusion During the early phase of the pandemic, when management strategies were highly uncertain, non-urgent and living donor transplants were frequently postponed. Emergent liver transplants continued regardless. These findings could help us navigate SOT in future epidemics. Limitations included a small sample and lack of assessment of clinical outcomes from postponing SOT. Disclosures Deepali Kumar, MD, MSc, FRCPC, Astellas (Individual(s) Involved: Self): Speakers’ bureau; Atara Biotherapeutics (Individual(s) Involved: Self): Grant/Research Support; GSK (Individual(s) Involved: Self): Consultant, Grant/Research Support; Merck (Individual(s) Involved: Both Myself and my Spouse/Partner): Advisor or Review Panel member, Grant/Research Support; Oxford immunotec (Individual(s) Involved: Self): Consultant, Grant/Research Support; Pfizer (Individual(s) Involved: Self): Speakers’ bureau; Roche (Individual(s) Involved: Self): Consultant, Grant/Research Support; Sanofi (Individual(s) Involved: Self): Advisor or Review Panel member; Shire/Takeda (Individual(s) Involved: Both Myself and my Spouse/Partner): Advisor or Review Panel member, Grant/Research Support Lara Danziger-Isakov, MD, MPH, Ansun (Individual(s) Involved: Self): Scientific Research Study Investigator; Astellas (Individual(s) Involved: Self): Scientific Research Study Investigator; Merck (Individual(s) Involved: Self): Consultant, Scientific Research Study Investigator; Pfizer (Individual(s) Involved: Self): Scientific Research Study Investigator; Shire (Individual(s) Involved: Self): Consultant, Scientific Research Study Investigator; Viracor: Grant/Research Support
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».