A Systematic Review on Poisoned Patients as Potential Organ Donors
Notice bibliographique
Résumé
Background: Organ failure constitutes a significant global health crisis, with millions of individuals awaiting organ transplants at any given time. Deceased donors, particularly those from intoxication deaths/toxicological causes, remain underutilized as organ donors despite the potential salvageability of organs. Overcoming biases against poisoned donors is essential in addressing the organ supply-demand gap and potentially saving lives. Enhancing the donor pool by incorporating these marginal or compromised donors is an imperative in the modern medical/transplant practice. This systematic review aims to comprehensively study the following. First, it seeks to examine the global profile of poisoned/intoxicated patients from whom organs have been harvested and transplanted to date. Second, it aims to analyses and consolidate the scientific rationale for assessing the suitability of poisoned patients as organ donors, while delineating factors affecting organ salvageability across different types of poisonings. In addition, it aims to assess the outcomes of transplantations utilizing organs from toxicological deaths based on available literature. Finally, the review aims to provide valuable insights that can inform future decisions regarding organ procurement and transplantation practices specifically concerning poisoned or intoxicated donors. Materials and Methods: A comprehensive search was conducted across PubMed, Web of Science, ProQuest, Cochrane Library, and Scopus using a meticulously designed search strategy. Studies that included patient data, focused on deceased poisoned donors, and provided access to full-text articles in English were included. Studies lacking patient data or involving non-human research were excluded. To assess the risk of bias and quality of the included studies, the Joanna Briggs Institute Critical Appraisal Checklists and the Newcastle-Ottawa Scale were used. Results: The initial search yielded 349 studies, from which 68 duplicates were removed before screening. After independent screening by the authors using Rayyan software, 170 records were excluded, leaving 111 articles for eligibility assessment. Of these, 66 met the inclusion criteria. Discussion: In the realm of organ transplantation, successful outcomes stemming from organ donations by poisoned donors, particularly in cases of drug/opioid overdose, carbon monoxide (CO) poisoning, and methanol intoxication, have been extensively documented. Numerous studies have shown that there is no major difference in short-term, medium-term, and long-term recipient outcomes between poisoned and nonpoisoned donors. Despite this evidence, transplant surgeons exhibit some hesitation in considering marginalized or compromised donors, such as poisoned patients, for organ donation. However, the literature presents a plethora of instances showcasing successful organ donations arising from a diverse array of poisonings, ranging from nicotine to hemlock ingestion, and even encompassing lung transplantation following fume poisoning (multiple-18, methanol-12, CO-9, cyanide-5, organophosphate-3, ethylene glycol-3, brodifacoum-2, carbamate-2, ethanol-1, hydrogen sulphide-1, nicotine-1, fume-1, doxepin-1, paraquat-1, hemlock-1, cocaine-1, ecstasy-1, acetaminophen-1 amanita phalloides-1, and trimipramine-1). Conclusion: There is a critical need for collaboration between medical toxicologists and transplant surgeons to comprehend the unique potential of transplant toxicology studies in expanding the donor pool to meet organ demand. Evidence strongly indicates that outcomes of transplants from poisoned donors and nonpoisoned donors are comparable, with complications not attributable to the toxicity of the substance. While there’s no single answer to all questions posed by transplant surgeons regarding poisoned patients, it is evident that harvesting organs from poisoned/intoxicated donors is no longer experimental but founded on robust scientific evidence and ample experience. Further efforts to consolidate this experience and establish precise inclusion and exclusion criteria for each type of poisoning are essential.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,006 |
| Bibliométrie | 0,011 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 source (Gemma direct ou Codex distillé), 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 ».