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Enregistrement W4397017980 · doi:10.1097/tp.0000000000005055

Are There Sex-based Differences in Excess Risk of Death With Graft Function After Kidney Transplant?

2024· letter· en· W4397017980 sur OpenAlexaff
Elizabeth Hendren, Reetinder Kaur, Jagbir Gill

Notice bibliographique

RevueTransplantation · 2024
Typeletter
Langueen
DomaineMedicine
ThématiqueRenal Transplantation Outcomes and Treatments
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésKidney transplantKidney transplantationMedicineKidneyFunction (biology)UrologyInternal medicineBiologyGenetics

Résumé

récupéré en direct d'OpenAlex

Even though kidney transplantation offers improved mortality compared with dialysis,1 there is still an excess risk of death after transplantation compared with the general population. These deaths may be attributed to graft loss or may occur in recipients with a functioning transplant (commonly caused by infection, malignancy, and cardiovascular disease). Death with graft function (DWGF) represents the largest cause of death for adults in the first year after kidney transplantation.2 The need to explore sex disparities in posttransplant outcomes is critical because it is known that female patients have reduced access to kidney transplantation and a higher rate of graft loss compared with male patients.3 Previously published retrospective cohort analyses have demonstrated higher rates of DWGF for adult male kidney transplant recipients compared with adult female recipients,4 but these analyses do not account for sex-based differences in mortality in the general population.5 To address this, Vinson et al6 have previously used the metric of excess mortality (which benchmarks posttransplant mortality against general population mortality) and have shown that female recipients younger than 45 y and older than 60 y who received a kidney from a male deceased donor had higher excess mortality after kidney transplantation compared with male recipients of the same age. However, whether the excess mortality in women is driven by DWGF, is related to whether the donor is male or female, or is attributed to death or after graft loss remains unknown. In this issue, Vinson et al report their findings of a follow-up retrospective cohort analysis of 3 large datasets (The American Scientific Registry of Transplant Recipients, International Collaborative Transplant Study, and Australia and New Zealand Dialysis and Transplant Registry) to investigate sex differences in the excess risk of DWGF among kidney transplant recipients.7 All recipients of a first deceased donor kidney transplant were categorized into age groups to account for how biologic differences between sexes change with development and aging. The death rate was then compared with publicly available data for the general population for each region in the study to calculate each patient’s expected probability of death. Overall, there was no significant difference in the excess risk of DWGF in women and men at all age groups, except for female recipients 0–12 y of age with male donors (relative excess risk, 1.68; 95% confidence interval, 1.24-2.29). Notably, having a male donor for a female recipient did not associate with an increased excess risk of death in all other age groups, suggesting that the findings in recipients 0–12 y of age in this study should likely not dissuade female patients from receiving a transplant from a male donor. The findings of this study contradict prior analyses4 that have demonstrated a higher risk of DWGF in male recipients and imply that the increased risk of DWGF among men reported in these studies may be attributed to population wide sex-based differences in mortality. Furthermore, these findings suggest that the increased excess risk of posttransplant mortality in women that was previously reported by Vinson et al cannot be attributed to DWGF, suggesting that there may be a higher risk of death among women during or after graft loss. Importantly, death after graft loss was not assessed in this analysis; therefore, it remains unknown if women indeed have a higher risk compared with men. Therefore, findings by Vinson et al point to the need for further evaluation of sex-specific mortality risks after transplant loss, including an evaluation of causes of graft loss and cause-specific death after graft loss. Importantly, the authors appropriately acknowledge that such an analysis may be challenging to do within the constraints of a retrospective analysis because it would risk introducing significant confounding bias.8 Therefore, prospective cohort studies may be indicated in this patient population to further understand sex-based disparities. The use of registry data remains critical in expanding our understanding of transplant care, and Vinson et al should be congratulated on attempting to provide a more comprehensive understanding of this issue across various regions. However, transplant registry analyses are limited by a lack of granular information about rejection, cause of graft failure, and cause of death. Additionally, there may be incomplete capture of death data. These limitations may explain the findings in this study of an increased excess risk of mortality among female recipients 0–12 y of age with male donors, which is a challenging observation to explain. Ultimately, these limitations speak to the need to enhance existing registries and the need for dedicated prospective studies. Although the results of the study are somewhat reassuring, because there is no demonstrated evidence of sex-based disparity in excess DWGF, the implication that sex-based differences in excess mortality after transplantation may be attributed to events related to graft loss is sobering and highlights the urgent need to further our understanding of this issue.

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)0,006
score de la tête « metaresearch » (Gemma)0,020
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,020
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,001
Communication savante0,0010,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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 Opus0,021
Tête enseignante GPT0,255
Écart entre enseignants0,234 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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