A New Diagnostic Algorithm for Antibody-Mediated Microcirculation Inflammation in Kidney Transplants
Notice bibliographique
Résumé
We studied the significance of microcirculation inflammation in kidney transplants, including 329 indication biopsies from 251 renal allograft recipients, who were mostly nonpresensitized (crossmatch negative). Glomerulitis (g) and peritubular capillaritis (ptc) were often associated with antibody-mediated rejection (65% and 75%, respectively), but were also found in other diseases in the absence of donor-specific antibody (DSA): T-cell-mediated rejection (ptc, g), glomerulonephritis (g) and acute tubular necrosis (ptc). To develop rules for reducing the nonspecificity of microcirculation inflammation and defining the best grading thresholds associated with DSA, we built and validated a decision tree to predict DSA. The decision tree revealed that g + ptc sum (addition of g-score plus ptc-score) was the best predictor of DSA, followed by time posttransplant, then C4d, which had a small role. Late biopsies with g + ptc > 0 showed higher frequency of DSA compared to early biopsies with g + ptc > 0 (79% vs. 27%). Microcirculation inflammation in early biopsies was often false positive (antibody-independent). The decision tree predicted DSA with higher sensitivity and accuracy than C4d staining. Microcirculation inflammation sum score predicted graft failure independently of time, C4d and transplant glomerulopathy. Thus any degree of microcirculation inflammation in late kidney transplant biopsies strongly indicates presence of DSA and predicts progression to graft failure. We studied the significance of microcirculation inflammation in kidney transplants, including 329 indication biopsies from 251 renal allograft recipients, who were mostly nonpresensitized (crossmatch negative). Glomerulitis (g) and peritubular capillaritis (ptc) were often associated with antibody-mediated rejection (65% and 75%, respectively), but were also found in other diseases in the absence of donor-specific antibody (DSA): T-cell-mediated rejection (ptc, g), glomerulonephritis (g) and acute tubular necrosis (ptc). To develop rules for reducing the nonspecificity of microcirculation inflammation and defining the best grading thresholds associated with DSA, we built and validated a decision tree to predict DSA. The decision tree revealed that g + ptc sum (addition of g-score plus ptc-score) was the best predictor of DSA, followed by time posttransplant, then C4d, which had a small role. Late biopsies with g + ptc > 0 showed higher frequency of DSA compared to early biopsies with g + ptc > 0 (79% vs. 27%). Microcirculation inflammation in early biopsies was often false positive (antibody-independent). The decision tree predicted DSA with higher sensitivity and accuracy than C4d staining. Microcirculation inflammation sum score predicted graft failure independently of time, C4d and transplant glomerulopathy. Thus any degree of microcirculation inflammation in late kidney transplant biopsies strongly indicates presence of DSA and predicts progression to graft failure.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».