Using machine learning to predict antibody response to SARS-CoV-2 vaccination in solid organ transplant recipients: the multicentre ORCHESTRA cohort.
Antibody response
COVID-19
Machine learning
SARS-CoV-2
Solid organ transplantation
Vaccination
Journal
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
ISSN: 1469-0691
Titre abrégé: Clin Microbiol Infect
Pays: England
ID NLM: 9516420
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
received:
19
12
2022
revised:
05
04
2023
accepted:
26
04
2023
medline:
23
10
2023
pubmed:
8
5
2023
entrez:
7
5
2023
Statut:
ppublish
Résumé
The study aim was to assess predictors of negative antibody response (AbR) in solid organ transplant (SOT) recipients after the first booster of SARS-CoV-2 vaccination. Solid organ transplant recipients receiving SARS-CoV-2 vaccination were prospectively enrolled (March 2021-January 2022) at six hospitals in Italy and Spain. AbR was assessed at first dose (t Overall, 1615 SOT recipients (1072 [66.3%] males; mean age±standard deviation [SD], 57.85 ± 13.77) were enrolled, and 1211 received three vaccination doses. Negative AbR rate decreased from 93.66% (886/946) to 21.90% (202/923) from t Almost a quarter of SOT recipients showed negative AbR after first booster dosage. Unfortunately, clinical information cannot efficiently predict negative AbR even with ML algorithms.
Identifiants
pubmed: 37150358
pii: S1198-743X(23)00201-X
doi: 10.1016/j.cmi.2023.04.027
pmc: PMC10212001
pii:
doi:
Substances chimiques
COVID-19 Vaccines
0
Antibodies, Viral
0
Types de publication
Multicenter Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1084.e1-1084.e7Informations de copyright
Copyright © 2023. Published by Elsevier Ltd.