WeChat Mini Program
Old Version Features

Pathogen Reduction for Platelets-A Review of Recent Implementation Strategies

PATHOGENS(2022)

Fdn IRCCS Ca Granda Osped Maggiore Policlin

Cited 11|Views10
Abstract
The development of pathogen reduction technologies (PRT) for labile blood components is a long-pursued goal in transfusion medicine. While PRT for red blood cells and whole blood are still in an early phase of development, different PRT platforms for plasma and platelets are commercially available and routinely used in several countries. This review describes complementary strategies recommended by the US FDA to mitigate the risk of septic reactions in platelet recipients, including PRT and large-volume delayed sampling, and summarizes the main findings of recent reports discussing economical and organizational issues of platelet PRT implementation. Sophisticated mathematical analytical models are available to determine the impact of PRT on platelet costs, shortages and outdates in different settings. PRT implementation requires careful planning to ensure the availability of sufficient economical, technological and human resources. A phased approach was used in most PRT implementation programs, starting with adult and pediatric immunocompromised patients at higher risk of developing septic platelet transfusion reactions. Overall, the reviewed studies show that significant progress has been made in this area, although additional efforts will be necessary to reduce the storage lesion of PRT platelets and to expand the sustainable applicability of PRT to all labile blood components.
More
Translated text
Key words
platelets,pathogen reduction,platelet transfusion,transmissible infections
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined