Skip to main navigation Skip to search Skip to main content

Predictors of clinical response in patients with ulcerative colitis treated with granulocyte-monocyte apheresis: analysis of the apheresis registry data

Translated title of the contribution: [Autom. eng. transl.] Predictors of clinical response in patients with ulcerative colitis treated with granulocyte-monocyte apheresis: analysis of the apheresis registry data
  • Pietro Manuel Ferraro
  • , Valeria D'Ovidio
  • , Giampaolo Bresci
  • , Marco Astegiano
  • , Beatrice Principi
  • , Renata D'Inca'
  • , Roberto Testa
  • , Daniela Valpiani
  • , Luisa Guidi
  • , Alessandro Armuzzi
  • , Francesco Costa
  • , Annalisa Aratari
  • , Maurizio Vecchi
  • , Roberto De Franchis
  • , Vincenza Di Leo
  • , Chiara Ricci
  • , Gabriele Riegler
  • , Elisabetta Colombo
  • , Giuseppe Repaci
  • , Pierenrico Lecis
  • Michele Silla, Stefano Passalacqua

Research output: Contribution to journalArticle

Abstract

We analyzed predictors of clinical response after a cycle of granulocytemonocyte apheresis in 173 patients with ulcerative colitis. Hemoglobin levels independently predicted good clinical outcome.
Translated title of the contribution[Autom. eng. transl.] Predictors of clinical response in patients with ulcerative colitis treated with granulocyte-monocyte apheresis: analysis of the apheresis registry data
Original languageItalian
Pages (from-to)144-146
Number of pages3
JournalGIORNALE ITALIANO DI NEFROLOGIA
Volume29 Suppl 54
Publication statusPublished - 2012

Keywords

  • Adult
  • Biological Markers
  • Colitis, Ulcerative
  • Female
  • Granulocytes
  • Hemoglobins
  • Humans
  • Leukapheresis
  • Male
  • Middle Aged
  • Monocytes
  • Predictive Value of Tests
  • Retrospective Studies
  • Sensitivity and Specificity
  • Treatment Outcome

Fingerprint

Dive into the research topics of '[Autom. eng. transl.] Predictors of clinical response in patients with ulcerative colitis treated with granulocyte-monocyte apheresis: analysis of the apheresis registry data'. Together they form a unique fingerprint.

Cite this