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Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis

BACKGROUND: This study investigated whether the inflammation prognostic index (IPI) and the mortality predicting index (MPI) at diagnosis could predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody (ANCA)‐associated vasculitis (AAV). METHODS: We included 223 AAV patients a...

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Autores principales: Do, Hyunsue, Song, Jason Jungsik, Park, Yong‐Beom, Lee, Sang‐Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373352/
https://www.ncbi.nlm.nih.gov/pubmed/34181278
http://dx.doi.org/10.1002/jcla.23885
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author Do, Hyunsue
Song, Jason Jungsik
Park, Yong‐Beom
Lee, Sang‐Won
author_facet Do, Hyunsue
Song, Jason Jungsik
Park, Yong‐Beom
Lee, Sang‐Won
author_sort Do, Hyunsue
collection PubMed
description BACKGROUND: This study investigated whether the inflammation prognostic index (IPI) and the mortality predicting index (MPI) at diagnosis could predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody (ANCA)‐associated vasculitis (AAV). METHODS: We included 223 AAV patients and reviewed their medical records. Clinical and laboratory data and AAV‐specific indices at diagnosis were assessed. The IPI was calculated as neutrophil‐to‐lymphocyte ratio (NLR) × C‐reactive protein to albumin ratio (CAR). Here, we newly developed an MPI (NLR × CAR × monocyte counts). RESULTS: The mean age of 223 patients (122 MPA, 57 GPA and 44 EGPA patients) was 59 years. The rate of mortality was 11.2%. Using the receiver operator characteristic curve for all‐cause mortality, the cut‐offs were calculated as NLR: 3.22, CAR: 3.25, IPI: 18.53 and MPI: 8367.82. In the univariable Cox hazard analysis, age, gender, smoking history, BVAS, FFS and over the cut‐off of each index showed statistical significance. As the indices share at least two mutual variables, the multivariable analysis was conducted four times based on each index. An IPI ≥18.53 (HR 3.162) and MPI ≥8367.82 (HR 3.356) were significantly associated with all‐cause mortality. CONCLUSIONS: This study developed a novel indicator, MPI, that uses the existing NLR and CAR indices and proved that it could predict all‐cause mortality in AAV patients.
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spelling pubmed-83733522021-08-24 Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis Do, Hyunsue Song, Jason Jungsik Park, Yong‐Beom Lee, Sang‐Won J Clin Lab Anal Research Articles BACKGROUND: This study investigated whether the inflammation prognostic index (IPI) and the mortality predicting index (MPI) at diagnosis could predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody (ANCA)‐associated vasculitis (AAV). METHODS: We included 223 AAV patients and reviewed their medical records. Clinical and laboratory data and AAV‐specific indices at diagnosis were assessed. The IPI was calculated as neutrophil‐to‐lymphocyte ratio (NLR) × C‐reactive protein to albumin ratio (CAR). Here, we newly developed an MPI (NLR × CAR × monocyte counts). RESULTS: The mean age of 223 patients (122 MPA, 57 GPA and 44 EGPA patients) was 59 years. The rate of mortality was 11.2%. Using the receiver operator characteristic curve for all‐cause mortality, the cut‐offs were calculated as NLR: 3.22, CAR: 3.25, IPI: 18.53 and MPI: 8367.82. In the univariable Cox hazard analysis, age, gender, smoking history, BVAS, FFS and over the cut‐off of each index showed statistical significance. As the indices share at least two mutual variables, the multivariable analysis was conducted four times based on each index. An IPI ≥18.53 (HR 3.162) and MPI ≥8367.82 (HR 3.356) were significantly associated with all‐cause mortality. CONCLUSIONS: This study developed a novel indicator, MPI, that uses the existing NLR and CAR indices and proved that it could predict all‐cause mortality in AAV patients. John Wiley and Sons Inc. 2021-06-28 /pmc/articles/PMC8373352/ /pubmed/34181278 http://dx.doi.org/10.1002/jcla.23885 Text en © 2021 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Do, Hyunsue
Song, Jason Jungsik
Park, Yong‐Beom
Lee, Sang‐Won
Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title_full Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title_fullStr Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title_full_unstemmed Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title_short Novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
title_sort novel mortality‐predicting index at diagnosis can effectively predict all‐cause mortality in patients with antineutrophil cytoplasmic antibody‐associated vasculitis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373352/
https://www.ncbi.nlm.nih.gov/pubmed/34181278
http://dx.doi.org/10.1002/jcla.23885
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