Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients

Enrico De Lorenzis; Paolo Parente; Gerlando Natalello; Salvatore Soldati; Silvia Laura Bosello; Andrea Barbara; Chiara Sorge; Svetlana Axelrod; Lucrezia Verardi; Pier Giacomo Cerasuolo; Giusy Peluso; Antonella Gemma; Marina Davoli; Donatella Biliotti; Vincenzo Bruzzese; Mauro Goletti; Mirko Di Martino; Maria Antonietta D'Agostino

doi:10.1016/j.jbspin.2022.105497

Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients

Enrico De Lorenzis
, Paolo Parente
, Gerlando Natalello
, Salvatore Soldati
, Silvia Laura Bosello
, Andrea Barbara
, Chiara Sorge
, Svetlana Axelrod
, Lucrezia Verardi
, Pier Giacomo Cerasuolo
, Giusy Peluso
, Antonella Gemma
, Marina Davoli
, Donatella Biliotti
, Vincenzo Bruzzese
, Mauro Goletti
, Mirko Di Martino
, Maria Antonietta D'Agostino^*

^*Autore corrispondente per questo lavoro

Department of Epidemiology Lazio Regional Health Service
University of Rome La Sapienza
Local public health office Roma 1
Sechenov First Moscow State Medical University
Ospedale Nuovo Regina Margherita

Risultato della ricerca: Contributo in rivista › Articolo

Abstract

No abstract available

Lingua originale	Inglese
pagine (da-a)	105497-N/A
Rivista	Joint Bone Spine
Volume	90
Numero di pubblicazione	2
DOI	https://doi.org/10.1016/j.jbspin.2022.105497
Stato di pubblicazione	Pubblicato - 2022

OSS delle Nazioni Unite

Questo processo contribuisce al raggiungimento dei seguenti obiettivi di sviluppo sostenibile

SDG 3 Salute e benessere

All Science Journal Classification (ASJC) codes

Reumatologia

Keywords

COVID-19
Epidemiology
Public health
Systemic autoimmune rheumatic disease

Accesso al documento

10.1016/j.jbspin.2022.105497

Altri file e collegamenti

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De Lorenzis, E., Parente, P., Natalello, G., Soldati, S., Bosello, S. L., Barbara, A., Sorge, C., Axelrod, S., Verardi, L., Cerasuolo, P. G., Peluso, G., Gemma, A., Davoli, M., Biliotti, D., Bruzzese, V., Goletti, M., Di Martino, M., & D'Agostino, M. A. (2022). Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients. Joint Bone Spine, 90(2), 105497-N/A. https://doi.org/10.1016/j.jbspin.2022.105497

@article{abf059d59a5345858f7502d62fb04898,

title = "Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients",

abstract = "No abstract available",

keywords = "COVID-19, Epidemiology, Public health, Systemic autoimmune rheumatic disease, COVID-19, Epidemiology, Public health, Systemic autoimmune rheumatic disease",

author = "\{De Lorenzis\}, Enrico and Paolo Parente and Gerlando Natalello and Salvatore Soldati and Bosello, \{Silvia Laura\} and Andrea Barbara and Chiara Sorge and Svetlana Axelrod and Lucrezia Verardi and Cerasuolo, \{Pier Giacomo\} and Giusy Peluso and Antonella Gemma and Marina Davoli and Donatella Biliotti and Vincenzo Bruzzese and Mauro Goletti and \{Di Martino\}, Mirko and D'Agostino, \{Maria Antonietta\}",

year = "2022",

doi = "10.1016/j.jbspin.2022.105497",

language = "English",

volume = "90",

pages = "105497--N/A",

journal = "Joint Bone Spine",

issn = "1297-319X",

publisher = "Elsevier Masson",

number = "2",

}

De Lorenzis, E, Parente, P, Natalello, G, Soldati, S, Bosello, SL, Barbara, A, Sorge, C, Axelrod, S, Verardi, L, Cerasuolo, PG, Peluso, G, Gemma, A, Davoli, M, Biliotti, D, Bruzzese, V, Goletti, M, Di Martino, M & D'Agostino, MA 2022, 'Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients', Joint Bone Spine, vol. 90, n. 2, pagg. 105497-N/A. https://doi.org/10.1016/j.jbspin.2022.105497

Risultato della ricerca: Contributo in rivista › Articolo

TY - JOUR

T1 - Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients

AU - De Lorenzis, Enrico

AU - Parente, Paolo

AU - Natalello, Gerlando

AU - Soldati, Salvatore

AU - Bosello, Silvia Laura

AU - Barbara, Andrea

AU - Sorge, Chiara

AU - Axelrod, Svetlana

AU - Verardi, Lucrezia

AU - Cerasuolo, Pier Giacomo

AU - Peluso, Giusy

AU - Gemma, Antonella

AU - Davoli, Marina

AU - Biliotti, Donatella

AU - Bruzzese, Vincenzo

AU - Goletti, Mauro

AU - Di Martino, Mirko

AU - D'Agostino, Maria Antonietta

PY - 2022

Y1 - 2022

N2 - No abstract available

AB - No abstract available

KW - COVID-19

KW - Epidemiology

KW - Public health

KW - Systemic autoimmune rheumatic disease

KW - COVID-19

KW - Epidemiology

KW - Public health

KW - Systemic autoimmune rheumatic disease

UR - https://publicatt.unicatt.it/handle/10807/221888

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U2 - 10.1016/j.jbspin.2022.105497

DO - 10.1016/j.jbspin.2022.105497

M3 - Article

SN - 1297-319X

VL - 90

SP - 105497-N/A

JO - Joint Bone Spine

JF - Joint Bone Spine

IS - 2

ER -

De Lorenzis E, Parente P, Natalello G, Soldati S, Bosello SL, Barbara A et al. Chronic related group classification system as a new public health tool to predict risk and outcome of COVID-19 in patients with systemic rheumatic diseases: A population-based study of more than forty thousand patients. Joint Bone Spine. 2022;90(2):105497-N/A. doi: 10.1016/j.jbspin.2022.105497