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

Risultato della ricerca: Contributo in rivista › Articolo in rivista

Lingua originale	English
pagine (da-a)	105497-105499
Numero di pagine	3
Rivista	Joint Bone Spine
Volume	90
DOI	https://doi.org/10.1016/j.jbspin.2022.105497
Stato di pubblicazione	Pubblicato - 2023

Keywords

COVID-19
Epidemiology
Public health
Systemic autoimmune rheumatic disease

OSS delle Nazioni Unite

Questo processo contribuisce al raggiungimento dei seguenti obiettivi di sviluppo sostenibile

Accesso al documento

10.1016/j.jbspin.2022.105497

Altri file e collegamenti

Link a IRIS PubliCatt

Cita questo

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. (2023). 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, 105497-105499. https://doi.org/10.1016/j.jbspin.2022.105497

@article{d984594012d8439c93ffdf64ee3a76ff,

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",

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 = "2023",

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

language = "English",

volume = "90",

pages = "105497--105499",

journal = "Joint Bone Spine",

issn = "1297-319X",

publisher = "Expansion Scientifique Francaise",

}

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 2023, '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, pagg. 105497-105499. https://doi.org/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. / De Lorenzis, Enrico; Parente, Paolo; Natalello, Gerlando et al.
In: Joint Bone Spine, Vol. 90, 2023, pag. 105497-105499.

Risultato della ricerca: Contributo in rivista › Articolo in rivista

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 - 2023

Y1 - 2023

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 - http://hdl.handle.net/10807/237507

U2 - 10.1016/j.jbspin.2022.105497

DO - 10.1016/j.jbspin.2022.105497

M3 - Article

SN - 1297-319X

VL - 90

SP - 105497

EP - 105499

JO - Joint Bone Spine

JF - Joint Bone Spine

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. 2023;90:105497-105499. doi: 10.1016/j.jbspin.2022.105497