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Objective: The presence of comorbidities can substantially affect patients’ quality of life, but data regarding their impact on idiopathic inflammatory myopathies (IIMs) are limited. Methods: We examined the prevalence of comorbidities in IIM patients, other autoimmune rheumatic diseases (oAIRDs) and healthy controls (HCs), using data from the self-reported COVAD-2 survey. We defined basic multimorbidity (BM) as the presence of ≥2 non-rheumatic chronic conditions and complex multimorbidity (CM) as the presence of ≥3 non-rheumatic chronic conditions affecting ≥3 organ systems. Hierarchical clustering on principal components was performed for grouping. Results: Among the COVAD respondents, 1558 IIMs, 4591 oAIRDs and 3652 HCs were analysed. IIMs exhibited a high burden of comorbidities (odds ratio [OR]: 1.62 vs oAIRDs and 2.95 vs HCs, P<0.01), BM (OR: 1.66 vs oAIRDs and 3.52 vs HCs, P<0.01), CM (OR: 1.69 vs AIRDs and 6.23 vs HCs, P<0.01) and mental health disorders (MHDs) (OR: 1.33 vs oAIRDs and 2.63 vs HCs, P<0.01). Among the IIM patients, those with comorbidities or MHDs had lower PROMIS Global Physical (PGP), PROMIS Global Mental (PGM), and PROMIS Physical Function (SF10) scores, and higher fatigue (F4a) scores (all P<0.001). PGP, PGM, SF10a and F4a were influenced by age, active disease, BM and MHDs. Four distinct clusters were identified among the IIMs according to comorbidities and PROMIS scores. Conclusion: Patients with IIMs have a higher burden of comorbidities that influence physical and mental health, identifiable as clinical clusters for optimized and holistic management approaches.
The impact of multimorbidity on Quality of Life in inflammatory myopathies: A cluster analysis from the COVAD dataset
Fornaro, Marco;Venerito, Vincenzo;Pellico, Maria Rosa;Iannone, Florenzo;Joshi, Mrudula;Chen, Yi-Ming;Tan, Ai Lyn;Saha, Sreoshy;Chatterjee, Tulika;Agarwal, Vishwesh;Shinjo, Samuel Katsuyuki;Hoff, Leonardo Santos;Kadam, Esha;Ziade, Nelly;Velikova, Tsvetelina;Hasan, A T M Tanveer;Shumnalieva, Russka;Milchert, Marcin;Tan, Chou Luan;Gracia-Ramos, Abraham Edgar;Cavagna, Lorenzo;Vaidya, Binit;Kuwana, Masataka;Shaharir, Syahrul Sazliyana;Knitza, Johannes;Makol, Ashima;Tehozol, Erick Adrian Zamora;Serrano, Jorge Rojas;Halabi, Hussein;Dey, Dzifa;Toro-Gutiérrez, Carlos Enrique;Goo, Phonpen Akarawatcharangura;Caballero-Uribe, Carlo V;Distler, Oliver;Katchamart, Wanruchada;Day, Jessica;Parodis, Ioannis;Nikiphorou, Elena;Chinoy, Hector;Agarwal, Vikas;Gupta, Latika;null, null;Sen, Parikshit;Javaid, Mahnoor;Andreoli, Laura;Lini, Daniele;Schreiber, Karen;Nune, Arvind;Tan, Ai Lyn;Patel, Aarat;Pauling, John D;Wincup, Chris;Barman, Bhupen;García-De La Torre, Ignacio;Colunga-Pedraza, Iris J;Merayo-Chalico, Javier;Chibuzo, Okwara Celestine;El Kibbi, Lina;Lilleker, James B;Salim, Babur;Gheita, Tamer;Saavedra, Miguel A;Griger, Zoltán;Kardes, Sinan;Vince, Melinda Nagy;Singh, Yogesh Preet;Ranjan, Rajiv;Jain, Avinash;Pandya, Sapan C;Pilania, Rakesh Kumar;Sharma, Aman;M, Manesh Manoj;Gupta, Vikas;Kavadichanda, Chengappa G;Patro, Pradeepta Sekhar;Ajmani, Sajal;Phatak, Sanat;Goswami, Rudra Prosad;Chowdhury, Abhra Chandra;Mathew, Ashish Jacob;Shenoy, Padnamabha;Asranna, Ajay;Bommakanti, Keerthi Talari;Shukla, Anuj;Pande, Arunkumar R;Chandwar, Kunal;Ghodke, Akanksha;Boro, Hiya;Fazal, Zoha Zahid;Vaidya, Binit;Cansu, Döndü Üsküdar;Yıldırım, Reşit;Gasparyan, Armen Yuri;Del Papa, Nicoletta;Sambataro, Gianluca;Fabiola, Atzeni;Govoni, Marcello;Parisi, Simone;Bocci, Elena Bartoloni;Sebastiani, Gian Domenico;Fusaro, Enrico;Sebastiani, Marco;Quartuccio, Luca;Franceschini, Franco;Sainaghi, Pier Paolo;Orsolini, Giovanni;De Angelis, Rossella;Danieli, Maria Giovanna;Grignaschi, Silvia;Giollo, Alessandro;Alunno, Alessia;Traboco, Lisa S;Wibowo, Suryo Anggoro Kusumo;Loarce-Martos, Jesús;Prieto-González, Sergio;Gonzalez, Raquel Aranega;Yoshida, Akira;Nakashima, Ran;Sato, Shinji;Kimura, Naoki;Kaneko, Yuko;Gono, Takahisa;Tomaras, Stylianos;Proft, Fabian Nikolai;Holzer, Marie-Therese;Gromova, Margarita Aleksandrovna;Aharonov, Or;Griger, Zoltán;Hmamouchi, Ihsane;El bouchti, Imane;Baba, Zineb;Giannini, Margherita;Maurier, François;Campagne, Julien;Meyer, Alain;Langguth, Daman;Limaye, Vidya;Needham, Merrilee;Srivastav, Nilesh;Hudson, Marie;Landon-Cardinal, Océane;Zuleta, Wilmer Gerardo Rojas;Arbeláez, Álvaro;Cajas, Javier;Silva, José António Pereira;Fonseca, João Eurico;Zimba, Olena;Ima-Edomwonyi, Uyi;Dedeke, Ibukunoluwa;Airenakho, Emorinken;Madu, Nwankwo Henry;Yerima, Abubakar;Olaosebikan, Hakeem;Becky, A;Koussougbo, Oruma Devi;Palalane, Elisa;So, Ho;Ugarte-Gil, Manuel Francisco;Chinchay, Lyn;Bernaola, José Proaño;Pimentel, Victorio;Fathi, Hanan Mohammed;Mohammed, Reem Hamdy A;Harifi, Ghita;Fuentes-Silva, Yurilís;Cabriza, Karoll;Losanto, Jonathan;Colaman, Nelly;Cachafeiro-Vilar, Antonio;Bautista, Generoso Guerra;Ho, Enrique Julio Giraldo;González, Raúl;Nunez, Lilith Stange;M, Cristian Vergara;Báez, Jossiell Then;Alonzo, Hugo;Pastelin, Carlos Benito Santiago;Salinas, Rodrigo García;Obiols, Alejandro Quiñónez;Chávez, Nilmo;Ordóñez, Andrea Bran;Argueta, Sandra;Llerena, Gil Alberto Reyes;Sierra-Zorita, Radames;Arrieta, Dina;Hidalgo, Eduardo Romero;Saenz, Ricardo;M, Idania Escalante;Morales, Roberto;Calapaqui, Wendy;Quezada, Ivonne;Arredondo, Gabriela
2025-01-01
Abstract
Objective: The presence of comorbidities can substantially affect patients’ quality of life, but data regarding their impact on idiopathic inflammatory myopathies (IIMs) are limited. Methods: We examined the prevalence of comorbidities in IIM patients, other autoimmune rheumatic diseases (oAIRDs) and healthy controls (HCs), using data from the self-reported COVAD-2 survey. We defined basic multimorbidity (BM) as the presence of ≥2 non-rheumatic chronic conditions and complex multimorbidity (CM) as the presence of ≥3 non-rheumatic chronic conditions affecting ≥3 organ systems. Hierarchical clustering on principal components was performed for grouping. Results: Among the COVAD respondents, 1558 IIMs, 4591 oAIRDs and 3652 HCs were analysed. IIMs exhibited a high burden of comorbidities (odds ratio [OR]: 1.62 vs oAIRDs and 2.95 vs HCs, P<0.01), BM (OR: 1.66 vs oAIRDs and 3.52 vs HCs, P<0.01), CM (OR: 1.69 vs AIRDs and 6.23 vs HCs, P<0.01) and mental health disorders (MHDs) (OR: 1.33 vs oAIRDs and 2.63 vs HCs, P<0.01). Among the IIM patients, those with comorbidities or MHDs had lower PROMIS Global Physical (PGP), PROMIS Global Mental (PGM), and PROMIS Physical Function (SF10) scores, and higher fatigue (F4a) scores (all P<0.001). PGP, PGM, SF10a and F4a were influenced by age, active disease, BM and MHDs. Four distinct clusters were identified among the IIMs according to comorbidities and PROMIS scores. Conclusion: Patients with IIMs have a higher burden of comorbidities that influence physical and mental health, identifiable as clinical clusters for optimized and holistic management approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/208062
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.