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IRIS
Objectives: Physical function in RA is largely influenced by multiple clinical factors, however, there is a growing body of evidence that psychological state and other comorbidities also play an essential role. Using data obtained in the COVID-19 Vaccination in Autoimmune Diseases study, an international self-reported e-survey, we aimed to explore the predictive ability of sociodemographic and clinical variables on Patient-Reported Outcomes Measurement Information System Physical Function Short Form 10a (PROMIS PF-10a) in RA and to investigate variation in disease activity and functional outcomes based on country-level socio-economic parameters. Methods: Patient demographics, disease characteristics including current symptom status, functional status and treatment variables, as well as income level of the country of residence, were extracted from survey responses. PROMIS PF-10a scores were compared across country income levels. The influence of extracted variables on reversed PROMIS PF-10a scores were investigated using negative binomial univariable- and multivariable regression. Results: A total of 1342 RA patients were included in this analysis. In the optimised parsimonious predictive model for reversed PROMIS PF-10a, older age, female gender, disease duration, fatigue and pain levels were independently associated with worse physical function, whereas Asian ethnicity, higher overall physical health ratings, ability to carry out everyday activities and residing in a country with an upper-middle or high-income level were independently associated with better physical function. Conclusion: Our study highlights that clinical factors remain strong predictors of physical function in RA, irrespective of individual and country-level socio-economic differences. Interestingly, high country-level income was associated with better physical function, irrespective of individual sociodemographic and clinical factors.
Determinants of physical function, as measured using PROMIS PF-10a, in patients with rheumatoid arthritis: results from the international COVID-19 Vaccination in Autoimmune Diseases (COVAD) study
Objectives: Physical function in RA is largely influenced by multiple clinical factors, however, there is a growing body of evidence that psychological state and other comorbidities also play an essential role. Using data obtained in the COVID-19 Vaccination in Autoimmune Diseases study, an international self-reported e-survey, we aimed to explore the predictive ability of sociodemographic and clinical variables on Patient-Reported Outcomes Measurement Information System Physical Function Short Form 10a (PROMIS PF-10a) in RA and to investigate variation in disease activity and functional outcomes based on country-level socio-economic parameters. Methods: Patient demographics, disease characteristics including current symptom status, functional status and treatment variables, as well as income level of the country of residence, were extracted from survey responses. PROMIS PF-10a scores were compared across country income levels. The influence of extracted variables on reversed PROMIS PF-10a scores were investigated using negative binomial univariable- and multivariable regression. Results: A total of 1342 RA patients were included in this analysis. In the optimised parsimonious predictive model for reversed PROMIS PF-10a, older age, female gender, disease duration, fatigue and pain levels were independently associated with worse physical function, whereas Asian ethnicity, higher overall physical health ratings, ability to carry out everyday activities and residing in a country with an upper-middle or high-income level were independently associated with better physical function. Conclusion: Our study highlights that clinical factors remain strong predictors of physical function in RA, irrespective of individual and country-level socio-economic differences. Interestingly, high country-level income was associated with better physical function, irrespective of individual sociodemographic and clinical factors.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/3015513
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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.
