RESUMO
BACKGROUND: A series of qualitative studies conducted by the OMERACT Myositis Working Group identified pain interference, fatigue, and physical function as highly important life impact domains for adults with idiopathic inflammatory myositis (IIM). In this study, our goal was to assess the responsiveness and minimal important difference of PROMIS pain interference (6a), fatigue (7a), and physical function (8b). METHODS: Adults with IIM from USA, Netherlands, Korea, Sweden, and Australia with two "clinical" visits were enrolled in this prospective study. Anchor questions on a Likert scale were collected at baseline, and manual muscle testing (MMT), physician and patient reported global disease activity, and PROMIS instruments were collected at both visits. Responsiveness was assessed with i) ANOVA, ii) paired t-test, effect size and standardized response mean, and iii) Pearson correlation. Minimal important difference (MID), minimal important change (MIC) and minimal detectable change (MDC) values were calculated. RESULTS: 114 patients with IIM (median age 60, 60 % female) completed both visits. Changes in PROMIS instruments were significantly different among anchor categories. Patients who reported improvement had a significant improvement in their PROMIS scores with at least medium effect size, while patients who reported worsening and stability did not show a significant change with weak effect size. PROMIS instruments had weak to moderate correlations with MMT, patient and physician global disease activity. MID was approximately 2-3 points for Pain Interference and 3-4 points for Fatigue and Physical Function forms based on the method used. MIC was approximately 4-5 for improvement of all the instruments, while MDC was 1.7-2 points for Pain Interference and Physical Function and 3.2-3.9 for Fatigue. CONCLUSION: This study provides evidence towards the responsiveness of the PROMIS instruments in a large international prospective cohort of adults with IIM supporting their use as PROMs in adult myositis.
Assuntos
Miosite , Medidas de Resultados Relatados pelo Paciente , Adulto , Humanos , Feminino , Masculino , Estudos Prospectivos , Dor , Miosite/complicações , Miosite/diagnóstico , Fadiga/diagnóstico , Fadiga/etiologiaRESUMO
The path of tokamak fusion and International thermonuclear experimental reactor (ITER) is maintaining high-performance plasma to produce sufficient fusion power. This effort is hindered by the transient energy burst arising from the instabilities at the boundary of plasmas. Conventional 3D magnetic perturbations used to suppress these instabilities often degrade fusion performance and increase the risk of other instabilities. This study presents an innovative 3D field optimization approach that leverages machine learning and real-time adaptability to overcome these challenges. Implemented in the DIII-D and KSTAR tokamaks, this method has consistently achieved reactor-relevant core confinement and the highest fusion performance without triggering damaging bursts. This is enabled by advances in the physics understanding of self-organized transport in the plasma edge and machine learning techniques to optimize the 3D field spectrum. The success of automated, real-time adaptive control of such complex systems paves the way for maximizing fusion efficiency in ITER and beyond while minimizing damage to device components.