重症肌无力
医学
德尔菲法
德尔菲
投票
物理疗法
循证医学
生活质量(医疗保健)
人口
比例(比率)
家庭医学
替代医学
精神科
护理部
计算机科学
病理
人工智能
法学
物理
操作系统
环境卫生
政治
量子力学
政治学
作者
Andreas Meisel,Francesco Saccà,Jennifer Spillane,John Vissing
摘要
Abstract Background Regular and consistent disease assessment could provide a clearer picture of burden in generalised myasthenia gravis (gMG) and improve patient care; however, the use of assessment tools in practice lacks standardisation. This modified Delphi approach was taken to review current evidence on assessment tool use in gMG and develop expert‐derived consensus recommendations for good practice. Methods A European expert panel of 15 experienced gMG neurologists contributed to development of this consensus, four of whom formed a lead Sub‐committee. The PICO (Population, Intervention, Control, Outcomes) framework was used to define six clinical questions on gMG assessment tools, a systematic literature review was conducted, and evidence‐based statements were developed. According to a modified Delphi voting process, consensus was reached when ≥70% of the experts rated agreement with a statement as ≥8 on a scale of 1–10. Results Eighteen expert‐ and evidence‐based consensus statements based on six themes were developed. Key recommendations include: consistent use of the Myasthenia Gravis Activities of Daily Living score (MG‐ADL) across clinical settings, followed by a simple question (e.g., Patient Acceptable Symptom State [PASS]) or scale to determine patient satisfaction in clinical practice; use of a Quantitative Myasthenia Gravis [QMG] or quality of life [QoL] assessment when the MG‐ADL indicates disease worsening; and consideration of symptom state to determine the timing and frequency of recommended assessments. Expert panel consensus was reached on all 18 statements after two voting rounds. Conclusions This process provided evidence‐ and expert consensus‐based recommendations for the use of objective and subjective assessment tools across gMG research and care to improve management and outcomes for patients.
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