Centre for Patient Reported Outcomes Research, University of Birmingham, Birmingham, UK.
Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Sci Rep. 2024 Sep 27;14(1):22083. doi: 10.1038/s41598-024-61827-4.
Post COVID-19 condition or long COVID is highly prevalent and often debilitating, with key symptoms including fatigue, breathlessness, and brain fog. There is currently a lack of evidence-based treatments for this highly complex syndrome. There is a need for clinical trial platforms to rapidly evaluate nonpharmacological treatments to support affected individuals with symptom management. We co-produced a mixed methods feasibility study to evaluate a multi-arm digital decentralised clinical trial (DCT) platform to assess non-pharmacological interventions for Long COVID, using pacing interventions as an exemplar. The study demonstrated that the platform was able to successfully e-consent participants, randomise them into one of four intervention arms, capture baseline data, and capture outcomes relevant to a health economic evaluation. The study also highlighted several challenges, including difficulties with recruitment, imposter participants, and high attrition rates. We highlight how these challenges can potentially be mitigated to make a fully powered DCT more feasible.
新冠后状况或长新冠极为普遍,且常导致身体虚弱,主要症状包括疲劳、呼吸急促和脑雾。目前,针对这种高度复杂的综合征,缺乏基于证据的治疗方法。需要临床试验平台来快速评估非药物治疗方法,以支持患有症状的个体进行症状管理。我们共同开展了一项混合方法可行性研究,以评估一种多臂数字去中心化临床试验(DCT)平台,该平台用于评估长新冠的非药物干预措施,以起搏干预作为范例。该研究表明,该平台能够成功地对参与者进行电子知情同意、将他们随机分配到四个干预组之一、收集基线数据,并收集与健康经济评估相关的结果。该研究还强调了一些挑战,包括招募困难、冒名顶替的参与者和高退出率。我们强调了如何减轻这些挑战,使完全功能的 DCT 更可行。