Sunkersing David, Goodfellow Henry, Mu Yi, Ramasawmy Mel, Murali Mayur, Adams Lawrence, FitzGerald Ted J, Blandford Ann, Stevenson Fiona, Bindman Julia, Robson Chris, Banerjee Amitava
University College London, London, UK.
Living With Ltd, London, UK.
JRSM Open. 2024 Aug 28;15(7):20542704241274292. doi: 10.1177/20542704241274292. eCollection 2024 Jul.
To investigate long COVID (LC) symptoms self-reported via a digital application. Explore associations between various demographic factors and intensity of LC symptoms.
A retrospective case series study. We analysed self-reported symptoms from 1008 individuals with LC between November 30, 2020, and March 23, 2022.
England and Wales.
Individuals with LC using the healthcare application in 31 post-COVID-19 clinics and self-reporting LC symptoms.
Highest reported LC symptoms, associations with demographic factors and intensity of symptoms.
109 symptom categories were identified, with pain (26.5%), neuropsychological issues (18.4%), fatigue (14.3%) and dyspnoea (7.4%) the most prevalent. The intensity of reported symptoms increased by 3.3% per month since registration. Age groups 68-77 and 78-87 experienced higher symptom intensity (32.8% and 86% higher, respectively) compared to the 18-27 age group. Women reported 9.2% more intense symptoms than men, and non-white individuals with LC reported 23.5% more intense symptoms than white individuals with LC. Higher education levels (national vocational qualification (NVQ) 3 to NVQ 5) were associated with less symptom intensity (27.7%, 62.8% and 44.7% less, respectively) compared to the least educated (NVQ 1-2). People in less deprived areas had less intense symptoms than those in the most deprived area. No significant association was found between index of multiple deprivation (IMD) decile and number of symptoms.
Treatment plans must prioritise addressing prevalent LC symptoms; we recommend sustained support for LC clinics. Demographic factors significantly influence symptom severity, underlining the need for targeted interventions. These findings can inform healthcare policies to better manage LC.
通过数字应用程序调查自我报告的新冠后综合征（LC）症状。探索各种人口统计学因素与LC症状强度之间的关联。
一项回顾性病例系列研究。我们分析了2020年11月30日至2022年3月23日期间1008名LC患者自我报告的症状。
英格兰和威尔士。
在31家新冠后诊所使用医疗保健应用程序并自我报告LC症状的患者。
报告的最严重LC症状、与人口统计学因素的关联以及症状强度。
确定了109种症状类别，其中疼痛（26.5%）、神经心理问题（18.4%）、疲劳（14.3%）和呼吸困难（7.4%）最为常见。自注册以来，报告症状的强度每月增加3.3%。与18-27岁年龄组相比，68-77岁和78-87岁年龄组的症状强度更高（分别高出32.8%和86%）。女性报告的症状强度比男性高9.2%，LC非白人患者报告的症状强度比LC白人患者高23.5%。与受教育程度最低（国家职业资格（NVQ）1-2级）的人群相比，较高教育水平（NVQ 3至NVQ 5级）与较低的症状强度相关（分别低27.7%、62.8%和44.7%）。贫困程度较低地区的人的症状强度低于最贫困地区的人。未发现多重贫困指数（IMD）十分位数与症状数量之间存在显著关联。
治疗计划必须优先解决常见的LC症状；我们建议持续支持LC诊所。人口统计学因素显著影响症状严重程度，凸显了针对性干预的必要性。这些发现可为医疗政策提供参考，以更好地管理LC。
