Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media.

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES JMIR infodemiology Pub Date : 2022-11-22 eCollection Date: 2022-07-01 DOI:10.2196/39849
Amélia Déguilhem, Joelle Malaab, Manissa Talmatkadi, Simon Renner, Pierre Foulquié, Guy Fagherazzi, Paul Loussikian, Tom Marty, Adel Mebarki, Nathalie Texier, Stephane Schuck
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引用次数: 1

Abstract

Background: Long COVID-a condition with persistent symptoms post COVID-19 infection-is the first illness arising from social media. In France, the French hashtag #ApresJ20 described symptoms persisting longer than 20 days after contracting COVID-19. Faced with a lack of recognition from medical and official entities, patients formed communities on social media and described their symptoms as long-lasting, fluctuating, and multisystemic. While many studies on long COVID relied on traditional research methods with lengthy processes, social media offers a foundation for large-scale studies with a fast-flowing outburst of data.

Objective: We aimed to identify and analyze Long Haulers' main reported symptoms, symptom co-occurrences, topics of discussion, difficulties encountered, and patient profiles.

Methods: Data were extracted based on a list of pertinent keywords from public sites (eg, Twitter) and health-related forums (eg, Doctissimo). Reported symptoms were identified via the MedDRA dictionary, displayed per the volume of posts mentioning them, and aggregated at the user level. Associations were assessed by computing co-occurrences in users' messages, as pairs of preferred terms. Discussion topics were analyzed using the Biterm Topic Modeling; difficulties and unmet needs were explored manually. To identify patient profiles in relation to their symptoms, each preferred term's total was used to create user-level hierarchal clusters.

Results: Between January 1, 2020, and August 10, 2021, overall, 15,364 messages were identified as originating from 6494 patients of long COVID or their caregivers. Our analyses revealed 3 major symptom co-occurrences: asthenia-dyspnea (102/289, 35.3%), asthenia-anxiety (65/289, 22.5%), and asthenia-headaches (50/289, 17.3%). The main reported difficulties were symptom management (150/424, 35.4% of messages), psychological impact (64/424,15.1%), significant pain (51/424, 12.0%), deterioration in general well-being (52/424, 12.3%), and impact on daily and professional life (40/424, 9.4% and 34/424, 8.0% of messages, respectively). We identified 3 profiles of patients in relation to their symptoms: profile A (n=406 patients) reported exclusively an asthenia symptom; profile B (n=129) expressed anxiety (n=129, 100%), asthenia (n=28, 21.7%), dyspnea (n=15, 11.6%), and ageusia (n=3, 2.3%); and profile C (n=141) described dyspnea (n=141, 100%), and asthenia (n=45, 31.9%). Approximately 49.1% of users (79/161) continued expressing symptoms after more than 3 months post infection, and 20.5% (33/161) after 1 year.

Conclusions: Long COVID is a lingering condition that affects people worldwide, physically and psychologically. It impacts Long Haulers' quality of life, everyday tasks, and professional activities. Social media played an undeniable role in raising and delivering Long Haulers' voices and can potentially rapidly provide large volumes of valuable patient-reported information. Since long COVID was a self-titled condition by patients themselves via social media, it is imperative to continuously include their perspectives in related research. Our results can help design patient-centric instruments to be further used in clinical practice to better capture meaningful dimensions of long COVID.

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识别法国长冠肺炎患者的特征和症状:基于社交媒体的数据挖掘信息流行病学研究
背景:长冠状病毒是指COVID-19感染后症状持续存在的疾病,是社交媒体引起的第一种疾病。在法国,法国标签#ApresJ20描述了感染COVID-19后持续超过20天的症状。由于缺乏医疗和官方实体的认可,患者在社交媒体上建立了社区,并将他们的症状描述为长期、波动和多系统的。虽然许多关于长期COVID的研究依赖于传统的研究方法,过程漫长,但社交媒体为快速流动的数据爆发提供了大规模研究的基础。目的:我们旨在识别和分析长途搬运工报告的主要症状、症状共现、讨论的话题、遇到的困难和患者概况。方法:根据公共网站(如Twitter)和健康相关论坛(如Doctissimo)的相关关键词列表提取数据。报告的症状是通过MedDRA字典识别的,按照提到症状的帖子数量显示,并在用户级别进行汇总。通过计算用户消息中的共同出现次数来评估关联,作为首选术语对。采用Biterm主题模型对讨论主题进行分析;手工探索困难和未满足的需求。为了确定与其症状相关的患者概况,使用每个首选术语的总数来创建用户级别的分层集群。结果:在2020年1月1日至2021年8月10日期间,总共有15,364条信息被确定为来自6494名长冠肺炎患者或其护理人员。我们的分析显示3种主要症状共现:乏力-呼吸困难(102/289,35.3%)、乏力-焦虑(65/289,22.5%)和乏力-头痛(50/289,17.3%)。报告的主要困难是症状管理(150/424,35.4%),心理影响(64/424,15.1%),显著疼痛(51/424,12.0%),总体幸福感恶化(52/424,12.3%),以及对日常和职业生活的影响(分别为40/424,9.4%和34/424,8.0%)。我们确定了与症状相关的3种患者特征:特征A (n=406例患者)只报告了虚弱症状;B组(n=129)表现为焦虑(n=129, 100%)、虚弱(n=28, 21.7%)、呼吸困难(n=15, 11.6%)和衰老(n=3, 2.3%);图C (n=141)描述呼吸困难(n=141, 100%)和虚弱(n=45, 31.9%)。大约49.1%的使用者(79/161)在感染后3个多月后仍表现出症状,20.5%(33/161)在感染后1年仍表现出症状。结论:长冠肺炎是一种挥之不去的疾病,影响着全世界人民的身体和心理。它会影响长途工作者的生活质量、日常工作和职业活动。社交媒体在提高和传达长途跋涉者的声音方面发挥了不可否认的作用,并可能迅速提供大量有价值的患者报告信息。长期以来,新冠肺炎是患者在社交媒体上自我命名的疾病,因此有必要在相关研究中不断纳入患者的观点。我们的研究结果可以帮助设计以患者为中心的仪器,进一步用于临床实践,以更好地捕获长COVID的有意义维度。
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