冠状病毒病 2019 年症状在急性期后的持续性:年龄、性别、合并症和感染严重程度是否有影响?

Mansi Shah, Atul Kakar, Atul Gogia, Shrishti Byotra, Vinus Taneja
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引用次数: 0

摘要

背景和目的:由于过去 3 年中在全球范围内发生了多波流行病,冠状病毒病(COVID)后症状持续存在并出现并发症已成为临床上经常遇到的问题。找出风险因素将使我们能够把有限的资源用于需要长期随访和治疗的亚组。通过这项前瞻性观察研究,我们的目的是在印度人群中建立症状持续与四个最有可能导致长期康复的风险因素(急性病严重程度、高龄、多种并发症和女性)之间的统计学相关性:300 名 COVID 逆转录聚合酶链反应(RTPCR)或抗原检测呈阳性的患者被纳入研究,为期 10 个月(从 2020 年 12 月获得伦理许可后至 2021 年 10 月)。在基线时记录症状,并通过预先设计的问卷进行随访,以评估其在 COVID 恢复后 1 个月、2 个月和 4 个月的持续性。采用适当的统计分析[皮尔逊相关性/方差分析(ANOVA)检验]来确定症状的持续性及其严重程度与存在的风险因素之间的相关性:结果:在我们的研究中,急性病的严重程度是每次随访间隔期症状持续存在及其严重程度的最重要决定因素(p < 0.001)。持续性症状的平均数量或严重程度随女性性别、年龄组的增加和多种合并症的存在而增加,但除了女性在 2 个月间隔期内的持续性疲劳外,其他症状的平均数量或严重程度与女性性别、年龄组的增加和多种合并症的存在之间的相关性在统计学上并不显著(P > 0.05):解释与结论:目前记录的持续性症状及其流行率只是长期罹患 COVID 患者的冰山一角。对有严重急性病史的患者应进行密切随访,以便及时发现这些病例并使其康复,因为这对这些患者的预后影响最大。
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Persistence of Coronavirus Disease 2019 Symptoms in Postacute Phase: Does Age, Sex, Comorbidities, and Severity of Infection Have an Impact?

Background and objective: Post-coronavirus disease (COVID) persistence of symptoms and the development of complications have become frequently encountered clinical problems due to multiple waves of the pandemic over the past 3 years across the world. Identifying risk factors would enable us to direct our limited resources toward the subgroups requiring long-term follow-up and treatment. With this prospective observational study, we aim to establish a statistical correlation between the persistence of symptoms and four of the most attributed risk factors for prolonged recovery: severity of acute illness, elderly age, presence of multiple comorbidities, and female gender in the Indian population.

Materials and methods: Three hundred patients with positive COVID reverse transcription polymerase chain reaction (RTPCR) or antigen tests were enrolled over 10 months (from December 2020, after obtaining ethical clearance, to October 2021). Symptoms were recorded at baseline and followed up with a predesigned questionnaire to assess their persistence at 1-, 2-, and 4-month intervals post-COVID recovery. Appropriate statistical analysis [Pearson's correlation/analysis of variance (ANOVA) test] was used to establish the correlation between the persistence of symptoms and their severity with the presence of risk factors.

Results: Severity of acute illness was the single most important determining factor of persistence of symptoms as well as their severity in our study (p < 0.001) at each follow-up interval. The correlation observed between average number or severity of persistent symptoms increased with female gender, increasing age-group and presence of multiple comorbidities was not significant statistically (p > 0.05) with exception of persistent fatigue in females at 2-month interval.

Interpretation and conclusion: Persistent symptoms and its prevalence recorded so far represents tip of the iceberg of patients suffering with long COVID. Patients with history of severe acute illness should be followed up closely for prompt identification and rehabilitation of these cases as it had maximum bearing on the outcome of these patients.

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