Mapping of long COVID condition in India: a study protocol for systematic review and meta-analysis.

IF 1.3 Q3 REHABILITATION
Frontiers in rehabilitation sciences Pub Date : 2025-02-13 eCollection Date: 2025-01-01 DOI:10.3389/fresc.2025.1419963
Nidhi Jain, Komal Shah, Roshani Chauhan, Abhishek Gupta, Priyanka Arora, Deepak Saxena, Dileep Mavalankar
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引用次数: 0

Abstract

Background: The COVID-19 pandemic has reported significant alarming aftereffects experienced by some individuals following acute sequelae of SARS-CoV-2 infection, commonly referred to as long COVID. Long COVID is a set of symptoms that remain for weeks or months, after the initial phase of COVID-19 infection is ended.

Objective: This study protocol outlines the methodology of a systematic review followed by a meta-analysis to comprehensively assess the chronic effects of COVID-19 infection on the Indian population and determine the likely risk factors connected to the development and persistence of long COVID.

Methodology: This study will employ comprehensive search through a custom-made search strategy across significant databases (PubMed, MEDLINE etc.) and grey literature to identify related literature from January 2020 to December 2023. A systematic review and meta-analysis will be conducted to synthesize data from various studies. The data synthesis will involve a comprehensive narrative and tabular presentation of outcome data from included studies, focusing on long-term effects of COVID-19 infection in Indian population. A meta-analysis will be conducted contingent upon the availability and suitability of data. If sufficient and comparable quantitative data are identified across the included studies, statistical synthesis will be undertaken. Subgroup and sensitivity analyses will manage confounders, while MedCalc software will facilitate a meta-analysis to assess pooled data. Publication bias will be evaluated using statistical tests to ensure the integrity of the findings. In the absence of adequate data, a narrative synthesis will be performed to summarize the findings systematically and transparently.

Conclusion: The anticipated findings will contribute to a refined understanding of this condition and its lingering symptoms, guiding healthcare interventions and future research endeavors to mitigate the impact of long COVID in the Indian population.

绘制印度长期COVID状况:用于系统评价和荟萃分析的研究方案。
背景:据报道,在 COVID-19 大流行中,一些人在感染 SARS-CoV-2 后出现急性后遗症,即通常所说的长 COVID。长COVID是指在COVID-19感染的初始阶段结束后,症状持续数周或数月:本研究方案概述了系统综述和荟萃分析的方法,以全面评估 COVID-19 感染对印度人群的慢性影响,并确定与长 COVID 的发展和持续相关的可能风险因素:本研究将采用定制的搜索策略,在重要数据库(PubMed、MEDLINE 等)和灰色文献中进行全面搜索,以确定 2020 年 1 月至 2023 年 12 月期间的相关文献。将进行系统综述和荟萃分析,以综合各项研究的数据。数据综合将包括对所纳入研究的结果数据进行全面叙述和列表,重点关注 COVID-19 感染对印度人群的长期影响。荟萃分析将视数据的可用性和适宜性而定。如果在纳入的各项研究中发现了充足且具有可比性的定量数据,则将进行统计综合分析。分组分析和敏感性分析将对混杂因素进行管理,而 MedCalc 软件将有助于进行荟萃分析以评估汇总数据。将使用统计检验对发表偏倚进行评估,以确保研究结果的完整性。在缺乏足够数据的情况下,将进行叙述性综合,以系统、透明的方式总结研究结果:预期的研究结果将有助于人们更好地了解这种疾病及其挥之不去的症状,从而指导医疗保健干预措施和未来的研究工作,以减轻印度人群中长期 COVID 的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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