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10.1016/j.eclinm.2021.100899

http://scihub22266oqcxt.onion/10.1016/j.eclinm.2021.100899
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suck abstract from ncbi


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pmid34036253      EClinicalMedicine 2021 ; 36 (ä): 100899
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  • Characteristics and predictors of acute and chronic post-COVID syndrome: A systematic review and meta-analysis #MMPMID34036253
  • Iqbal FM; Lam K; Sounderajah V; Clarke JM; Ashrafian H; Darzi A
  • EClinicalMedicine 2021[Jun]; 36 (ä): 100899 PMID34036253show ga
  • BACKGROUND: A significant proportion of individuals experience lingering and debilitating symptoms following acute COVID-19 infection. The National Institute for Health and Care Excellence (NICE) have coined the persistent cluster of symptoms as post-COVID syndrome. This has been further sub-categorised into acute post-COVID syndrome for symptoms persisting three weeks beyond initial infection and chronic post-COVID syndrome for symptoms persisting beyond twelve weeks. The aim of this review was to detail the prevalence of clinical features and identify potential predictors for acute and chronic post-COVID syndrome. METHODS: A systematic literature search, with no language restrictions, was performed to identify studies detailing characteristics and outcomes related to survivorship of post-COVID syndrome. The last search was performed on 6 March 2021 and all pre-dating published articles included. A means of proportion meta-analysis was performed to quantify characteristics of acute and chronic post-COVID syndrome. Study quality was assessed with a specific risk of bias tool. PROSPERO Registration: CRD42020222855. FINDINGS: A total of 43 studies met the eligibility criteria; of which, 38 allowed for meta-analysis. Fatigue and dyspnoea were the most prevalent symptoms in acute post-COVID (0.37 and 0.35) and fatigue and sleep disturbance in chronic post-COVID syndrome (0.48 and 0.44), respectively. The available evidence is generally of poor quality, with considerable risk of bias, and are of observational design. INTERPRETATION: In conclusion, this review highlights that flaws in data capture and interpretation, noted in the uncertainty within our meta-analysis, affect the applicability of current knowledge. Policy makers and researchers must focus on understanding the impact of this condition on individuals and society with appropriate funding initiatives and global collaborative research.
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