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One-year temporal changes in long COVID prevalence and characteristics: a systematic review and meta-analysis.
Huang, Qiangru; Jia, Mengmeng; Sun, Yanxia; Jiang, Binshan; Cui, Dan; Feng, Luzhao; Yang, Weizhong.
  • Huang Q; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Jia M; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Sun Y; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Jiang B; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Cui D; Department of Pulmonary and Critical Care Medicine, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, China; Department of Pulmonary and Critical Care Medicine, National Center for Respiratory Medicine, Center of Respiratory Medicine, National Clinical Rese
  • Feng L; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Yang W; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China. Electronic address: yangweizhong@cams.cn.
Value Health ; 2022 Nov 24.
Article in English | MEDLINE | ID: covidwho-20237002
ABSTRACT

OBJECTIVES:

This study aimed to explore the 1-year temporal change in prevalence, variety, and potential risk factors of long COVID symptoms, and to further predict the prognostic trends of long COVID.

METHODS:

We searched electronic databases for related studies published from January 2020 to February 2022, and conducted one group meta-analysis and locally weighted regression explore the monthly temporal change in the prevalence of each long COVID symptom in 1-year follow-up period.

RESULTS:

A total of 137 studies were included in meta-analysis, including 134,093 participants. The temporal change of any long COVID symptom showed a steep decrease initially (from 92% at acute phase to 55% at 1-month follow-up), followed by stabilization at approximately 50% during 1-year follow-up. Six months or more after the acute phase, the odds ratio (OR) of population characteristic factors increased, such as female gender (from 1.62 to 1.82), while the OR value of acute phase-related factors (severe/critical and hospitalization) decreased. As for specific symptoms, about two-thirds of the symptoms did not significantly reduce during the 1-year follow-up, and the neuropsychiatric symptoms showed a higher long-term prevalence (approximately 25%) and longer persistence than physical-symptoms.

CONCLUSIONS:

The temporal changes in the prevalence and characteristics speculate that long COVID may persist longer than expected. In particular, we should pay more attention to neuropsychiatric symptoms and other symptoms for which there is no significant downward trend in prevalence. The influence of acute phase-related factors for long COVID gradually decreases over time, while the influence of population characteristic-related gradually increases.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Reviews / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal subject: Pharmacology Year: 2022 Document Type: Article Affiliation country: J.jval.2022.11.011

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Reviews / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal subject: Pharmacology Year: 2022 Document Type: Article Affiliation country: J.jval.2022.11.011