As COVID-19 becomes endemic, identifying vulnerable population groups for severe infection outcomes and defining rapid and effective preventive and therapeutic strategies remains a public health priority. We performed an umbrella review, including comprehensive studies (meta-analyses and systematic reviews) investigating COVID-19 risk for infection, hospitalization, intensive care unit (ICU) admission, and mortality in people with psychiatric disorders, and outlined evidence- and consensus-based recommendations for overcoming potential barriers that psychiatric patients may experience in preventing and managing COVID-19, and defining optimal therapeutic options and current research priorities in psychiatry. We searched Web of Science, PubMed, and Ovid/PsycINFO databases up to 17 January 2022 for the umbrella review. We synthesized evidence, extracting when available pooled odd ratio estimates for the categories "any mental disorder" and "severe mental disorders." The quality of each study was assessed using the AMSTAR-2 approach and ranking evidence quality. We identified four systematic review/meta-analysis combinations, one meta-analysis, and three systematic reviews, each including up to 28 original studies. Although we rated the quality of studies from moderate to low and the evidence ranged from highly suggestive to non-significant, we found consistent evidence that people with mental illness are at increased risk of COVID-19 infection, hospitalization, and most importantly mortality, but not of ICU admission. The risk and the burden of COVID-19 in people with mental disorders, in particular those with severe mental illness, can no longer be ignored but demands urgent targeted and persistent action. Twenty-two recommendations are proposed to facilitate this process.

Joint European policy on the COVID-19 risks for people with mental disorders: An umbrella review and evidence- and consensus-based recommendations for mental and public health

Mazza, Mario Gennaro;Benedetti, Francesco;
2022-01-01

Abstract

As COVID-19 becomes endemic, identifying vulnerable population groups for severe infection outcomes and defining rapid and effective preventive and therapeutic strategies remains a public health priority. We performed an umbrella review, including comprehensive studies (meta-analyses and systematic reviews) investigating COVID-19 risk for infection, hospitalization, intensive care unit (ICU) admission, and mortality in people with psychiatric disorders, and outlined evidence- and consensus-based recommendations for overcoming potential barriers that psychiatric patients may experience in preventing and managing COVID-19, and defining optimal therapeutic options and current research priorities in psychiatry. We searched Web of Science, PubMed, and Ovid/PsycINFO databases up to 17 January 2022 for the umbrella review. We synthesized evidence, extracting when available pooled odd ratio estimates for the categories "any mental disorder" and "severe mental disorders." The quality of each study was assessed using the AMSTAR-2 approach and ranking evidence quality. We identified four systematic review/meta-analysis combinations, one meta-analysis, and three systematic reviews, each including up to 28 original studies. Although we rated the quality of studies from moderate to low and the evidence ranged from highly suggestive to non-significant, we found consistent evidence that people with mental illness are at increased risk of COVID-19 infection, hospitalization, and most importantly mortality, but not of ICU admission. The risk and the burden of COVID-19 in people with mental disorders, in particular those with severe mental illness, can no longer be ignored but demands urgent targeted and persistent action. Twenty-two recommendations are proposed to facilitate this process.
2022
COVID-19
mental health
psychiatry
recommendations
umbrella review
Consensus
Humans
Policy
Public Health
COVID-19
Mental Disorders
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/132111
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