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Effect of the COVID-19 pandemic on incidence of long-term conditions in Welsh residents: a population linkage study.
Qi, Cathy; Osborne, Timothy; Bailey, Rowena; Hollinghurst, Joe; Akbari, Ashley; Cooper, Alison; Peters, Holly; Law, Rebecca-Jane; Lewis, Ruth; Edwards, Adrian; Lyons, Ronan.
Afiliação
  • Qi C; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK.
  • Osborne T; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK. Electronic address: timothy.osborne@swansea.ac.uk.
  • Bailey R; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK.
  • Hollinghurst J; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK.
  • Akbari A; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK.
  • Cooper A; School of Medicine, Cardiff University, Cardiff, UK.
  • Peters H; School of Medicine, Cardiff University, Cardiff, UK.
  • Law RJ; Health and Social Services, Welsh Government, Cardiff, UK.
  • Lewis R; School of Medical and Health Sciences, Bangor University, Bangor, UK.
  • Edwards A; School of Medicine, Cardiff University, Cardiff, UK.
  • Lyons R; Population Data Science, Faculty of Medicine, Swansea University, Swansea, UK.
Lancet ; 400 Suppl 1: S69, 2022 11.
Article em En | MEDLINE | ID: mdl-36930016
ABSTRACT

BACKGROUND:

The COVID-19 pandemic had direct and indirect effects on health. Indirect effects on long term medical conditions (LTCs) are unclear. We examined trends in recorded incidences of LTCs and quantified differences between expected rates and observed rates from 2020 onwards.

METHODS:

This is a population data linkage study using primary and secondary care data within the Secure Anonymised Information Linkage Databank. We included data of Welsh residents diagnosed with any of 17 identified LTCs for the first time between Jan 1, 2000, and Dec 31, 2021. LTC's include mental health conditions, respiratory diseases, and heart conditions among others, generally chosen in line with the Quality and Outcomes Framework. The primary outcome was incidence rates (monthly number of new cases per 100 000 population). For each LTC, we did interrupted time series analysis of incidence rates from 2015 to 2021. Expected rates from between Jan 1, 2020, to Dec 31, 2021, were predicted using overall trends and seasonal patterns from the preceding 5 years and compared with observed rates.

FINDINGS:

We included 5 476 012 diagnoses from 2 257 992 individuals diagnosed with at least one LTC between Jan 1, 2000, to Dec 31, 2021. Across multiple long-term conditions, there was an abrupt reduction in observed incidence of new diagnoses from March to April 2020, followed by a general increase in incidence towards prepandemic rates. The conditions with the largest percentage difference between the observed and expected incidence rates in 2020 and 2021 were chronic obstructive pulmonary disease (38·4% lower than expected), depression (28·3% lower), hypertension (25·5% lower), and anxiety disorders (24·9% lower). The condition with the largest absolute difference between observed and expected incidence rates was anxiety disorders, with 830 per 100 000 less in 2020 and 2021 compared with observed rates.

INTERPRETATION:

The reduction in incidence rates of LTCs suggests an underreporting of LTCs, especially during 2020 and early 2021. The emergence of these yet undiagnosed cases could result in a surge of new patients in the near future.

FUNDING:

This work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença Pulmonar Obstrutiva Crônica / COVID-19 Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença Pulmonar Obstrutiva Crônica / COVID-19 Idioma: En Ano de publicação: 2022 Tipo de documento: Article