COVID-19 increases risk of developing chronic diseases

COVID-19 increases risk of developing chronic diseases

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

In a recent study posted to the medRxiv* preprint server, researchers determine the correlation between severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, age, and the new onset diagnoses of chronic or worsening of the pre-existing conditions.

This review strictly adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 reporting guidelines and followed a priori protocol prospectively registered and is now available on PROSPERO.

Study: Associations between SARS-CoV-2 infection and incidence of new chronic condition diagnoses: a systematic review. Image Credit: urbans / Shutterstock.com

Background

For healthcare systems to prepare for a potential increased demand for resources and infrastructure to manage people with post-acute sequelae SARS-CoV-2 infection (PASC), there must be a rough estimate for the future burden of this disease. It is also important to assess whether there is an association between SARS-CoV-2 infection and increased risk of PASC or long-coronavirus disease 2019 (COVID-19).

About the study

In the present study, researchers extensively searched MEDLINE and EMBASE databases between January 1, 2020, and October 4, 2022, to gather observational studies, which included prospective and retrospective studies, from Organization for Economic Co-operation and Development (OECD) countries with a control group adjusting for gender and comorbidities.

After two reviewers independently screened 50% of titles/abstracts, an artificial intelligence (AI)-based machine learning feature known as DistillerAI functioned as the second reviewer. Next, two other reviewers screened the full article text of the records selected in stage one. This was followed by one reviewer who extracted data and assessed the risk of bias, while the other verified the results.

During the assessment of chronic conditions post-SARS-CoV-2 infection, the team focused on cardiovascular, respiratory, neurological, and musculoskeletal diseases, cancer, and diabetes. They also evaluated conditions within each category and used random-effects meta-analysis to estimate pooled hazard ratios (HR). In subgroup analyses, variables such as time since infection, vaccination status, and SARS-CoV-2 variants of concern (VOCs) were considered.

Study findings

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A total of 4,648 unique records were identified from all databases and 24 articles from other sources. However, the final sample for the meta-analyses comprised 25 studies from six countries, with 15, four, and three from the United States, Germany, and the United Kingdom, respectively, and one each from Denmark, Korea, and Sweden.

Eight of the 25 studies confirmed that the control group was reverse transcription-polymerase chain reaction (RT-PCR)-negative for SARS-CoV-2, while two eligible studies found that chronic diseases developed after COVID-19-related hospitalization.

The strict eligibility criteria of the study, which accounted for gender and relevant comorbidities, likely reduced the number of eligible studies at high risk of bias. Nevertheless, 72% of the studies had a moderate risk of bias, whereas only three had a low risk of bias. The most frequent concern for risk of bias in these studies was the potential for misclassification.

Regarding certainty of the evidence, it remained between moderate and high concerning associations between SARS-CoV-2 infection and new-onset chronic conditions. The most certainty was observed in correlations between SARS-CoV-2 infection and new onset of chronic cardiac issues in individuals aged 65 years and older from outpatient or mixed care groups, as well as those who were naturally more vulnerable to many chronic diseases.  

The researchers could not identify studies reporting a worsening of pre-existing chronic illnesses after SARS-CoV-2 infection; however, there still might be an association between these two conditions. Likewise, data on new-onset chronic illnesses and COVID-19-related hospitalizations remained scarce, with only two studies reporting an association.

The current review also highlighted a substantial lack of evidence for cancer diagnoses post-COVID-19. Social distancing mandates and lockdowns early during the pandemic likely hindered people from accessing cancer screening, thus creating a potential backlog of missed diagnoses.

Conclusions

According to the authors, this is the first systematic review documenting a correlation between SARS-CoV-2 infection and new-onset chronic illnesses that has been stratified by age group.

The review findings showed an increased risk of certain chronic health conditions post-COVID-19; however, the extent of this risk directly remains uncertain due to other factors. Perhaps the observational design of the reviewed studies did not fully consider increased healthcare monitoring in infected individuals.

An increased risk of new onset of some chronic diseases, including cardiovascular and respiratory disease diagnoses, was also observed.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • Preliminary scientific report. Gaudet, L. A., Pillay, J., Saba, S., et al. (2023). Associations between SARS-CoV-2 infection and incidence of new chronic condition diagnoses: a systematic review. medRxiv. doi:10.1101/2023.02.21.23286181. https://www.medrxiv.org/content/10.1101/2023.02.21.23286181v1.

Posted in: Medical Science News | Medical Research News | Medical Condition News | Disease/Infection News | Healthcare News

Tags: Artificial Intelligence, Cancer, Chronic, Coronavirus, Coronavirus Disease COVID-19, Diabetes, Healthcare, Machine Learning, Musculoskeletal, Pandemic, Polymerase, Polymerase Chain Reaction, Respiratory, Respiratory Disease, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome, Transcription

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Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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