Researchers characterize and predict post-acute sequelae of SARS-CoV-2 infection

In a recent study posted to the medRxiv* preprint server, researchers characterized and predicted post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC) infection.

Study: Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 infection (PASC) in a Large Academic Medical Center in the US. Image Credit: Kateryna Kon/Shutterstock
Study: Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 infection (PASC) in a Large Academic Medical Center in the US. Image Credit: Kateryna Kon/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

The rising number of coronavirus disease 2019 (COVID-19)-recovered persons suffering from post-acute sequelae of SARS-CoV-2 infection (PACS) has become a global concern. However, the development of efficient treatments has been impeded by the novelty of this disease and the scant information available about the underlying pathomechanisms.

About the study

In the present study, researchers described PASC-associated diagnoses and developed models for risk assessment.

The study involved eligible individuals who were patients of Michigan Medicine (MM) and who were diagnosed with COVID-19 or tested positive for real-time reverse transcriptase polymerase chain reaction (RT-PCR) for SARS-CoV-2 infection between 10 March 2020 and 31 August 2022. Data from RT-PCR tests were gathered for employee screening, standard screening at hospital admission, and routine screening before treatments. Symptomatic as well as asymptomatic subjects participated in the study. The index date for each participant was either their initial COVID-19 diagnosis or positive RT-PCR test, whichever was earlier.

The remaining COVID-19-positive patients were further divided into groups: (1) "no PASC" patients who had no recorded PASC diagnosis and (2) patients having a recorded diagnosis of PASC. Diagnoses for PASC were determined using either observation of the ICD10-CM codes B94.8, which indicated sequelae related to other specified infectious and parasitic disorders or U09.9, which indicated unspecified PASC or entries for PASC in the diagnosis component of the Problem Summary List (PSL) of the electronic health records (EHR) database.

Subsequently, the team conducted phenome-wide association studies (PheWASs) to identify enriched phenotypes associated with the post-COVID-19 era and putative PASC predisposing phenotypes related to the pre- and acute-COVID-19 periods.

Additionally, the team divided PASC patients into groups according to ICD10 diagnoses that corresponded to 29 phenotypic concepts that had previously been reported as typical PASC symptoms and that were simultaneously recorded with their initial PASC diagnoses. Furthermore, patient characteristics were assessed and adjusted for socioeconomic status and other factors, including age, gender, race/ethnicity, person-per-square-mile population density, and neighborhood disadvantage index (NDI) without Black community proportion.

Results

A PASC diagnosis was reported by 1,724 of the 63,675 COVID-19 positive patients a minimum of two months following their initial COVID-19 diagnosis or RT-PCR positive result. Within three months of COVID-19 diagnosis, the incidence of clinically confirmed PASC varied between 0.18% to 1.8%. The second peak of COVID-19 positive people at MM coincided with the largest quarterly number of PASC infections recorded in the fourth quarter of 2021.

The team also found that compared to controls, PASC cases had slightly longer periods covered in the pre-test EHRs than controls and had a higher chance of being older, female, and receiving primary care at MM in the previous two years.

Almost 34.3% of individuals reported shortness of breath, 30.6% experienced anxiety, 28.5% had fatigue and malaise, 27.2% had depression, 25.4% suffered from sleep disturbances, 23.6% reported asthma, 21.4% experienced headaches, 13.8% had migraine, 13.0% had a cough, and 12.6% had joint pain. All of the 29 PASC symptoms that were examined were enriched, with 27 of them reaching phenome-wide significance and two did not. PheWAS also suggested the enrichment of several illnesses, including musculoskeletal problems, infectious diseases, as well as digestive disorders.

PheWAS compared 1,212 cases to 11,919 matched controls, utilizing only the diagnoses reported at least two weeks before being COVID-19 positive. This allowed the identification of putative pre-COVID-19 symptoms that predispose COVID-19 diagnoses to PASC. Out of the 1,405 examined PheCodes, phenome-wide relevance was exhibited for irritable bowel syndrome (IBS), nausea and vomiting, concussion, respiratory abnormalities, food allergies, and general circulatory disease.

The frequencies and corresponding signals across the three PheWAS were employed to determine if PASC-associated phenotypes associated with the pre- and acute-COVID-19 periods resulted in novel PASC symptoms or whether they become long-term PASC symptoms by themselves.

Conclusion

Overall, the study demonstrated an agnostic screening of time-stamped EHR data that revealed a wide range of diagnoses linked with PASC across several categories. The study also noted a complex arrangement of possible predisposing factors which may be used to develop risk stratification strategies. However, extensive research will be required to adequately characterize PASC and its variants, particularly with regard to long-term effects, and to take into account more thorough risk models.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 15 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Bhavana Kunkalikar

Written by

Bhavana Kunkalikar

Bhavana Kunkalikar is a medical writer based in Goa, India. Her academic background is in Pharmaceutical sciences and she holds a Bachelor's degree in Pharmacy. Her educational background allowed her to foster an interest in anatomical and physiological sciences. Her college project work based on ‘The manifestations and causes of sickle cell anemia’ formed the stepping stone to a life-long fascination with human pathophysiology.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Kunkalikar, Bhavana. (2023, May 15). Researchers characterize and predict post-acute sequelae of SARS-CoV-2 infection. News-Medical. Retrieved on December 26, 2024 from https://www.news-medical.net/news/20221025/Researchers-characterize-and-predict-post-acute-sequelae-of-SARS-CoV-2-infection.aspx.

  • MLA

    Kunkalikar, Bhavana. "Researchers characterize and predict post-acute sequelae of SARS-CoV-2 infection". News-Medical. 26 December 2024. <https://www.news-medical.net/news/20221025/Researchers-characterize-and-predict-post-acute-sequelae-of-SARS-CoV-2-infection.aspx>.

  • Chicago

    Kunkalikar, Bhavana. "Researchers characterize and predict post-acute sequelae of SARS-CoV-2 infection". News-Medical. https://www.news-medical.net/news/20221025/Researchers-characterize-and-predict-post-acute-sequelae-of-SARS-CoV-2-infection.aspx. (accessed December 26, 2024).

  • Harvard

    Kunkalikar, Bhavana. 2023. Researchers characterize and predict post-acute sequelae of SARS-CoV-2 infection. News-Medical, viewed 26 December 2024, https://www.news-medical.net/news/20221025/Researchers-characterize-and-predict-post-acute-sequelae-of-SARS-CoV-2-infection.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
How viral persistence and immune dysfunction drive long COVID