What are the risk factors associated with post-acute SARS-CoV-2 infection?

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In a recent study posted to the Research Square* preprint server, researchers assessed the risk factors and predictive models for post-acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Study: Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative. Image Credit: CROCOTHERY/Shutterstock
Study: Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative. Image Credit: CROCOTHERY/Shutterstock

*Important notice: Research Square publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

During the post-acute phase of their infection, SARS-CoV-2-infected patients may develop additional, incidental diseases. Post-acute sequelae of coronavirus disease 2019 (COVID-19) infection (PASC) symptoms are highly variable and affect a variety of organ systems. Few studies have examined the predictability and related risk factors of these illnesses.

About the study

In the present study, researchers conducted a thorough investigation of the predictability of a wide range of incident PASC conditions and associated risk variables.

The study utilized two de-identified electronic health records (EHR) datasets obtained from the OneFlorida + Clinical Research Network (CRN) and the INSIGHT CRN. The INSIGHT CRN featured longitudinal clinical data on almost 12 million patients residing in the New York City metropolitan region, whereas the OneFlorida + CRN comprised the EHR information of approximately 15 million patients residing in Florida as well as select cities in Alabama and Georgia.

The team assessed a list of probable PASC outcomes, such as anxiety disorders, depressive disorders, and general PASC signs and symptoms. Incident conditions were defined in the COVID-19 patients who suffered from the condition 31 to 180 days after their acute infection but did not have the condition three to seven years prior. A list of confounders was also compiled that included basic demographics, socioeconomic level with respect to the infection period, comorbidities, and acute phase care settings, including hospital admission and intensive care unit (ICU) admission.

Adult patients with a minimum of one SARS-CoV-2 antigen test or polymerase chain reaction (PCR) between 1 March 2020 and 30 November 2021 were included. To ensure that the patients were linked to the healthcare system and monitored throughout the study period, the team required at least one diagnostic code within three years to seven days prior to the index date and a minimum of one diagnosis code between 31 days and 180 days after the index date.

Each patient was followed up with from 31 days following his/her index date up to the day when the target outcome or death was recorded, the last date of any documented entries in the database, 180 days had passed since the baseline, or until the end of the study observational window, whichever occurred first.

Results

The INSIGHT cohort comprised 35,275 adult patients with laboratory-confirmed SARS-CoV-2 infection, with 326,126 control individuals without infection. There was a correlation between diverse incident conditions and heterogeneous predictive performance. The intensity of acute COVID-19 was related to an increased chance of developing new incident symptoms in the post-acute phase.

Patients hospitalized during the acute phase or in ICU had a greater probability of receiving any event diagnosis relative to patients who were not admitted to the hospital during the acute phase. ICU patients exhibited a 4.7-fold increased risk of a myopathy diagnosis, a 2.5-fold increased risk of pressure ulcer diagnosis, a 2.3-fold increased risk of thromboembolism diagnosis, and a 2.1-fold increased risk of malaise and fatigue diagnosis in comparison to non-hospitalized patients.

In the post-acute COVID-19 phase, patients aged 75 years or older displayed a higher likelihood of being diagnosed with a variety of probable PASC diseases, such as dementia, COPD, malnutrition, cerebral ischemia, pressure ulcer, cognitive difficulties, and anemia compared to those aged between 55 and 64 years. Individuals between the ages of 65 and 74 years had a higher likelihood of being diagnosed with heart failure, diabetes mellitus, and dementia compared to those in the reference group. In contrast, younger patients between the ages of 20 and 39 years had a higher probability of developing milder possible PASC diseases, such as acute pharyngitis, anxiety disorder, and headache than patients in the control group.

The team observed that patients infected during the SARS-CoV-2 Delta variant-dominated period between July 2021 and November 2021 had an increased risk of experiencing incident pharyngitis, abdominal pain, chest pain, dyspnea, and general PASC signs and symptoms with the U099/B948 ICD codes during the post-acute COVID-19 phase in comparison to patients infected between the reference period of March to June 2020.

The team also noted that suffering from one or more baseline issues was related to a higher chance of probable PASC diagnoses, such as malnutrition, fluid problems, anemia, and chest discomfort. In particular, cancer patients had an elevated risk for a variety of post-acute illnesses, including atelectasis, malnutrition, fever, pulmonary fibrosis, and anemia, as compared to individuals without any diagnosed cancer at baseline. Individuals with chronic kidney disease at baseline were more likely to be diagnosed with anemia and heart failure.

Conclusion

The study findings showed the risk variables related to newly occurring PASC conditions and created predictive models to detect individuals at risk for these conditions. The study demonstrated that various predictive PASC diagnoses are connected with acute phase severity. However, PASC diagnoses that are less predictable pose a continuing difficulty that may not respond to other strategies designed to reduce the severity of acute COVID-19.

*Important notice: Research Square 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:
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.

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