A Case-Crossover Phenome-wide Association Study (PheWAS) for Understanding Post-COVID-19 Diagnosis Patterns
Authors: Haupert Spencer R. , Shi Xu , Chen Chen , Fritsche Lars G. , Mukherjee Bhramar 
Published: July 2022

Importance

Post COVID-19 condition (PCC) is known to affect a large proportion of COVID-19 survivors. Robust study design and methods are needed to understand post-COVID-19 diagnosis patterns in all COVID-19 survivors, not just the ones clinically diagnosed with PCC.

Objective

To assess which diagnoses appear more frequently after a COVID-19 infection and how they differ by COVID-19 severity and vaccination status.

Design

We applied a case-crossover phenome-wide association study (PheWAS) in a retrospective cohort of COVID-19 survivors, comparing the occurrences of 1,649 diagnosis-based phenotype codes (PheCodes) pre- and post-COVID-19 infection periods in the same individual using a conditional logistic regression.

Setting

Patients tested for or diagnosed with COVID-19 at Michigan Medicine from March 10, 2020 through May 1, 2022.

Participants

36,856 SARS-CoV-2-positive patients and 141,615 age- and sex-matched SARS-CoV-2-negative patients as a comparison group for sensitivity analysis.

Exposure

SARS-CoV-2 virus infection as determined by RT-PCR testing and/or clinical evaluation.

Main Outcomes and Measures

We compared the rate of occurrence of 1,649 disease classification codes in “pre-” and “post-COVID-19 periods”. We studied how this pattern varied by COVID-19 severity and vaccination status at the time of infection.

Results

Using a case-crossover PheWAS framework, we found mental, circulatory, and respiratory disorders to be strongly associated with the “post-COVID-19 period” for the overall COVID-19-positive cohort. A total of 325 PheCodes reached phenome-wide significance (p<3e-05), and top hits included cardiac dysrhythmias (OR=1.7 [95%CI: 1.6-1.9]), respiratory failure, insufficiency, arrest (OR=3.1 [95%CI: 2.7-3.5]) and anxiety disorder (OR=1.7 [95%CI: 1.6-1.8]). In the patients with severe disease, we found stronger associations with many respiratory and circulatory disorders, such as pneumonia (p=2.1e-18) and acute pulmonary heart disease (p=2.4e-8), and the “post-COVID-19 period,” compared to those with mild/moderate disease.

Test negative patients exhibited a somewhat similar association pattern to those fully vaccinated, with mental health and chronic circulatory diseases rising to the top of the association list in these groups.

Conclusions and Relevance

Our results confirm that patients experience myriad symptoms more than 28 days after SARS-CoV-2 infection, but especially mental, circulatory, and respiratory disorders. Our case-crossover PheWAS approach controls for within-person confounders that are time-invariant. Comparison to test negatives with a similar design helped identify enrichment specific to COVID-19. As we look into the future, we must be aware of COVID-19 survivors’ healthcare needs in the period after infection.

Key Points

Question

What patterns of clinical diagnosis tend to occur more frequently after a COVID-19 infection and how do they vary by COVID-19 severity and vaccination status?

Findings

In a cohort of 36,856 COVID-19-positive patients, using a case-crossover phenome-wide association analysis that controls for within-subject confounders, we found symptoms such as anxiety disorder, cardiac dysrhythmias, and respiratory failure to be significantly associated with the “post-COVID-19 period.” Patients with severe COVID-19 were more likely to receive diagnoses related to respiratory conditions in their “post-COVID-19 period” compared to those with mild/moderate COVID-19. The landscape of phenome-wide association signals for the vaccinated group featured common chronic conditions when compared to the signals in the unvaccinated group.

Meaning

Symptoms across multiple organ systems, especially in the mental, circulatory, and respiratory domains, were associated with the “post-COVID-19 period.” Characterization of post-COVID-19 diagnosis patterns is crucial to understand the long term and future healthcare burden of COVID-19.