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Published on: April 13, 2021
Electronic health record analysis identifies kidney disease as the leading risk factor for hospitalization in
Matthew T Oetjens1, Jonathan Z Luo1, Alexander Chang1
1Geisinger, Danville, Pennsylvania, United States of America.
Insights
Pre-existing kidney disorders significantly increase the risk of hospitalization for individuals with coronavirus disease 2019 (COVID-19). This study identified multiple kidney-related conditions as strong predictors of severe COVID-19 outcomes.
Area of Science:
- Medical research
- Genomics and bioinformatics
- Public health
Background:
- Identifying individuals at high risk for severe coronavirus disease 2019 (COVID-19) requires empirical data on risk-increasing conditions.
- A comprehensive assessment of pre-existing clinical phenotypes associated with COVID-19 hospitalization is needed.
Purpose of the Study:
- To quantitatively assess pre-COVID-19 pandemic clinical phenotypes associated with COVID-19 related hospitalization.
- To identify specific pre-existing conditions that increase the risk of severe outcomes from SARS-CoV-2 infection.
Main Methods:
- A phenome-wide association study (PheWAS) was conducted using electronic health record (EHR) data from SARS-CoV-2 positive patients.
- Retrospective analysis of integrated health system data assessed pre-pandemic clinical phenotypes linked to COVID-19 hospitalization.
Main Results:
- Twenty-one clinical phenotypes across five disease categories were significantly associated with COVID-19 hospitalization (P<1.60x10-4).
- Kidney disorders, including end-stage renal disease and stage 5 chronic kidney disease (CKD), showed the strongest association (OR=11.07).
- Other significant phenotypes included cardiovascular, respiratory, and metabolic conditions, such as congestive heart failure and type 2 diabetes.
Conclusions:
- Pre-existing kidney disorders are the most significant factors associated with COVID-19 hospitalization in the studied US healthcare system.
- Quantitative estimates highlight the substantial contribution of specific pre-existing conditions to COVID-19 severity.
Background:
Empirical data on conditions that increase risk of coronavirus disease 2019 (COVID-19) progression are needed to identify high risk individuals. We performed a comprehensive quantitative assessment of pre-existing clinical phenotypes associated with COVID-19-related hospitalization.
Methods:
Phenome-wide association study (PheWAS) of SARS-CoV-2-positive patients from an integrated health system (Geisinger) with system-level outpatient/inpatient COVID-19 testing capacity and retrospective electronic health record (EHR) data to assess pre-COVID-19 pandemic clinical phenotypes associated with hospital admission (hospitalization).
Results:
Of 12,971 individuals tested for SARS-CoV-2 with sufficient pre-COVID-19 pandemic EHR data at Geisinger, 1604 were SARS-CoV-2 positive and 354 required hospitalization. We identified 21 clinical phenotypes in 5 disease categories meeting phenome-wide significance (P<1.60x10-4), including: six kidney phenotypes, e.g. end stage renal disease or stage 5 CKD (OR = 11.07, p = 1.96x10-8), six cardiovascular phenotypes, e.g. congestive heart failure (OR = 3.8, p = 3.24x10-5), five respiratory phenotypes, e.g. chronic airway obstruction (OR = 2.54, p = 3.71x10-5), and three metabolic phenotypes, e.g. type 2 diabetes (OR = 1.80, p = 7.51x10-5). Additional analyses defining CKD based on estimated glomerular filtration rate, confirmed high risk of hospitalization associated with pre-existing stage 4 CKD (OR 2.90, 95% CI: 1.47, 5.74), stage 5 CKD/dialysis (OR 8.83, 95% CI: 2.76, 28.27), and kidney transplant (OR 14.98, 95% CI: 2.77, 80.8) but not stage 3 CKD (OR 1.03, 95% CI: 0.71, 1.48).
Conclusions:
This study provides quantitative estimates of the contribution of pre-existing clinical phenotypes to COVID-19 hospitalization and highlights kidney disorders as the strongest factors associated with hospitalization in an integrated US healthcare system.
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