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In a recent article posted on medRxiv*, longitudinal clinical phenotypes were described based on respiratory ordinal scales. According to the study, demographics, clinical features, laboratory tests, and radiographic observations correlated with coronavirus disease 2019 (COVID-19) trajectory.

Study: Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: results from the IMPACC study. Image Credit: sfam_photo/Shutterstock

Background

The host-pathogen interaction dictates the outcome of most diseases caused by microbial infections. An in-depth investigation of these interactions can facilitate the identification of promising biomarkers and host-directed therapeutic approaches against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the post-acute sequelae of COVID-19 (PASC). 

Several previous studies that investigated the host-pathogen interaction were limited by small sample size and fewer clinical characteristics, while a cross-sectional design with laboratory data was typically recorded at a single time point. 

To address these shortcomings, an effective method was developed that considered the entire disease course and the patient’s problems. Longitudinal data integration is an effective method to identify disease severity considering the entirety of the disease course in terms of patient problems, the persistence of symptoms, and resource use.

Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) considers clinical, laboratory, and radiographic data. It incorporates a longitudinal biologic collection of blood and respiratory secretions for in-depth immunologic and virologic testing – with a one-year follow-up post-discharge.

The present study examined the IMPACC trial results to better comprehend the relationship between the characteristics of patients hospitalized with coronavirus 2019 (COVID-19) and their outcomes to enhance COVID-19 therapies and the disease outcomes –to improve patient management.

The study

IMPACC was a prospective observational cohort study conducted on 1,164 patients from 20 hospitals across the United States. Based on the severity of respiratory sickness, a seven-point ordinal scale was used to evaluate the disease severity. This study examined patient characteristics using unsupervised clustering of the respiratory ordinal score (OS) over time to capture the dynamics of disease progression. 

Findings

The study identified five disease course trajectories – brief length of stay; intermediate length of stay; intermediate length of stay with discharge limitations; prolonged hospitalization; and fatal. 

Regarding presenting symptoms, shortness of breath and altered mental status were related to more severe disease, whereas gastrointestinal symptoms were correlated to less severe disease progression. The time between symptom onset and hospitalization was not significantly linked with a worse prognosis.

Further, the patients were prospectively questioned quarterly for one year following discharge for PASC. Over 28 days, demographics, comorbidities, radiographic observations, clinical laboratory values, SARS-CoV-2 polymerase chain reaction (PCR), and serology were collected. A multivariable logistic regression analysis was conducted.

The results showed that age (65 years or older), Latinx ethnicity, specific comorbidities, and the presence of chest radiography infiltrate and selected biomarkers at baseline were related to a more severe disease course and poorer outcomes.

These findings suggested that a larger SARS-CoV-2 viral load at presentation was associated with a more severe illness. On calculating the ratio of anti-receptor-binding domain (RBD) levels to the cycle threshold (Ct) values, it was noted that prolonged hospitalization showed a markedly lower ratio than the other trajectories over the first 28 days post-infection. Particularly, this study is unique in verifying this observation in a larger sample and demonstrating the connection between longitudinal viral load monitoring and clinical disease progression.

Hispanic/Latinx ethnicity was related to an elevated risk of more severe disease; however, neither race nor ethnicity was ultimately connected to mortality when analyzing the multivariable risk in the most severely ill groups.

The results of this prospective analysis were consistent with previous reports in exhibiting a lack of association between obesity and poor COVID-19 outcome. Furthermore, this study failed to link remdesivir or glucocorticoid use to virus clearance. 

Additionally, 51% of the patients had at least one PASC symptom. Females showed a higher preponderance of PASC, despite the study cohort being predominantly male. This finding depicted that males were at a greater risk of COVID19-related hospitalization.

Conclusion

High baseline viral load and its persistence were linked with COVID-19 disease severity, according to the present investigation. Whereas fatal SARS-CoV-2 cases were related to the lowest anti-RBD and S immunoglobulin (Ig)G concentrations.

These results imply that a deficient antiviral immune response––which is important for virus clearance––may play a crucial role in short-term mortality. The determined ratio (binding IgG/PCR Ct value) reflected host-pathogen interactions and was a practical method for patient risk classification.

Blood, upper and lower respiratory samples collected from this cohort can be immunophenotyped to identify immunological endotypes related to COVID-19 severity and/or symptom persistence. This can aid in discovering the predictive and prognostic traits of COVID-19 and devising theories concerning the cellular and molecular foundation of the disease and recovery.

*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.

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