Posted in a recent article on medRxiv†, longitudinal clinical phenotypes were described based on respiratory ordinal scales. According to the study, demographics, clinical features, lab tests and radiographic observations correlated with the trajectory of coronavirus disease 2019 (COVID-19).
The interaction between host and pathogen determines the outcome of most diseases caused by microbial infections. An in-depth investigation of these interactions may 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 consequences of COVID-19 (PASC).
Several previous studies examining host-pathogen interaction have been limited by small sample size and fewer clinical features, while a cross-sectional design with laboratory data was typically captured at a single time point.
To address these shortcomings, an effective method has been developed that takes into account the entire disease course and the patient’s problems. Longitudinal data integration is an effective method of identifying disease severity, taking into account the full disease course in terms of patient problems, ongoing symptoms and resource use.
Immunophenotyping assessment in a COVID-19 cohort (IMPACC) considers clinical, laboratory and radiographic data. It includes a longitudinal biological collection of blood and respiratory secretions for in-depth immunological and virological testing – with a one-year follow-up after discharge.
The current study examined the results of the IMPACC study to examine the relationship between the characteristics of patients hospitalized with coronavirus 2019 (COVID-19) and their results to improve COVID-19 therapies and disease outcomes – to improve patient management, better understand.
IMPACC was a prospective observational cohort study conducted in 1,164 patients from 20 hospitals in the United States. Based on the severity of respiratory disease, a seven-point ordinal scale was used to evaluate the severity of the disease. This study examined patient characteristics using uncontrolled clustering of the respiratory ordinal score (OS) over time to capture the dynamics of disease progression.
The study identified five disease progression pathways – short-stay; intermediate length of stay; interim length of stay with dismissal restrictions; prolonged hospitalization; and deadly.
In terms of symptom presentation, dyspnea and altered mental status were related to more severe disease, while gastrointestinal symptoms were correlated to less severe disease progression. The time between symptom onset and hospitalization was not significantly linked to a worse prognosis.
Furthermore, the patients were prospectively surveyed for one year after discharge for PASC. Demographics, co-morbidities, radiographic observations, clinical laboratory values, SARS-CoV-2 polymerase chain reaction (PCR), and serology were collected over 28 days. A multivariable logistic regression analysis was performed.
The results showed that age (65 years or older), Latinx ethnicity, specific co-morbidities, 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 greater SARS-CoV-2 viral load at presentation was associated with more severe disease. When calculating the ratio of anti-receptor binding domain (RBD) levels to cycle threshold (Ct) values, it was noted that long-term hospitalization showed a significantly lower ratio than the other ranges during the first 28 days after infection. Notably, this study is unique in verifying this observation in a larger sample and demonstrating the association between longitudinal viral load monitoring and clinical disease progression.
Hispanic/Latin ethnicity was related to an increased risk of more serious disease; neither race nor ethnicity was ultimately associated with mortality when analyzing multivariate risk in the most critically ill groups.
The results of this prospective analysis were consistent with previous reports and showed a lack of association between obesity and a poor COVID-19 outcome. In addition, this study could not link the use of remdesivir or glucocorticoids to virus clearance.
In addition, 51% of patients had at least one PASC symptom. Women showed a higher predominance of PASC, despite the study cohort being predominantly male. This finding showed that men were at greater risk of COVID19-related hospitalization.
According to the current study, the high viral load at baseline and its persistence were associated with the severity of COVID-19 disease. While fatal SARS-CoV-2 cases were associated with the lowest anti-RBD and S-immunoglobulin (Ig)G concentrations.
These results imply that a defective antiviral immune response – which is important for virus clearance – may play a crucial role in short-term mortality. The established ratio (binding IgG/PCR Ct value) reflected host-pathogen interactions and was a practical method for patient risk classification.
Blood, upper and lower airway samples collected from this cohort may be subjected to immunophenotyping to identify immunological endotypes related to the severity of COVID-19 and/or the persistence of symptoms. This can help discover the predictive and prognostic properties of COVID-19 and come up with theories about the cellular and molecular basis of disease and recovery.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, that should guide clinical practice/health-related behavior or be treated as established information.
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