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In a recent study published in The Lancet Infectious Diseases, researchers performed a retrospective population-wide cohort study using anonymized data in Hong Kong, China, review flonase between February 26 and July 3, 2022.

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They determined the incidences of severe acute respiratory syndrome coronavirus (SARS-CoV-2) rebound, related risk factors, and outcomes in hospitalized patients with a confirmed diagnosis of coronavirus disease 2019 (COVID-19) when the Omicron BA.2.2 variant was predominant.

Background

Concerted efforts by researchers and medical professionals led to the discovery of oral antivirals for COVID-19 treatment. Nirmatrelvir–ritonavir therapy helped lower the risk of hospitalization and mortality in patients at high risk of progressing to severe illness.

However, reports of viral rebound following this treatment (though anecdotal) are increasing continuously, which has implications for the clinical management of COVID-19 patients and their isolation. Likewise, though scarce, there is evidence of viral rebound after molnupiravir treatment. In this regard, there is a need for more data from post-marketing surveillance of both oral antivirals.

Earlier, clinicians in Hongkong prescribed oral antivirals to COVID-19 patients as clinically appropriate; however, after the advent of Omicron in early March 2022, the guidelines specified preferential use of nirmatrelvir–ritonavir over molnupiravir, unless the patient was on any concomitant medication contraindicated for this therapy.

While researchers have established a standard definition of viral rebound (by now) for some other viruses (e.g., human immunodeficiency virus/HIV), the same remains pending for SARS-CoV-2. Nonetheless, if viral bound does happen, it is crucial to identify its incidence in patients receiving and not receiving oral antivirals in clinical practice.

About the study

In the present study, researchers searched Scopus and PubMed till October 21, 2022, for published studies, primarily case studies and observational cohort studies, examining COVID-19 or viral load rebound. They identified COVID-19 cases from the eSARS database of Hong Kong's Department of Health.

The study population comprised patients receiving either five-day therapy of oral molnupiravir (800 mg twice a day) or nirmatrelvir–ritonavir (100mg ritonavir-boosted 300mg nirmatrelvir twice a day) during the observation period, though completion of this regimen was not compulsory for inclusion.

The control cohort had hospitalized patients with non-oxygen-dependent COVID-19 who did not receive either drug during the study period.

All included patients had confirmed COVID-19, as assessed via reverse transcription-polymerase chain reaction (RT-PCR) done within three days before or after hospital admission, thus, showing a cycle threshold (C_T) value on hospital admission. The team used C_T values as a substitute for SARS-CoV-2 burden, where a reduction of nearly three units in C_T value indicated an eight-fold increase in viral ribonucleic acid (RNA).

Further, the team retrieved patients' electronic health records (EHRs) from Hong Kong's hospital authority. They gathered information on their age, gender, medical history, and comorbidities based on Charlson Comorbidity Index (CCI), drugs they were taking (antibiotics, systemic steroids), and even laboratory tests and inpatient procedures within the past 12 months.

The team used a generalized-additive mixed-effects model to estimate daily C_T value. They produced line plots of the averaged predicted daily CT value for the first 21 days since the index date, which indicated the date of the first COVID-19-positive test result, symptom onset, or the initiation of drug therapy. In addition, they stratified the approximate period over which viral shedding decreased towards the detectable levels by age group (less than or over 65 years), CCI score (of less than six or more), and vaccination status.

A multivariable logistic regression model assessed potential predictors for viral burden rebound and presented their association with the prespecified clinical outcomes as odds ratios (ORs) with 95% confidence intervals (CI). Moreover, they performed sensitivity analyses and calculated the absolute risk differences in clinical outcomes between patients with and without viral burden rebound in each group.

Study findings

Of 4592 hospitalized patients, 1998 and 2594 were women and men, respectively. The incidence of SARS-CoV-2 burden rebound did not vary markedly across the three study groups. Accordingly, the researchers noted this in 16/242 patients in the nirmatrelvir–ritonavir, 27 of 563 patients in the molnupiravir, and 170 of 3787 patients in the control group.

Among the patients receiving nirmatrelvir–ritonavir therapy, the odds of a viral burden rebound were lower in those not fully vaccinated; the odds were higher in those aged 18 to 65 years, with a CCI score of over six and those taking corticosteroids. Likewise, among the patients receiving molnupiravir, people aged 18 to 65 years or taking concomitant corticosteroids had increased odds of a viral rebound.

Irrespective of the type of treatment received, immunocompromised patients remained at higher odds of SARS-CoV-2 rebound; within five days, the association between its incidence and presentation of the composite clinical outcome was nullified. The study results confirmed that antiviral treatment had no direct effect on the rate of COVID-19 rebound. In addition, its occurrence caused no adverse clinical outcome.

Conclusions

The study results confirmed that SARS-CoV-2 burden rebound was not uncommon among all patients, irrespective of oral antiviral therapy use. Some patient groups showed increased odds of rebound, but it did not result in adverse clinical outcomes. Like COVID-19 vaccines, their usage offers more benefit than risk, especially for COVID-19 patients at risk of fatal consequences.

However, there remains an urgent need to institute a standard definition of COVID-19 rebound for future research, identify the molecular mechanisms governing it, and its possible variation(s) by dosage, time, and duration of antiviral treatments.

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.