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. 2021 Feb 23;118(8):e2017962118.
doi: 10.1073/pnas.2017962118.

Modeling SARS-CoV-2 viral kinetics and association with mortality in hospitalized patients from the French COVID cohort

Affiliations

Modeling SARS-CoV-2 viral kinetics and association with mortality in hospitalized patients from the French COVID cohort

Nadège Néant et al. Proc Natl Acad Sci U S A. .

Abstract

The characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral kinetics in hospitalized patients and its association with mortality is unknown. We analyzed death and nasopharyngeal viral kinetics in 655 hospitalized patients from the prospective French COVID cohort. The model predicted a median peak viral load that coincided with symptom onset. Patients with age ≥65 y had a smaller loss rate of infected cells, leading to a delayed median time to viral clearance occurring 16 d after symptom onset as compared to 13 d in younger patients (P < 10-4). In multivariate analysis, the risk factors associated with mortality were age ≥65 y, male gender, and presence of chronic pulmonary disease (hazard ratio [HR] > 2.0). Using a joint model, viral dynamics after hospital admission was an independent predictor of mortality (HR = 1.31, P < 10-3). Finally, we used our model to simulate the effects of effective pharmacological interventions on time to viral clearance and mortality. A treatment able to reduce viral production by 90% upon hospital admission would shorten the time to viral clearance by 2.0 and 2.9 d in patients of age <65 y and ≥65 y, respectively. Assuming that the association between viral dynamics and mortality would remain similar to that observed in our population, this could translate into a reduction of mortality from 19 to 14% in patients of age ≥65 y with risk factors. Our results show that viral dynamics is associated with mortality in hospitalized patients. Strategies aiming to reduce viral load could have an effect on mortality rate in this population.

Keywords: SARS-CoV-2; mortality; viral dynamics.

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Conflict of interest statement

Competing interest statement: J. Guedj has worked as a consultant for ROCHE Company.

Figures

Fig. 1.
Fig. 1.
Nasopharyngeal viral load data in 655 patients from the French COVID cohort. (A) Longitudinal viral load data expressed in time since symptom onset. (B) Viral load data in samples where virus culture was done. Red, positive culture; black, negative culture. The connective lines indicate serial samples from the same patients (44 samples from 37 patients) (C) Viral load at admission according to the time since symptom onset; the blue line is the regression line of viral load vs. time. (D) Kaplan−Meier curve of cumulative incidence of mortality. Patients lost to follow-up were censored at the last time point where they were known to be alive.
Fig. 2.
Fig. 2.
Individual predictions of nasopharyngeal viral kinetics in the 42 patients for which more than three serial samples were available after day 14. The solid and dotted lines (blue, age <65 y; orange, age ≥65 y) are the individual predictions of viral load with the final model and target cell-limited model, respectively (Table 2). The circles are the observed data according to age, and triangles are data below the limit of quantification.
Fig. 3.
Fig. 3.
Description of the individual viral load kinetic profiles. (A) Median of the individual predicted viral load kinetics. Solid lines, total viral load levels; dashed lines, infectious virus. Dots represents the observed data, and triangles are data below the limit of quantification. (B) Median of the predicted instantaneous loss rate of productively infected cells. (C) Distribution of the predicted time to viral clearance in the patients. Dashed lines represent the predicted median of time to viral clearance. Viral kinetic parameters were obtained by using the EBE (see Materials and Methods). Blue, patients aged <65 y; orange, patients aged ≥65 y.
Fig. 4.
Fig. 4.
Individual viral load and survival profiles and predictions according to the initiation of a putative antiviral treatment initiated at admission. (A) Median of the individual predicted viral load, V(t) (Eqs. 13); y.o., years old. (B) Median of the predicted instantaneous hazard function, h(t). (C) Median of the predicted death rate, 1 − S(t) (Eq. 4). Solid lines, predicted profile without treatment; dashed lines, treatment with 90% efficacy; dotted lines, treatment with 99% efficacy; blue, patients aged <65 y; orange, patients aged ≥65 y. The profiles are calculated in each of the following population of patients: age <65 y and absence of other significant risk factor (male gender or chronic pulmonary disease, Left), age <65 y and presence of at least one risk factor (Center Left), age ≥65 y and absence of other risk factor (Center Right), and age ≥65 y and presence of at least one other significant risk factor (Right).

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